Robust operation strategy enabling a combined wind/battery power plant for providing energy and frequency ancillary services

Abstract This paper presents a methodology that enables a combined wind/battery power plant to participate in the energy and ancillary-services market. Due to uncertainties of both the wind-power output and the system-regulation demand, the day-ahead optimization strategy and real-time operational management of the power plant must be studied. Firstly, in day-ahead optimization, this paper presents two data-processing methods to analyze the probabilistic distribution of the two uncertainty factors, from the perspective of defining a robust optimal strategy in both markets. Then, in real-time operation, a model predictive control (MPC)-based strategy is proposed to increase the performance of the wind-power plant by managing the battery storage. The methodology is evaluated using historical prices of energy and ancillary-service reserves. In addition to confirming the effectiveness of the proposed methodology, the result shows that deploying the battery can provide extra flexibility to a wind farm for providing symmetric reserve services. Moreover, the data-driven approach using historical wind-generation data and regulation signals can improve the performance of the plant.