March 19th 2009 EWEC 2009 – Marseille Tryggvi Jónsson ENFOR A/S & DTU Informatics

1. March 19th 2009 EWEC 2009, Marseille Forecasting Day-ahead Electricity Prices and Regulation Costs in Markets With Significant Wind Power Penetration March 19th 2009 EWEC 2009 – Marseille Tryggvi Jónsson ENFOR A/S & DTU Informatics Pierre Pinson DTU Informatics Henrik Madsen DTU Informatics

2. March 19th 2009 EWEC 2009, Marseille Intro • The nature of wind power places it inside the equilibrium at almost all times. • Wind power enters the day-ahead electricity supply function as a stochastic quantity with uncertainty attached to it. • The most rapid changes in the supply function are mostly owed to wind power. • Case study: • DK-1 area of Nord Pool’s Elspot • Nord Pool hydro dominated – DK-1 heavily penetrated by wind

3. March 19th 2009 EWEC 2009, Marseille On the market power of wind energy (forecasts) - I

4. March 19th 2009 EWEC 2009, Marseille On the market power of wind energy (forecasts) – II

5. March 19th 2009 EWEC 2009, Marseille Model for forecasting day-ahead prices • Propose a three layer approach to forecast the day-ahead price consisting of: • A mapping of forecasted wind power penetration and time to the average prices • Dynamical weighting of recently observed prices and prediction error together with the output from the first layer. • Uncertainty estimation conditioned upon the forecasted wind power penetration and the forecasted mean price • New observations considered as soon as they become available • Older observations discounted either exponentially or by a rolling window

6. March 19th 2009 EWEC 2009, Marseille Forecasting properties Root Mean Square Error Forecasts on January 12th 2007

7. March 19th 2009 EWEC 2009, Marseille Forecasting regulation costs • Imbalances on the producers side are priced by a two price model at Elspot • Implies no regulation costs for producers bringing the system back to balance • Forecasting of regulation costs is done in two steps • Prediction of the sign of the system imbalance • Probabilistic forecasting of the penalty Cost Up regulation hours Down regulation hours Imbalance

8. March 19th 2009 EWEC 2009, Marseille Predicting the system’s imbalance sign • Predict the imbalance sign by binary classification for each “direction” • Do not believe in linearly separable non-overlapping classes • Explanatory variables are • Forecasted wind power penetration • Spot price forecast • Time variables • Import/Export forecasts

9. March 19th 2009 EWEC 2009, Marseille Predicting the imbalance penalties • Predict price intervals with certain probabilities directly • Predictions conditioned upon the forecasted sign Down regulation Up regulation

10. March 19th 2009 EWEC 2009, Marseille Summary & Final Remarks • The impact of wind power forecasts on the day-ahead prices is substantial and nonlinear • Same applies for regulation costs • Wind power forecasts therefore play an important role in price forecasting • More intelligent trading with benefits for both producers and the system as a whole • More efficient risk hedging as well • Methods are operationally available and results indicate that they can be tailored to other markets