Risk-constrained optimal bidding strategy for a wind power producer with battery energy storage system using extended mathematical programming

Wind power producers (WPP) in India, currently, are restricted from participating in the short-term energy market due to the uncertainty in their power generation. Consequently, they might lose an excellent opportunity to maximise their revenue. WPPs, with installed BESS and proper risk management, could promisingly participate in the market and minimise the penalty for deviating from the schedule. This paper devises an optimal bidding strategy for a WPP to participate in the day-ahead and real-time energy markets considering the uncertainties present in wind power generation and market electricity price. At the same time, it also aims to minimise the power deviation during real-time delivery. The paper incorporates CVaR as a risk measure and formulates a two-layer stochastic optimisation problem while employing multiple scenarios of the uncertain data. The upper layer of the problem decides the day-ahead offering, while the lower layer deals with the real-time operation. The stochastic problem is further reformulated using extended mathematical programming, which benefits in reducing the mathematical complexity of the problem. Wind power data from an actual wind farm located in Gujarat, India is taken as a test-study. Various potential case-studies are presented to illustrate the effectiveness of the proposed bidding strategy.