Stochastic Optimal Planning of Battery Energy Storage Systems for Isolated Microgrids

Abstract

A novel stochastic planning framework is proposed to determine the optimal battery energy storage system (BESS) capacity and the year of installation in an isolated microgrid using a new representation of the BESS energy diagram. The BESS enhances microgrid operation via load leveling and reserve provisions in conjunction with the spinning reserve from dispatchable distributed generation (DG) units. A decomposition-based approach is proposed to solve the problem of stochastic planning of BESS under uncertainty. The optimal decisions minimize the net present value (NPV) of total expected costs over a multiyear horizon taking into consideration the optimal BESS operation considering a novel matrix representing BESS energy capacity degradation. The proposed approach is solved in two stages as mixed-integer linear programming problems to ensure the convergence of the stochastic optimization problem. The optimal ratings of the BESS are determined in the first stage, while the optimal installation year is determined in the second stage. The approach ensures utilizing the allocated budget effectively by performing several iterations. Extensive studies considering four types of BESS technologies for deterministic, Monte Carlo Simulations, and stochastic cases are presented to demonstrate the effectiveness of the proposed approach.