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Secure System Scheduling with High Wind Penetrations

Secure System Scheduling with High Wind Penetrations. J. Kennedy March 2009. Contents. Background to the Irish Power system Problems scheduling the System Spinning and standing reserve on the system Wilmar scheduling model Adjustment of reserve requirements Fast start balancing plant

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Secure System Scheduling with High Wind Penetrations

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  1. Secure System Scheduling with High Wind Penetrations J. Kennedy March 2009

  2. Contents • Background to the Irish Power system • Problems scheduling the System • Spinning and standing reserve on the system • Wilmar scheduling model • Adjustment of reserve requirements • Fast start balancing plant • Conclusions Future Research … 2

  3. Background (Growth of Wind Generation) • Currently (2008 data): • 10% wind energy penetration in Ireland • 2% wind energy penetration in the UK • Projections for 2020 indicate: • 42% wind energy penetration likely in Ireland & • 13% wind energy penetration likely in the UK [1] • Instantaneous power penetration could be much greater • Achieving projected growth figures will: • Significantly reduced imported natural gas in the UK & Ireland • Reduce Carbon emissions, inline with government targets 3

  4. Background (Challenges of Large Scale Wind) • Balancing problems due to wind: • Increased uncertainty (limitations to wind forecasts accuracy) • Variability, increased cycling of thermal plant [2] • Increased part loading of thermal plant • Balancing options: 4

  5. High wind penetrations 30% wind penetration Light load on Sunday morning Strong wind 5

  6. Wilmar Scheduling Model • Developed by Risø for Denmark, Finland, Germany, Norway and Sweden • Realistic forecasting mode • Modified to include mixed Integer variables for use in Irish system • Used extensively in the All Island Grid Study report • Deterministic mode - assumes a perfect forecast • Stochastic mode – assumes a realistic forecast error • Incorporates: Day ahead, and intraday scheduling; Unit ramp rates Min/Max unit generation; Min unit up and down times Temperature dependent start-up costs; Realistic unit reserves Time variable fuel costs; Carbon tax; Stochastic optimisation • Validated against Plexos in the All Island Grid Study 6

  7. Reserve classification Spinning Non-spinning? Non-spinning 7

  8. Assumptions for 2020 As per AIGS: • 1000 MW of asynchronous interconnection • 100 MW interconnection available for tertiary reserve • 6000 MW of installed wind (portfolio 5) Tertiary reserve (90 seconds to 5 minutes) covers: 100% of largest scheduled unit + additional tertiary reserve due to wind Replacement reserve (5 minutes onwards) covers: 90th percentile of total forecast error 8

  9. Assumptions for 2020 • Tertiary reserve (90 seconds to 5 minutes) covers: 100% of largest scheduled unit + additional tertiary reserve due to wind Provide from off-line plant? 9

  10. Operational costs and reserve Deterministic mode 10

  11. Fast start off-line plant for TR1 • Additional tertiary reserve due to wind supplied from off-line plant • For 6000 MW wind, 131 MW of extraTR1 required – easily achieved • Tertiary reserve cost reduced by 22%,or €3.6 M • 146 less start-ups per year with modified TR1 • 213 less start-ups per year on plant larger than 110 MW 11

  12. Conclusions • Allow offline plant to participate in Tertiary reserve band one • Sufficient fast start generation already available for high wind penetration scenarios • Reducing TR1 from online plant, reduces cycling of thermal plant, a major worry of new AIGS • Existing peaking plant more profitable for owners 12

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