Generator Interconnection and Deliverability Study Methodology Technical Paper

Transcription

1 Generator Interconnection and Deliverability Study Methodology Technical Paper July 2, 2013

2 Generator Interconnection and Deliverability Study Methodology Table of Contents Introduction... 1 Section One: Background Information on the Basis for the Methodology and an Overview of the Methodology... 3 Background... 3 Overview of the Methodology... 7 Section Two: On-Peak Generation Deliverability Assessment Methodology...17 Background...17 Study Objectives...18 Baseline analysis...18 General Procedures and Assumptions...19 Specific Assumptions...22 Section Three: Examples of Application of Deliverability Assessment Methodology Whirlwind Example Borrego Area Example ECO/BUE Area Deliverability Constraint and Mitigation Example North of Lugo Deliverability Constraints and Mitigations Example Northern California Deliverability Constraint and Mitigation Example Central California Example Desert Area Deliverability Constraints and Mitigations Example (TPP) Desert Area Deliverability Constraints and Mitigations Example (GIP) South of Vincent Deliverability Constraints and Mitigation Examples Path 43 (North of SONGS) Deliverability Constraint and Mitigation Example i

3 Generator Interconnection and Deliverability Study Methodology List of Figures Figure I-1: Electric transmission network in California... 8 Figure I-2: Electric power plant locations in California... 8 Figure I-3: Depiction of resource shortage Scenario 1 in California... 9 Figure I-4: Depiction of resource shortage Scenario 2 in California Figure I-5: Depiction of a Study Group Based on the 5% Distribution Factor Threshold Figure I-6: Example Production Duration Curve Showing 70% Exceedance Level Figure I-7: Example Production Duration Curve Showing Combined 70% Exceedance Level Figure I-8: Example Production Curve Showing Production Levels Counted by the 70% Exceedance Level Calculation Figure 1.1: Illustration of Generator Grouping for Whirlwind Transformer Bank Flows Figure 1.2: Initial Dispatch Whirlwind Transformers Figure 1.3: Stressed Dispatch Whirlwind Transformers Figure 1.4: Traditional Power Flow Dispatch Whirlwind Transformers Figure 2.1: Illustration of Generator Grouping for Borrego Area Figure 2.2: Initial Dispatch Borrego Area Figure 2.3: Stressed Dispatch Borrego Area Figure 2.4: Traditional Power Flow Dispatch Borrego Area Figure 3.1: Illustration of Generator Grouping for ECO/BUE Area Figure 3.2: Initial Dispatch ECO/BUE Area Figure 3.3: Stressed Dispatch ECO/BUE Area Figure 3.4: Stressed Dispatch with Mitigation ECO/BUE Area Figure 3.5: Off-Peak Study ECO/BUE Area Figure 4.1: Illustration of Generator Grouping for Kramer Lugo 230 kv No.1 & 2 Overloads Figure 4.2: Initial Dispatch North of Lugo Figure 4.3: Stressed Dispatch North of Lugo Figure 4.4: Stressed Dispatch with Mitigation North of Lugo Figure 4.5: Traditional Power Flow Dispatch North of Lugo Figure 4.6: Traditional Power Flow Dispatch with Mitigation North of Lugo Figure 5.1: Illustration of Generator Grouping for Vaca Dixon WindUnit_POI Constraint Figure 5.2: Initial Dispatch (Pre-Contingency) Vaca Dixon to WindUnit_POI Constraint Figure 5.3: Initial Dispatch (Post-Contingency) Vaca Dixon to WindUnit_POI Constraint Figure 5.4: Stressed Dispatch (Post-Contingency) Vaca Dixon to WindUnit_POI Constraint Figure 5.5: Stressed Dispatch with SPS Mitigation (Post-Contingency) Vaca Dixon to WindUnit_POI Constraint Figure 5.6: Traditional Power Flow (Pre-Contingency) Vaca Dixon to WindUnit_POI Constraint Figure 5.7: Traditional Power Flow (Post-Contingency) Vaca Dixon to WindUnit_POI Constraint Figure 5.8: Traditional Power Flow with SPS Mitigation (Post-Contingency) Vaca Dixon to WindUnit_POI Constraint Figure 6.1: Illustration of Generation Grouping for Panoche-Dos Amigos Flow Figure 6.2: Initial Dispatch (Pre-Contingency) Panoche to Dos Amigos Flow Figure 6.3: Initial Dispatch (Post-Contingency) Panoche to Dos Amigos Flow Figure 6.4: Stressed Dispatch (Pre-Contingency) Panoche to Dos Amigos Flow... Error! Bookmark not defined. Figure 6.5: Stressed Dispatch (Post-Contingency) Panoche to Dos Amigos Flow... Error! Bookmark not defined. ii

4 Generator Interconnection and Deliverability Study Methodology Figure 6.6: Stressed Dispatch with Mitigations for other Deliverability Constraints (Post-Contingency) Panoche to Dos Amigos Flow Figure 6.7: Traditional Power Flow Dispatch (Pre-Contingency) Panoche to Dos Amigos Flow... Error! Bookmark not defined. Figure 6.8: Traditional Power Flow Dispatch (Post-Contingency) Panoche to Dos Amigos Flow... Error! Bookmark not defined. Figure 6.9: Traditional Power Flow Dispatch with Mitigations for Other Deliverability Constraints (Post- Contingency) Panoche to Dos Amigos Flow Figure 7.1: Illustration of Generator Grouping for Lugo Victorville Constraint Figure 7.2: Initial Dispatch (Pre-Contingency) Lugo to Victorville Constraint Figure 7.3: Initial Dispatch (Post-Contingency) Lugo to Victorville Constraint Figure 7.4: Post-Dispatch of 1500 MW Generation (Pre-Contingency) Lugo to Victorville Constraint. 110 Figure 7.5: Post-Dispatch of 1500 MW Generation (Post-Contingency) Lugo to Victorville Constraint 111 Figure 7.6: Post-Dispatch of Facility Loading Adder (Pre-Contingency) Lugo to Victorville Constraint. 112 Figure 7.7: Post-Dispatch of Facility Loading Adder (Post-Contingency) Lugo to Victorville Constraint Figure 7.8: Post-Dispatch of Facility Loading Adder with Mitigation (Pre-Contingency) Lugo to Victorville Constraint Figure 7.9: Post-Dispatch of Facility Loading Adder with Mitigation (Post-Contingency) Lugo to Victorville Constraint Figure 7.10: Traditional Power Flow Dispatch (Pre-Contingency) Lugo to Victorville Constraint Figure 7.11: Traditional Power Flow Dispatch (Post-Contingency) Lugo to Victorville Constraint Figure 7.12: Traditional Power Flow Dispatch with Mitigation (Pre-Contingency) Lugo to Victorville Constraint Figure 7.13: Traditional Power Flow Dispatch with Mitigation (Post-Contingency) Lugo to Victorville Constraint Figure 8.1: Illustration of Generator Grouping for Lugo Eldorado Constraint Figure 8.2: Initial Dispatch (Pre-Contingency) Lugo to Eldorado Constraint Figure 8.3: Initial Dispatch (Post-Contingency) Lugo to Eldorado Constraint Figure 8.4: Post-Dispatch of 1500 MW Generation (Pre-Contingency) Lugo to Eldorado Constraint Figure 8.5: Post-Dispatch of 1500 MW Generation (Post-Contingency) Lugo to Eldorado Constraint. 136 Figure 8.6: Post-Dispatch of Facility Loading Adder (Pre-Contingency) Lugo to Eldorado Constraint Figure 8.7: Post-Dispatch of Facility Loading Adder (Post-Contingency) Lugo to Eldorado Constraint. 138 Figure 8.8: Post-Dispatch of Facility Loading Adder with Lugo Eldorado Upgrade (Pre-Contingency) Lugo to Eldorado Constraint Figure 8.9: Post-Dispatch of Facility Loading Adder with Lugo Eldorado Upgrade (Post-Contingency) Lugo to Eldorado Constraint Figure 8.10: Post-Dispatch of Facility Loading Adder with Lugo Eldorado Upgrade & Red Bluff Valley Line (Pre-Contingency) Lugo to Eldorado Constraint Figure 8.11: Post-Dispatch of Facility Loading Adder with Lugo Eldorado Upgrade & Red Bluff Valley Line (Post-Contingency) Lugo to Eldorado Constraint Figure 8.12: Traditional Power Flow Dispatch (Pre-Contingency) Lugo to Eldorado Constraint Figure 8.13: Traditional Power Flow Dispatch (Post-Contingency) Lugo to Eldorado Constraint Figure 8.14: Traditional Power Flow Dispatch with Lugo Eldorado Upgrade & Red Bluff Valley Line (Pre-Contingency) Lugo to Eldorado Constraint Figure 8.15: Traditional Power Flow Dispatch with Lugo Eldorado Upgrade & Red Bluff Valley Line (Post-Contingency) Lugo to Eldorado Constraint Figure 9.1: Illustration of Generator Grouping for Vincent 500/230kV Transformer Overload iii

5 Generator Interconnection and Deliverability Study Methodology Figure 9.2: Initial Dispatch (Pre-Contingency) South of Vincent Constraint Figure 9.3: Initial Dispatch (Post-Contingency) South of Vincent Constraint Figure 9.4: Stressed Dispatch (Pre-Contingency) South of Vincent Constraint Figure 9.5: Stressed Dispatch (Post-Contingency) South of Vincent Constraint Figure 9.6: Initial Dispatch after Removing Generators (Pre-Contingency) South of Vincent Constraint Figure 9.7: Initial Dispatch after Removing Generators (Post-Contingency) South of Vincent Constraint Figure 9.8: Stressed Dispatch after Removing Generators (Pre-Contingency) South of Vincent Constraint Figure 9.9: Stressed Dispatch after Removing Generators (Post-Contingency) South of Vincent Constraint Figure 9.10: Traditional Power Flow after Removing Generators (Pre-Contingency) South of Vincent Constraint Figure 9.11: Traditional Power Flow after Removing Generators (Post-Contingency) South of Vincent Constraint Figure 10.1: Illustration of Generator Grouping for Path 43 Constraint Figure 10.2: Initial Dispatch Path 43 Constraint Figure 10.3: Post-Dispatch of 1500 MW Generation Path 43 Constraint Figure 10.4: Post-Dispatch of Facility Loading Adder Path 43 Constraint Figure 10.5: Post-Dispatch of Facility Loading Adder with mitigation Path 43 Constraint Figure 10.6: Traditional Power Flow Dispatch Path 43 Constraint Figure 10.7: Traditional Power Flow Dispatch with Mitigation Path 43 Constraint iv

6 Generator Interconnection and Deliverability Study Methodology List of Tables Table II-1: Resource Dispatch Assumptions Table 1.1: Whirlwind 500/230kV Transformer Flows Deliverability Methodology Table 1.2: Whirlwind 500/230kV Transformer Flows Traditional Power Flow Approach Table 1.3: Grouping and Dispatch of Generators behind Whirlwind Transformers Table 2.1: Borrego Area Line Flows Deliverability Methodology Table 2.2: Borrego Area Line Flows Traditional Power Flow Approach Table 2.3: Grouping and Dispatch of Generators in Borrego Area Table 2.4: Grouping and Dispatch of Generators in Borrego Area Traditional Power Flow Approach Table 3.1: ECO 230/138 kv Transformer Flows Deliverability Methodology Table 3.2: ECO 230/138 kv Transformer Flows Off-Peak Study Table 3.3: Grouping and Dispatch of Generators in ECO/BUE Area Table 3.4: Dispatch of Generators in ECO/BUE Area Off-Peak Study Table 4.1: Imports and ETC Relevant to North of Lugo Constraints Table 4.2: Potential Overloads as North of Lugo Constraints Table 4.3: Kramer Lugo 230 kv No.1 & 2 Line Flows Deliverability Methodology Table 4.4: Kramer Lugo 230 kv No.1 & 2 Line Flow with Kramer Llano 500kV Upgrades Table 4.5: Grouping and Dispatch of Generators behind Kramer Lugo Constraint Table 5.1: Imports and ETC Relevant to PG&E North Study Area Table 5.2: Grouping and Dispatch of Generators behind the Vaca Dixon WindUnit_POI Constraint Table 5.3: Flow on the Vaca Dixon WindUnit_POI #3 line Table 5.4: Comparison of Available MW (Name Plate, Pmax) and Dispatched MW Table 5.5: Comparison of the deliverability and reliability study impact due to the WindUnit POI-Vaca Dixon #1 & #2 contingency Table 6.1: Imports and ETC Relevant to Fresno Study Area Table 6.2: Grouping and Dispatch of Generators behind Panoche-Dos Amigos Flow Table 6.3: Total Dispatch for Units in the 5% Circle versus Total Nameplate Values Table 6.4: Deliverability and Traditional Power Flow Loading Levels Table 7.1: Imports and ETC Relevant to Desert Area Constraints Table 7.2: Potential Overloads as Desert Area Constraints Table 7.3: Grouping and Dispatch of Generators behind by Lugo Victorville Constraint Table 7.4 Facility Load Adder (FLA) Calculation Table 7.5: Lugo Victorville Line Flow Deliverability Methodology Table 8.1: Imports and ETC Relevant to Desert Area Constraints Table 8.2: Potential Overloads as Desert Area Constraints Table 8.3: Grouping and Dispatch of Generators behind Lugo Eldorado Constraint Table 8.4: Facility Loading Adder (FLA) Calculation Table 8.5: Lugo - Eldorado Line Flow Deliverability Methodology Table 8.6: Lugo - Eldorado Line Flow with Upgrades Table 9.1: Imports and ETC Relevant to South of Vincent Constraint Table 9.2: Potential South of Vincent Overload Table 9.3: Grouping and Dispatch of Generators Constrained by Vincent 500/230kV Transformer Overload Table 9.4: Facility Loading Adder (FLA) Calculation Table 9.5: Vincent Transformer Bank Flow Deliverability Methodology Table 9.6: Generators Removed to Reduce Vincent Transformer Bank Loading v

7 Generator Interconnection and Deliverability Study Methodology Table 10.1: Imports and ETC Relevant to SDG&E Area Study Table 10.2: Potential Overload on Path Table 10.3 Facility Load Adder (FLA) Calculation Table 10.4: Path 43 Flow Deliverability Methodology Table 10.5: Path 43 Flow Traditional Study Methodology Table 10.6: Grouping and Dispatch of Generators behind Path 43 Constraint vi

8 Generator Interconnection and Deliverability Study Methodology Introduction Deliverability is an essential element of any resource adequacy requirement. Specifically, Load Serving Entities (LSEs) must be able to show that the supplies they intend to procure to meet their load requirements can be delivered to load when needed. Otherwise, such resources are of little, if any, value for the purposes of resource adequacy. The California Public Utilities Commission (CPUC) requires LSEs to demonstrate the deliverability of the resources they procure in both their annual resource plans and their longterm resource plans. An effective deliverability assessment is essential in short-term resources plans so that the LSEs will be able to count their resources to determine whether they satisfy the Commission s planning reserve margin. For long-term procurement planning, such an assessment additionally ensures that LSEs identify capacity needs that may be met by deliverable generation, or demand response but which require forward commitment to implement the desired solution, thus providing for an appropriate coordination between resource planning and transmission planning. The ISO deliverability methodology is the result of much stakeholder discussion. It was developed through a number of stakeholder meetings and conference calls during 2004 through It has been utilized since the serial group for ISO generation interconnection studies. However, for the serial group interconnection studies performed between 2006 and through 2008 the PTOs performed power flow studies and identified delivery transmission upgrades. The deliverability assessment was then performed on cases with those upgrades already modeled, so there were no major upgrades identified as needed by the deliverability assessment beyond what the PTOs had already identified. Starting with the Transition Cluster interconnection study in 2008, the deliverability study was used to identify all delivery network upgrades. The PTOs still identified upgrades beyond what the ISO identified but the ISO determined that congestion management could be used in lieu of upgrades identified by the PTOs but not required by the deliverability assessment. In both the serial interconnection studies and the Transition Cluster the deliverability study methodology generally identified the need for fewer upgrades than traditional study methodologies. However with the amount of generation in the queue five times the amount expected to actually be built, we still see significant transmission upgrades using the deliverability assessment methodology. The methodology relies on sophisticated generation dispatch tools and does not rely on a single snapshot power flow typically used in traditional methodologies, so it seems to be a mystery to some stakeholders. Some stakeholders seem to have attributed the cause of high transmission upgrade costs to the deliverability study methodology and expressed a need for the ISO to provide more detailed information on the methodology. This paper offers a detailed explanation of the ISO deliverability study methodology, and includes numerous detailed examples of the methodology being applied. As demonstrated by these examples, congestion management has been applied system wide as means to mitigate overloads identified under more stressed operating conditions than the deliverability assessment and SPS are used extensively to mitigate contingency overloads as long as the SPS design complies with the ISO new SPS guideline. This paper consists of three sections: Section One is background information on the basis for the methodology and an overview of the methodology. In this section references are provided 1

9 Generator Interconnection and Deliverability Study Methodology from FERC Order 2003 and the CPUC resource adequacy proceedings that highlight the basis for the methodology. This section also includes a description of the ISO generation interconnection reliability assessment that is performed along with the deliverability assessment. In addition to going over the generation deliverability assessment, this section will also briefly go over the import deliverability assessment. Section Two is a complete description of the methodology, and Section Three provides examples of the methodology being applied. 2

10 Generator Interconnection and Deliverability Study Methodology Section One: Background Information on the Basis for the Methodology and an Overview of the Methodology Background As part of developing its proposal to comply with FERC s Order No regarding the interconnection of new generating facilities, the ISO developed and proposed to FERC a deliverability test. The purpose was to assess the deliverability of new generation to serve load on the ISO s system. Experience at that time indicated that while California had added needed new generating capacity to the system, not all of that capacity was deliverable to load on the system because of the presence of transmission constraints. Therefore, although not requiring all new generation to be deliverable, the ISO proposed in its Order 2003 compliance filing to assess deliverability for those generators seeking to count for resource adequacy so that the sponsors of new generation projects could deliver the output of the new plants to the aggregate of load for resource adequacy counting purposes. During the stakeholder process developing the ISO deliverability test, a baseline analysis was performed by the ISO to demonstrate to stakeholders, in full detail, the test that would be conducted as part of this interconnection process. The deliverability test verifies a generating facility s ability to deliver its energy to load on the ISO Controlled Grid under peak load conditions and identifies the required Network Upgrades to enable the generating facility to deliver its full output to load on the ISO Controlled Grid based on specified study assumptions. That is, a generating facility s interconnection is studied with the ISO Controlled Grid at peak load, under a variety of severely stressed conditions to determine whether, with the generating facility at full output, the aggregate of generation in the local area can be delivered to the aggregate of load on the ISO Controlled Grid, consistent with the ISO s reliability criteria and procedures. (This definition for deliverability comes from the FERC interconnection order, and this methodology for assessing deliverability has been developed from consultation with PJM officials about their practices.) In addition, the ISO methodology, based on guidance in FERC Order 2003, ensures that the deliverability of a new resource is assessed on the same basis as all other existing resources interconnected to the ISO Controlled Grid. Because the deliverability assessment focuses on the deliverability of generation capacity when the need for capacity is the greatest (i.e. peak load conditions), it does not ensure that a particular generation facility will not experience congestion during other operating periods. Furthermore, as will be shown in the example study results, the deliverability test does not ensure that there will not be congestion during certain low probability, high generation dispatch conditions during the summer peak load period. Specific References from FERC Order 2003 and CPUC Resource Adequacy Proceeding The following references from FERC Order 2003 and the CPUC resource adequacy proceeding highlight the basis for the methodology. 3

11 Generator Interconnection and Deliverability Study Methodology FERC Order 2003 requires that two interconnection service options are offered: Energy Resource Interconnection Service (ERIS) and Network Resource Interconnection Service (NRIS). ERIS generation can compete in the ISO market against other generators. Paragraph 753 of FERC Order 2003 describes ERIS: ERIS would allow the Interconnection Customer to connect its Generating Facility to the Transmission System and be eligible to deliver its output using the existing capacity of the Transmission System on an "as available" basis. In an area with a bid-based energy market ERIS would allow the Interconnection Customer to place a bid to sell into the market and the Generating Facility would be dispatched if the bid is accepted. The ISO Tariff refers to this type of generation as Energy Only Deliverability Status (EODS) generation. EODS generation has a net qualifying capacity (NQC) for resource adequacy planning of zero. In other words EODS generation cannot be counted to meet the 115% planning reserve margin requirement. NRIS generation meets generation capacity planning requirements while satisfying regional reliability criteria 1. Paragraph 769 of FERC order 2003 describes NRIS: Network Upgrades required under NRIS integrate the Generating Facility into the Transmission System in a manner that ensures that aggregate generation can meet aggregate load while satisfying regional reliability criteria and generation capacity planning requirements. The ISO Tariff refers to this type of generation as Full Capacity Deliverability Status (FCDS) generation. FCDS generation meets generation capacity planning requirements while satisfying regional reliability criteria. FCDS generation can be counted to meet the 115% planning reserve requirement. CPUC Decision D adopted the CAISO s deliverability methodology to determine deliverability of qualifying resources. The CAISO published a preliminary deliverability baseline analysis report and conducted a stakeholder meeting in May 2005, after the Resource Adequacy Proceeding Phase 2 workshops were concluded 2. During the deliverability study, EODS generation is turned off, so that it does not impact the deliverability of full capacity generation. Some people have argued that it is not reasonable to dispatch the system with only FCDS resources. However these stakeholders are missing the point of the resource adequacy requirement. The ISO is required to be able to keep the lights on if resource adequacy resources were the only ones available, because by definition we can t count on the EODS resources even if these EODS resources have operated in the past instead of nearby FCDS resources. In most cases, generators choose to be EODS because they don t want to pay for transmission upgrades. As a result, EODS resources can only be reliably dispatched when they displace full capacity resources. If we counted on EODS resources and all FCDS resources for resource adequacy planning purposes we would not be able to dispatch both types of resources at the same time, and therefore we would not have a dependable resource supply in our resource plans. 1 FERC Order 2003 Paragraphs 768, 769 and Appendix C 2 CPUC Decision D

12 Generator Interconnection and Deliverability Study Methodology Although the transmission impacts of EODS generation and FCDS generation are studied much differently, Order 2003 requires that new FCDS generation is studied the same as all existing FCDS generation has been studied, as described in FERC Order 2003 Paragraph 768: NRIS entitles the Generating Facility to be treated in the same manner as the Transmission Provider's own resources for purposes of assessing whether aggregate supply is sufficient to meet aggregate load within the Transmission Provider's Control Area, or other area customarily used for generation capacity planning. In 2005 the ISO demonstrated through a stakeholder process that all existing resources could meet its deliverability assessment test methodology, except in a couple of locations where minor upgrades such as wave trap replacements were required. Order 2003 also requires that the transmission interconnection studies of FCDS generation are based on NERC Reliability Standards. The pro forma LGIP provided in FERC order 2003 describes the interconnection study to establish NRIS for a new generator as being based on peak load conditions and a variety of severely stressed conditions with the new generator and generators in the local area at full output. These assumptions are to ensure that the new generator can be delivered to the aggregate of load consistent with the applicable reliability criteria. In FERC Order 2003, Appendix C LGIP Section states the following: The Interconnection Study for NRIS shall assure that Large Generating Facility's interconnection is studied at peak load, under a variety of severely stressed conditions, to determine whether, with the Large Generating Facility at full output, the aggregate of generation in the local area can be delivered to the aggregate of load on the Transmission Provider s Transmission System, consistent with the Transmission Provider s reliability criteria and procedures. Specific References from NERC Reliability Standards Order 2003 requires that the transmission interconnection studies of FCDS generation are based on NERC Reliability Standards. Interconnection studies of FCDS generation include both a reliability assessment and a deliverability assessment. The reliability assessment is performed on both the EODS and FCDS generation, but the deliverability assessment is only performed on the FCDS generation. This section provides several references to the NERC reliability standards that apply to interconnection studies of both EODS and FCDS generation. The references describe the scope of the studies that must be performed. When reliability concerns are identified during the studies, corresponding mitigation plans must be identified. If the redispatch of generation through the ISO market (also known as congestion management) is determined to be feasible as a mechanism to mitigate the identified reliability concern then congestion management may be the identified mitigation plan. When congestion management is identified as feasible for EODS generation then it is generally the recommended mitigation. As described earlier, the deliverability methodology only addresses certain dispatch conditions during summer peak load conditions. If reliability concerns are identified during non-summer peak load conditions, or under generation dispatch conditions beyond those specified in the deliverability methodology, then congestion management is recommended as the mitigation, when it is feasible, for FCDS generation. NERC Reliability Standard FAC 002 Coordination of Plans for New Generation, Transmission, and End-User Facilities is an applicable reliability standard for generation interconnection studies. It requires steady-state, short-circuit, and dynamics studies as necessary to evaluate 5

13 Generator Interconnection and Deliverability Study Methodology system performance under both normal and contingency conditions in accordance with Reliability Standards TPL-001, TPL-002, and TPL-003. NERC Reliability Standard TPL 002 requires single contingency analysis, and NERC Reliability Standard TPL 003 requires common mode N-2 contingency analysis and bus outages. NERC Reliability Standard FAC 010 System Operating Limits Methodology for the Planning Horizon is also an applicable reliability standard for generation interconnection studies. It requires an analysis starting with all facilities in service and following any of the multiple contingencies identified in Reliability Standard TPL-003 the system shall demonstrate transient, dynamic and voltage stability; all facilities shall be operating within their facility ratings and within their thermal, voltage and stability limits; and cascading or uncontrolled separation shall not occur. NERC Reliability Standard TPL 003 requires common mode N-2 contingency analysis and bus outages. The system operating limits established in the planning horizon must be observed in generation deliverability studies. Mitigation of NERC Reliability Standard Compliance Concerns When reliability concerns are identified during the studies, corresponding mitigation plans must be identified. If the redispatch of generation through the ISO market (also known as congestion management) is determined to be feasible as a mechanism to mitigate the identified reliability concern then congestion management may be the identified mitigation plan. When congestion management is identified as feasible for EODS generation then it is generally the recommended mitigation. As we saw, Order 2003 intended EODS generation to compete with existing generation in order to get access to the transmission system. Therefore the use of congestion management to mitigate delivery constraints identified in EODS interconnection studies is expected. This is because EODS generation is expected to need to compete against generation in the local area to get access to the transmission system under most stressed system conditions. On the other hand, Order 2003 required that FCDS generation must be deliverable without displacing existing full capacity generation under summer peak load conditions. Therefore, FCDS generation must be deliverable along with the other FCDS generation in the local area during summer peak load conditions under a variety of severely stressed system conditions. As described earlier, the deliverability methodology only addresses certain dispatch conditions during summer peak load conditions. If reliability concerns are identified during non-summer peak load conditions, or under generation dispatch conditions beyond those specified in the deliverability methodology, then congestion management is recommended as the mitigation, when it is feasible, for FCDS generation. In EODS and FCDS interconnection studies the ISO and PTO perform short circuit and stability studies. We also perform power flow analysis to identify the need for upgrades if congestion management would not sufficiently mitigate the identified problem. In the FCDS interconnection studies we also perform a deliverability assessment. In addition to EODS and FCDS, the ISO also offers Partial Capacity Deliverability Status (PCDS) to generation. However for study purposes we can subdivide a partially deliverable generation project into an FCDS portion and an EODS portion and then study each portion accordingly. The interconnection customer is allowed to choose which level of service they want. A generation deliverability assessment will identify for the interconnection customer the required network upgrades needed for FCDS or PCDS. 6

14 Generator Interconnection and Deliverability Study Methodology Overview of the Methodology As discussed earlier, in 2004 and 2005 the ISO proposed the generation deliverability methodology to CPUC for Resource Adequacy purposes and to FERC for generator interconnection purposes. In 2005 the ISO completed a baseline generation deliverability assessment of all generation expected to be in operation during summer Also in 2005 the CPUC and FERC generally approved methodology for use in Resource Adequacy and Generator Interconnection processes, and in 2006 the ISO began applying deliverability methodology to new generator projects in the generator interconnection queue. The baseline generation deliverability assessment confirmed, using the ISO deliverability methodology that existing generating units in the ISO balancing area together with historical summer peak imports levels were deliverable. This study validated the methodology in an open stakeholder process. It also established evidence that the ISO applies the same methodology to both existing and planned generation. The methodology is based on the premise that FCDS resources within a given sub-area must be able to be exported to other parts of the balancing area experiencing a resource shortage due to forced generation outages. As stated earlier, this deliverability methodology is based on the PJM methodology and this fundamental concept is from the PJM methodology. Transmission Deliverability Analysis during a Resource Shortage Condition The purpose of the deliverability assessment methodology is to test the ability of the transmission system to export resources within a given sub-area to other parts of the balancing area experiencing a resource shortage. This test is a complex analysis of the transmission system under a variety of severely stressed generation dispatch conditions under summer peak load conditions when a resource shortage is most likely. The analysis is complex because there are roughly 25,000 Miles of transmission lines and hundreds of transmission transformers networked together to reliably deliver about 1000 geographically dispersed generating units to geographically dispersed load or to potentially constrain the deliverability of this generation, resulting in unserved customers. Figures I-1 and I-2 show the electric transmission network and the locations of the numerous electric generation resources in California. The loading on the transmission network depends entirely on the availability and dispatch of the generation resources. Under certain combinations of generation availability and dispatch the transmission system can be overloaded and the only way to prevent a transmission equipment failure is to reduce the dispatch of some of the generation. In a resource shortage scenario, if the generation must be reduced then some of the load cannot be served. Power system computer models of the transmission and generation system in Figures I-1 and I-2 are utilized to test numerous generation availability and dispatch scenarios during resource shortage conditions and the capability of the transmission system to accommodate these scenarios. 7

15 Generator Interconnection and Deliverability Study Methodology Transmission Lines in California Figure I-1: Electric transmission network in California Power Plants in California Figure I-2: Electric power plant locations in California 8

16 Generator Interconnection and Deliverability Study Methodology Resource shortage conditions are typically caused by a number of generation equipment mechanical failures on several large generating units or fuel interruptions during summer peak load conditions. During resource shortage conditions, all available generation capacity in the ISO balancing area is dispatched to avoid interrupting customer service. Figure I-3 depicts a typical resource shortage scenario. In the scenario shown, all generation in Pocket 1 is available and needs to be dispatched at full output to serve all customers in the ISO balancing area. Figure I-3: Depiction of resource shortage Scenario 1 in California 9

17 Generator Interconnection and Deliverability Study Methodology Figure I-4: Depiction of resource shortage Scenario 2 in California Figure I-4 shows another typical resource shortage scenario in California. In Scenario 2, all generation in Pocket 2 is available and needs to be dispatched at full output to serve all customers in the CAISO control area. The deliverability assessment methodology is designed to ensure that available generation in the various generation pockets, for all reasonable generation availability scenarios, will not be constrained by transmission limitations during resource shortages. One additional point is that, generally, the exact location of the set of generating unit outages, graphically represented by the small black squares, does not significantly change the results of the deliverability analysis of the generation pocket. The units forced out in Scenarios 1 and 2 are outside of the generation pocket study area, so their status and dispatch levels, in aggregate, do not significantly impact the results of the analysis within the study area. This is an important observation because there are literally hundreds of thousands of generation forced outage scenarios that can result in a resource shortage conditions. However, all of these scenarios can generally be represented, in a power system model, by evenly distributing the unavailable generation amount across all generating units in the ISO balancing area. Then, using that power system model, generation within a particular generation pocket can be tested for deliverability during all potential resource shortage conditions by maximizing the output of 10

18 Generator Interconnection and Deliverability Study Methodology the available generation within the generation pocket. This fundamental technique was learned from the PJM generation deliverability methodology. Overview of the Deliverability Analysis Testing Process The previous section describes the general approach for the deliverability methodology. This section builds on the concepts introduced in the previous section and describes additional concepts that need to be understood in order to understand the ISO deliverability methodology. At a high level, the test procedure can be thought of as the following three basic steps. First we build the initial power flow base case. Second, we utilize a commercially available software tool to perform generation sensitivity analysis to identify potentially limited generation pockets. At the most granular level, the sensitivity analysis identifies the exact generation facilities that have the highest flow impact on a particular transmission facility with all other facilities in-service and during forced outages of other facilities. Then the generation with the highest flow impact on that facility is increased a nominal amount to assess the potential for that facility to be overloaded under stressed system conditions. All ISO controlled facilities are analyzed to determine if they are limiting the deliverability of generation within the ISO deliverability methodology parameters. Initial Base Case Dispatch As described above, all generation is dispatched in the initial base case at close to maximum dependable capacity. The selected percentage dispatch below maximum capacity considers the average forced outage rates of the generators, spinning reserve, and unexpected retirement of generation capacity across the system. For the cluster studies we have been dispatching all generation at 80% of maximum dependable capacity. Because we are modeling a resource shortage scenario, it is assumed that all available generation is being dispatched, and due to the shortage condition, the incremental dispatch cost of generation is not affecting the dispatch. For the cluster studies, the amount of generation in the interconnection queue far exceeds the amount needed to achieve a load and resource balance. Therefore the queued generation is organized into geographic areas, and five to ten base cases are built with each case designed to focus on a particular geographic area. Then the queued generation in these areas is dispatched similar to the existing generation (e.g. 80% of dependable capacity). Identification of Generation Pockets Associated with Individual Transmission Facility Constraints As described above, each transmission line and transformer is analyzed individually starting from the initial base case dispatch. A study group is established for each line and transformer that includes all generation with a 5% distribution factor or greater on the particular line or transformer. The 5% distribution factor threshold is also used by PJM in their deliverability analysis methodology. For each analyzed facility, an electrical circle is drawn which includes all units that have a 5% or greater distribution factor (DFAX) on the facility being analyzed. The 5% Circle can also be referred to as the study group for the particular facility being analyzed. Capacity generation dispatch inside the study group is increased to determine the loading on the line or transformer under stressed system conditions. Generation outside the study group is proportionally decreased to maintain the balance between loads and resources. This process is intended to test the ability of available resources inside of the study group to be dispatched at full output when various resources across the ISO system are unavailable during a resource 11

19 Generator Interconnection and Deliverability Study Methodology shortage condition. Figure I-5 shows a sample system and the creation of a study group around the Gregg-Borden line. The distribution factor for each generator is shown and the dashed line is drawn around the generators with a 5% distribution factor or greater to show the generation pocket boundary. Note that increasing Helms output 100 MW and scaling the remaining generation in the ISO balancing area down by 100 MW will increase the flow on the line by 23 MW. Figure I-5: Depiction of a Study Group Based on the 5% Distribution Factor Threshold Generation Dispatch inside the Study Group The outputs of capacity units in the 5% Circle study group are increased starting with units with the largest impact on the transmission facility. The number of units to be increased within a group is limited to an amount of generation that can be reasonably expected to be simultaneously available, and the likelihood of all of the units within a group being available at the same time becomes smaller as the number of units in the group increases. The objective of the ISO deliverability methodology is to ensure that roughly 80% of the time, the transmission system will not constrain the output of generation in a study group during a resource shortage condition. The cumulative availability of twenty units with a 7.5% forced outage rate would be 21%. Therefore, no more than twenty units are increased to their maximum output within a study group. All remaining generation within the ISO balancing area is proportionally displaced, to maintain a load and resource balance. The amount of generation increased also needs to be limited because decreasing the remaining generation can cause problems that are more closely related to a generation deficiency in a load pocket rather than a generation pocket deliverability problem. Therefore, no more than a 1500 MW increment of generation is increased within a study group. 12

20 Generator Interconnection and Deliverability Study Methodology For groups where the 20 units with the highest impact on the facility can be increased more than 1500 MW, the impact of the remaining amount of generation to be increased will be considered using a Facility Loading Adder. The Facility Loading Adder is calculated by taking the remaining MW amount available from the 20 units with the highest impact times the DFAX for each unit. An equivalent MW amount of generation with negative DFAXs will also be included in the Facility Loading Adder, up to 20 units. Negative Facility Loading Adders are set to zero. Some of the examples in Section Three of the report show examples of the Facility Loading Adder. Import Assumptions California is now, and will likely remain, dependent on a significant level of imports to satisfy its energy and resource requirements. Therefore, it is likely that as part of fulfilling their obligation to procure sufficient resources (reserves) in the forward market to serve their respective loads, the LSEs will contract with out-of-state resources. This is appropriate and necessary. The ability to rely on imports to satisfy reserve requirements is entirely dependent on the deliverability of such out-of-state resources to and from the intertie points between the ISO s system and the neighboring systems. While the existing system may be able to satisfy the procurement plans of any one LSE, it likely will not be able to transmit the sum of LSEs needs. Each LSE may well plan to rely on the same potentially constrained transmission paths to deliver their out-of-state resources. Therefore, the transmission system should be checked to make sure that simultaneous imports can be accommodated. When relying on imports to serve load, each LSE should be required to ensure that they have assessed the deliverability of such resources from the tie point to load on the ISO s system. Transmission constraints can impact the simultaneous deliverability of imports and internal generation. As a result, the interaction between the deliverability of imports and the deliverability of generation needs to be examined. The ISO generation deliverability assessment includes, as an input assumption, the amount of imports and existing transmission contract related encumbrances electrically flowing over the ISO Controlled Grid. Whatever import capacity is available to LSEs for resource adequacy planning purposes is also the basis for the import assumptions in the internal generation deliverability analysis. Historical import information is the basis for determining the amount of import levels to be allocated to LSEs. In addition to using historical data, existing transmission contract information is also utilized. It is assumed that the entities that have contracted for the transmission capacity are already relying on this import capability in their resource plans, so this transmission is not reallocated. Generation Capacity Study Assumptions Existing generation dependable capacity is modeled in the deliverability study base cases based on their Net Qualifying Capacity posted on ISO website. The NQC is determined based on a methodology that generally sets the dependable capability of a generator close to its nameplate capability. However, for intermittent generation the NQC is based on its production level during summer peak load hours and therefore the NQC of intermittent generation can be substantially lower than nameplate capability. The qualifying capacity of intermittent generation is calculated based on a 70% exceedance methodology. A production duration curve is created for each intermittent generation project (e.g. wind and solar generation). An example curve is 13

21 Generator Interconnection and Deliverability Study Methodology shown in Figure I-6. From this curve one can identify the production level that is exceeded 70% of the time during the 100 hours included in the data. This is done for each generation project individually. Figure I-6: Example Production Duration Curve Showing 70% Exceedance Level However, a diversity adder is then added to the 70% exceedance level calculated for each project by itself. The diversity adder is calculated by adding the production of all wind and solar generation across the state for each summer peak load hour. Then the aggregate 70 % exceedance level is calculated for the entire state. The individual 70% exceedance levels are adjusted upwards so that the sum of NQC values of all intermittent generation is equal to the 70% exceedance value that was calculated for the entire state. The diversity adder captures the diversity value of intermittent generation across the state. Due to the nature of wind patterns, there can be strong winds in Southern California and no wind in Northern California, or it can be the other way around. Aggregating the intermittent generation in Northern California and Southern California results in a more reliable wind resource. However, the high wind production levels must be deliverable or this value is lost. Figure I-7 shows a simple diversity adder calculation example with two 100 MW wind plants. The blue and red curves are the production duration curve for Wind Plants 1 and 2 respectively, and the green curve is their combined production duration curve. Wind Plants 1 and 2 have a 70% exceedance level of 8 MW and 11 MW respectively. However, their combined 70 % exceedance level is 33 MW. Therefore each plant is given a diversity adder of 7 MW. As a result Wind Plant 1 and 2 have an NQC of 15 MW and 18 MW. 14

22 Generator Interconnection and Deliverability Study Methodology Figure I-7: Example Production Duration Curve Showing Combined 70% Exceedance Level An important consideration is that the diversity adder results in counting production levels from Wind Plants 1 and 2 that are higher than their NQC levels. Figure I-8 shows blue and red lines representing 24 hours, during the summer peak load period, of simultaneous production levels for Wind Plants 1 and 2 respectively. Hour number 10 in the Figure is highlighted in yellow because that hour is counted in the 70 % exceedance calculation for the combined output of both wind plants. The important point is that hour number 10 includes a production level from one of the wind plants that is about 33 MW which is about twice its NQC level. If the wind generation from Wind Plant 1 were constrained by the transmission in hour number 10 then the diversity benefit of the wind between Wind Plant 1 and 2 would be lost for that hour. Figure I-8: Example Production Curve Showing Production Levels Counted by the 70% Exceedance Level Calculation Another important consideration is that the 70% exceedance value methodology results in counting resources that are not available or derated 30% of the time. A typical resource is not available or derated about 5% to 10% of the time. However, as can be seen by Figure I-8 a 15

23 Generator Interconnection and Deliverability Study Methodology renewable resource produces much more than its NQC level. The production level above its NQC level compensates for the fact that it is unavailable or derated below its NQC level 30% of the time. However, if the production level above its NQC level and even above its diversity adder level is not deliverable then it cannot be depended upon to compensate for the high unavailability rate of the intermittent generation. In order to ensure that the production levels utilized in the diversity adder and production levels above the diversity adder that compensate for the high unavailability of intermittent generation the ISO tests the deliverability of intermittent generation at a 50% exceedance level and in some very specific and localized circumstances at a 20% exceedance level, during summer peak load hours. The 50% exceedance level is utilized for major constraints that have large amounts of generation behind the constraint, including a mix of conventional, solar, or wind. The 20% exceedance level is only utilized for very localized constraints with only wind or only solar generation behind the constraint. Using this methodology has resulted in ample deliverability for intermittent wind generation especially when compared to traditional power flow study methods. Participating transmission owners have criticized the ISO deliverability study assumptions for intermittent generation as taking too much risk and allowing too much generation to interconnect without transmission upgrades. Other stakeholders have made the opposite argument. Based on utilizing this method for over five years, the ISO believes it has found the appropriate balance of assumptions for studying the deliverability of intermittent generation. 16

24 Generator Interconnection and Deliverability Study Methodology Section Two: On-Peak Generation Deliverability Assessment Methodology Background The CAISO s deliverability study methodology for resource adequacy purposes was discussed extensively in the CPUC s Resource Adequacy Proceeding in 2004, and was generally adopted in that proceeding. It was also accepted by FERC as a reasonable implementation of LGIP Section 3.3.3, during the FERC Order 2003 compliance filing process. The paper describes the study methodology and provides detailed real system example studies where the methodology has been used. Example studies using traditional study methodologies, that were utilized before this deliverability study methodology was introduced, are also provided for comparison. A generator deliverability test is applied to ensure that capacity is not "bottled" from a resource adequacy perspective. This would require that each electrical area be able to accommodate the full output of all of its capacity resources and export, at a minimum, whatever power is not consumed by local loads during periods of peak system load. Export capabilities at lower load levels can affect the economics of both the system and area generation, but generally they do not affect resource adequacy. Therefore, export capabilities at lower system load levels are not assessed in this deliverability test procedure. Deliverability, from the perspective of individual generator resources, ensures that, under normal transmission system conditions, if capacity resources are available and called on, their ability to provide energy to the system at peak load will not be limited by the dispatch of other capacity resources in the vicinity. This test does not guarantee that a given resource will be chosen to produce energy at any given system load condition. Rather, its purpose is to demonstrate that the installed capacity in any electrical area can be run simultaneously, at peak load, and that the excess energy above load in that electrical area can be exported to the remainder of the control area, subject to contingency testing. In short, the test ensures that bottled capacity conditions will not exist at peak load, limiting the availability and usefulness of capacity resources for meeting resource adequacy requirements. In actual operating conditions energy-only resources may displace capacity resources in the economic dispatch that serves load. This test would demonstrate that the existing and proposed capacity units in any given electrical area could simultaneously deliver full energy output to the control area. The electrical regions, from which generation must be deliverable, range from individual buses to all of the generation in the vicinity of the generator under study. The premise of the test is that all capacity in the vicinity of the generator under study is required, hence the remainder of the system is experiencing a significant reduction in available capacity. However, since localized capacity deficiencies should be tested when evaluating deliverability from the load perspective, the dispatch pattern in the remainder of the system is appropriately distributed as proposed in Table 1. Failure of the generator deliverability test when evaluating a new resource in the generator interconnection study brings about the following possible consequences. If the addition of the resource will cause a deliverability deficiency, then the resource should not be fully counted 17

25 Generator Interconnection and Deliverability Study Methodology towards resource adequacy reserve requirements until transmission system upgrades are completed to correct the deficiency. A generator that meets this deliverability test may still experience substantial congestion in the local area. To adequately analyze the potential for congestion, various stressed conditions (i.e., besides the system peak load conditions) will be studied as part of the overall interconnection study for the new generation project. Depending on the results of these other studies, a new generator may wish to fund transmission reinforcements beyond those needed to pass the deliverability test to further mitigate potential congestion or relocate to a less congested location. The procedure proposed for testing generator deliverability follows. Study Objectives The goal of the proposed ISO Generator Deliverability Study Methodology is to determine if the aggregate of generation output in a given area can be simultaneously transferred to the remainder of ISO Control Area. Any generators requesting Full or Partial Capacity Deliverability Status in their interconnection request to the ISO Controlled Grid will be analyzed for deliverability in order to identify the Delivery Network Upgrades necessary to obtain this status. The ISO deliverability test methodology is designed to ensure that facility enhancements and cost responsibilities can be identified in a fair and nondiscriminatory manner. Baseline analysis In order to ensure that existing resources could pass this deliverability assessment, a Phase I Generation and Import Deliverability Study was completed that established the deliverability of all existing generation connected to the ISO Controlled Grid. This study included generation projects expected to be commercially operating during summer The study also established the deliverability of a specified level of imports that were tested during the generation deliverability test. All Full or Partial Capacity Generation Status generation projects interconnected to the ISO system since 2006 and planned to be interconnected to have also been tested using this deliverability assessment methodology. However, during the period from approximately 2006 through 2008, this deliverability study methodology was not utilized to identify the need for delivery network transmission upgrades. During that time frame, generation interconnection projects were studied serially rather than in clusters and the PTOs utilized traditional study methodologies to identify the need for delivery network upgrades. The deliverability study methodology was then utilized to verify that the PTO identified upgrades were sufficient to pass the deliverability test. Because the traditional methodologies tended to be more conservative the identified upgrades were always more than sufficient to mitigate the identified delivery constraints. However, because the deliverability methodology utilizes more sophisticated tools which systematically create thousands of moderately stressed scenarios, the deliverability methodology would sometimes identify additional constraints that would need to be mitigated. Traditional study methodologies would only consider a few stressed scenarios but would compensate for the limited number of scenarios by overstressing the system. Starting in approximately 2009, the deliverability methodology was exclusively utilized to identify needed delivery network upgrades that are needed to ensure that all existing and new FCDS or PCDS generation would be deliverable for resource adequacy planning purposes. 18

26 Generator Interconnection and Deliverability Study Methodology General Procedures and Assumptions Step 1: Electrically organize into study areas the proposed new generation units that are to be tested for deliverability. These electrical areas will be based on engineering knowledge of the transmission system constraints on existing and new generation dispatch. Generating units will be organized by transmission limitations that will be expected to constrain the generation. Base cases will be built that focus on each area. Because the total MW of proposed generation usually exceeds the amount that is needed to balance loads and resources, several base cases may need to be created, each of which will focus on at least one of the areas. If an area is not the focus, then generation in that area may be dispatched at zero, but will be available to be turned on during the analysis. Step 2: For each base case created in step 1, dispatch ISO resources and imports as shown in Table II-1. This base case will be used for two purposes: (1) it will be analyzed using a DC transfer capability/contingency analysis tool to screen for potential deliverability problems, (2) it will be used to verify the problems identified during the screening test, using an AC power flow analysis tool. Step 3: Using the screening tool, the ISO transmission system is essentially analyzed facility by facility to determine if normal or contingency overloads can occur. For each analyzed facility, an electrical circle is drawn which includes all units (including unused Existing Transmission Contract (ETC) injections) that have a 5% or greater distribution factor (DFAX) or Flow Impact 3 on the facility being analyzed. Then load flow simulations are performed, which study the worstcase combination of generator output within each 5% Circle. The 5% Circle can also be referred to as the study group for the particular facility being analyzed. Step 4: Using an AC power flow analysis tool and post processing software, verify and refine the analysis of the overload scenarios identified in the screening analysis. The outputs of capacity units in the 5% Circle are increased starting with units with the largest impact on the transmission facility. No more than twenty 4 units are increased to their maximum output. In addition, no more than 1500 MW of generation is increased. All remaining generation within the Control Area is proportionally displaced, to maintain a load and resource balance. The number of units to be increased within a group is limited because the likelihood of all of the units within a group being available at the same time becomes smaller as the number of units in the group increases. The amount of generation increased also needs to be limited because decreasing the remaining generation can cause problems that are more closely related to a generation deficiency in a load pocket rather than a generation pocket deliverability problem. 3 See note on Flow Impact in Section 4.1 Specific Assumptions. The electrical circle drawn which includes all generators that have a 5% or greater distribution factor (DFAX) or Flow Impact on the facility being analyzed is referred to as the 5% Circle. 4 The cumulative availability of twenty units with a 7.5% forced outage rate would be 21%--the ISO proposes that this is a reasonable cutoff that should be consistently applied in the analysis of large study areas with more than 20 units. Hydro units that are operated on a coordinated basis because of the hydrological dependencies should be moved together, even if some of the units are outside the study area, and could result in moving more than 20 units. 19

27 Generator Interconnection and Deliverability Study Methodology For groups where the 20 units with the highest impact on the facility can be increased more than 1500 MW, the impact of the remaining amount of generation to be increased will be considered using a Facility Loading Adder. The Facility Loading Adder is calculated by taking the remaining MW amount available from the 20 units with the highest impact times the DFAX for each unit. An equivalent MW amount of generation with negative DFAXs will also be included in the Facility Loading Adder, up to 20 units. Negative Facility Loading Adders should be set to zero. Step 5: Once the initially identified overloaded facilities are verified, all new generators inside the 5% Circle are responsible for mitigating the overload. Once a mitigation plan has been identified it will be modeled and the deliverability assessment will be repeated to demonstrate that all of the new generation is deliverable with the mitigation plan modeled. Mitigation plans may be identified that address multiple constraints and this can result in combining several study groups into one larger group responsible for the cost of the mitigation. If additional overloaded facilities are found, then the mitigation plan will be modified or expanded, as needed, to ensure the deliverability of the new generation. 20

28 Table II-1: Resource Dispatch Assumptions Resource Type Base Case Dispatch Available to Selectively Increase Output for Worst-Case Dispatch? Existing Capacity Resources (Note 1) Proposed Capacity Resources (Note 2) Energy-Only Resources Imports (Note 3) 80% to 95% of Summer Peak Net Qualified Capacity (NQC) Y Up to 100% of NQC 80% to 95% of Summer Peak Qualified Capacity (QC) Y Up to 100% of QC Minimum commitment and dispatch to balance load and N maintain expected imports Maximum summer peak simultaneous historical net imports by branch group Load Non-pump load 1 in 5 simultaneous peak load level for CAISO. N N Pump load Within expected range for Summer peak load hours (Note 4). N N Available to Scale Down Output Proportionally with all Control Area Capacity Resources? Y Note 1: All existing FCDS and PCDS units should be dispatched at the same percentage of their unconstrained Net Qualified Capacity, but this level may fluctuate to account for differing expectations of system-wide forced outages, retirements, and spinning reserve levels. Some units with a high likelihood of retirement within the near future may be dispatched at zero to balance loads and resources, but will be available to be turned on during the analysis. See discussion on Wind and other Intermittent Generation in Section 4.1 Specific Assumptions. Note 2: Proposed FCDS and PCDS resources will be organized electrically into study areas. Base cases will be developed that focus on each of the study areas. If a study area is not the focus, it may be dispatched at zero in that case. Note 3: Maximum summer peak simultaneous historical net imports by branch group are the basis for determining the maximum import capability that can be allocated for resource adequacy purposes. Historically unused ETCs will be considered during the analysis, but will not be simultaneously represented in the base case. Historically unused Existing Transmission Contracts (ETC s) crossing control area boundaries will be modeled as zero MW injections at the tie point, but available to be turned on at remaining contract amounts for screening analysis. For historically congested import paths expected to be increased by upgrades with all regulatory approvals in place, the portion of the incremental upgrade expected to be utilized immediately during summer peak can also be represented in the analysis similar to unused Existing Transmission Contracts. During the base case development, import flows on Branch Groups electrically remote from the generation group, that is the focus of the base case being created in Steps 1 and 2, can be moderately reduced to balance loads and resources. Note 4: Summer peak load hours are approximately the 50 to 100 hours in the months of August and September when Control Area load is between 90% and 100% of maximum annual load. N Y 21

29 Specific Assumptions Distribution Factor (DFAX) Percentage of a particular generation unit s incremental increase in output that flows on a particular transmission line or transformer when the displaced generation is spread proportionally, across all dispatched resources available to scale down output proportionally with all control area capacity resources in the Control Area, shown in Table II-1. Generation units are scaled down in proportion to the dispatch level of the unit. G-1 Sensitivity A single generator may be modeled off-line entirely to represent a forced outage of that unit. This is consistent with the ISO Grid Planning Standards that analyze a single transmission circuit outage with one generator already out of service and system adjusted as a NERC level B contingency. System adjustments could include increasing generation outside the study area. The number of generators increased outside the study area should limited to 20. Municipal Units Treat like all other Capacity Resources unless existing system analysis identifies problems. Energy-Only Resources If it is necessary to dispatch Energy Resources to balance load and maintain expected import levels, these units should not contribute to any facility overloads with a DFAX of greater than 5%. Energy Resource units should also not mitigate any overloads with a DFAX of greater than 5%. WECC Path Ratings All WECC Path ratings (e.g. Path 15 and Path 26) must be observed during the deliverability test. Flow Impact Generators that have a Flow Impact (DFAX*Generation Capacity) > 5% of applicable facility rating or OTC will also be included in the Study Area. Wind and other Intermittent Generation When this deliverability methodology was created, the Qualified Capacity of intermittent generation was calculated as the average production between the hours of 12PM-6PM, during the months of May through September (QC period). In order to ensure the deliverability during this entire QC period this generation may be dispatched over the range of production levels that are included in the QC calculation. If the intermittent generation is electrically grouped with other types of generation, then the cumulative availability of this generation will determine how much the intermittent generation can be increased during the deliverability analysis. For example, if only wind generation is in the group (scenario 1), then it will be increased to the production level expected to be exceeded less than 20% of the time for that group during the QC period. If 20 or more non-wind generation units are in the group (scenario 2), then the wind generation would not be increased above its average output during the QC period. The maximum wind 22

30 generation output level would be interpolated for groups in between the two scenarios above. If wind and intermittent solar generation are both significantly represented in the group, then a scenario with average production during the QC period, for both types will be assessed. Voltage and Stability Problems If the delivery of output from proposed new generation projects results in voltage or stability problems under generation dispatch scenarios consistent with this procedure, then these problems must be mitigated in order to ensure the deliverability of these new generation projects. 23

31 Section Three: Examples of Application of Deliverability Assessment Methodology This section provides step by step detail of how the CAISO generation and import Deliverability Assessment is performed illustrating example deliverability constraints and the groups of generation identified under different practical scenarios. These examples are derived from some recent deliverability assessments performed for the generation interconnection and transmission planning processes. Although the deliverability assessment methodology is performed the same way for all example constraints and generation groups behind those constraints, some elements of the methodology do not apply for all examples. To facilitate understanding, the examples are generally presented in increasing order of complexity. Example 1 is one of the simplest examples. In this example, there are 17 generation projects representing 3759MW of Tehachapi area solar and wind generation radially connected through three ISO controlled 500/230kV transformer banks. The total capacity of three 500/230kV transformer banks is 3360MW, which is less than the installed capacity generation that can flow through the transformer banks. The example shows that all of the generation is fully deliverable based on the deliverability methodology but that using a traditional study methodology the transformers show an 11% overload. However congestion management would be used to mitigate the 11% overload, and all of the generation could still be counted for resource adequacy. Example 2 is similar to example 1 except that it includes some energy only deliverability status (EODS) generation. In this example, there are three generation projects representing 51 MW of solar generation in the Borrego area radially connected through two ISO controlled 69 kv lines in series. Twenty MW of the 51 MW is EODS, and the remaining 31 MW is FCDS generation. The example shows that all of the FCDS generation is fully deliverable based on the deliverability methodology, but with all of the generation producing the lines show a 58% overload. However congestion management would be used to mitigate the 58% overload, and all of the FCDS generation could still be counted for resource adequacy. The EODS generation could not, by definition, be counted for resource adequacy. Example 3 is also a radial system example with generation connected in a small geographic area. In this example, there are twelve generation projects representing 674 MW of wind and solar generation in the South San Diego area radially connected through an ISO controlled 230/138 kv transformer in series with a 138 kv line. The transformer capability is insufficient based on the deliverability methodology and a second transformer is identified as needed. However, this example also shows that during the off-peak period, the 138 kv line can be overloaded by 10%, and congestion management is needed to mitigate this overload. However, the generation is still considered deliverable for resource adequacy purposes in spite of the need for congestion management. Example 4 examines a more complex system than the first three examples because it covers a much larger geographical area even though it is served by a sparse electrical network, and the system is mostly electrically radial from the rest of the ISO system. In 24

32 this example, there are 57 generation projects and existing generating units identified behind the constraint representing 3101 MW of a mix of generating types in the North of Lugo area. This example shows that, according to the deliverability methodology, only 20 of the generating units are assumed to be producing based on their maximum dependable output level, and the remaining 37 generating units are at a reduced output level. Two 230 kv lines are shown to be overloaded with all lines in-service, and a new 500 kv line is identified as needed to mitigate the deliverability constraint. With the mitigation modeled and using a traditional study methodology a 500/230 kv transformer is identified as overloaded and requires congestion management to mitigate the overload. However, all of the generation in the generation group is deliverable for resource adequacy purposes once the mitigation is in-place in spite of the need for congestion management under more stressed generation output conditions. Example 5 examines a deliverability constraint affecting a group of generation spread over a large geographic area served by a part of the ISO system that is in parallel with the rest of the ISO system in Northern California. In this example, there are 91 generation projects and existing generating units identified behind the constraint representing 3876 MW of a mix of generating types in the northern California area. This example again shows that only 20 of the generating units are assumed to be producing based on their maximum dependable output level and the remaining 71 generating units are at a reduced output level. The study focuses on the addition of one wind generation project that is part of the queue cluster study and is in the study group behind the identified constraint. The addition of the wind project overloads a 230 kv line during a contingency of both circuits on a parallel double circuit tower-line. Disconnecting the wind generation project during the contingency via a special protection system is identified as the recommend mitigation to ensure the deliverability of the wind generation project along with the previously queued and existing generation in the group behind the constraint. Example 6 is similar to example 5 in that it examines a large geographic area in parallel with the rest of the ISO system, but is in central California. In this example, there are 95 generation projects and existing generating units identified behind the constraint representing 5288 MW of a mix of generating types in the central California area. This example again shows that only 20 of the units are assumed to be producing based on their maximum dependable output level and the remaining 75 generating units are at a reduced output level. The potential constraint is a 230 kv line overloaded by a contingency of a parallel 230 kv line. However, the results of applying the deliverability methodology indicated that the generation was not constrained and no mitigation was needed. However, utilizing a traditional study methodology the 230 kv line was 128% loaded and requires congestion management to mitigate the overload. However, all of the generation in the generation group is deliverable for resource adequacy purposes in spite of the need for congestion management under more stressed generation output conditions. Example 7 is first of the most complex examples provided. In this example, there are 165 generation projects and existing generating units identified behind the constraint representing MW of a mix of generating types in the southwestern desert area of California and ISO controlled portions of the adjacent states. Deliverability of imported power from the adjacent states is also affected by the constraint in this example whereas in the previous six examples import deliverability was not affected by the constraint. This example shows that only two generating units are increased to their maximum 25

33 dependable output level because according to the methodology no more than 1500 MW of generation can be increased. However, as described in Step 4 of the deliverability methodology described in Section 2 of this paper a facility loading adder study mechanism is triggered when the 1500 MW limit is reached. The facility loading adder calculation is shown in detail in this example. This example is also the only example that is derived from the transmission planning process. Example 8 is similar to Example 7 except that Example 8 is based on the generation interconnection process. This example also demonstrates how the delivery network upgrades are identified and then removed per Technical Bulletin for QC1 ~ QC4. Example 9 is a complex example of the South of Vincent constraint that limits the deliverability of generation in Tehachapi area and PG&E area, as well as import from Northwest to PG&E. In this example, the facility loading adder calculation is triggered. But the net flow impact from the facility loading adder is 0. Example 10 is a complex example of the San Diego area. It is the only example where the deliverability constraint is a WECC Path Rating. 26

34 1. Whirlwind Example SCE s Whirlwind Substation is a generation collector substation in Tehachapi. There is 3759MW generation interconnection at Whirlwind in the queue. Based on the deliverability assessment, three 500/230kV transformer banks are identified in the current plan. The total capacity of three 500/230kV transformer banks is 3360MW, which is less than the installed capacity generation that must be delivered through the transformer banks. Therefore, congestion will occur when the total available output exceeds the level tested by the deliverability assessment and the generation will be curtailed. Step 1: General study area The Whirlwind substation is in the SCE Northern Area as shown in Figure 1.1. For purposes of this example the SCE Northern Area is established as the study area as described in Step 1 of the methodology. SCE Northern Area includes Big Creek area, Ventura area and Tehachapi area that are north of Vincent. Step 2: Initial dispatch All generators in SCE Northern Area are initially dispatched to 80% of PMAX according to the methodology. In this example, PMAX s represent the average production during the QC period for both wind or solar generators in the area, which are 40% of installed capacity for wind generators and 85% for solar generators. The initial flows on the transformer banks are shown in Table 1.1 and Figure 1.2. Step 3: Grouping of generators There are three Whirlwind 500/230kV transformers modeled. All the generators connecting to the Whirlwind 230kV bus form the 5% Circle for the transformer normal condition loading. Each generator has 33% DFAX on one of the transformers. Grouping of the generators are shown in Figure 1.1 and Table 1.3. Step 4: Stressed Dispatch As described in Step 4 of the methodology, generators inside the 5% Circle are dispatched to PMAX. The stressed power flow is shown in Figure 1.3 and Table 1.1. Table 1.1: Whirlwind 500/230kV Transformer Flows Deliverability Methodology Facility Contingency Initial Flow Stressed Flow Whirlwind 500/230kV Base Case 57% 71% Transformer No. 1, 2 or 3 Step 5: Mitigation Using the deliverability assessment methodology, the Whirlwind transformer capacity is not a binding deliverability constraint in this example. Although the total installed 27

35 generation capacity exceeds the transformation capacity, the generators were found to be deliverable for RA purpose due to the methodology appropriately taking into account the complementary nature of wind and solar intermittent generation. As specified in Section 2 the wind and the solar are both modeled at their individual 50% exceedance production level during the summer peak load period. Therefore, the 4 th Whirlwind 500/230kV transformer bank is not required. If a traditional power flow approach were to be used, the 4 th Whirlwind 500/230kV transformer bank would have been required to mitigate the normal condition overloads of Whirlwind transformer banks. The traditional dispatch is shown in Figure 1.4 and Table 1.2. Table 1.2: Whirlwind 500/230kV Transformer Flows Traditional Power Flow Approach Facility Contingency Stressed Flow Whirlwind 500/230kV Base Case 111% Transformer No. 1, 2 or 3 28

36 Midway Vincent Windhub Antelope 500kV Whirlwind 230kV Midway generators SCE Northern Area Highwind Whirlwind Windhub Antelope Vincent Lugo Mira Loma LEGEND 500 kv Facilities 230 kv Facilities 5% DFAX Circle Figure 1.1: Illustration of Generator Grouping for Whirlwind Transformer Bank Flows 29

37 # DFAX Table 1.3: Grouping and Dispatch of Generators behind Whirlwind Transformers Flow Impact Generator Name Plate Pmax Initial Dispatch Stressed Dispatch Renewable Zone Technology Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Total Solar Wind Type 30

38 Figure 1.2: Initial Dispatch Whirlwind Transformers 31

39 Figure 1.3: Stressed Dispatch Whirlwind Transformers 32

40 Figure 1.4: Traditional Power Flow Dispatch Whirlwind Transformers 33

41 2. Borrego Area Example Borrego Substation in the SDG&E area is radially connected to the ISO system through two ISO controlled 69kV lines in series. There are 51MW of new generation interconnecting to the Borrego Substation, among which 31MW is Full Capacity Deliverability Status (FCDS) generation and 20MW is Energy Only Deliverability Status (EODS) generation. This example shows that the FCDS generation is fully deliverable, based on the deliverability methodology. However, congestion management is needed to make sure the two 69kV lines are not overloaded with the inclusion of all 51MW of generation. Step 1: General study area For purposes of this example the SDG&E area is established as the general study area as described in Step 1 of the methodology. Step 2: Initial dispatch ISO generation resources and imports are dispatched as described in Step 2 of the methodology. In this example, the study group is found to have only solar generation. Therefore, the Pmax data for the intermittent generation is set to a 20% exceedance production level during summer peak load hours when identifying the Borrego area constraints, which is 100% of the nameplate for the solar generation. Details of the initial dispatch of generation are provided in Table 2.3 below. Step 3: Grouping of generators During the DC power flow screening, there are no overloads identified for the Borrego area generators. However, since the traditional study methodology identified constraints in this area, a comparison of the different approaches used is shown below. As described in Step 3 of the methodology, the study identifies the generators with 5% or higher flow distribution factor (5% Circle) on Borrego-Narrows 69 kv line under normal condition with all lines in service. Table 2.3 lists all the generators that are in the 5% Circle. The renewable generators are listed at the point of interconnection in Table 2.3. The grouping of the generators is also illustrated in Figure 2.1. Step 4: Stressed Dispatch As described in Step 4 of the methodology, generation units with the highest flow impact on the constraint are then dispatched to Pmax until 20 units are dispatched or 1500 MW of generation is increased. In this example, neither of these limits are reached. The power flow plots for the initial and stressed cases are shown in Figure 2.2 and Figure 2.3. As the result of the stressed dispatch, the Borrego-Narrows 69 kv line is still under 100% of its normal rating. Therefore, there are no deliverability constraints identified due to Borrego area generators. 34

42 Table 2.1: Borrego Area Line Flows Deliverability Methodology Overloaded Facility Contingency Initial Flow Stressed Flow Borrego-Narrows 69 kv Base Case 56% 82% Narrows-Warners 69 kv Base Case 44% 66% If a traditional study methodology is used, EO generators as well as FC generators will both be dispatched in this area. Table 2.4 shows the generation that is dispatched in this case. Table 2.2 shows the loading on the lines using traditional study methodology. Table 2.2: Borrego Area Line Flows Traditional Power Flow Approach Overloaded Facility Contingency Stressed Flow Borrego-Narrows 69 kv Base Case 158% Narrows-Warners 69 kv Base Case 132% Figure 2.4 shows the power flow on the system using traditional study methodology. Step 5: Mitigation As described in Step 5 of the methodology a mitigation plan needs to be identified and tested to ensure that it allows the new generation to pass the deliverability test. Since there are no deliverability constraints identified in this area, there are no DNUs identified for the projects. The overloads identified using the traditional study methodology can be mitigated by using congestion management. A dispatch limit needs to be enforced using congestion management mechanisms in the ISO market to ensure that the flow on Borrego-Narrows 69 kv line does not exceed its normal rating. 35

43 Warners Borrego DFAX=100% Lilac Rincon SDG&E Borrego Area Valley Center Creelman Santa Ysabel Narrows Boulder Creek Tap LEGEND 69 kv Facilities Overload x Contingency 5% DFAX Circle Figure 2.1: Illustration of Generator Grouping for Borrego Area 36

44 Table 2.3: Grouping and Dispatch of Generators in Borrego Area Type # DFAX Flow Impact Generator Name Plate Pmax Initial Dispatch Stressed Dispatch Renewable Zone Technology BORREGO Non-CREZ Solar PV Queued BORREGO Non-CREZ Solar PV Queued Total Table 2.4: Grouping and Dispatch of Generators in Borrego Area Traditional Power Flow Approach # Generator Name Plate Stressed Dispatch Renewable Zone Technology Type Queued- BORREGO Non-CREZ Solar PV FCDS Queued- BORREGO Non-CREZ Solar PV FCDS Queued- BORREGO Non-CREZ Solar PV EODS Total

45 % MW Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED Borrego % Figure 2.2: Initial Dispatch Borrego Area 38

46 % MW Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED Borrego % Figure 2.3: Stressed Dispatch Borrego Area 39

47 % MW Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED Borrego % Figure 2.4: Traditional Power Flow Dispatch Borrego Area 40

48 3. ECO/BUE Area Deliverability Constraint and Mitigation Example SDG&E s East County Substation (ECO)/Boulevard (BUE) area is a local radial system connected to the ISO system through an ISO controlled 230/138kV transformer in series with a 138kV line. There are 674MW of wind and solar generation interconnecting in the ECO/BUE area. Based on the deliverability assessment methodology, the transformer bank capacity is insufficient and a second transformer bank is needed. Under the offpeak condition, the 138kV line could also be overloaded with the inclusion of the 674MW of new generation. Congestion management is needed to make sure the line is not overloaded. Step 1: General study area For purposes of this example the SDG&E was established as the study area as described in Step 1 of the methodology. Step 2: Initial dispatch For example purposes, the study model for this deliverability assessment is generally built upon the peak power flow base case used in a recent cluster study. ISO generation resources and imports are dispatched as described in Step 2 of the methodology. Since the study group is found to have a mix of wind and solar generation, the Pmax data for the intermittent generation is set to a 50% exceedance production level during summer peak load hours when identifying the ECO/BUE area constraints, which is 40% of the nameplate for the wind generation and 85% of nameplate for solar generation. Details of the Initial Dispatch of generation are provided in Table 3.3 below. During the DC power flow screening, there was an N-0 overload identified on the ECO 230/138 kv transformer. Step 3: Grouping of generators As described in Step 3 of the methodology, the study identified generators with a 5% or higher flow distribution factor (5% DFAX) on the ECO 230/138 kv transformer with all transmission facilities in-service. Table 3.3 lists all the generators that are in the 5% Circle. The new generators are listed at the point of interconnection in Table 3.3. The grouping of the generators is also illustrated in Figure 3.1. Step 4: Stressed Dispatch As described in Step 4 of the methodology, generation units with the highest flow impact on the constraint are then dispatched to Pmax until 20 units are dispatched or 1500 MW of generation is increased. In this example, neither of these limits is reached. The power flow plots for the initial and stressed cases are shown in Figure 3.2 and Figure

49 As the result of the stressed dispatch, the ECO 230/138 kv transformer is above 100% of its normal rating. This overload would need to be mitigated by adding a second ECO 230/138 kv transformer. Table 3.1: ECO 230/138 kv Transformer Flows Deliverability Methodology Overloaded Facility Contingency Initial Flow Stressed Flow ECO 230/138 kv Base Case 83% 103% ECO-BUE 138 kv line Base Case 27% 34% Step 5: Mitigation As described in Step 5 of the methodology a mitigation plan needs to be identified and tested to ensure that it allowed the new generation to pass the deliverability test. To mitigate the normal overload on ECO 230/138 kv transformer, a second transformer is added to the model. Figure 3.4 shows the power flow on the system with mitigation. An off-peak deliverability study is then performed for informational purposes only. During the off-peak study, wind generation is dispatched to 100% of nameplate and solar generation is dispatched to 85% of nameplate. The mitigation needed in the peak deliverability study is modeled in the off-peak study. Table 3.2 shows the results of the off-peak study. Table 3.2: ECO 230/138 kv Transformer Flows Off-Peak Study Overloaded Facility Contingency Stressed Flow ECO 230/138 kv #1 Base Case 78% ECO 230/138 kv #2 Base Case (mitigation for peak study) 78% ECO-BUE 138 kv line Base Case 110% The off-peak study identified an N-0 overload on ECO-BUE 138 kv line that is not seen in the on-peak deliverability study. Since the off-peak study is for informational purposes only, no mitigation is required for this overload to obtain FCDS. This overload is expected to be mitigated by congestion management. Figure 3.5 shows the power flow for the off-peak study. 42

50 Suncrest Ocotillo Miguel SDG&E ECO/BUE Area ECO 500 kv ECO 230 kv Imperial Valley North Gila Boulevard East 138 kv DFAX=100% ECO 138 kv Existing 500 kv Facilities Facilities under construction, CPUC Approved, or Upgrades Triggered by Higher Queued Projects Overload 5% DFAX Circle Figure 3.1: Illustration of Generator Grouping for ECO/BUE Area 43

51 # DFAX Flow Impact Generator Table 3.3: Grouping and Dispatch of Generators in ECO/BUE Area Name Plate Pmax Initial Dispatch Stressed Dispatch Renewable Zone Technology Type BOULEVRD San Diego South Wind Queued BOULEVRD San Diego South Wind Queued ECO San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued ECO San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued Total Wind Solar

52 Table 3.4: Dispatch of Generators in ECO/BUE Area Off-Peak Study # Generator Name Plate Stressed Dispatch Renewable Zone Technology 1 BOULEVRD San Diego South Wind 2 BOULEVRD San Diego South Wind 3 ECO San Diego South Solar PV 4 BOULEVRD San Diego South Solar PV 5 BOULEVRD San Diego South Solar PV 6 BOULEVRD San Diego South Solar PV 7 ECO San Diego South Solar PV 8 BOULEVRD San Diego South Solar PV 9 BOULEVRD San Diego South Solar PV 10 BOULEVRD 5 4 San Diego South Solar PV 11 BOULEVRD 5 4 San Diego South Solar PV 12 BOULEVRD 3 3 San Diego South Solar PV Total Wind Solar

53 % MW Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED ECO/BUE 138/69 kv % Figure 3.2: Initial Dispatch ECO/BUE Area 46

54 % MW Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED ECO/BUE 138/69 kv % Figure 3.3: Stressed Dispatch ECO/BUE Area 47

55 % MW Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED ECO/BUE 138/69 kv % Figure 3.4: Stressed Dispatch with Mitigation ECO/BUE Area 48

56 % MW Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED ECO/BUE 138/69 kv % Figure 3.5: Off-Peak Study ECO/BUE Area 49

57 4. North of Lugo Deliverability Constraints and Mitigations Example The North of Lugo Area refers to generating resources electrically located in the following renewable energy zones: Inyokern, Kramer, Victorville, Barstow, San Bernardino-Lucerne, Pisgah, and Nevada-C. It is a large geographical area served by a sparse electrical network and mostly radial from the rest of the ISO system. Various deliverability constraints have been identified in this area. The Kramer Lugo 230kV line constraint is taken as an example to demonstrate the deliverability assessment methodology. In this example, network upgrades are needed to support generation deliverability for the purpose of counting the generation for Resource Adequacy. However, congestion management is still needed under more stressed generation conditions. Step 1: General study area For purposes of this example the North of Lugo Area is established as the study area as described in Step 1 of the methodology. Step 2: Initial dispatch For example purposes, the study model for this deliverability assessment is generally built upon the peak power flow base case. ISO generation resources and imports are dispatched as described in Step 2 of the methodology. The 2012 summer peak NQC is used as Pmax for existing generating units ( For new thermal generating units, Pmax is the installed capacity. Since the study group is found to have more than 20 units of conventional, wind and intermittent solar generation, the Pmax data for the intermittent generation is set to 50% exceedance production level during summer peak load hours, which is roughly 40% of the nameplate for the wind generation and 85% of the nameplate for the intermittent solar generation. Existing generators across the ISO and new generators in the study area are initially dispatched to 80% of Pmax. Details of the Initial Dispatch of generation are provided in Table 4.5 below. Consistent with the ISO allocation of import capability for resource adequacy planning purposes, imports are modeled at the maximum summer peak simultaneous historical level by branch groups. The historically unused existing transmission contracts (ETCs) crossing control area boundaries are modeled as zero MW injections at the tie point, but available to be turned on at remaining contract amounts. Table 4.1 below shows relevant imports and unused ETCs. The initial power flow in the study area is shown in Figure

58 Table 4.1: Imports and ETC Relevant to North of Lugo Constraints Net Import MW Branch Group Name Branch Group Description SILVERPK_BG Silver Peak NV Energy to SCE 0 0 INYO_BG Inyo LADWP to SCE 0 0 Import Unused ETC & TOR MW During the DC power flow screening, the study identified the following potential overloads which require new transmission facilities to mitigate in Table 4.2. Table 4.2: Potential Overloads as North of Lugo Constraints Normal Condition Contingency Overloaded Facilities Kramer - Lugo 230 kv No.1 Kramer - Lugo 230 kv No.2 The overloads were analyzed following Step 3 to Step 5 below. Step 3: Grouping of generators As described in Step 3 of the methodology, the study identified the generators with 5% or higher distribution factor (DFAX) or flow impact on Kramer Lugo 230 kv No.1 or 2 under the normal condition. Table 4.5 lists the all the generators that are in the 5% Circle, which includes existing generators, and new generators in the generation interconnection queue. The new generators are listed at the point of interconnection. The grouping of the generators is also illustrated in Figure 4.1. The initial power flow under the normal condition is shown in Figure 4.2. Step 4: Stressed Dispatch As described in Step 4 of the methodology, generation units with the highest flow impact on the constraint are then dispatched to Pmax until 20 units are dispatched or 1500 MW of generation was increased. In this example, 20 units are dispatched. The power flow after the 20 unit redispatch is shown in Figure 4.3. As the result of the stressed dispatch, the Kramer Lugo 230 kv No.1 & 2 are loaded to 112% of their normal rating, as summarized in Table 4.3. Table 4.3: Kramer Lugo 230 kv No.1 & 2 Line Flows Deliverability Methodology Overloaded Facility Contingency Initial Flow Stressed Flow Kramer Lugo 230 kv No.1 & 2 Normal Condition 95% 112% In this example, the generators constrained by the identified overloads are electrically located in many renewable zones and consist of hydro, thermal, geothermal, wind, and solar generators. The total installed generation behind the constraint is 3,101 MW. The deliverability assessment modeled total NQC level of 2,782 MW and 2,585 MW was 51

59 actually dispatched based on the methodology and resulted in the identified the overload. Step 5: Mitigation As described in Step 5 of the methodology a mitigation plan is identified and tested to ensure that it allows the new generation to pass the deliverability test. The Kramer-Llano 500 kv upgrade is proposed to increase the export capability for the North of Lugo area and thus reduce the flows on the Kramer-Lugo 230 kv No.1 & 2. The Kramer Llano 500 kv upgrade involves upgrading Kramer 230 kv substation to 500 KV with one 500/230 kv transformer, building a new Llano 500kV switching station that loops into the existing Lugo Vincent 500 kv No. 1, and building a new Kramer Llano 500kV line. The flows on Kramer Lugo 230 kv lines with the Kramer Llano 500kV upgrade are summarized in Table 4.4. Table 4.4: Kramer Lugo 230 kv No.1 & 2 Line Flow with Kramer Llano 500kV Upgrades Facility Contingency Stressed Flow Kramer Lugo 230 kv No. 1 & 2 Normal Condition 44% Figures 4.5 and Figure 4.6 show the power flow on the system, using a traditional study methodology, before and after the proposed upgrade. In Figure 4.6 the Kramer 500/230 kv transformer is still loaded to 112% of its normal rating. In general, the traditional study methodology stresses the system more than the deliverability study methodology and indicates the need for congestion management even if all the generators are deliverable for the Resource Adequacy purpose. 52

60 Figure 4.1: Illustration of Generator Grouping for Kramer Lugo 230 kv No.1 & 2 Overloads 53

61 # DFAX Flow Impact Table 4.5: Grouping and Dispatch of Generators behind Kramer Lugo Constraint Generator Name Plate (MW) Pmax (MW) Initial Dispatch (MW) Stressed Dispatch (MW) Renewable Zone Technology Type Notes Kramer 230 kv Solar PV Queued Lockhart Solar Thermal Queued Lockhart Solar Thermal Queued MC GEN Thermal Existing LUZ8 G Solar Thermal Existing LUZ9 G Solar Thermal Existing ALTA 4ST Thermal Existing Inyokern, ALTA 3ST Kramer, Thermal Existing Kramer Victorville, Solar PV Queued kv Barstow, Inyokern San 115 kv Bernardino Thermal Queued ALTA 2G ALTA41GT Lucerne, Nevada-C Thermal Thermal Existing Existing ALTA42GT Thermal Existing ALTA31GT Thermal Existing ALTA32GT Thermal Existing ALTA 1G Thermal Existing MOGEN G Thermal Existing Jasper Solar PV Queued BORAX I Thermal Existing 20 unit dispatch limit 54

62 Kramer 115 kv Solar PV Queued Control 115 kv Geothermal Queued Control 115 kv Geothermal Queued OXBOW G Geothermal Existing SUNGEN3G Solar Thermal Existing SUNGEN4G Solar Thermal Existing SUNGEN5G Solar Thermal Existing SUNGEN6G Solar Thermal Existing SUNGEN7G Solar Thermal Existing NAVYII4G Geothermal Existing NAVYII5G Geothermal Existing NAVYII6G Geothermal Existing Control 115 kv Geothermal Queued Kramer 115 kv Thermal Queued Lockhart Solar Thermal Queued BLM E7G Geothermal Existing BLM E8G Geothermal Existing BLM W9G Geothermal Existing Control 115 kv Geothermal Queued CALGEN1G Geothermal Existing Jasper Solar PV Queued No change to queued dispatch; existing generation reduced to balance the increase of generation. 55

63 SEGS 2G Solar Thermal Existing CALGEN2G Geothermal Existing CALGEN3G Geothermal Existing Kramer 115 kv Solar PV Queued KERRMGEE Thermal Existing Kramer 115 kv Solar PV Queued CSA DIAB Geothermal Existing Jasper Solar PV Queued Cool Water 115 kv Solar PV Queued BSPHYD Hydro Existing SEGS 1G Solar Thermal Existing Jasper Wind Queued BSPHYD Hydro Existing RUSH Hydro Existing Roadway Solar PV Queued KERRGEN Thermal Existing POOLUWD Hydro Existing Queued Total 1,383 1,226 9,82 1,143 Total 3,101 2,782 2,226 2,585 56

64 Figure 4.2: Initial Dispatch North of Lugo 57

65 Figure 4.3: Stressed Dispatch North of Lugo 58

66 Figure 4.4: Stressed Dispatch with Mitigation North of Lugo 59

67 Figure 4.5: Traditional Power Flow Dispatch North of Lugo 60

68 Figure 4.6: Traditional Power Flow Dispatch with Mitigation North of Lugo 61

69 5. Northern California Deliverability Constraint and Mitigation Example The following example demonstrates how the deliverability methodology is applied to identify and mitigate a deliverability constraint caused by the addition of a single wind generator. The deliverability constraint affects a group of generation spread over a large geographic area served by a part of the ISO system that is in parallel with the rest of the ISO system in Northern California. The constraint is an overload of part of the Vaca Dixon Delevan 230kV line under an outage condition and is not binding before adding the wind generator. Therefore, a special protection system is identified as the most effective mitigation to ensure the deliverability of the wind generator along with all the other previously queued and existing generation in the group behind this constraint. The example cited is from a recent generation cluster study. The wind generator under discussion is interconnecting in the PG&E North study area. Step 1: General study area For the purposes of this example, the PG&E North Study Area is analyzed. The PG&E North Study Area includes the Greater Bay Area, North Bay, North Coast, Central Valley, North Valley and Humboldt. Step 2: Initial dispatch For example purposes, the study model for this deliverability assessment is generally built upon the peak power flow base case from a recent cluster study. A coincident 1-in-5 year heat wave for the CAISO balancing authority area (BAA) load is modeled in the base case. The summer peak load is approximately 27,500 MW in the PG&E system. ISO generation resources and imports are dispatched as described in Step 2 of the methodology. The 2013 summer peak NQC is used as Pmax for existing thermal generating units ( Since the study group is found to be a mix of more than 20 thermal generators and a few wind generators, the Pmax data for the wind generators is set to 50% exceedance production level during summer peak load hours, which is 28% of the installed nameplate capacity. Existing generating units across the ISO and new generators in the study area are initially dispatched at 80% of Pmax. Details of the initial dispatch of generation are provided in Table 5.2 below. The relevant import targets and unused ETCs are shown in Table 5.1 below. The initial power flow in the study area is shown in Figure

70 Table 5.1: Imports and ETC Relevant to PG&E North Study Area Branch Group Name Branch Group Description Net Import MW Import Unused ETC MW COI_BG California Oregon Interface - Northwest to PG&E CASCADE_BG Cascade Delta 115kV line 36 0 SUMMIT_BG Summit Drum 115kV lines & Summit 60kV tie between Sierra and PG&E 6 0 Step 3: Grouping of generators During the DC power flow screening, the study identified a potential overload on the Vaca Dixon WindUnit_POI No kv line for the outage of WindUnit_POI Vaca Dixon No. 1 and No kv lines. The overload is analyzed in Step 3 to Step 5 below. WindUnit_POI is a new switching station that loops into the existing Vaca Dixon Cortina 230 kv No. 1, Vaca Dixon Delevan 230 kv No. 1 and No. 2 lines. As described in Step 3 of the methodology, the study identified the generators with 5% or higher flow distribution factor (5% DFAX) on Vaca Dixon WindUnit_POI #3 230kV line during the outage of WindUnit_POI Vaca Dixon #1 & #2 230kV lines. Table 5.2 lists all the generators that are in the 5% Circle, which includes existing generators and new generators in the generation interconnection queue. The new generators are listed at the corresponding Point of Interconnection in Table 5.2. The constraint and associated 5% Circle are also illustrated in Figure 5.1. There are 91 generators totaling 3830MW installed capacity in the 5% Circle. However, one wind generator has a significantly higher DFAX than the rest of the generators. 63

71 Figure 5.1: Illustration of Study Group area for Vaca Dixon WindUnit_POI Constraint 64

72 Table 5.2: Grouping and Dispatch of Generators behind the Vaca Dixon WindUnit_POI Constraint No DFAX Flow Impact Bus Name Name Plate Rating (Pmax2) Pmax Initial Dispatch Stressed Dispatch Technology Type Notes WindUnit Wind Queued WADHAM Conventional Existing COLUSGT Conventional Queued Geysers Conventional Queued GEYSR Conventional Existing GEYSR Conventional Existing GEYSER Conventional Existing GEYSER Conventional Existing GEYSER Conventional Existing TRINTY Conventional Existing TRINTY Conventional Existing SPRINGCR Conventional Existing SPRINGCR Conventional Existing SHASTA Conventional Existing SHASTA Conventional Existing SHASTA Conventional Existing SHASTA Conventional Existing SHASTA Conventional Existing J.F.CARR Conventional Existing J.F.CARR Conventional Existing Top 20 units that were increased to Pmax to create stressed dispatch 65

73 Redbud Wind Queued INDIAN V Conventional Existing BLCKBUTT Conventional Existing CSC HYDR Conventional Existing CSC HYDR Conventional Existing POTTRVLY Conventional Existing POTTRVLY Conventional Existing POTTRVLY Conventional Existing GEO.ENGY Conventional Existing GEO.ENGY Conventional Existing KEKAWAK Conventional Existing GERBER F Conventional Existing Lassen Conventional Existing Lassen Conventional Queued COLEMAN Conventional Existing FAIRHAVN Conventional Existing HUMB_G Conventional Existing HUMB_G Conventional Existing HUMB_G Conventional Existing HUMB_G Conventional Existing HUMB_G Conventional Existing HUMB_G Conventional Existing HUMB_G Conventional Existing HUMB_G Conventional Existing HUMB_G Conventional Existing No Change to queued dispatch. Existing generation may have slightly reduced to balance the increase of generation 66

74 HUMB_G Conventional Existing INSKIP Conventional Existing LP SAMOA Conventional Existing PAC.LUMB Conventional Existing PAC.LUMB Conventional Existing PAC.LUMB Conventional Existing SCOTIATP Wind Queued SOUTH G Conventional Existing VOLTA Conventional Existing VOLTA Conventional Existing SPI_AND Conventional Queued CLOVER Conventional Existing COWCRK Conventional Existing COWCRK Conventional Existing KILRC Conventional Existing KILRC Conventional Existing OLSEN Conventional Existing SMPSN-AN Conventional Existing SPI_AND Conventional Existing TKO Conventional Existing WEBR FL Conventional Existing WHEELBR Conventional Existing WHEELBR Conventional Existing WHEELBR Conventional Existing WHEELBR Conventional Existing 67

75 KESWICK Conventional Existing KESWICK Conventional Existing KESWICK Conventional Existing RDGCT Conventional Existing RDGCT Conventional Existing RDGCT Conventional Existing RDGCT Conventional Existing RDGCT Conventional Existing RDGSTEAM Conventional Existing BRNYFRST Conventional Existing HAT CRK Conventional Existing HAT CRK Conventional Existing HATLOST Conventional Existing HATLOST Conventional Existing HATLOST Conventional Existing MALCHA Conventional Existing MC ARTHR Conventional Existing PAC.ENGY Conventional Existing PIT 1 U Conventional Existing PIT 1 U Conventional Existing SPI-BURN Conventional Existing Total

76 Step 4: Stressed Dispatch As described in Step 4 of the methodology, generation units with the highest flow impact on the constraint are then dispatched to their Pmax until 20 units are dispatched or 1500 MW of generation is increased. In this example, 20 units are dispatched to their PMAX. Redispatching the 20 generators to their Pmax results in increasing the total amount of generation in the 5% circle by 501 MW as can be seen from Table 5.2. Table 5.3 shows that the redispatch of the 20 units results in an increase in the flow on the Vaca Dixon WindUnit_POI #3 230kV line from 84% to 105%. Figures 5.4 and 5.5 depict the increase in flow on the Vaca Dixon WindUnit_POI #3 230kV line from the initial dispatch case to the stressed dispatch case. Table 5.4 provides a comparison of available MW (Nameplate and Pmax) and the dispatched MW. Table 5.3: Flow on the Vaca Dixon WindUnit_POI #3 line Overloaded Facility Contingency Initial Flow Stressed Flow Vaca Dixon Windunit_POI #3 WindUnit_POI Vaca Dixon #1 & #2 230kV line 230kV lines 84% 105 % Table 5.4: Comparison of Available MW (Name Plate, Pmax) and Dispatched MW Name Plate Pmax Initial Dispatch Stressed Dispatch Total MW 5% Circle for the Vaca Dixon Windunit_POI #3 230kV Line Constraint 3876 MW 3297 MW 2645 MW 3103 MW Step 5: Mitigation As described in Step 5 of the methodology, a mitigation plan is identified and tested to ensure that it allows the new generation to pass the deliverability test. The 105% overload on the Vaca Dixon Windunit_POI #3 230kV line is successfully mitigated by tripping the new WindUnit via an SPS. This is the least cost solution that can effectively mitigate the overload, in comparison to reconductoring the line. Figures 5.2 to 5.5 show the one-line diagrams that depict the flow on the Vaca Dixon Windunit_POI #3 230kV line under the normal conditions (all elements in), under contingency conditions with initial dispatch, under contingency conditions with stressed dispatch and with the SPS mitigation implemented. Traditional Power Flow Analysis To provide a comparison, the same contingency is also simulated in the traditional power flow analysis with all the units in the area dispatched at their Pmax. It is found that 69

77 the maximum overload on the Vaca Dixon Windunit_POI #3 230kV line is 122% of its emergency rating for the same contingency as against the 105% overload seen in the deliverability analysis. However, the recommended SPS is sufficient to mitigate the overload in the traditional power flow study. Table 5.5: Comparison of the deliverability and reliability study impact due to the WindUnit POI-Vaca Dixon #1 & #2 contingency Overloaded Facility Vaca Dixon Windunit_POI #3 230kV line Contingency Overload in Deliverability Analysis WindUnit_POI Vaca Dixon #1 & #2 230kV lines 105% 122 % Overload in Traditional Power Flow Figures 5.6 to 5.8 show the one-line diagrams that depict the flow on the Vaca Dixon Windunit_POI #3 230kV line under the pre-contingency and post-contingency scenarios using a traditional power flow analysis. 70

78 Figure 5.2: Initial Dispatch (Pre-Contingency) Vaca Dixon to WindUnit_POI Constraint 71

79 Figure 5.3: Initial Dispatch (Post-Contingency) Vaca Dixon to WindUnit_POI Constraint 72

80 Figure 5.4: Stressed Dispatch (Post-Contingency) Vaca Dixon to WindUnit_POI Constraint 73

81 Figure 5.5: Stressed Dispatch with SPS Mitigation (Post-Contingency) Vaca Dixon to WindUnit_POI Constraint 74

82 Figure 5.6: Traditional Power Flow (Pre-Contingency) Vaca Dixon to WindUnit_POI Constraint 75

83 Figure 5.7: Traditional Power Flow (Post-Contingency) Vaca Dixon to WindUnit_POI Constraint 76

84 Figure 5.8: Traditional Power Flow with SPS Mitigation (Post-Contingency) Vaca Dixon to WindUnit_POI Constraint 77

85 6. Central California Example The following example demonstrates how the deliverability methodology is applied to examine deliverability of generators spread over a large geographic area in parallel with the rest of the ISO system in central California. The case under study is similar to the one utilized for a recent GIP study. This example concentrates on the Panoche-Dos Amigo 230 kv line which is observed to be overloaded in the traditional power flow analysis, but not in the generation and import deliverability studies. All of the generation in the generation group is deliverable for resource adequacy purposes in spite of the need for congestion management under more stressed generation output conditions. Step 1: General Study Area For purposes of this example, the Fresno area is analyzed. The Fresno Study Area comprises of Fresno, and San Joaquin Valley. Step 2: Initial dispatch For example purposes, the study model for this deliverability assessment is generally built upon the peak power flow base case from a recent GIP study. The transmission system models all the approved transmission upgrades and required network upgrades for generator projects studied prior to the cluster being studied. A coincident 1-in-5 year heat wave for the ISO BAA load was modeled in the base case. Non-pump load was the 1-in-5 peak load level for ISO. Pump load is dispatched within expected range for summer peak load hours. ISO generation resources and imports are dispatched as described in Step 2 of the methodology. The 2013 summer peak NQC is used as Pmax for existing thermal generating units ( For new thermal generating units, Pmax is the maximum capacity. Since the Study Group had more than 20 units of conventional, wind and solar generation, the Pmax values for the intermittent generation units in the PG&E area was set to 50% exceedance production level during summer peak load hours and 85% of the nameplate for the solar generation units. An exceedance level of 50% for the wind units is roughly 52% of the nameplate value of the wind generation units. Existing generators across the ISO and new generators in the study area are initially dispatched to 80% of their Pmax values. Details of the Initial Dispatch of generation are provided Table 6.2. Consistent with the CAISO allocation of import capability for resource adequacy planning purposes, Imports were modeled at the maximum summer peak simultaneous historical level by branch group.. Table 6.1 below shows the relevant imports. 78

86 Table 6.1: Imports and ETC Relevant to Fresno Study Area Branch Group Name Branch Group Description Net Import MW Import Unused ETC MW COI_BG California Oregon Interface - Northwest to PG&E CASCADE_BG Cascade Delta 115kV line 36 0 SUMMIT_BG Summit Drum 115kV lines & Summit 60kV tie between Sierra and PG&E 6 0 Step 3: Grouping of generators As described in Step 3 of the methodology, the study identifies the generators with 5% or higher flow distribution factor (5% DFAX) on the Panoche-Dos Amigos 230 kv line for the contingency of Los Banos-Panoche 230 kv line as shown in Table 6.2. Figure 6.1 below illustrates the 5% Circle for the Panoche-Dos Amigos facility. 79

87 Westley Bellota Los Banos Dos Amigo Borden 70 kv DFAX = 5% Mendota 115 kv Sub Gregg Helms DFAX = 6% Kearney 70 kv system DFAX = 10% Moss Landing Kearney Herndon DFAX = 11% Panoche DFAX = 13% Helm DFAX = 12% MCCall DFAX = 7% Schindler 115 kv Sub DFAX = 10% Helms 70 kv DFAX = 10% Kings River Generation, Balch,Haas, Pine Flat Generation Morro Bay Gates Henrietta DFAX = 5% Henrietta 115 kv DFAX = 5% Midway Contingency 230 kv lines 115 kv lines 5% DFAX cir* Overload ** * The DFAX circle is drawn for illustrative purposes only. The facility was not overloaded in deliverability analysis. ** Overload was seen in Reliability analysis only. Figure 6.1: Illustration of Generation Grouping for Panoche-Dos Amigos Flow 80

88 Table 6.2: Grouping and Dispatch of Generators behind Panoche-Dos Amigos Flow No DF Flow Generator Name Name plate Pmax Initial Stressed Technology Type Note Impact Dispatch Dispatch CGEN Solar PV Queued Top 20 units CGEN Solar PV Queued dispatched to HELMS Hydro Existing PMAX to create stressed HELMS Hydro Existing dispatch HELMS Hydro Existing CGEN Solar PV Queued CGEN Solar PV Queued PANO_BS Thermal Existing PANO_BS Thermal Existing PANO_BS Thermal Existing PANO_BS Thermal Existing KERCKHOF Thermal Existing CGEN Solar PV Queued CGEN Solar PV Queued STAR_GT Gas Existing STAR_GT Gas Existing 81

89 CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued WHD_PAN Gas Existing HAAS Hydro Existing HAAS Hydro Existing PINE FLT Hydro Existing PINE FLT Hydro Existing PINE FLT Hydro Existing CGEN Solar PV Queued AGRICO Thermal Existing No Change to queued dispatch. Existing generation may have slightly reduced to balance the increase of generation AGRICO Thermal Existing AGRICO Thermal Existing DG_PAN Gas Existing CHOWCOGN Thermal Existing EXCHQUER Hydro Existing 82

90 GWF_HEP Gas Existing GWF_HEP Gas Existing SARGCN G Thermal Existing BAF COG Thermal Existing BAF COG Thermal Existing KCTYPKER Thermal Existing CGEN Solar PV Queued KERCKHOF Hydro Existing KERCKHOF Hydro Existing KERCKHOF Hydro Existing KINGSRIV Hydro Existing BALCH Hydro Existing KRCDPCT Gas Existing KRCDPCT Gas Existing BLCH Hydro Existing BLCH Hydro Existing CGEN Solar PV Queued 83

91 CGEN Biomass Queued CGEN Biomass Queued BIO PWR Biomass Existing CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued 84

92 BORDEN D Hydro Existing CHWCHLA Biomass Existing SJ2GEN Hydro Existing SJ3GEN Hydro Existing CRANEVLY Hydro Existing FRIANTDM Hydro Existing FRIANTDM Hydro Existing FRIANTDM Hydro Existing CHV.COAL Gas Existing CHV.COAL Gas Existing WISHON Hydro Existing WISHON Hydro Existing WISHON Hydro Existing WISHON Hydro Existing WISHON Hydro Existing SALNR GN Gas Existing BULLD Gas Existing 85

93 ULTR.PWR Biomass Existing KINGSBUR Gas Existing SANGERCO Gas Existing DINUBA E Thermal Existing CGEN Solar PV Queued CGEN Solar PV Queued MCCALL Hydro Existing FRESNOWW Thermal Existing FRESNOWW Thermal Existing FRESNOWW Thermal Existing CGEN Solar PV Queued CGEN Solar PV Queued CGEN Solar PV Queued Total

94 Step 4: Stressed Dispatch As described in Step 4 of the methodology, generation units with the highest flow impact on the constraint are then dispatched to Pmax until 20 units are dispatched or 1500 MW of generation is increased. In this example 20 units in the 5% circle with highest flow impact are increased to their maximum output (Pmax). Table 6.2 shows the stressed dispatch levels for the 20 generators in the 5% Circle. Figures 6.2 and 6.3 represent the pre-contingency base case conditions. Figure 6.4 shows flow on the Panoche-Dos Amigo 230 kv line flow Post-Contingency. Table 6.3 summarizes the deliverability study initial dispatch and stressed dispatch, traditional power flow dispatch and the Pmax of generators in the 5% Circle of the Panoche-Dos amigo 230 kv line flow. Table 6.3: Total Dispatch for Units in the 5% Circle versus Total Nameplate Values Gen Dispatch (DFAX > 5%) Pgen (MW) Pmax (MW) Name Plate (MW) Deliverability Initial Dispatch % Deliverability Stressed Dispatch % Traditional Power Flow Dispatch % Pgen/Installed Step 5: Mitigation The flows on the Panoche-Dos Amigos 230 kv line are for illustrative purposes only. In the example the facility does not overload in the deliverability assessment. Hence, no mitigation is proposed. However, as discussed below, a traditional power flow analysis does identify an overload and congestion management is recommended to make sure the line is not overloaded. Traditional Power Flow Analysis Table 6.4 compares the traditional power flow analysis and the corresponding deliverability loading for the example. Table 6.4: Deliverability and Traditional Power Flow Loading Levels Deliverability Traditional Contingency Facility Power Flow Los Banos-Panoche 230 kv Panoche-Dos Amigos 230 kv 96% 109% Figure 6.5 shows the flow on the Panoche-Dos Amigos 230 kv line for the outage of the Los Banos-Panoche 230 kv line in the traditional power flow case. Congestion management is recommended to mitigate the overload on the Panoche-Dos Amigo 230 kv line. 87

95 Figure 6.2: Initial Dispatch (Pre-Contingency) Panoche to Dos Amigos Flow 88

96 Figure 6.3: Initial Dispatch (Post-Contingency) Panoche to Dos Amigos Flow 89

97 90

98 Figure 6.4: Stressed Dispatch (Post-Contingency) Panoche to Dos Amigos Flow 91

99 92

100 Figure 6.5: Traditional Power Flow Dispatch (Post-Contingency) Panoche to Dos Amigos Flow 93

101 7. Desert Area Deliverability Constraints and Mitigations Example (TPP) The Desert Area refers to generating resources electrically located in the following renewable energy zones: Pisgah, Mountain Pass, New Mexico, Palm Springs, Riverside East, San Diego South, Imperia, and Arizona. Deliverability constraints have been identified for the Desert Area in both the ISO Transmission Planning Process (TPP) and the generation interconnection studies. The example below is derived from the 2012/2013 TPP base portfolio deliverability assessment. Step 1: General study area For purposes of this example the Desert Area is established as the study area as described in Step 1 of the methodology. Step 2: Initial dispatch For example purposes, the study model for this deliverability assessment is generally built upon the peak power flow base case for the base portfolio in the 2012/2013 TPP cycle. The same transmission system as in the base portfolio power flow peak case is modeled. A coincident 1-in-5 year heat wave for the ISO BAA load is modeled in the base case. Non-pump load is the 1-in-5 peak load level for ISO. Pump load is dispatched within expected range for summer peak load hours. ISO generation resources and imports are dispatched as described in Step 2 of the methodology. The most recent summer peak NQC is used as Pmax for existing thermal generating units ( For new thermal generating units, Pmax is the installed capacity. Since the study group is found to have more than 20 units of conventional, wind and solar generation, the Pmax data for the intermittent generation is set to 50% exceedance production level during summer peak load hours, which is roughly 40% of the nameplate for the wind generation in southern California and 85% of the nameplate for the solar generation. Existing generators across the ISO and new generators in the study area are initially dispatched to 80% of Pmax. Some generators with a high potential of retiring are dispatched at 0 MW, but available to be turned on. Details of the Initial Dispatch of generation are provided in Table 7.4 below. Consistent with the ISO allocation of import capability for resource adequacy planning purposes, Imports are modeled at the maximum summer peak simultaneous historical level by branch group. The historically unused existing transmission contracts (ETCs) 94

102 crossing control area boundaries are modeled as zero MW injections at the tie point, but available to be turned on at remaining contract amounts 5. Table 7.1 below shows relevant imports and unused ETCs. The initial power flow in the study area is shown in Figure 7.2. Table 7.1: Imports and ETC Relevant to Desert Area Constraints Net Import MW Branch Group Name Branch Group Description Lugo-Victorville-BG Victorville Lugo 500kV line 1, BLYTHE_BG Blythe 161kV WAPA to SCE 45 0 ELDORADO_MSL Moenkopi Eldorado 500kV line 1,213 0 McCullough Eldorado 500kV line MCCULLGH_MSL NSO Eldorado 230kV line Mead Eldorado 230kV lines Mead Bob Tap 230kV line MEAD_MSL Mead Camino 230kV lines NGILABK4_BG N. Gila 500/100kV transformer banks HooDoo Wash N. Gila 500kV line Palo Verde Colorado River 500kV PALOVRDE_MSL line 2, PARKER_BG Gene Parker 230kV line SYLMAR-AC_MSL Sylmar 230kV LADWP to SCE Import Unused ETC & TOR MW During the DC power flow screening, the study identified the following potential overload in Table In this example, several of the Unused ETCs come on during the analysis at their remaining contract amounts. They are then manually replaced in the model by dispatching an equal amount of available existing generation that could plausibly represent generation that could be imported across the corresponding tie-line. 95

103 Table 7.2: Potential Overloads as Desert Area Constraints Overloaded Facility Contingency Lugo - Victorville 500kV No. 1 Lugo - Eldorado 500kV No. 1 Red Bluff - Colorado River 500kV No. 1 & 2 Devers - Red Bluff 500kV No. 1 & 2 McCullough - Victorville 500kV No. 1 McCullough - Victorville 500kV No. 2 Lugo - Victorville 500kV No. 1 Base Case Base Case Devers - Red Bluff 500kV No. 1 & 2 Red Bluff - Colorado River No. 1 & 2 Lugo - Victorville 500kV No. 1 Lugo - Eldorado 500kV No. 1 & Eldorado - Mohave 500kV No. 1 Each of the overloads are analyzed following Step 3 to Step 5 below. The analysis concludes that all the overloads could be mitigated by the same Lugo Eldorado upgrade. Therefore, they are grouped together and named Desert Area Constraints. Among these constraints, the overload of Lugo Victorville 500kV line under the Devers Red Bluff 500kV No. 1 & No. 2 outage has the largest 5% Circle. The 5% Circles of the other constraints are all a subset of the largest 5% Circle. To illustrate the study methodology, the analysis of the overload of the Lugo Victorville 500kV transmission line under the Devers Red Bluff 500kV No.1 & No.2 outage is provided here. Step 3: Grouping of generators As described in Step 3 of the methodology, the study identifies the generators with a 5% or higher flow distribution factor (5% DFAX) on the Lugo Victorville 500kV line under the outage of Devers Red Bluff 500kV No. 1 & No. 2. Table 7.3 lists all the generators that are in the 5% Circle, which includes existing generators, renewable generators in the base portfolios and equivalent generators representing unused ETCs. The renewable generators are listed at the point of interconnection in Table 7.3. The grouping of the generators is also illustrated in Figure 7.1. An SPS tripping up to 1400MW generation at Red Bluff and Colorado River is modeled in the study. The initial power flow following the contingency and SPS action is shown in Figure

104 Big Creek DFAX=9% Rector Springville Marketplace (LADWP) Crystal (APS) Navajo (APS) Mandalay Santa Clara DFAX=13% Ormond Beach Vestal Magunden Pastoria Warne Moorpark DFAX=16% SCE Northern Area Bailey Pardee Sylmar DFAX=29% Serrano DFAX=5% Adelanto (LADWP) LADWP System Rancho Vista Alberhills Suncrest Miguel Mira Loma Valley DFAX=58% Victorville (LADWP) Lugo DFAX=10% ECO DFAX=9% SDGE Area Jasper Devers Pisgah x Imperial Valley McCullough (LADWP) DFAX=25% SCE East of Pisgah Area SCE Eastern Area Mead (APS) DFAX=22% Eldorado Moenkopi (APS) Merchant Colorado River Mojave Westwing (APS) Yavapai (APS) DFAX=18% Palo Verde Redbluff DFAX=18% Hassayampa Hoodoo Wash (APS) DFAX=10% DFAX=14% (APS) N. Gila 500 kv Facilities LEGEND 230 kv Facilities Overload x Contingency 5% DFAX Circle Figure 7.1: Illustration of Generator Grouping for Lugo Victorville Constraint 97

105 # DFAX 98 Flow Impact Generator Table 7.3: Grouping and Dispatch of Generators behind by Lugo Victorville Constraint Name Plate Pmax Initial Dispatch Stressed Dispatch Renewable Zone Technology Type Notes ORMOND2G ORMOND1G Thermal Thermal OTC OTC 1500MW dispatch limit SYLMARLA BG The impact of this generation is considered through the Facility Loading Adder, as shown later in this example MEAD S BG VICTORVL BG MCCULLGH BG MRCHNT Thermal Existing MRCHNT Thermal Existing IVANPAH Mountain Pass Large Scale Solar PV RPS CRAZY EYE El Dorado Solar Thermal RPS CRAZY EYE El Dorado Solar Thermal RPS ELDORADO El Dorado Large Scale Solar PV RPS HOODOO WASH Arizona Large Scale Solar PV RPS PALOVRDE BG MANDLY2G Thermal Existing MANDLY1G Thermal Existing MRCHNT Thermal Existing N.GILA BG IVANPAH Mountain Pass Solar Thermal RPS PARKER BG COLORADO RIVER Riverside East Large Scale Solar PV RPS Tripped by COLORADO RIVER Riverside East Solar Thermal RPS SPS RED BLUFF Riverside East Solar Thermal RPS RED BLUFF Riverside East Large Scale Solar PV RPS RED BLUFF Riverside East Large Scale Solar PV RPS RED BLUFF Riverside East Large Scale Solar PV RPS RED BLUFF Riverside East Large Scale Solar PV RPS

106 RED BLUFF Riverside East Solar Thermal RPS COPRMTN Solar PV Existing No change COPRMTN Solar PV Existing IVANPAH Mountain Pass Solar Thermal RPS IVANPAH Mountain Pass Solar Thermal RPS MESQUITE Arizona Large Scale Solar PV RPS MESQUITE Arizona Large Scale Solar PV RPS MESQUITE Arizona Large Scale Solar PV RPS PITCHGEN Thermal Existing TENNGEN Thermal Existing TENNGEN Thermal Existing SAUGUS NonCREZ Small Solar PV RPS SAUGUS Tehachapi Biogas RPS WARNE Hydro Existing WARNE Hydro Existing MANDLY3G Thermal Existing OXGEN Thermal Existing PROCGEN Thermal Existing S.CLARA Thermal Existing WILLAMET Thermal Existing EXGEN Thermal Existing CHARMIN Thermal Existing EXGEN Thermal Existing ALAMO SC Thermal Existing ELLWOOD Thermal Existing MCGPKGEN Thermal Existing CAMGEN Thermal Existing GOLETA Distributed Solar - SCE Small Solar PV RPS PSTRIAG Thermal Existing PSTRIAG Thermal Existing 99 to renewable dispatch; existing generation reduced to balance the increase of generation.

107 PSTRIAS Thermal Existing PSTRIAG Thermal Existing PSTRIAS Thermal Existing LRP-U Thermal Existing TDM STG Thermal Existing TDM CTG Thermal Existing TDM CTG Thermal Existing INTBST Thermal Existing INTBCT Thermal Existing IMPERIAL VALLEY Imperial Large Scale Solar PV RPS IMPERIAL VALLEY Imperial Large Scale Solar PV RPS IMPERIAL VALLEY Imperial Large Scale Solar PV RPS IMPERIAL VALLEY Imperial Large Scale Solar PV RPS IMPERIAL VALLEY Imperial Large Scale Solar PV RPS IMPERIAL VALLEY Imperial Large Scale Solar PV RPS IMPERIAL VALLEY Imperial Large Scale Solar PV RPS IMPERIAL VALLEY Imperial Large Scale Solar PV RPS SUNCREST Imperial Wind RPS SUNCREST Imperial Wind RPS EASTWOOD Hydro Existing OMAR1G Thermal Existing OMAR2G Thermal Existing OMAR3G Thermal Existing OMAR4G Thermal Existing PANDOL Thermal Existing PANDOL Thermal Existing SYCCYN1G Thermal Existing SYCCYN2G Thermal Existing SYCCYN3G Thermal Existing SYCCYN4G Thermal Existing ULTRAGEN Thermal Existing 100

108 VESTAL Thermal Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing B CRK Hydro Existing MAMOTH1G Hydro Existing MAMOTH2G Hydro Existing PORTAL Hydro Existing KAWGEN Thermal Existing KR Thermal Existing KR Thermal Existing PASADNA Thermal Existing PASADNA Thermal Existing BRODWYSC Thermal Existing LAKEGEN Thermal Existing ECO Baja Wind RPS 101

109 ECO Baja Wind RPS GOODRICH DG-SCA Muni Small Solar PV RPS VESTAL Distributed Solar - SCE Small Solar PV RPS RECTOR Distributed Solar - SCE Small Solar PV RPS RECTOR Distributed Solar - SCE Small Solar PV RPS RECTOR Distributed Solar - SCE Small Solar PV RPS RECTOR Distributed Solar - SCE Small Solar PV RPS RECTOR Distributed Solar - SCE Small Solar PV RPS RECTOR Distributed Solar - SCE Small Solar PV RPS RECTOR Distributed Solar - SCE Small Solar PV RPS SPRINGVL Distributed Solar - SCE Small Solar PV RPS SPRINGVL Distributed Solar - SCE Small Solar PV RPS SPRINGVL Distributed Solar - SCE Small Solar PV RPS SPRINGVL Distributed Solar - SCE Small Solar PV RPS SPRINGVL Distributed Solar - SCE Small Solar PV RPS BOULEVRD Distributed Solar - SDGE Small Solar PV RPS ECO San Diego South Wind RPS ECO San Diego South Wind RPS ECO San Diego South Wind RPS ECO San Diego South Wind RPS 102

110 ECO San Diego South Wind RPS ECO San Diego South Wind RPS ECO San Diego South Wind RPS ECO San Diego South Wind RPS BSPHYD Hydro Existing BSPHYD Hydro Existing CSA DIAB Hydro Existing OXBOW G Thermal Existing RUSH Hydro Existing LUNDY Hydro Existing POOLE Hydro Existing CONTROL Kramer Geothermal RPS CSA DIAB Kramer Geothermal RPS CONTROL Nevada C Geothermal RPS CONTROL Nevada C Geothermal RPS NEENACH Tehachapi Large Scale Solar PV RPS NEENACH Tehachapi Large Scale Solar PV RPS OTAYMST Thermal Existing OTAYMGT Thermal Existing OTAYMGT Thermal Existing OTAY MESA Thermal Existing OTAY MESA Thermal Existing OTAY MESA Thermal Existing Distributed Solar PRCTRVLY TELECYN RPS Total Total SDGE Small Solar PV RPS Distributed Solar - SDGE Small Solar PV RPS 103

111 Step 4: Stressed Dispatch As described in Step 4 of the methodology, generation units with the highest flow impact on the constraint are then dispatched to Pmax until 20 units are dispatched or 1500 MW of generation was increased. In this example, dispatching the first two generators resulted in 1500MW of increased generation. The power flows, pre- and post-contingency, after the 1500MW re-dispatch are shown in Figure 7.4 and Figure 7.5. Then, the impact of next eighteen (18) generators with the highest flow impacts is considered, pursuant to the methodology, using the facility loading adder (FLA). As listed in Table 7.4, the FLA first calculates the impact of increasing the output of the next eighteen generators from initial dispatch to Pmax s. That results in a total of MW change of generation and MW increase of the Lugo Victorville flow. Then the FLA estimates flow impact from MW generation with the highest opposite flow impacts on the constraint. The total negative flow impact is MW. The net FLA flow impact is the sum of the positive and negative flow impacts and added to the line flow after 1500MW re-dispatch. The final overload is determined to be 106% of the emergency rating. The power flow base case is then produced by scaling the eighteen generators selected for the positive FLA to the level that results in the determined flow. The pre-contingency and post-contingency FLA power flow plots are provided in Figure 7.6 and Figure 7.7. Table 7.4 Facility Load Adder (FLA) Calculation 104 Positive FLA Flow Impact NO Generator DF Initial Dispatch FLA Dispatch PGEN Change DF*PGEN Change 2 ORMOND1G SYLMARLA MEAD S VICTORVL MCCULLGH PALOVRDE N.GILA IVANPAH CRAZY EYE CRAZY EYE ELDORADO HOODOO WASH MRCHNT MANDLY2G MANDLY1G MRCHNT

112 MRCHNT PARKER IVANPAH Total Negative FLA Flow Impact NO Generator DF Initial Dispatch FLA Dispatch PGEN Change DF*PGEN Change 1 HIDEDST HIDEDCT HIDEDCT HIDEDCT MTNVIST MTNVIST MNTV-ST MNTV-ST IEEC-G IEEC-G DIABLO DIABLO MORRO MORRO ALAMT5 G ALAMT6 G S.ONOFR S.ONOFR Total A. Net FLA flow change (Positive + Negative) 399 B. Flow Before FLA 2368 C. Estimated Flow After FLA (A+B) 2767 D. Flow % (C Rating 100%) 106

113 106

114 Table 7.5 summarizes the flow of Lugo Victorville line in the initial dispatch and final stressed dispatch. For comparison purpose, Figure 7.10 and Figure 7.11 show the power flow on the system pre- and postcontingency using a traditional study methodology. In Figure 7.11 the Lugo-Victorville is loaded to 135% of its emergency rating. Table 7.5: Lugo Victorville Line Flow Deliverability Methodology Overloaded Facility Contingency Initial Flow Stressed Flow Lugo - Victorville 500kV No. 1 Devers - Red Bluff 500kV No. 1 & 2 84% 106% In this example, the generators constrained by the identified overload are electrically located in many renewable zones and non-renewable zones and consists of thermal, geothermal, hydro, wind, large scale solar and distributed solar generators. The total installed generation behind the constraint is 14987MW. The deliverability assessment models total NQC level of MW and MW is actually dispatched based on the methodology and resulted in the identified the overload. Step 5: Mitigation As described in Step 5 of the methodology a mitigation plan is identified and tested to ensure that it allows the new generation to pass the deliverability test. Operating the Lugo Eldorado 500kV line with 70% series compensation could greatly reduce the flow from Victorville to Lugo. However, the increased flow overloads the Lugo Eldorado 500kV line, whose rating is limited by the series capacitors and terminal equipment. Therefore, the series capacitors and terminal equipment need to be upgraded to higher rating. Figure 7.8 and Figure 7.9 show the stressed power flow with upgraded Lugo Eldorado 500kV line operating with 70% compensation. Figure 7.12 and Figure 7.13 show the power flow on the system, using a traditional study methodology, with upgraded Lugo Eldorado 500kV line operating with 70% compensation. In Figure 7.13 the Lugo-Victorville is loaded to 102% of its emergency rating and would require additional upgrades. Under the deliverability methodology these remaining overloads would be mitigated using congestion management. 107

115 108 Figure 7.2: Initial Dispatch (Pre-Contingency) Lugo to Victorville Constraint

116 109 Figure 7.3: Initial Dispatch (Post-Contingency) Lugo to Victorville Constraint

117 Figure 7.4: Post-Dispatch of 1500 MW Generation (Pre-Contingency) Lugo to Victorville Constraint 110

118 111 Figure 7.5: Post-Dispatch of 1500 MW Generation (Post-Contingency) Lugo to Victorville Constraint

119 112 Figure 7.6: Post-Dispatch of Facility Loading Adder (Pre-Contingency) Lugo to Victorville Constraint

120 113 Figure 7.7: Post-Dispatch of Facility Loading Adder (Post-Contingency) Lugo to Victorville Constraint

121 114 Figure 7.8: Post-Dispatch of Facility Loading Adder with Mitigation (Pre-Contingency) Lugo to Victorville Constraint

122 115 Figure 7.9: Post-Dispatch of Facility Loading Adder with Mitigation (Post-Contingency) Lugo to Victorville Constraint

123 Figure 7.10: Traditional Power Flow Dispatch (Pre-Contingency) Lugo to Victorville Constraint 116

124 Figure 7.11: Traditional Power Flow Dispatch (Post-Contingency) Lugo to Victorville Constraint 117

125 118 Figure 7.12: Traditional Power Flow Dispatch with Mitigation (Pre-Contingency) Lugo to Victorville Constraint

126 119 Figure 7.13: Traditional Power Flow Dispatch with Mitigation (Post-Contingency) Lugo to Victorville Constraint

127 8. Desert Area Deliverability Constraints and Mitigations Example (GIP) The Desert Area refers to generating resources electrically located in the following renewable energy zones: Pisgah, Mountain Pass, New Mexico, Palm Springs, Riverside East, San Diego South, Imperia, and Arizona. Deliverability constraints have been identified for the Desert Area in both the ISO Transmission Planning Process (TPP) and the generation interconnection studies. The example below is derived from a recent generator interconnection procedures (GIP) cluster deliverability assessment. The previous TPP example provides detailed analysis for the overload of Lugo Victorville 500kV line. This example provides additional information by focusing on the next worst constraint for the area, i.e. overload of Lugo Eldorado 500kV line. Step 1: General study area For purposes of this example, the study of Desert Area deliverability constraints is organized as two study areas Eastern Bulk System and East of Pisgah Bulk System as described in Step 1 of the methodology. The reason for having two study areas, as opposed to one in the previous TPP example, is that it is infeasible to have one meaningful Desert Area base case given the huge amount of new generation in Desert Area to be studied in recent generator interconnection procedures (GIP) cluster studies. While studying either area, stressed dispatch is created based on the actual grouping of the generators behind the constraint. Therefore, both study areas generate similar study results. For purposes of this example, the Eastern study area analysis is provided. Step 2: Initial dispatch For example purposes, the study model for this deliverability assessment is generally built upon the peak power flow base case from a recent cluster study. The transmission system models all the approved transmission upgrades and required network upgrades for generator projects studied prior to cluster being studied. A coincident 1-in-5 year heat wave for the ISO BAA load was modeled in the base case. Non-pump load was the 1-in-5 peak load level for ISO. Pump load is dispatched within expected range for summer peak load hours. ISO generation resources and imports are dispatched as described in Step 2 of the methodology. The 2012 summer peak NQC is used as Pmax for existing thermal generating units ( For new thermal generating units, Pmax is the installed capacity. Since the study group is found to have more than 20 units of conventional, wind and solar generation, the Pmax data for the intermittent generation was set to 50% exceedance production level during summer peak load hours, which is roughly 40% of the nameplate for the wind generation in southern California and 85% of the nameplate for the solar generation. Existing generators across the ISO and new generators in the study area are initially dispatched to 80% of Pmax. Details of the Initial Dispatch of generation are provided in Table 8.3 below. 120

128 Consistent with the ISO allocation of import capability for resource adequacy planning purposes, Imports are modeled at the maximum summer peak simultaneous historical level by branch group. The historically unused existing transmission contracts (ETCs) crossing control area boundaries are modeled as zero MW injections at the tie point, but available to be turned on at remaining contract amounts 6. Table 8.1 below shows relevant imports and unused ETCs. The initial power flow in the study area is shown in Figure 8.2. Branch Group Name Table 8.1: Imports and ETC Relevant to Desert Area Constraints Branch Group Description Net Import MW Lugo-Victorville-BG Victorville Lugo 500kV line 1, BLYTHE_BG Blythe 161kV WAPA to SCE 90 0 ELDORADO_MSL Moenkopi Eldorado 500kV line 1,011 0 McCullough Eldorado 500kV line MCCULLGH_MSL NSO Eldorado 230kV line Mead Eldorado 230kV lines Mead Bob Tap 230kV line MEAD_MSL Mead Camino 230kV lines NGILABK4_BG N. Gila 500/100kV transformer banks PALOVRDE_MSL HooDoo Wash N. Gila 500kV line Palo Verde Colorado River 500kV line 2, PARKER_BG Gene Parker 230kV line SYLMAR-AC_MSL Sylmar 230kV LADWP to SCE Import Unused ETC & TOR MW During the DC power flow screening, the study identified the following potential overloads in Table In this example, several of the Unused ETCs come on during the analysis at their remaining contract amounts. They are then manually replaced in the model by dispatching an equal amount of available existing generation that could plausibly represent generation that could be imported across the corresponding tie-line. 121

129 Table 8.2: Potential Overloads as Desert Area Constraints Contingency Lugo - Victorville 500 kv No. 1 Palo Verde - Colorado River 500 kv No. 1 Colorado River - Red Bluff 500 kv No. 1 & 2 Overloaded Facilities Eldorado-Lugo 500 kv No. 1 Devers - Red Bluff 500 kv No. 1 & 2 Lugo - Eldorado 500 kv No. 1 Eldorado - Mohave 500 kv No. 1 Palo Verde - Colorado River 500 kv No. 1 Colorado River - Red Bluff 500 kv No. 1 & 2 Lugo-Victorville 500 kv No. 1 Devers - Red Bluff 500 kv No. 1 & 2 Each of the overloads are analyzed following Step 3 to Step 5 below. The overloads could be mitigated by the combination of Lugo Eldorado upgrade and a new Colorado River Valley 500kV line. Therefore, they are grouped together and named Desert Area Constraints. Among these constraints, the overload of Lugo Victorville 500kV line under the Devers Red Bluff 500kV No. 1 & No. 2 outage has the largest 5% Circle. 5% Circles of the other constraints are all a subset of the largest 5% Circle. The analysis of the Lugo Victorville 500kV line overload is similar to the previous TPP example although the magnitude of the overload is much higher. To provide additional details for the Desert Area constraints, this example focuses more on the analysis of overload of Eldorado Lugo 500kV transmission line under the Devers Red Bluff 500kV No.1 & No.2 outage while the overload of Lugo Victorville can still be observed in all the power flow plots. Step 3: Grouping of generators As described in Step 3 of the methodology, the study identifies the generators with 5% or higher flow distribution factor (5% DFAX) on Lugo - Eldorado 500kV line under the outage of Devers Red Bluff 500kV No. 1 & No. 2. Table 8.3 lists all the generators that are in the 5% Circle, which includes existing generators, new generators in the generation interconnection queue and equivalent generators representing unused ETCs. The new generators are listed at the corresponding Point of Interconnection in Table 8.3. The grouping of the generators is also illustrated in Figure 8.1. An SPS tripping up to 1400MW generation at Red Bluff and Colorado River is modeled in the study. The initial power flow following the contingency and SPS action is shown in Figure

130 Marketplace (LADWP) Crystal (APS) Navajo (APS) Adelanto (LADWP) Victorville (LADWP) Jasper Pisgah McCullough (LADWP) DFAX=16% SCE East of Pisgah Area Mead (APS) DFAX=16% Eldorado Moenkopi (APS) Merchant Mojave Yavapai (APS) Serrano Rancho Vista Alberhills Suncrest Miguel Mira Loma Valley Lugo Devers SDGE Area ECO DFAX=5% x Imperial Valley Redbluff DFAX=12% DFAX=5% Colorado River Westwing (APS) SCE Eastern Area DFAX=12% Palo Verde DFAX=12% DFAX=11% Hassayampa Hoodoo Wash (APS) (APS) N. Gila 500 kv Facilities LEGEND 230 kv Facilities Overload x Contingency 5% DFAX Circle Figure 8.1: Illustration of Generator Grouping for Lugo Eldorado Constraint 123

131 # DFAX Flow Impact Table 8.3: Grouping and Dispatch of Generators behind Lugo Eldorado Constraint Generator Name Plate Pmax Initial Dispatch Stressed Dispatch Renewable Zone Technology Type Notes Mesquite Arizona Solar PV & Thermal Queued 1500MW dispatch limit MEAD S BG The impact Crazy Eye Eldorado Solar PV Queued MCCULLGH BG Eldorado Eldorado Solar PV Queued Eldorado Eldorado Solar PV Queued Ivanpah Mountain Pass Solar PV Queued Crazy Eye Eldorado Solar PV Queued Primm Mountain Pass Solar PV Queued Imperial Valley Imperial Solar PV Queued Mohave Eldorado Solar PV Queued Ivanpah Mountain Pass Solar Thermal Queued PALOVRDE Riverside East BG Colorado River Riverside East Solar Thermal Queued Merchant Eldorado Solar PV Queued Colorado River Riverside East Solar PV Queued N.GILA BG of this generation is considered through the Facility Loading Adder, as shown later in this example. 124

132 Merchant Eldorado Solar PV Queued Imperial Valley Imperial Solar PV Queued Colorado River Riverside East Solar Thermal Queued Red Bluff Riverside East Solar Thermal Queued Tripped by SPS Colorado River Riverside East Solar PV Queued Red Bluff Riverside East Solar PV Queued MRCHNT Thermal Existing No change MRCHNT Thermal Existing to queued dispatch; MRCHNT Thermal Existing existing CM Solar Eldorado Solar PV Existing generation PARKER BG reduced to Colorado balance the River Thermal Queued increase of Colorado generation River Thermal Queued Colorado River Thermal Queued LRP-U Thermal Existing BOULEVRD San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued BOULEVRD San Diego Wind Queued 125

133 South BOULEVRD San Diego South Wind Queued IV GEN Thermal Existing IV GEN Thermal Existing IV GEN Thermal Existing INTBST Thermal Existing INTBCT Thermal Existing ECO San Diego South Wind Queued ECO San Diego South Wind Queued ECO San Diego South Wind Queued Imperial Valley Imperial Solar PV Queued Imperial Valley Imperial Solar Thermal Queued Hoodoo Wash Arizona Solar PV Queued Imperial Valley Imperial Solar PV Queued Imperial Valley Imperial Solar PV Queued BOULEVRD San Diego South Wind Queued Imperial Valley Imperial Solar PV Queued Imperial Valley Imperial Solar PV Queued 126

134 Imperial Valley Imperial Solar PV Queued ECO San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued Imperial Valley Imperial Solar PV Queued BOULEVRD San Diego South Solar PV Queued BOULEVRD San Diego South Solar PV Queued ECO San Diego South Solar PV Queued Imperial Valley Imperial Solar PV Queued BLYTHE Riverside East Solar PV Queued Ivanpah Mountain Pass Solar Thermal Queued Ivanpah Mountain Pass Solar Thermal Queued Red Bluff Riverside East Solar PV Queued Red Bluff Riverside East Solar PV Queued Red Bluff Riverside East Solar PV Queued Red Bluff Riverside East Solar PV Queued Red Bluff Riverside Solar Thermal Queued 127

135 Colorado River Primm Red Bluff Red Bluff Queued Total Total East Riverside East Solar Thermal Queued Mountain Pass Solar PV Queued Riverside East Solar PV Queued Riverside East Solar PV Queued Step 4: Stressed Dispatch As described in Step 4 of the methodology, generation units with the highest flow impact on the constraint are then dispatched to Pmax until 20 units are dispatched or 1500 MW of generation is increased. In this example, dispatching the first generator resulted in 1500MW of increased generation. The power flows pre- and post-contingency after the 1500MW re-dispatch are shown in Figure 8.4 and Figure 8.5. Then, the impact of next nineteen (19) generators with the highest flow impacts is estimated using the facility loading adder (FLA). As listed in Table 8.4, the FLA first calculates the impact of increasing the output of the next nineteen generators from initial dispatch to Pmax s. That results in a total of MW change of generation and MW increase of the Lugo Eldorado flow. Then the FLA estimates flow impact from MW generation with the highest opposite flow impacts on the constraint. The total negative flow impact is -102MW. The net FLA flow impact is the sum of the positive and negative flow impacts and added to the line flow after 1500MW re-dispatch. The final overload is determined to be 140% of the emergency rating. The power flow base case is then produced by scaling the nineteen generators selected for the positive FLA to the level that results in the determined flow. The power flows pre- and post-contingency after the facility loading adder action are shown in Figure 8.6 and Figure

136 Table 8.4: Facility Loading Adder (FLA) Calculation Positive FLA Flow Impact NO Generator DF Initial Dispatch FLA Dispatch PGEN Change DF*PGEN Change 1 Mesquite MEAD S Crazy Eye MCCULLGH Eldorado Eldorado Ivanpah Crazy Eye Primm Imperial Valley Mohave Ivanpah PALOVRDE Colorado River Merchant Colorado River N.GILA Merchant Imperial Valley Colorado River Total

137 Negative FLA Flow Impact NO Generator DF Initial Dispatch FLA Dispatch PGEN Change DF*PGEN Change 1 WINDHUB WINDHUB WHIRLWIND WHIRLWIND WHIRLWIND WHIRLWIND WHIRLWIND WHIRLWIND WHIRLWIND WHIRLWIND WHIRLWIND VINCENT ANTELOPE MIDWAY EL SEGUNDO Total A. Net FLA flow change (Positive + Negative) 531 B. Flow Before FLA 1769 C. Estimated Flow After FLA (A+B) 2300 D. Flow % (C Rating 100%) 140% 130

138 Table 8.5 summarizes the flow of Lugo Eldorado line in the initial dispatch and final stressed dispatch. For comparison purpose, Figure 8.12 and Figure 8.13 show the power flow on the system pre- and post-contingency using a traditional study methodology. In Figure 8.13 the Lugo-Eldorado line is loaded to 155% of its emergency rating. Table 8.5: Lugo - Eldorado Line Flow Deliverability Methodology Overloaded Facility Contingency Initial Flow Stressed Flow Lugo Eldorado 500kV No. 1 Devers - Red Bluff 500kV No. 1 & 2 96% 140% In this example, the generators constrained by the identified overload are electrically located in many renewable zones and non-renewable zones and consists of thermal, wind, and solar generators. The total installed generation behind the constraint is MW. The deliverability assessment models total NQC level of MW and 9323 MW is actually dispatched based on the methodology and resulted in the identified the overload. Step 5: Mitigation As described in Step 5 of the methodology a mitigation plan is identified and tested to ensure that it allows the new generation to pass the deliverability test. The Lugo Eldorado upgrade as discussed in the previous TPP example is the first mitigation to be considered due to the relatively small scope of the upgrade and great effectiveness. Figure 8.8 and Figure 8.9 show the stressed power flow with upgraded Lugo Eldorado 500kV line operating with 70% compensation. The Lugo Eldorado line is stilled loaded to 108% of the upgraded rating. To fully mitigate the overload, a new Red Bluff Valley 500kV line is added. Figure 8.10 and Figure 8.11 show the stressed power flow with both Lugo Eldorado upgrade and Red Bluff to Valley line. The line flows are summarized in Table 8.6. Table 8.6: Lugo - Eldorado Line Flow with Upgrades Facility Contingency Lugo Eldorado 500kV No. 1 Devers Red Bluff 500kV No. 1 & 2 Lugo Eldorado Upgrade Stressed flow 108% Lugo Eldorado Upgrade and New Red Bluff Valley 500kV Line Stressed Flow 91% Figure 8.14 and Figure 8.15 show the power flow on the system, using a traditional study methodology with the proposed upgrades. In Figure 8.15 the Lugo-Eldorado line is still loaded to 103% of its emergency rating even with both Lugo Eldorado upgrade and a new Red Bluff Valley 500kV line. In general, the traditional study methodology stresses the system more than the deliverability study methodology and indicates the need for congestion management even if all the generators are deliverable for Resource Adequacy purposes. 131

139 Application of Technical Bulletin for Queue Clusters 1-4 To support the deliverability of all queued generators in this example would require both Lugo Eldorado upgrade and new Red Bluff Valley 500kV line. However, as compared to the previous TPP example, the need for the new Red Bluff Valley 500kV line is driven by amount of queued renewable far exceeding the volume in the 33% RPS portfolio. The upgrade therefore qualified for removal from the Delivery Network Upgrade requirement for the queued generators by applying the following criteria from the Technical Bulletin of Deliverability Requirements for Queue Clusters 1-4 and Determination of Net Qualifying Capacity ( QueueClusters1-4_Determination-NetQualifyingCapacity.pdf): A delivery network upgrade originally identified during the GIP Phase II interconnection study process for the current cluster (i.e., clusters 1 and 2) may be removed from the Phase II study results if the upgrade is not needed in the current transmission plan and satisfies at least one of the following criteria: (a) The network upgrade consists of new transmission lines 200 kv or above, and has capital costs of $100 million or greater; or (b) The network upgrade has a capital cost of $200 million or more. 132

140 Figure 8.2: Initial Dispatch (Pre-Contingency) Lugo to Eldorado Constraint 133

141 Figure 8.3: Initial Dispatch (Post-Contingency) Lugo to Eldorado Constraint 134

142 Figure 8.4: Post-Dispatch of 1500 MW Generation (Pre-Contingency) Lugo to Eldorado Constraint 135

143 Figure 8.5: Post-Dispatch of 1500 MW Generation (Post-Contingency) Lugo to Eldorado Constraint 136

144 Figure 8.6: Post-Dispatch of Facility Loading Adder (Pre-Contingency) Lugo to Eldorado Constraint 137

145 Figure 8.7: Post-Dispatch of Facility Loading Adder (Post-Contingency) Lugo to Eldorado Constraint 138

146 Figure 8.8: Post-Dispatch of Facility Loading Adder with Lugo Eldorado Upgrade (Pre-Contingency) Lugo to Eldorado Constraint 139

147 Figure 8.9: Post-Dispatch of Facility Loading Adder with Lugo Eldorado Upgrade (Post-Contingency) Lugo to Eldorado Constraint 140

148 Figure 8.10: Post-Dispatch of Facility Loading Adder with Lugo Eldorado Upgrade & Red Bluff Valley Line (Pre-Contingency) Lugo to Eldorado Constraint 141

149 Figure 8.11: Post-Dispatch of Facility Loading Adder with Lugo Eldorado Upgrade & Red Bluff Valley Line (Post-Contingency) Lugo to Eldorado Constraint 142

150 Figure 8.12: Traditional Power Flow Dispatch (Pre-Contingency) Lugo to Eldorado Constraint 143

151 Figure 8.13: Traditional Power Flow Dispatch (Post-Contingency) Lugo to Eldorado Constraint 144

152 Figure 8.14: Traditional Power Flow Dispatch with Lugo Eldorado Upgrade & Red Bluff Valley Line (Pre-Contingency) Lugo to Eldorado Constraint 145

153 Figure 8.15: Traditional Power Flow Dispatch with Lugo Eldorado Upgrade & Red Bluff Valley Line (Post-Contingency) Lugo to Eldorado Constraint 146

154 9. South of Vincent Deliverability Constraints and Mitigation Examples The South of Vincent deliverability constraint refers to the operating limit driven by thermal overload or voltage instability for the loss of both Vincent Lugo 500kV No. 1 and No. 2 transmission lines. This constraint has been identified in the generation interconnection studies and limits deliverability of generators in the PG&E area and SCE Northern area. Due to the delay on Tehachapi Renewable Transmission Project (TRTP) Segment 8A, the deliverability of the Tehachapi area generators has been a concern. This example is derived from a sensitivity deliverability assessment assuming Segment 8A would not be in-service in time to support deliverability of queued generation. Step 1: General study area For purposes of this example the SCE Northern Area is established as the study area as described in Step 1 of the methodology. The SCE Northern Area includes the Big Creek area, Ventura area and Tehachapi area that are north of Vincent. Step 2: Initial dispatch For example purposes, the study model for this deliverability assessment is generally built upon the peak power flow base case from a recent cluster study. The transmission system models all the approved transmission upgrades and required network upgrades for generator projects with the exception of TRTP. The following elements of TRTP are not modeled as the result of Segment 8A delay: Vincent Mira Loma 500kV No. 1 transmission line. The following TRTP segments are modeled. Segment 1: Segment 2: Segment 3: Segment 4: Antelope Pardee 230kV No. 1 line Antelope Vincent 500kV No. 1 line Windhub Highwind 230kV No. 1 line Antelope Whirlwind 500 kv No. 1 line 147

155 Segment 5: Segment 9: Segment 10: Segment 11: Whirlwind 500kV switching station looping into Midway Vincent 500kV No. 3 line Antelope Vincent 500kV No.2 line Whirlwind 500/230kV substation Upgrade of the existing Antelope, Vincent, Mesa, Gould, and Mira Loma Substations to accommodate new T/L construction and system compensation elements. Whirlwind Windhub 500kV No. 1 line Vincent Mesa 230 kv No. 1 line A coincident 1-in-5 year heat wave for the ISO BAA load is modeled in the base case. Non-pump load is the 1-in-5 peak load level for ISO. Pump load is dispatched within expected range for summer peak load hours. ISO generation resources and imports are dispatched as described in Step 2 of the methodology. The 2012 summer peak NQC is used as Pmax for existing thermal generating units ( For new thermal generating units, Pmax is the installed capacity. Since the study group is found to have more than 20 units of conventional, wind and solar generation, the Pmax data for the intermittent generation was set to 50% exceedance production level during summer peak load hours, which is roughly 40% of the nameplate for the wind generation in southern California, 28% of the nameplate for the wind generation in northern California, and 85% of the nameplate for the solar generation. Existing generators across the ISO and new generators in the study area are initially dispatched to 80% of Pmax. Details of the initial dispatch of generation are provided in Table 9.3 below. Consistent with the ISO allocation of import capability for resource adequacy planning purposes, Imports are modeled at the maximum summer peak simultaneous historical level by branch group. The historically unused existing transmission contracts (ETCs) crossing control area boundaries are modeled as zero MW injections at the tie point, but available to be turned on at remaining contract amounts. Table 9.1 below shows relevant imports and unused ETCs. The initial power flow in the study area is shown in Figure

156 Table 9.1: Imports and ETC Relevant to South of Vincent Constraint Branch Group Name Branch Group Description Net Import MW Lugo-Victorville-BG Victorville Lugo 500kV line COI_BG California Oregon Interface NOB_BG Pacific DC Intertie (PDCI) SYLMAR-AC_MSL Sylmar 230kV LADWP to SCE Import Unused ETC & TOR MW During DC power flow screening, the study identified the following potential overload in Table 9.2. Table 9.2: Potential South of Vincent Overload Overloaded Facility Contingency Vincent 500/230kV bank No. 1 Vincent Lugo 500kV No. 1 & No. 2 The overload is analyzed following Step 3 to Step 5 below. The analysis concludes that all the generators north of Vincent are not deliverable without TRTP Segment 8A. However, the deliverable MW as determined using the deliverability methodology far exceeds the amount of generation the TRTP was designed to support under the traditional power flow approach. In an area, such as Tehachapi, where there is a mix of wind and solar generators, the deliverability methodology accounts for the complementary nature of different production profiles from different technology. The deliverability assessment produces much less conservative results than the traditional power flow approach. On the other hand, it must be emphasized that passing the deliverability test does not guarantee the generators could generate at their maximum outputs under all expected operating conditions. Step 3: Grouping of generators As described in Step 3 of the methodology, the study identifies the generators with 5% or higher flow distribution factor (5% DFAX) on Vincent 500/230kV transformer bank under the outage of Vincent - Lugo 500kV No. 1 & No. 2. Table 9.3 lists the all the generators that are in the 5% Circle, which includes existing generators, new generators in the generation interconnection queue, and an equivalent generator representing unused ETC. The new generators are listed at the point of interconnection in Table 9.3. The grouping of the generators is also illustrated in Figure

157 Captain Jack Malin Olinda DFAX=5% Round Mountain PG&E Area DFAX=7% DFAX=9% Midway SCE Northern Area DFAX=9% DFAX=9% Highwind Whirlwind Windhub DFAX=9% Antelope Vincent x Lugo LEGEND 500 kv Facilities 230 kv Facilities Overload x Contingency 5% DFAX Circle Figure 9.1: Illustration of Generator Grouping for Vincent 500/230kV Transformer Overload 150

158 # DFAX Table 9.3: Grouping and Dispatch of Generators Constrained by Vincent 500/230kV Transformer Overload Flow Impact Generator Name Plate Pmax Initial Dispatch Stressed Dispatch Renewable Zone Technology Type Notes Gates Westlands Thermal Queued 1500MW Contra Costa Solano Thermal Queued dispatch Tesla-Bellota limit kV lines NonCrez Thermal Queued Table Mountain- Tesla 500kV NonCrez Thermal Queued COLUSGT NonCrez Thermal Queued MALIN BG Existing DIABLO Thermal Existing DIABLO Thermal Existing Moss-Panoche and Coburn- Panoche 230kV NonCrez Solar Queued Diablo Canyon - Midway 500kV NonCrez Solar Queued Schindler Westlands Solar Queued Helm-Panoche 230kV and Panoche- Kearney 230kV Westlands Solar Queued Mendota- Dairyland 115kV Westlands Solar Queued The impact of this generation is considered through the Facility Loading Adder, as shown later in this example. 151

159 Los Banos- Panoche 230kV Los Banos Solar Queued Rio Oso- Lockford 230kV NonCrez Solar Queued MOSSLND Thermal Existing MOSSLND Thermal Existing Eastshore NonCrez Thermal Queued Angiola Westlands Solar Queued PTSB Thermal Existing BREEZE Tehachapi Wind Existing No change SOUTHWND Tehachapi Wind Existing CANWIND Tehachapi Wind Existing BREEZE Tehachapi Wind Existing BOREL Tehachapi Hydro Existing ZONDWND Tehachapi Wind Existing GOLDTOWN Tehachapi Wind Existing ZONDWND Tehachapi Wind Existing DUTCHWND Tehachapi Wind Existing SITE 4B Tehachapi Wind Existing CANWIND Tehachapi Wind Existing SITE 4B Tehachapi Wind Existing MIDWIND Tehachapi Wind Existing NORTHWND Tehachapi Wind Existing ARBWIND Tehachapi Wind Existing KERNRVR Tehachapi Hydro Existing skyrivr Tehachapi Wind Existing to queued dispatch; existing generation reduced to balance the increase of generation. 152

160 skyrivr Tehachapi Wind Existing FLOWIND Tehachapi Wind Existing ENWIND Tehachapi Wind Existing MORWIND Tehachapi Wind Existing Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Solar Queued Highwind Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued 153

161 Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Highwind Tehachapi Wind Queued Highwind Tehachapi Wind Queued Highwind Tehachapi Wind Queued 154

162 Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Windhub Tehachapi Wind Queued Windhub Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Highwind Tehachapi Wind Queued Windhub Tehachapi Solar Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Whirlwind Tehachapi Wind Queued Windhub Tehachapi Solar Queued Windhub Tehachapi Solar Queued Whirlwind Tehachapi Wind Queued Highwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Wind Queued 155

163 Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Windhub Tehachapi Solar Queued Arco-Carneras 70kV Westlands Solar Queued Arco- Twisselman 70kV Westlands Solar Queued Belridge - Temblor 115kV Westlands Solar Queued Blackwell Westlands Solar Queued Camden Junction- Lemoore Tap 70kV Westlands Solar Queued Chevron Westlands Thermal Queued Coalinga 1- Gates 70kV Westlands Solar Queued Copus Road Westlands Solar Queued Divide-Cabrillo 115kV NonCrez Wind Queued Gates- Coalinga 70kV Westlands Solar Queued Gates-Gregg 230kV Westlands Solar Queued Guernsey - Henrietta 70kV Westlands Solar Queued Henrietta Westlands Thermal Queued 156

164 Henrietta - Lemoore 70kV Westlands Solar Queued Henrietta- Guernsey 70kV Westlands Solar Queued Henrietta- Jacobs Corner 70kV Westlands Solar Queued Henrietta- Tulare Lake 70kV Westlands Solar Queued Henrietta- Tulare Lake 70kV Westlands Solar Queued Jacobs Corner Westlands Solar Queued Jacobs Corner Westlands Solar Queued Jacobs Corner Westlands Solar Queued Kern Oil Westlands Thermal Queued Kern-Old River 70kV Westlands Solar Queued Lamont Westlands Solar Queued Midway- Morro Bay 230kV Carrizo South Solar Queued Morro Bay- Midway 230kV Carrizo South Solar Queued Morro Bay- Midway 230kV Carrizo South Solar Queued Semitropic- Midway 115kV Westlands Solar Queued 157

165 Smyrna- Alpaugh 115kV Westlands Solar Queued Smyrna- Alpaugh 115kV Westlands Solar Queued Smyrna- Alpaugh 115kV Westlands Solar Queued Smyrna- Alpaugh 115kV Westlands Solar Queued Smyrna- Alpaugh 115kV Westlands Solar Queued Smyrna- Alpaugh 115kV Westlands Solar Queued Taft-Cuyama 70kV Westlands Solar Queued Weedpatch - San Bernard 70kV Westlands Solar Queued Weedpatch- Wheeler Ridge 70kV Westlands Solar Queued Wheeler Ridge-Lamont 115kV Westlands Solar Queued Wheeler Ridge-Lamont Westlands Solar Queued 158

166 115kV Morrobay - Midway 230kV Westlands Wind Queued Borden MERCED Solar Queued Coalinga - Schindler 70kV Westlands Solar Queued Corcoran- Kingsburg 115kV Westlands Solar Queued Corcoran- Kingsburg 115kV Westlands Solar Queued Giffen Westlands Solar Queued Hammond Westlands Solar Queued Helm Westlands Solar Queued Henrietta- GWF 115kV Westlands Solar Queued Los Banos-Dos Amigos 230kV Westlands Solar Queued Mendota Los Banos Solar Queued Mendota-San Joaquin-Helm 69kV Westlands Solar Queued Mendota-San Joaquin-Helm 70kV Westlands Solar Queued Mendota-San Joaquin-Helm 70kV Westlands Solar Queued Mendota-San Westlands Solar Queued 159

167 Joaquin-Helm 70kV Merced MERCED Solar Queued Oro Loma - Panoche 115kV Westlands Solar Queued Panoche-Oro Loma 115kV Westlands Solar Queued Panoche-Oro Loma 115kV Westlands Solar Queued Panoche- Schindler 115kV Westlands Solar Queued Panoche- Schindler 115kV Westlands Solar Queued Stoud Westlands Solar Queued Stroud Westlands Solar Queued Stroud Westlands Solar Queued Stroud Westlands Solar Queued Stroud Westlands Solar Queued Stroud Westlands Solar Queued Strout Westlands Solar Queued Strout Westlands Solar Queued Wesix Westlands Solar Queued Newhall NonCrez Thermal Queued Birds Landing Solano Wind Queued Birds Landing Solano Wind Queued Birds Landing Solano Wind Queued 160

168 Contra Costa Solano Thermal Queued Contra Costa- Delta SW Yard 230kV Solano Solar Queued Eastshore NonCrez Wind Queued Geysers - Cloverdale 115kV NonCrez Thermal Queued Gold Hill-Eight Mile 230kV NonCrez Solar Queued Kelso NonCrez Thermal Queued Lambie-Contra Costa 230kV Solano Wind Queued Lone Tree- Cayetano Solano Wind Queued Los Esteros NonCrez Thermal Queued Pittsburg - Kirker - Columbia Steel 115kV Solano Solar Queued Pittsburg-Tesla 230kV Solano Wind Queued Redbud- Cortina 115kV NonCrez Wind Queued Salado - Newman 60kV NonCrez Solar Queued Salado- Newman #1 60kV NonCrez Solar Queued Schulte Westlands Thermal Queued 161

169 Schulte Westlands Solar Queued Solado NonCrez Solar Queued Tesla - Keslo 230kV NonCrez Wind Queued Tesla 115 kv NonCrez Wind Queued Woodland- Davis 115kV NonCrez Solar Queued Tulloch NonCrez Solar Queued Cascade- Cottonwood 115kV NonCrez Thermal Queued Nicolaus- Marysville 60kV NonCrez Solar Queued Rio Dell NonCrez Wind Queued 219 ~ ~ PG&E distribution system NonCrez Mixed Queued 285 ~ ~ ~ 0.02 PG&E existing generators Mixed Existing SCE Northern Area (Tehachapi) Queued Total Total

170 Step 4: Stressed Dispatch As described in Step 4 of the methodology, generation units with the highest flow impact on the constraint are then dispatched to Pmax until 20 units are dispatched or 1500MW of generation is increased. In this example, dispatching the first three generators results in 1500MW of increased generation. Then, the impact of next seventeen (17) generators with the highest flow impacts is estimated using the facility loading adder (FLA). The flow impact of the equivalent MW amount of generation with negative DFAXs is also estimated. The net FLA impact is negative. Therefore, the FLA is set to 0 according to the methodology. The FLA calculation is explained in Table 9.4. Table 9.4: Facility Loading Adder (FLA) Calculation Positive FLA Flow Impact NO Generator DF Initial Dispatch FLA Dispatch PGEN Change DF*PGEN Change 3 Tesla-Bellota 230kV lines Table Mountain-Tesla 500kV COLUSGT MALIN DIABLO DIABLO Moss-Panoche and Coburn-Panoche 230kV Diablo Canyon - Midway 500kV Schindler Helm-Panoche 230kV and Panoche-Kearney 230kV Mendota-Dairyland 115kV Los Banos-Panoche 230kV Rio Oso-Lockford 230kV MOSSLND MOSSLND Eastshore Angiola

171 20 PTSB Total Negative FLA Flow Impact NO Generator DF Initial Dispatch FLA Dispatch PGEN Change DF*PGEN Change 1 El Segundo Red Bluff Imperial Valley Colorado River Colorado River Colorado River Colorado River Total A. Net FLA flow change (Positive + Negative) -156 B. Flow Before FLA 2368 C. Estimated Flow After FLA (=B) 2368 D. Flow %

172 The result of the stressed dispatch is summarized in Table 9.5. The stressed power flows pre- and post-contingency are shown in Figure 9.4 and Figure 9.5. Table 9.5: Vincent Transformer Bank Flow Deliverability Methodology Overloaded Facility Contingency Initial Flow Stressed Flow Vincent 500/230kV Bank No. 1 Lugo Vincent 500kV No. 1 & 2 100% 107% In this example, the generators constrained by the identified overload are electrically located in many renewable zones and non-renewable zones and consist of thermal, hydro, wind, and solar generators. The total installed generation behind the constraint is 56024MW. The deliverability assessment modeled total NQC level of 46261MW and 32239MW is actually dispatched based on the methodology and resulted in the identified the overload. Among them, 7610MW generators are installed in the SCE Northern Area, i.e. Tehachapi renewable zone. The deliverability assessment modeled total NQC level of 4303MW in Tehachapi due to a mix of different type of resources in the area and only 3442MW is actually dispatched in the stressed dispatch. In a typical power flow study, all the Tehachapi generators would be dispatched at their full output, which creates significant power transfer from North of Vincent to South of Vincent that the transmission system is insufficient to support. Undeliverable MW After removing generators with total 1044MW installed capacity, the Vincent transformer bank is loaded to 99% in the deliverability test. The power flows of initial dispatch preand post-contingency are shown in Figure 9.6 and Figure 9.7. The power flows of stressed dispatch pre- and post- contingency are shown in Figure 9.8 and Figure 9.9. Table 9.6: Generators Removed to Reduce Vincent Transformer Bank Loading # DFAX Flow Impact Generator Name Plate Renewable Zone Technology Windhub Tehachapi Solar Queued Windhub Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Wind Queued Windhub Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Whirlwind Tehachapi Solar Queued Total For comparison, Figure 9.10 and Figure 9.11 show the power flows under the traditional approach with the generators in Table 9.6 removed. Tehachapi generators are dispatched to their full outputs. To solve the power flow, tremendous fictitious VAR support is needed. In the pre-contingency case, the total VAR injection at Vincent and Antelope is about 2000MVar. Overloads of Vincent 500/230kV transformer banks are Type 165

173 observed under the normal condition. In the post-contingency case, the total VAR injection at Vincent and Antelope is about 5510MVar and significant overloads are identified on Vincent 500/230kV transformer banks and South of Vincent 230kV lines. 166

174 Figure 9.2: Initial Dispatch (Pre-Contingency) South of Vincent Constraint 167

175 Figure 9.3: Initial Dispatch (Post-Contingency) South of Vincent Constraint 168

176 Figure 9.4: Stressed Dispatch (Pre-Contingency) South of Vincent Constraint 169

177 Figure 9.5: Stressed Dispatch (Post-Contingency) South of Vincent Constraint 170

178 Figure 9.6: Initial Dispatch after Removing Generators (Pre-Contingency) South of Vincent Constraint 171

179 Figure 9.7: Initial Dispatch after Removing Generators (Post-Contingency) South of Vincent Constraint 172

180 Figure 9.8: Stressed Dispatch after Removing Generators (Pre-Contingency) South of Vincent Constraint 173

181 Figure 9.9: Stressed Dispatch after Removing Generators (Post-Contingency) South of Vincent Constraint 174

182 Figure 9.10: Traditional Power Flow after Removing Generators (Pre-Contingency) South of Vincent Constraint 175

183 Figure 9.11: Traditional Power Flow after Removing Generators (Post-Contingency) South of Vincent Constraint 176

184 10. Path 43 (North of SONGS) Deliverability Constraint and Mitigation Example The Path 43 (North of SONGS) deliverability constraint has been identified in recent cluster studies for the SDG&E Area. The SDG&E Area refers to generating resources electrically located in the following renewable energy zones: San Diego South, Imperial, Arizona and SDG&E Non-CREZ. Step 1: General study area For purposes of this example, all generation in the SDG&E area was established as the study area as described in Step 1 of the methodology. Step 2: Initial dispatch For example purposes, the study model for this deliverability assessment was generally built upon the peak power flow base case used in a recent cluster study. The same transmission system as in the recent cluster power flow peak case was modeled. A coincident 1-in-5 year heat wave for the ISO BAA load was modeled in the base case. Non-pump load was the 1-in-5 peak load level for ISO. Pump load was dispatched within expected range for summer peak load hours. ISO generation resources and imports were dispatched as described in Step 2 of the methodology. The most recent summer peak NQC was used as Pmax for existing thermal generating units ( xls). For new thermal generating units, Pmax was the installed capacity. Since the study group was found to have more than 20 units of conventional, wind and solar generation, the Pmax data for the intermittent generation was set to 50% exceedance production level during summer peak load hours, which is roughly 40% of the nameplate for the wind generation in southern California and 85% of the nameplate for the solar generation. Existing generators across the ISO and new generators in the study area were initially dispatched to 80% of Pmax. Some generators with a high potential of retiring were dispatched at 0 MW, but available to be turned on. Details of the Initial Dispatch of generation are provided in Table below. Consistent with the ISO allocation of import capability for resource adequacy planning purposes, Imports were modeled at the maximum summer peak simultaneous historical level by branch group. The historically unused existing transmission contracts (ETCs) crossing control area boundaries were modeled as zero MW injections at the tie point, but available to be turned on at remaining contract amounts. Table 10.1 below shows relevant imports and unused ETCs. The initial power flow in the study area is shown in Figure

185 Table 10.1: Imports and ETC Relevant to SDG&E Area Study Branch Group Name Branch Group Description Net Import MW CFE_BG Tijuana Otay Mesa 230kV line ROA Imperial Valley 230kV line Coachella Mirage 230kV line IID-SCE_BG 0 Ramon Mirage 230kV line 1500 Dixie Land Imperial Valley 230kV line IID-SDGE_BG 0 El Centro Imperial Valley 230kV line NGILABK4_BG N. Gila 500/69kV banks PALOVRDE_MSL HooDoo Wash N. Gila 500kV line Hassayampa N. Gila 500kV line Palo Verde Colorado River 500kV line Import Unused ETC MW During the DC power flow screening, the study identified the following potential overload in Table Table 10.2: Potential Overload on Path 43 Overloaded Facility Contingency WECC Path 43 (North of SONGS) Base Case Path 43 includes the following 230 kv transmission lines: San Onofre-Santiago #1 and #2, San Onofre-Viejo, and San Onofre-Serrano. The rating of Path 43 is 2,440 MW. The overload was analyzed following Step 3 to Step 5 below. Step 3: Grouping of generators As described in Step 3 of the methodology, the study identified the generators with 5% or higher flow distribution factor (5% DFAX) on Path 43 under N-0 condition. Table 10.6 lists the all the generators that are in the 5% Circle, which includes existing generators, new generators requesting interconnection and equivalent generators representing unused ETCs. The renewable generators are listed at the point of interconnection in Table The grouping of the generators is also illustrated in Figure Step 4: Stressed Dispatch As described in Step 4 of the methodology, generation units with the highest flow impact on the constraint were then dispatched to Pmax until 20 units were dispatched or 1500 MW of generation was increased. In this example, dispatching the first 12 generators resulted in 1500MW of increased generation. The power flow after the 1500MW redispatch is shown in Figure Then, the impact of next 8 generators with the highest flow impacts was determined using the facility loading adder (FLA). As shown in Table 10.3, the FLA first calculates the impact of increasing the output of the next 8 generators from initial dispatch to Pmax s. That results in a total of 296MW change of 178

186 generation and 108MW increase of the Path 43 flow. Then the FLA estimates flow impact from 296MW generation with the highest opposite distribution factors on the constraint. The total negative flow impact is -26MW. The net FLA flow impact is the sum of the positive and negative flow impacts and added to the line flow after 1500MW redispatch. The power flow base case is then produced by scaling the 8 generators selected for the positive FLA to the level that results in the determined flow. The power flow after the facility loading adder action is shown in Figure As the result of the stressed dispatch, the loading on Path 43 is at 109% of its rating, as summarized in Table Figure 10.6 shows the power flow using traditional study methodology. Table 10.5 shows the loading on Path 43 using traditional study methodology. 179

187 Table 10.3 Facility Load Adder (FLA) Calculation Positive FLA Flow Impact NO Generator DF Initial Dispatch FLA Dispatch PGEN Change DF*PGEN Change 12 PEN_CT PEN_ST OTAYMGT OTAYMGT IV GEN IMPERIAL VALLEY ECO MISSION-CARLTON HILLS IMPERIAL VALLEY Total 1,401 1, Negative FLA Flow Impact NO Generator DF Initial Dispatch FLA Dispatch PGEN Change DF*PGEN Change 1 GATES Total A. Net FLA flow change (Positive + Negative) 82 B. Flow Before FLA 2,572 C. Estimated Flow After FLA (A+B) 2,654 D. Flow % (C Rating 100%)

188 Table 10.4: Path 43 Flow Deliverability Methodology Overloaded Facility Contingency Initial Flow Stressed Flow Path 43 Base Case 65% 109% Table 10.5: Path 43 Flow Traditional Study Methodology Overloaded Facility Contingency Stressed Flow Path 43 Base Case 143% In this example, the generators constrained by the identified overload are electrically located in many renewable zones and non-renewable zones and consists of thermal, wind, and large scale solar generators. The total installed generation behind the constraint is 9,557MW. The deliverability assessment modeled a total of 7,972MW actually dispatched based on the methodology and resulted in the identified the overload. Step 5: Mitigation As described in Step 5 of the methodology a mitigation plan was identified and tested to ensure that it allowed the new generation to pass the deliverability test. The identified constraint on Path 43 can be mitigated by adding a new 230 kv line between Capistrano and Serrano substations. Figure 10.5 shows the stressed power flow with the upgrade modeled. Figures 10.6 and 10.7 show the power flow on the system, using a traditional study methodology, before and after mitigation. Even with the mitigation, the loading on Path 43 is at 128% and would require additional upgrades. Under the deliverability methodology this remaining overload would be mitigated using congestion management. 181

189 Path 43 Viejo Santiago Serrano Alberhills Valley Devers SCE Redbluff Colorado River Palo Verde San Onofre Capistrano SDG&E Suncrest Miguel Ocotillo Imperial Valley Hoodoo Wash Hassayampa (APS) ECO N. Gila Existing Facilities Facilities under construction, CPUC Approved, or Upgrades Triggered by Higher Queued Projects Overload 5% DFAX Circle Figure 10.1: Illustration of Generator Grouping for Path 43 Constraint 182

190 Table 10.6: Grouping and Dispatch of Generators behind Path 43 Constraint # DFAX Flow Impact Generator Name Plate Pmax Initial Dispatch Stressed Dispatch Renewable Zone Technology Type Notes ENCINA Thermal Existing 1500 MW ENCINA Thermal Existing dispatch limit S.ONOFR3 1,124 1, ,124 Nuclear Existing S.ONOFR3 1,124 1, ,124 Nuclear Existing S.ONOFRE Nuclear Queued Queued ENCINA Thermal Queued ENCINA Thermal IMPERIAL Queued VALLEY Imperial Solar PV Queued OTAYMESA Thermal OTAYMST Thermal Existing PEN_CT Thermal Existing PEN_CT Thermal Existing PEN_CT Thermal Existing The impact of PEN_ST Thermal Existing this generation is OTAYMGT Thermal Existing considered through the OTAYMGT Thermal Existing Facility Loading IV GEN Thermal Existing Adder, as shown IMPERIAL Queued later in this VALLEY Imperial Solar PV 183

191 San Diego Queued ECO South Wind MISSION- Queued CARLTON HILLS Thermal IMPERIAL VALLEY Imperial Solar PV Queued example LRP-U Thermal Existing No change to INTBCT Thermal Existing IMPERIAL VALLEY Imperial Solar PV Queued IV GEN Thermal Existing IV GEN Thermal Existing INTBST Thermal Existing IMPERIAL VALLEY Imperial Solar PV Queued PA99MWQ Thermal Existing PA99MWQ Thermal Existing IMPERIAL VALLEY Imperial Solar PV Queued LRKSPBD Thermal Existing LRKSPBD Thermal Existing CALPK_BD Thermal Existing CALPK_EC Thermal Existing CALPK_ES Thermal Existing GOALLINE Thermal Existing MEF MR Thermal Existing MEF MR Thermal Existing renewable dispatch; existing generation reduced to balance the increase of generation. 184

192 San Diego Queued BOULEVRD South Wind San Diego Queued BOULEVRD South Wind Queued BORDER Thermal IMPERIAL Queued VALLEY Imperial Solar PV EC GEN Thermal Existing DIVISION Thermal Existing ES GEN Thermal Existing NOISLMTR Thermal Existing OY GEN Thermal Existing N.GILA BG BORREGO SDGE Non- CREZ Solar PV Queued LkHodG Small Hydro Existing LkHodG Small Hydro Existing POINTLMA Thermal Existing POINTLMA Thermal Existing KUMEYAAY Wind Existing BORDER SDGE Non- CREZ Biomass Queued CAPSTRNO Thermal Existing ENCINAGT Thermal Existing CABRILLO Thermal Existing 185

193 CARLTNHS Thermal Existing CARLTNHS Thermal Existing CHCARITA Thermal Existing EASTGATE Thermal Existing MESAHGTS Thermal Existing MISSION Thermal Existing OTAY Thermal Existing Queued Total 3,462 2,758 2,168 2,484 Total 9,557 8,823 6,387 7,

194 % MW Path 43: 1594 MW (65%) Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED SDGE % SCE (S.ONOFRE) % Unused ETC % Figure 10.2: Initial Dispatch Path 43 Constraint 187

195 % MW Path 43: 2571 MW (105%) Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED SDGE % SCE (S.ONOFRE) % Unused ETC % Figure 10.3: Post-Dispatch of 1500 MW Generation Path 43 Constraint 188

196 % MW Path 43: 2658 MW (109%) Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED SDGE % SCE (S.ONOFRE) % Unused ETC % Figure 10.4: Post-Dispatch of Facility Loading Adder Path 43 Constraint 189

197 % MW Path 43: 2434 MW (100%) Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED SDGE % SCE (S.ONOFRE) % Unused ETC % Figure 10.5: Post-Dispatch of Facility Loading Adder with mitigation Path 43 Constraint 190

198 % MW Path 43: 3481 MW (143%) Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED SDGE % SCE (S.ONOFRE) % Unused ETC % Figure 10.6: Traditional Power Flow Dispatch Path 43 Constraint 191

199 % MW Path 43: 3117 MW (128%) Generators inside 5% circle PGEN PMAX INSTALLED PGEN/INSTALLED SDGE % SCE (S.ONOFRE) % Unused ETC % Figure 10.7: Traditional Power Flow Dispatch with Mitigation Path 43 Constraint 192