DG Transmission Impact Analysis for Rate Determination GTMax Software Demonstration Thomas D. Veselka (U.S. DOE National Laboratory) Prepared for Distributed Generation Tariff Workshop Midwest CHP Initiative Midwest CHP Application Center U.S. DOE Chicago Regional Office May 14 th, 2003
The Generation and Transmission Maximization (GTMax) Model Optimizes Power System Operations Estimates the value ($) of power system components Combined heat and power (CHP) plants Hydro and thermal power plants Firm purchase and sales contracts Spot or pool market activities Power exchanges and interchange Transmission systems Physical and institutional constraints Generating capability Technical operating minimum Ramping restrictions (change in operations over time) Fuel and reservoir storage limits Simulations One hour time-step Each run solves for a single week
GTMax Simulates Power System Operations and Energy Transactions Hydro & Thermal Resources Operational Restrictions Firm Contracts Hydro Cascade Specifications Demands & Curtailments GTMax Model Transmission & Distribution System Value of Energy & Energy Savings Line and Path Level ATC 1 1. Available Transfer Capability (ATC) Hourly Generation Revenues & Expenses Purchase & Sales Reservoir Operations Contractual Power Flows & LMP 2 2. Locational Marginal Price (LMP)
GTMax Uses a Network Representation of the Power System Hydro & Thermal Plants Pumped Storage Demand Substation Spot Market Delivery Point Hydro Cascade Transmission
GTMax Power Networks Contain Five Types of Electricity Demands Service territory loads -- Demand Node Bilateral contract loads (if any) -- Firm Sales Node Hourly market sales (if economical) -- Spot Market Node Pumping loads for pumped hydro -- Pumping Node Interchanges and exchanges out of the system -- Interchange Node and Exchange Out Node * Additional electricity must be produced because of T&D losses
GTMax Contains Six Types of Power Supply Resources Thermal units -- Thermal Node Baseload Peakers Hydro power plants -- Hydro Node Run-of-river Storage Pumped storage Combined Heat and Power (CHP) plants -- CHP Node Bilateral purchase contracts -- Firm Purchase Node Hourly market purchases -- Spot Market Node Interchanges and exchanges out of the system -- Interchange Node and Exchange In Node
The Transmission System Links Activities Hydro GENERATION Spot Market Demand Centers DISTRIBUTION Thermal Bilateral Purchase TRANSMISSION Sub Station Interchange (In)
In GTMax, Hourly Electricity Bid Prices Are Specified for Each Supply Resource as a Series of Blocks Energy Offers ($/MWh) 30 25 20 15 10 5 Minimum bid (must-run block) Total plant capability is the sum of the blocks 0 50 100 150 200 250 Generation Level (MW)
GTMax Balances Supply & Demand Bids from All Market Participants to Determine Market Clearing Prices (Simplified Example) 80 70 Supply Demand High Prices Result in Lower Pool Market Sales & Demand Curtailments (Dispatchable Load) Market Price ($/MWh) 60 50 40 30 This is the market price that consumers pay and the generator is paid Due to transmission congestion this point must be determined for each zone or region 20 10 Market Bids Are Loaded by Price 0 0 100 200 300 400 500 600 700 Demand (MWh)
Without Transmission Congestion, Market Prices Are Nearly Identical at All Locations Western System Eastern System 1234 1959 2139 163 Uniform market prices 696 Demand level West to east energy transport 750 696 Hydro generation & spills Thermal generation
Transmission Bottlenecks Result in Different Regional Prices Signals where to Build Power Plants or Transmission Lines Western System No energy transfers Eastern System 1322 262 2050 2050 Western generation decreases Large price difference 27.9 $/MWh - West 124.7 $/MWh - East 801 1265 Eastern generation increase
Power Operations in GTMax Respond to Market Forces Through Locational Price Signals 35 160 30 140 Market Price ($/MWh) 25 20 15 10 120 100 80 60 40 Generation (MWh) 5 20 0 1 2 3 4 5 6 7 8 9 101112131415161718192021222324 Hour of the Day 0 Power Electricity Production (MWh) Value of Energy ($/MWh)
GTMax Power Plant Operations Are Constrained by Technical Limitations Power plant (hydro) or unit (thermal) capability Technical minimum production levels Maximum hourly output Fuel stocks and supply limits Daily minimum & maximum energy Change in daily energy production Hourly up & down ramp rate restrictions Change in generation from one hour to the next Daily up & down ramp rate restrictions Change in generation over a 24 hour period Operational Limitations Influence the Economic and Financial Value of a Power Supply Resource
The GTMax Hydropower Dispatch Is Constrained by Reservoir Limitations Maximum reservoir elevation level Minimum reservoir elevation level Daily reservoir elevation change Change over 2-day & 3-day periods Elevation levels are functions of: Initial reservoir conditions Hourly up-stream reservoir releases Side flows Pumped water from a lower reservoir Hourly reservoir releases Water extracted for irrigation or other uses Elevation volume function GTMax computes the marginal value of water
Power Operations Account for System Needs & Security/Reliability RS Regulation services (RS) Affects minimum & maximum generation Spinning reserves (SR) Affects maximum generation Unit commitments Base block is expensive and its capacity is not needed by the system to meet the demand RS and SR requirements are specified on a regional basis Capability (MW) Base Block Peak Block Decrease Maximum Increase Minimum Base Block Peak Block ALC
The CHP Representation in GTMax Considers Both the Electricity Market and the Demand for Heat Power Grid Connection LMP $ Power Power Local Power Demand Power CHP CHP Limits Energy Throughput Capacity Production Efficiencies Limits on Heat/Power Ratios Fuel $ Alternative Heat Supply Heat & Steam Demand Heat Heat Heat $
The Polish Energy Market Agency Used GTMax to Estimate the Financial Viability of Small CHPs in Poland (International Atomic Energy Agency Technical Cooperation Project) The Economic Value of CHP Electricity Is the Difference Between the With and Without CHP Scenarios CHP
Operation of New Cogenerators in Poland Is Driven by Locational Market Prices and Technological Limitations Local CHP Generation (MWh) 25 20 15 10 CHP Generation (MWh) Market Clearing Price North Region ($/MWh) 5 0 Sun Mon Tue Wed Thu Fri Sat 50 45 40 35 30 25 20 15 10 5 0 Market Clearing Price North Region ($/MWh)
Revenues From New CHP Power Sales Are Greater Than Production Costs 1200 Revenues+Expenses (US$) 1000 800 600 400 200 0 Incremental Cost ($) Revenue ($) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hour of Day (Thursday)
Economic and Financial Benefits of CHPs Are a Function of the Supply and Demand Balance (Assuming the CHP Bid/Supply Cost Is Lower Than the Equilibrium Price) 80 Market Price ($/MWh) 70 60 50 40 30 On-Peak Savings (12 $/MWh) With a New CHP Under an LMP Market Rule, All Suppliers Have Lower Revenues While Consumers Have Lower Prices Small Off-Peak Savings CHP On-Peak Supply Demand 20 10 0 Off-Peak Depending on the Rate Structure Financial Implications May Differ Significantly 0 100 200 300 400 500 600 700 Demand (MWh)
Increasing CHP Generating Capability Decreases Economic and Financial Incentives (Assuming CHP Bids/Supply Costs Are Lower Than the Equilibrium Price) 80 Market Price ($/MWh) 70 60 50 40 30 20 10 1 st CHP Savings (12 $/MWh) 2 nd CHP Savings (10 $/MWh) 3 rd CHP Savings (9 $/MWh) A Balance Must Be Found Between Financial Incentives & Economic Benefits 3 rd CHP 1 st CHP 2 nd CHP Supply Demand 0 0 100 200 300 400 500 600 700 Demand (MWh)
GTMax Has Been Used for Numerous Studies and Several Activities Are Currently Underway Power Marketing EIS for the Western Area Power Administration Flaming Gorge Operations EIS for the Bureau of Reclamation (BOR) Role and Value of Hydropower in the Future Southeastern European Regional Electricity Market for USAID Balkan transmission line study for ENRON and USTDA GTMax training and model enhancements for Comision Nacional de Energia Atomica (CNEA), Buenos Aires, Argentina (USDOE) Polish power market study through an IAEA technical cooperation project GTMax Philippine DOE training course and power market games for USAID Hell s Canyon Project is being conducted by the BOR, U.S. Department of the Interior and U.S. Fish & Wildlife Service GTMax will be used to model Loveland Area Projects (WAPA) GTMax will be linked to the WAPA SCADA in Montrose Colorado to assist power marketers
Argonne Is Developing the Electricity Markets Complex Adaptive System (EMCAS) Model to Simulate Market Participant Behavior Represents multiple market participants (agents) with decentralized decision-making agent based modeling Incorporates agent learning and adaptation based on performance and changing conditions A wide range of market strategies are available to the different agents User-specified market rules affect the behavior of individual agents as well as the system [Agent based simulation] has considerable similarity to the mathematical theory of games of strategy, but, unlike the generalized games solved by von Neuman or Nash, these are repeated games with non-zero sum payoffs. A.M. Wildberger, EPRI
EMCAS Uses an Agent-Based Architecture to Represent Participants in the Electricity Marketplace Market Information System Regulator Random Event Generator Customers Demand Companies Power Markets ISO/RTO Physical Generators Transmission System Generation Companies Markets: Pool Bilateral Scheduling Dispatch Settlement Transmission Companies May be single administrative agent with 4 major functions
In EMCAS, Company Agents Seek to Maximize the Corporate Utility Function, Not Overall Social Utility Each company agent can have a set of corporate objectives Profit Market share other Multiple objectives can be combined into a utility function Utility Function = f (Profit, Market Share,..other..) Not all companies necessarily have the same objectives Not all companies necessarily use the same utility function
Agents Obtain Information and Decide Among Options Available to Them TIME EXAMPLE: GENERATION COMPANY AGENT LOOK SIDEWAYS Competing unit availability Own cost structure Market rules Agent Decision Rules LOOK BACK (Short and Long-Term Memory) Bid accepted/rejected Unit utilization Unit profitability Market price vs bid price Weather & load DECISION OUTPUT Bid structure: capacity blocks for different markets Bid prices for each block and market LOOK AHEAD Own unit availability Prices Weather Load
There Are Multiple Advantages to the EMCAS Agent-Based Simulation Decentralized decision making is represented Alternative company strategies can be simulated Adaptation occurs in the simulation Market rules can be tested Transient conditions can be studied Contributors to system problems can be identified
Summary GTMax is a network model that simulates the flow of electricity, fuel, heat, power, and money among various activity nodes The model optimizes power system operations within physical and institutional constraints Locational market prices act as signals for power produces and consumers The EMCAS model uses agent-based modeling methods to predict market participant behavior GTMax has been used extensively over the past several years and can be used in support of future CHP tariff studies