Optimal Daily Scheduling of Distributed Battery Energy Storage Systems Considering Battery Degradation Cost

Abstract

Distributed battery energy storage systems (BESSs) have been increasingly installed on the residential side to perform peak shaving and help improve photovoltaic (PV) energy utilization efficiency. However, associated battery degradation issues occur as BESSs are frequently operated, impairing economic benefits. Thus, this paper proposes an optimal daily scheduling method of distributed BESSs considering battery degradation cost. This method aims to maximize operating profits for BESS aggregators participating in electricity market, while minimizing the battery degradation cost. Firstly, a new linear model to calculate battery depth of discharge is developed, which can be efficiently involved in optimization models. Then, a battery daily degradation cost model is developed by utilizing a capital recovery factor and a curve fitting technique. Last, a daily scheduling optimization model considering the battery degradation cost is formulated and a scenario-based stochastic optimization method is applied to address uncertainties of PV generation and loads. Simulations indicate high economic efficiency of the proposed method for distributed BESSs.