Optimal offering strategies to the day-ahead market by a wind power producer

This paper develops a computational tool, based on two-stage stochastic programming, for a wind power producer bidding in the electricity market. The uncertainty related to electricity market prices and wind power production is taken into account. A hybrid intelligent technique, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, enables the generation of scenarios. Besides, risk aversion is considered using the conditional value-at-risk methodology. Computer simulation results are provided and analyzed. Finally, conclusions are duly drawn.