Profit maximization of wind power producers with risk control considering uncertainty

Wind power has emerged as one of the most prominent and rapidly expanding clean energy sources. But, with the subsidies offered and reduced incentives, wind power producers (WPP) need to formulate efficient bidding schemes to make their investments profitable. The purpose of this study is to create a stochastic decision model that will maximize the earnings of WPP participating in both day-ahead (DA) and balancing markets (BM). However, the participation of WPP in the DA market can lead to significant deviations from the initial preferred schedule due to the uncertainties associated with its offering decisions. These include uncertainties from intermittent wind power, energy prices, and imbalance penalties. Hence, a set of plausible scenarios is used to model each uncertainty. Further, a conditional value-at-risk (CVaR) metric is incorporated into the model for risk control to manage the risks related to the offering decisions. Numerical results from a case study are presented to demonstrate the efficacy of the suggested approach in increasing the WPP expected profit and lowering the associated risks.