Integrating Wind Power Efficiently into Electricity Markets Poses New Regulatory Challenges

Transcription

1 PSERC Webinar, January 19, 2010 Integrating Wind Power Efficiently into Electricity Markets Poses New Regulatory Challenges Tim Mount Department of Applied Economics and Management Cornell University

2 Acknowledgements The research used in this presentation was supported by the U.S. Department of Energy through the Consortium for Electric Reliability Technology Solutions (CERTS) and by the Power Systems Engineering Research Center (PSERC). Engineers: Lindsay Anderson, Hsiao-Dong Chiang, Andrew Hunter, Bob Thomas, Lang Tong, Francis Vanek, Max Zhang at Cornell University Economists: Alberto Lamadrid, Surin Maneevitjit, Tim Mount, Dick Schuler, Bill Schulze at Cornell University Judy Cardell at Smith College Dan Shawhan at RPI 2

3 New Goals for Energy Policy OBJECTIVE Mitigate the effects of climate change President Obama s proposed goal is to reduce national emissions of greenhouse gases by 80% by NECESSARY STEPS Generate electricity from renewable (and nuclear?) sources of energy and replace fossil fuels like coal (or use CCS) Use electricity for transportation and replace petroleum fuels ( improved urban air quality) Make buildings energy efficient and use ground-source heat pumps for space conditioning with thermal storage Decentralize energy sources and controls 3

4 Outline INVESTIGATE THE EFFECTS OF RENEWABLES Add wind generating capacity to replace coal capacity Determine the effects on: Annual earnings of the conventional generating units in the wholesale market Missing money needed to maintain their Financial Adequacy and the System Adequacy of the network CASE STUDY Use a 30-bus test AC network in a deregulated market Determine the generating capacity needed to maintain System Adequacy ENDOGENOUSLY Determine the Total Annual System Cost IDEAL DISTRIBUTION NETWORK 4

5 Current Reliability Standards North-American Electric Reliability Council (NERC) 1. Operating Reliability The ability of the electric system to withstand sudden disturbances such as electric short circuits or unanticipated failure of system elements. [Determining the dispatch of installed capacity and levels of reserves --- the system operators problem] 2. System Adequacy The ability of the electric system to supply the aggregate electrical demand and energy requirements of customers at all times, taking into account scheduled and reasonably expected unscheduled outages of system elements. [Ensuring there is enough generation and transmission capacity --- the planners problem] PLANNERS SHOULD ADD A THIRD CRITERION 3. Financial Adequacy The ability of the wholesale market, supplemented by capacity markets and regulation, to provide sufficient income streams to make the generators and transmission owners financially viable. [Ensuring that the resources needed for System Adequacy are financially viable --- another problem for planners] 5

6 30-Bus Test Network Area 1 - Urban - High Load - High Cost - VOLL = $10,000/MWh Area 3 - Rural - Low Load - Low Cost - VOLL = $5,000/MWh Upgrade AC Tie Line Wind Farm +105MW Wind -35MW Coal Area 2 - Rural - Low Load - Low Cost - VOLL = $5,000/MWh 6

7 Scenarios Considered Case 1: NO Wind, Initial System Capacity Case 2: NORMAL Wind* 105MW of variable wind replaces 35MW of coal in Area 2 Case 3: NICE Wind* Variability of wind smoothed by storage in Area 2 Case 4: NASTY Wind* Variable wind with a must-take contract in Area 2 Cases 1UP, 2UP, 3UP and 4UP Same as Cases 1, 2, 3 and 4 with Upgraded AC Tie Line * Represents 25% of the total installed generating capacity 7

8 Analysis Uses the Cornell SuperOPF Determining the optimal power flows for operations and planning on an AC network are computationally complex due to many non-linear constraints (Kirchhoff s Laws). Traditional Approach SuperOPF Break into manageable sub-problems using DC approximations sequential optimization using proxy constraints incorrect prices Use a full AC network in a single mathematical programming framework. co-optimization of the dispatch with explicit contingencies correct prices 8

9 Co-optimization Minimize the Expected Cost of Dispatch over Different States of the System Contingency 1 Base Case Contingency 2. Contingency k 9

10 Simplified Objective Function min p k C Gi (G ik ) + C Ri (R i ) G, R K k =0 I i=1 [ ] + VOLLj J j =1 LNSjk Subject to meeting LOAD and all of the nonlinear AC CONSTRAINTS of the network Where k is a STATE/CONTINGENCY i is a GENERATOR j is a LOAD p k is a PROBABILITY C G (G i ) is the COST of generating G i MWh C R (R i ) is the COST of providing R i MW of RESERVES VOLL j is the VALUE OF LOST LOAD LNS jk is the LOAD NOT SERVED KEY FEATURES: Contingencies have a finite economic cost (LNS) Total capacity committed is determined endogenously 10

11 Key Capabilities of the SuperOPF Determines the commitment of real energy and reactive power and the locations of up and down reserves needed to maintain Operating Reliability ENDOGENOUSLY Determines the economic cost of failing to meet standards of Operating Reliability (i.e. the cost of the expected quantity of load-not-served priced at VOLL for a set of credible contingencies) Provides a consistent mechanism for subsequent redispatching and pricing when more information about uncertain quantities is available (e.g. Load, Wind Speed) The same analytical framework can be used for planning purposes to evaluate System Adequacy 11

12 Contingencies Considered (Generator Outages, Line Outages and Wind Speeds) 97% 3% All Equipment Failures are Specified at the Lowest Realization of Wind (Case 0) 12

13 Normal and Nice Wind Scenarios Three Wind Forecasts with Four Possible Outcomes for each one Forecasted Wind Speed Probability of Forecast Wind Output (% of installed MW) Output Probability (Conditional on Forecast) Normal Nice LOW (0-5 m/s) MEDIUM (5-13 m/s) HIGH (13+ m/s) 11% 46% 43% 0% 35% 66% 7% 35% 26% 33% 35% 5% 73% 38% 3% 6% 41% 24% 38% 55% 20% 62% 55% 18% 93% 58% 38% 0% 35% 14% 66% 70% 4% 94% 70% 3% 100% 70% 79% 13

14 Payments by Customers in the Wholesale Market Total Annual Payments by Customers are determined by ranking the hourly loads for a year and aggregating them into100 bins (typical hours). The expected cost for each hour is determined by: 1) Determining the day-ahead commitment of generating capacity and reserve capacity using the expected forecast of wind speed 2) Evaluating the cost for all contingencies using all three forecasts of wind speed (High, Medium and Low) 3) Use the appropriate probabilities to determine the expected cost Congestion Rents = Total Annual Payments by Customers Total Annual Payments to Generators Total Annual Earnings for Generators = Total Annual Payments to Generators Total Annual Operating Costs (Zero Operating Costs assumed for Wind Generation) 14

15 Total Annual Payments By Customers in the Wholesale Market $82,000 $62,000 $42,000 $22,000 $2,000 -$18,000 Annual Wholesale Payments ($1000/Year) case1 case1 UP case2 case2 UP case3 case3 UP case4 case4 UP Congestion Rent Wind Net Revenue Gen Net Revenue Operating Costs 1) Conventional Generators are the big losers and Customers are the big winners with NORMAL and NICE Wind 2) Congestion Rents are relatively small and maybe negative 3) Revenues for Wind Generators are relatively small Case 1: NO Wind with Initial System Capacity Case 1UP: NO Wind + Upgraded AC Tie Line Case 2: NORMAL Wind Case 2UP: NORMAL Wind + Upgraded AC Tie Line Case 3: NICE Wind Case 3UP: NICE Wind + Upgraded AC Tie Line Case 4: NASTY Wind Case 4UP: NASTY Wind + Upgraded AC Tie Line 15

16 Overview of the Wholesale Results The wholesale costs to customers are much lower with NORMAL and NICE Wind, and higher with NASTY Wind The wholesale costs to customers are even lower with a tie line upgrade A lot more wind is spilled with NORMAL and NICE Wind compared to NASTY Wind More Load-Not-Served with NASTY Wind WHAT ARE THE IMPLICATIONS FOR CAPITAL COSTS? 16

17 Calculating the Missing Money Needed to Cover Annualized Capital Costs For Transmission Owners Congestion Rents = Total Annual Payments by Customers Total Annual Revenue received by Generators Missing Money = Allowed Capital Costs + O&M Costs Congestion Rents For Generating Units Total Annual Net Revenue = Total Annual Revenue Total Annual Operating Costs (Zero Operating Costs for Wind Generation) Minimum Net Revenue = Annualized Capital Cost x MW Committed to meet the Peak System Load (i.e. to maintain System Adequacy) By type of generating unit (e.g. $88,000/MW/year for G1 and G2 in Area 1) Missing Money = Minimum Net Revenue Total Annual Net Revenue 17

18 Missing Money for Generating Units Capacity Payments Total Annual System Cost ALTERNATIVE METHODS OF PAYMENT FOR GENERATORS Market 1. DEREGULATED MARKET Capacity Price = Missing Money by Unit/ MW Committed for System Adequacy Capacity Payments in a Capacity Market = Maximum Capacity Price in a Region paid to all MW Committed in that Region Area 1 for Gen 1 and Gen 2 Areas 2 and 3 for Gen 3 6 Market 2. MISSING MONEY ONLY Capacity Payments = Max[ Missing Money by Unit, 0 ] Market 3. REGULATED MARKET Allowed Capital Costs = (Minimum Net Revenue)/2 to reflect the BOOK value versus MARKET value of the Capital Assets of Generators Missing Money = Allowed Capital Costs Total Annual Net Revenue Capacity Payments = Sum of positive and negative Missing Money 18

19 Maintaining System Adequacy 20 MW Conventional Capacity Needed Compared to Case 1 with NO Wind case case1 UP case2 case2 UP case3 case3-24 UP 12 9 case4 case4 UP Case 1: NO Wind with Initial System Capacity Case 1UP: NO Wind + Upgraded AC Tie Line Case 2: NORMAL Wind Case 2UP: NORMAL Wind + Upgraded AC Tie Line Case 3: NICE Wind Case 3UP: NICE Wind + Upgraded AC Tie Line Case 4: NASTY Wind Case 4UP: NASTY Wind + Upgraded AC Tie Line 19

20 Capacity Payments Per MW of Generating Capacity DEREGULATED MARKET case1 case1 UP AVERAGE CAPACITY PRICE ($1000/MW/year) case2 case2 UP case3 case3 UP case4 case4 UP TRANS GEN Lower Wholesale Prices for NORMAL and NICE Wind are offset by a Higher Prices for Capacity The number of MW needed for System Adequacy also affects Capacity Payments Case 1: NO Wind with Initial System Capacity Case 1UP: NO Wind + Upgraded AC Tie Line Case 2: NORMAL Wind Case 2UP: NORMAL Wind + Upgraded AC Tie Line Case 3: NICE Wind Case 3UP: NICE Wind + Upgraded AC Tie Line Case 4: NASTY Wind Case 4UP: NASTY Wind + Upgraded AC Tie Line 20

21 Total Annual System Costs ($1000/Year) Mkt. 1. DEREGULATED MARKET $162,000 $142,000 $122,000 $102,000 $82,000 $62,000 $42,000 $22,000 $2,000 -$18,000 case1 case1 UP case2 case2 UP case3 case3 UP case4 case4 UP Fuel Costs Net Earn Gens Net Earn Wind MM Paid to Gens Congestion MM Paid to Trans Load Not Served Case 1: NO Wind with Initial System Capacity Case 1UP: NO Wind + Upgraded AC Tie Line Case 2: NORMAL Wind Case 2UP: NORMAL Wind + Upgraded AC Tie Line Case 3: NICE Wind Case 3UP: NICE Wind + Upgraded AC Tie Line Case 4: NASTY Wind Case 4UP: NASTY Wind + Upgraded AC Tie Line 21

22 Total Annual System Costs for Different Types of Market $190 Total Annual System Costs $170 $150 $1000/Year $130 $110 $90 $70 $50 NO Wind NORMAL NICE NASTY Mkt. 1: Deregulated Mkt. 2: Missing Money Mkt. 3: Regulated Differences in Total Costs caused by different CAPITAL COSTS Deregulated > Missing Money > Regulated for ALL Wind Cases PRICE of Capital is HIGH for NORMAL and NICE Wind Larger savings in Regulated Markets 22

23 Savings in Total Annual System Costs for Different Types of Market I $50 $40 $30 Savings from Adding Wind Capacity $1000/Year $20 $10 $0 -$10 -$20 -$30 -$40 NO Wind NORMAL NICE NASTY Mkt. 1: Deregulated Mkt. 2: Missing Money Mkt. 3: Regulated Differences in Savings caused by different CAPITAL COSTS Deregulated < Missing Money < Regulated for NORMAL and NICE Wind - Capacity Payments are a relatively large proportion of Total Costs Savings are negative for NASTY Wind 23

24 Savings in Total Annual System Costs for Different Types of Market II $60 $50 $40 Savings from Upgrading the Tie Line $1000/Year $30 $20 $10 $0 -$10 NO Wind NORMAL NICE NASTY Mkt. 1: Deregulated Mkt. 2: Missing Money Mkt. 3: Regulated Differences in Savings caused by different CAPITAL COSTS No consistent ranking for different markets Savings for NO, NORMAL and NICE Wind are relatively SMALL Savings are large for NASTY Wind because the upgrade relieves network constraints with high levels of wind generation 24

25 Need a New Dynamic Rate Structure Adding wind generation will result in: Wholesale Energy Prices going DOWN Capacity Prices going UP All customers should pay for both Energy and Capacity Real-time nodal prices for the ENERGY used Correct price for the CAPACITY demanded at the system peak The financial viability of storage technologies and controllable load depends on getting the Capacity Price and Capacity Demanded measured correctly 25

26 IDEAL Distribution Networks I THE PROBLEM Impractical for most Residential and small Commercial customers to pay for both Energy and Capacity: Difficult to measure Capacity correctly for individual customers Responses to Real-Time Prices for Energy are relatively slow Information overload for many customers inefficient response A SOLUTION Aggregate the loads of small customers and manage them as a single Wholesale customer: Better management of the aggregate load and peak capacity demanded Rapid response possible using wireless signals/automatic controls Augments voluntary responses by customers Simplifies the operations for Transmission System Operators 26

27 IDEAL Distribution Networks II Need a new generation of engineer/managers to operate and manage community distribution systems: Manage new Distributed Energy Resources effectively Reduce costs for customers by managing the aggregate peak load Provide new capabilities to support the bulk-power grid Provide economic incentives to individual customers Cornell has proposed an Intelligent Dependable Energy with Active Load (IDEAL) Campus Network: Diverse types of Distributed Energy Resources already exist New facilities for training students will be developed An IDEAL campus network will lead to IDEAL community networks 27

28 Integrating Wind Generation: Conclusions I With higher penetrations of wind capacity: The Financial Adequacy of conventional generators will be an increasingly important issue for maintaining System Adequacy Lower Capacity Factors will make the missing money cost of meeting the system peak load more expensive per MW The cost of ramping dispatch patterns to offset the variability of wind generation will increase (a focus of current research) 28

29 Integrating Wind Generation: Conclusions II Adding controllable load and storage: Can help to compensate for wind variability Can flatten and smooth daily load patterns Can mitigate price spikes Can respond to equipment failures (contingencies) Can reduce the System Peak Load Can reduce the amount of conventional generating capacity needed to maintain reliability standards Can increase the Capacity Factors of conventional generators Can reduce the problem of Financial Adequacy for conventional generators 29

30 Integrating Wind Generation: Conclusions III Financial Adequacy of an IDEAL Network Need an overhaul of current regulatory practices, particularly in Deregulated Markets, to ensure: Participants receive financial incentives that reflect the true system costs/benefits Institutional/regulatory barriers to establishing a more decentralized structure for operating and managing the grid are removed Distribution Operator/Managers should pay the correct prices for ENERGY and PEAK DEMAND Distribution Operator/Managers should receive the correct payments for providing RAMPING and other ANCILLARY SERVICES 30

31 Cornell Combined Heat & Power Project Smart substation 2 x 15MW Gas turbines THANK YOU 31 Questions?