Optimal participation and risk mitigation of wind generators in an electricity market

Abstract

Forecasted output of wind electric generators (WEGs) in a 24-h horizon has large uncertainties. These uncertainties pose a challenge while computing optimal bids necessary for participating in the day-ahead unit commitment process (DACP) thus limiting their integration and success. This study proposes a new optimal participation strategy for a WEG that employs an energy storage device (ESD) for participating in the DACP. The WEG is modelled to function as a price-taker. The proposed formulation has two objectives: (a) maximise returns from the market considering the best forecast; and (b) minimise risks considering the forecast uncertainties. Risk in the participation strategy is quantified by computing expected energy not served (EENS). The multiobjective mixed integer linear programming formulation is transformed into a fuzzy optimisation problem and solved. Through suitable examples, the ESD is shown to play two important roles: (a) it helps to shift wind energy produced during hours with low marginal prices to those hours with higher marginal prices by appropriately storing and releasing it. This shift can be forward or backward in time. (b) The second crucial role played by ESD, upon minimising EENS, is to maintain an energy reserve akin to spinning reserve such that the risk of the optimal participation schedule is the least.