Distributed energy storage planning method considering multi-point aggregation effect

Abstract

ABSTRACT The economic performance and utilization rate have become the key factors limiting the development of energy storage systems (ESS). From the perspective of the aggregation effect manifested by multi-point ESS, an inspired concept of “aggregation configuration, decentralized location” is proposed. Based on this concept, this paper proposes a planning method using two-stage optimization including sizing, siting and operational optimization for distributed energy storage (DES). The first-stage optimization aims to maximize the net present value (NPV) of aggregate ESS, while the second stage aims to mitigate the voltage fluctuation after the integration of distributed PV generation. In addition, the operational optimization for both the aggregate ESS and individual DES units are considered to better achieve the objectives of the two-stage optimization, and the particle swarm optimization (PSO) algorithm is employed to solve the planning problem. Case studies show that the proposed method helps to ensure the global NPV over the lifespan of aggregate ESS by considering operational optimization and depth of charge (DOD). Compared with the centralized ESS solution, the proposed multi-point DES solution can improve the overall voltage fluctuation mitigation capability by more than 40%. With the PV capacity penetration rate varying from 0 ~ 210%, sensitivity analysis reveals that when the penetration rate is close to 100%, the aggregate ESS has better economic performance and voltage fluctuation mitigation capability.