Security-Constrained Generation Resource Planning. Jae Hyung ROH ECE Department, IIT June 19, 2007

Transcription

1 Security-Constrained Generation Resource Planning Jae Hyung ROH ECE Department, IIT June 19, 2007

2 Restructuring of Power Industry Before Restructuring After Restructuring GenCo GenCo Generation Transmission Independent Power Producers Bidding Bidding Power Pool Bidding Distribution IPPs PPA TransCo Direct Marketing Bidding Bidding Customer DistCo Consumer DistCo Consumer Consumer group

3 Milestones in Resource Planning Before Restructuring After Restructuring What to Decide Who makes decision Objective Technology, expansion size, sites, timing Utility or Regulatory body Minimization of social cost Same as before Individual Generation companies (GENCOs) Maximization of profit What to consider Technical Aspects System reliability Economical Aspects Fuel cost & maintenance cost installation cost Cost escalation rate Social Discount rate Technical Aspects System Reliability Accessibility to network Economical Aspects Fuel cost & maintenance cost installation cost Cost escalation rate Financial discount rate Future electricity price

4 Electric Power and Power Electronics Center June

5 Infrastructure Under-Investment Under-investment in power systems has negative consequences: higher congestion costs, higher system maintenance costs, more frequent transmission-related service interruptions, increased opportunities for market power exercise.

6 Reasons for Under-Investment Extended periods of uncertainty over energy policies and transmission ownership and operation, Market participants focused on business opportunities in merchant generation and transmission and energy marketing, The cap on retail energy rates has made it difficult to recover investment costs, Due to the regulatory ambiguity, most transmission companies have limited their investments until the market structure is established. Transmission investments are difficult to justify to state regulators since much of the benefits are to accrue over a wide region while the customers of the local utility will be paying the costs.

7 Coordination of Generation and Transmission in Generation Resource planning Objective of the model Introduce the impact of transmission security and competition to generation resource planning. Price Signal Plans Solution Scheme GENCOS Iterative optimization process between GENCOs and the ISO applying Lagrangian relaxation Security Signal and Benders decomposition techniques. Market security and price signals are defined and regarded as effective mechanism for coordination ISO

8 Coordination of Generation and Transmission in Generation Resource planning Locational capacity signal Reflect the generating unit s impact on network security Provide an active direction for capacity installation. For instance, if a new unit at certain site contributes significantly to system security, the value of unit capacity would be high Calculated by Benders decomposition and subgradient method Locational price signal Reflect competition among GENCOs and locations of generating units Provides a direction for unit installation. It represents the value of energy produced by a new unit. Obtained via optimal power flow (OPF).

9 Coordination of Generation and Transmission in Generation Resource planning GENCOs Planning GENCO 1 GENCO 2 GENCO n LMP Loop X1 X2 Check accumulative Benders cuts & Update corresponding multipliers Xn LR Loop Benders Loop Check network security Calculate LMP Final Solution

10 Coordination of Generation and Transmission in Generation Resource planning Modeling procedure Step 1. GENCOs make their own decisions on capacity investments. Step 2. The ISO aggregates GENCOs planning proposals and checks the adequacy of network Step 3. If the network security is not met, the ISO provides GENCOs with capacity signals for revising their investment plans. Step 4. If the network security is met, the ISO calculates price signal and provides it to GENCOs. Step 5. The revised GENCOs decisions are submitted iteratively to the ISO and the iterative process will continue until generation resource investment process reaches an equilibrium

11 Detailed Flow Diagram 1 Benders Master Problem Benders Subproblem GENCO 1 GENCOs Planning GENCO 2 GENCO n Benders Loop Check network security X1 X2 Xn Yes Violation? LR Loop Check accumulative Benders cuts & Update corresponding multipliers Max iteration? LMP Loop Optimal Operation Subproblem No Change in plans? No Yes Yes End No Feasible solution exist? Calculate LMP Yes Select best planning result among feasible solutions Final Solution 1

12 Individual GENCO s Planning Problem (Benders Master Problem) Objective function Profit maximization based on predicted electricity prices Profit = Revenue Production costs Investment cost Max Y R R E C * P * P CI * X GE GC OC OC Constraints Generating unit characteristics such as capacity, heat rate and ramping Availability of sites for adding generating units Types of generating units to be added at each candidate site Availability of funds Decision variables New generating units installation status s.t. 0 PG PG,max CI * X Fund E C * P * P GE GC * X

13 System Security Check Problem (Benders Subproblem) Objective function Minimization of nodal load balance mismatch Constraints First Kirchoff s law for nodal power balance Second Kirchoff s law for lines Generation and line flow limits Min F S s. t. 0 P 0 P 1 S 2 K * PL S PL PL PL GE,max ref 0 GC GE btm 1 max P P S 2 btn mn GC,max A* P B* P Benders cuts Transformed into locational capacity signal by Lagrangian relaxation technique, and added to generation planning problem (master problem) when the objective function is larger than 0. mn * Xˆ P ˆ C + λ *P GC,max*(X-X) 0 λ D Benders cut

14 Optimal Operation Problem & Locational Price Signal Objective function Minimization of system costs Constraints Same as security check problem Locational Marginal Price Locational Marginal Price (LMP) at each node in the system is the corresponding Lagrangian multiplier for the nodal power balance constraint LMP is used for locational price signal Min F BID* P s. t. K * PL A * P B* P ref PL PL PL 0 P 0 P 0 GC GE btm max P P btn mn GC,max GE,max mn D * Xˆ ρ

15 Case Study, 2 Bus System Assumption Planning period : 10 year Three different line capacities of 80 MW, 100 MW, and 120 MW are considered to see the impact of transmission constraint on generation resource planning. Unit A1 Existing Unit A2 Cand. 10% of system load Bus 1 Bus 2 80MW or 100MW or 120MW Unit B1 Existing Unit B2 Cand. 90% of system load New generation units and load data GENCO Capacity (MW) Bus installation cost (Thousand $/ W?Year) Operation Cost ($/MWh) Year Winter Summer Spring Fall A B Existing Existing

16 Case Study, 2 Bus System Generation units construction status by transmission capacity Line Cap. 80 MW 100 MW 120 MW Proposed Unit A2 Unit B2 Unit A2 Unit B2 Unit A2 Unit B2 Installation N Year 3 Year 3 Year 3 Year 3 N Incentive for new generating capacity (Thousand$/year) Line Cap. 80 MW 100 MW 120 MW Unit Unit A2 Unit B2 Unit A2 Unit B2 Unit A2 Unit B2 Year Year Year Year Year

17 Case Study, 2 Bus System Generation units construction status by transmission capacity Line Cap. 80 MW 100 MW 120 MW Proposed Unit A2 Unit B2 Unit A2 Unit B2 Unit A2 Unit B2 Installation N Year 3 Year 3 Year 3 Year 3 N Total payment to GENCOs and GENCOs profit (Million$/year) Line Capacity 80 MW 100 MW 120 MW ISO s Payment GENCOs Profit GENCO 1 s Profit GENCO 2 s Profit

18 Case Study, 2 Bus System Line capacity 80MW Unit B2 located at load center (bus 2) was built. Capacity signal, i.e. incentive is high enough for unit B2 to make profit even though its operation cost is very high. Incentive for adding the unit at bus 1 was relatively low because the low line limit in this case made the new generating unit at bus 1 contribute slightly to the reduction of load curtailment at bus 2. Line capacity 100MW Both new units are added. Incentive on capacity at bus 1 is higher than that of 80MW case because the line is less congested. Lowered LMP resulted in a lower total payment to GENCOs even though two candidate units are built. Line capacity 120MW Only the cheap unit A2 at bus 1 (remote from load center) Lowest LMP and no incentive payment to unit B2 resulted in lower total payment to GENCOs than line capacity 100MW case.

19 Case Study, 2 Bus System Application to transmission expansion Three transmission cases show a proper expansion of transmission capacity could contribute to the reduction of total payment to GENCOs. If the transmission expansion cost is less than the added payment to GENCOs, the best option is to expand the line capacity to 120MW in such cases. $/MWh Million $ Line Capacity 80 Line Capacity 100 Line Capacity 120 1/1 1/2 1/3 1/4 2/1 2/2 2/3 2/4 3/1 3/2 3/3 3/4 4/1 4/2 4/3 4/4 5/1 5/2 5/3 5/4 LMP at Bus 2 Time (Year/Subperiod) GENCO 1 Profit GENCO 2 Profit Total Revenue 80MW 100MW 120MW Financial Results

20 Case Study, IEEE 30 Bus System Assumption Planning period: 15 year Discount rate: 5% System configuration: 44 lines, 21 demand sides, 5 GENCO, 7 existing units and 22 candidate units Study cases Case 0: no TR constraint Case 1: Each line capacity is 300MW (reference) Case 2: line 8 & 16 expanded to 400MW Case 3: discount rate 10% Case 4: change in GENCO2 s bidding strategy from 1.2 to

21 Case Study, IEEE 30 Bus System Generation units installation status by case Year Case 0 Case 1 Case 2 Case 3 Case , 9, 17 8, 17 8, 9, , , , 29 4, 27, 28, 29 27, 28, 29 7, , , 26 15

22 Case Study, IEEE 30 Bus System Financial results (Million $) Case 0 Case 1 Case 2 Case 3 Case 4 GENCO GENCO GENCO GENCO GENCO Total Profit of GENCOs ISO s Payment to GENCOs Average Payment per MWh ($)

23 Case Study, IEEE 30 Bus System Case 0: No transmission constraints Installation of units 8 and 17 in year 7 and unit 9 and unit 12 in year 12 to supply the additional load Unit 8, 9, 12 and 17 have the same capacity and cost structure except location. Thus, without TR constraint, these units will have the same revenue structure once installed. The only factor influencing the installation decision is the GENCO s ownership. Unit 8, 9 and 12 belong to GENCO 2 and unit 17 to GENCO 3. GENCO 2 might want to install more units (unit 9 or unit 12) in year 7. While GENCO 3 insists on unit 17 installation in year 7, GENCO 2 concludes that it is more profitable to install its remaining candidate units in year 12. This case shows the interaction among GENCOs in the market.

24 Case Study, IEEE 30 Bus System Case 1: Each transmission line capacity is 300MW Compared with Case 0, generating units are installed earlier to solve security violations caused by limited transmission line capacity. The incentive for new capacity is big enough for these units to be profitable in early years. Transmission constraints resulted in the installation of units 7 and 29 instead of unit 12. The cumulative payment to GENCOs is higher than that of Case 0.

25 Case Study, IEEE 30 Bus System Case 2: Line 8 & 16 expanded to 400MW to mitigate congestion in Case 1 The mitigation of congestion resulted in the deferred installation of units and cancellation of unit 9. The smaller units 4, 27, 28 are installed instead of unit 7 and 9 due to a modified power dispatch caused by increased line capacity. The overall generating capacity is reduced compared to Case 1 This type of study is useful in decision making for reinforcing transmission lines versus adding generating units. If the expansion cost of transmission lines 8 and 16 is less than the savings in the ISO s payment, transmission reinforcement would be a better option.

26 Case Study, IEEE 30 Bus System Case 3: Discount rate 10% Installation of capital-intensive units (e.g., units 7 and 9) is cancelled or deferred. This anticipated result shows that the proposed model works effectively when financial aspects of generation planning are included in decision making. Case 4: GENCO2 s bidding strategy No changes in GENCOs investment plans. The ISO s total payment to GENCOs increased slightly, while the GENCO 2 s profit decreased. GENCO 2 may not raise its bidding coefficient.

27 Observations The proposed model brings transmission and electricity markets into the sphere of long-term generation resource planning. Using Benders decomposition and Lagrangian relaxation technique, the model simulated the interaction among GENCOs, interaction between ISO and GENCOs, and the impact of transmission on the generation resource planning. Tests on 2-bus system show the effectiveness of the proposed model which can successfully coordinate and simulate the process of long term generation resource planning in restructured power markets.