Optimal offering strategy considering the risk management for wind power producers in electricity market

This paper provides a technique based on stochastic programming to optimally solve the wind power problem faced by the uncertainty. Uncertainties regarding the wind availability, market prices, and balancing energy needs are considered throughout the paper. The objective of this paper is to derive the best offering strategy for a wind power producer in a Short-Term electricity market, while limiting the risk of expected profit and required reserve due to wind speed forecast volatility. Risk aversion is explicitly modeled using the conditional value-at-risk methodology. ARIMA techniques are used to predict next-day electricity prices and wind speed forecast. For more performance the probability distribution function of the error between forecasted value and realized value to scenario generation is used. A realistic of numerical case studies demonstrates the interest and the effectiveness.

► We provide the best offering strategy for a wind power producer in an electricity market.
► The strategy includes the uncertainty of wind availability, prices, and balancing energy.
► Offering strategy in markets may be enhanced with a CVaR for limiting the risk.
► Pdf of error between forecasted and realized values is used to real scenario generation.
► The optimal required reserve is determined.