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Hybrid Stochastic/Robust Offering Strategy for Coordinated Wind Power and Compressed Air Energy Storage in Multielectricity Markets

Coordinated operation of renewable resources and storage devices can reduce the undesirable effects of poor predictability of renewable producers. This article proposes a three-stage hybrid robust/stochastic framework to model the coordinated operation of wind producers and compressed air energy storage in the form of a mixed-integer linear programming problem. The proposed algorithm derives robust offering curves to participate in the day-ahead market. In addition to the day-ahead market, intraday and balancing markets are considered for reducing the negative effects of poor predictability of wind speed. In the proposed hybrid framework, intraday and balancing market prices as well as wind speed are modeled by proper scenarios, while robust optimization is used to model the day-ahead price uncertainty. Besides, the risks of stochastic parameters are modeled by the conditional value at risk (CVaR). Based on the results of robust optimization, the uncertainty of the day-ahead market price reduces the aggregator profit by 21.3% in the worst case, whereas CVaR results show a 13.2% profit reduction due to the worst-case scenario realization in stochastic parameters.