Stochastic optimal regulation service strategy for a wind farm participating in the electricity market

As modern wind farms have the ability to provide regulation service for the power system, wind power plant operators may be motivated to participate in the regulating market to maximize their profit. In this paper, an optimal regulation service strategy for a wind farm to participate in the regulating market is proposed. The relationship between up regulation price and wind power level, and the relationship between the probability of up regulation and the wind power level are studied. The stochastic optimization is adopted to find the optimal ratio for regulation service. The Monte Carlo method is used in the stochastic optimization to deal with the uncertainty of the up regulation price and the up regulation activation of the power system. The Danish short-term electricity market and a wind farm in western Denmark are chosen to evaluate the effect of the proposed strategy. Simulation results show the proposed strategy can increase the revenue of wind farms by leaving a certain amount of wind power for regulation service.