Wind Energy Trading Benefits Through Short Term Forecasting Andrew Tindal

1. Wind Energy Trading Benefits Through Short Term ForecastingAndrew Tindal

2. Modelling method Wind Energy Trading Benefits for the UK and Spain Individual wind farm Portfolio Topics Covered

3. L Overview of Forecasting Method • Inputs • Numerical Weather Prediction • SCADA System • Site Measurements Weather Service • Output • Power Forecast

4. Wind Energy Variability • Variable? • Yes • Unpredictable? • No

5. Wind Energy Trading Benefits • Analysis based on GH experience of operating forecasting services in the UK and Spain. • UK Analysis • Assumptions • Calculations based on day ahead predictions • Trade price taken as average of sell and buy prices • All of forecast sold at trade price • Excess energy sold at sell price • Shortfall bought at buy price • Prices obtained from Elexon website, “Best View Prices”:http://www.elexon.co.uk/marketdata/PricingData/default.aspx

6. Forecasting for a single wind farm 10 months of data in 2005 used for analysis Benefit of forecasting shown as average revenue versus the significance placed on the forecast Optimum bid factor of 1.02, gives £33.2 per MWh Even penalty for over or under prediction, therefore bid factor close to 1 Best persistence: £29.0 per MWh Spilling energy: £28.5 per MWh

7. Forecasting for a portfolio of wind farms • Portfolio Effect • Synoptic weather conditions affect different locations at different times • Local topographic effects are reduced • Random errors reduced • Analysis • Three wind farms analysed • Wind farm separation, max = 450 km, min = 180 km. • Ratio of installed capacity of wind farms = 2.5 : 1 : 2.2 • Due to issues with concurrent data the analysis period was limited to 4 months, Oct 05 to Jan 06. • Noticeably higher average energy prices than for single wind farm analysis period • Single Farm, Jan 05 to Oct 05 ~ £37 per MWh • Portfolio, Oct 05 to Jan 06 ~ £76 per MWh

8. Portfolio effect • ~5% reduced MAE

9. Portfolio effect • ~5% reduced MAE • ~£3 per MWh increased revenue Weighted average of individual optimum predictions

10. UK forecasting benefit • Single wind farm = £5/MWh • Portfolio + £3/MWh • UK trading is more complex that this example • but … No forecasting = missed value

11. Wind Energy Trading Benefits • Spain • Participation in the pool market requires the producer to forecast production. • Market Assumptions • Average pool price = €56 per MWh (based on average OMEL prices for 2005) • Deviation penalty = 27% pool price • Reference Tariff (TMR) = €76.6 per MWh • Power guarantee = €4.8 per MWh • Premium = 40% TMR • Incentive = 10% TMR • Reactive power complement = 4% TMR • Market Tariff = €102.2 per MWh – penalty • Alternative option: sell using the Regulated Tariff, currently forecasts not required • Regulated Tariff = 90% TMR + reactive power complement • = €72.0 per MWh

12. Forecasting for a single wind farm Benefit of forecasting shown as average revenue versus forecast horizon • Market revenue > €87 per MWh. • Regulated Tariff = €72 per MWh • Accurate forecasts can add €7 per MWh Daily market revenue using persistence forecasts

13. Analysis Three wind farms analysed Wind farm separation, max = 600 km, min = 280 km. Ratio of installed capacity of wind farms = 1.5 : 3.3 : 1 Due to issues with concurrent data the analysis period was conducted using simplified models with no live feedback. Identical market assumptions were used as for the single wind farm case. Forecasting for a portfolio of wind farms

14. Portfolio effect • ~5% reduced MAE • ~€2.5 per MWh increased revenue Weighted average of individual predictions for the daily market

15. Spanish forecasting benefit • Single wind farm = €7/MWh • Portfolio + €2.5/MWh • Spanish trading is more complex than this example • but … No forecasting = missed value

16. Forecasting is available now Real financial benefits for wind farm operators/traders Single wind farm: UK + £5/MWh Spain + €7/MWh Portfolio: UK + £3/MWh Spain + €2.5/MWh Conclusion