Optimal Day-ahead Scheduling of Islanded Microgrid Considering Risk-based Reserve Decision

Due to the lack of support from the main grid, the intermittency of renewable energy sources (RESs) and the fluctuation of load will derive uncertainties to the operation of islanded microgrids (IMGs). It is crucial to allocate appropriate reserve capacity for the economic and reliable operation of IMGs. With the high penetration of RESs, it faces both economic and environmental challenges if we only use spinning reserve for reserve support. To solve these problems, a multi-type reserve scheme for IMGs is proposed according to different operation characteristics of generation, load, and storage. The operation risk due to reserve shortage is modeled by the conditional value-at-risk (CVaR) method. The correlation of input variables is considered for the forecasting error modeling of RES and load, and Latin hypercube sampling (LHS) is adopted to generate the random scenarios of the forecasting error, so as to avoid the dimension disaster caused by conventional large-scale scenario sampling approaches. Furthermore, an optimal day-ahead scheduling model of joint energy and reserve considering risk-based reserve decision is established to coordinate the security and economy of the operation of IMGs. Finally, the comparison of numerical results of different schemes demonstrate the rationality and effectiveness of the proposed scheme and model.