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Secure System Scheduling with High Wind Penetrations

Explore the challenges and solutions of scheduling a power system with high wind energy penetration. Learn about the Wilmar Scheduling Model, reserve requirements adjustment, and fast start balancing plants to achieve efficient wind power integration.

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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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