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Briefing on Market Performance Mark Rothleder Director, Market Analysis and Development Board of Governors Meeting General Session November 1-2, 2010 Markets continue to perform well. Key observations: Prices remain competitive and


  1. Briefing on Market Performance Mark Rothleder Director, Market Analysis and Development Board of Governors Meeting General Session November 1-2, 2010

  2. Markets continue to perform well.  Key observations:  Prices remain competitive and consistent with market conditions  Price convergence improves as seasonal flexibility increases  Exceptional dispatches remain at low levels  Congestion revenue rights (CRR) revenue adequacy continues to improve  Price corrections decreased  Areas of focus:  Improve market convergence  Improve forecasting  Provide for dispatch flexibility Slide 2

  3. Frequency and magnitude of 5-minute price volatility decreased as seasonal online ramping capability increased. • Price volatility reduced in summer as more flexible resources committed. 3.0% • Price volatility in July and August due to fires affecting transmission 2.5% Percent of real-time intervals 2.0% 1.5% 1.0% 0.5% 0.0% Jan Feb Mar Apr May Jun Jul Aug Sep 2010 $250 to $500 $500 to $750 $750 to $1000 $1000 to LMP Slide 3

  4. Intermittency of wind production contributes to real-time price volatility Wind forecast gap resulting in 250MW-300MW loss of supply Slide 4

  5. Price convergence between markets improved in last quarter. Average Hourly PGAE LAP Prices Increased online resource flexibility during summer improved convergence $60 $50 $40 $30 $20 $10 $0 Jan Feb Mar Apr May Jun Jul Aug Sep Day-ahead Hour-ahead Real-time 2010 Slide 5

  6. Day ahead exceptional dispatch volumes continue to decrease as more operational constraints are incorporated into the market. 35 30 Approx. 3% of total daily energy 25 Thousands of MWh Per Day 20 15 Approx. 1% of total daily energy 10 5 0 -5 Implemented additional minimum Implemented additional outage-based -10 online constraint. Minimum online commitment constraints. -15 1-Jul 17-Jul 2-Aug 18-Aug 3-Sep 19-Sep 5-Oct 21-Oct 6-Nov 22-Nov 8-Dec 24-Dec 9-Jan 25-Jan 10-Feb 26-Feb 14-Mar 30-Mar 15-Apr 1-May 17-May 2-Jun 18-Jun 4-Jul 20-Jul 5-Aug 21-Aug 6-Sep 22-Sep Day-Ahead Real-Time INC Real-Time DEC Slide 6

  7. Monthly congestion revenue rights revenue adequacy stabilized. Note: Net balancing account includes auction revenues Slide 7

  8. Frequency of price corrections continues to decrease. Slide 8

  9. Publishing day-ahead market on time every day for last two months. 2010 DA Publish Time 15:50 15:30 15:10 14:50 14:30 Time 14:10 13:50 13:30 13:10 12:50 12:30 12:10 11:50 Date Slide 9

  10. Real-time market success rate reduced slightly. Hour-Ahead and Real-Time Unit Comimttment Success Rate 100.00% 99.50% Small increase in failures due to: 99.00% 1) software infeasible solutions Percentage of Successful Completions 2) database related issues 98.50% 98.00% 97.50% 97.00% 96.50% 96.00% . 95.50% HASP RTUC Monthly 95.00% Performance % Success Fa % Success January 99.06% 97.09% Hour Ahead Scheduling Process Real Time Unit Commitment February 98.81% 97.12% Hour Ahead March 99.33% 96.91% Scheduling Process (HASP) April 99.58% 98.66% Real Time Unit May 100.00% 99.42% Commitment Process (RTUC) June 99.58% 99.03% July 99.06% 98.88% August 99.87% 99.42% September 99.17% 98.94% October(thru 10/23) 99.60% 99.78% Slide 10

  11. Real-time market completions Real Time Dispatch Success Rate 100.00% 99.80% • Real-time dispatch successful completion declined due to some database timeouts. 99.60% Percentage of Successful Completions • Database was split in October to address 99.40% 99.20% 99.00% 98.80% . 98.60% Real-Time Monthly 98.40% Performance % Success January February March April May June July August September October January 99.40% Real Time Dispatch February 99.75% March 99.66% Real Time 5 Min Dispatch April Intervals 99.36% May 99.42% June 99.00% July 98.97% August 99.06% September 98.96% October(thru 10/23) 99.70% Slide 11

  12. Areas of focus going forward:  Increase robustness of system  Increase the flexibility of the market to respond to changes in conditions  Improve load forecasting capabilities Slide 12

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