Optimal Configuration Method of Distributed Photovoltaic Energy Storage System

The stochastic and intermittent characteristics of photovoltaic (PV) power generation lead to suboptimal resource utilization. Energy storage systems (ESS), characterized by flexible control and rapid response, have emerged as an effective solution to address PV grid integration challenges and enhance energy consumption efficiency. Currently, the high investment costs of ESS remain a critical constraint for their widespread deployment. From a cost-benefit perspective, this paper investigates the optimal configuration of ESS in distributed PV systems. A two-layer optimization model is first established, targeting the minimization of total system costs, considering constraints such as ESS installation locations, capacity, state of charge (SOC), and grid operational limits. The outer layer employs a genetic algorithm (GA) to optimize ESS location, power rating, and capacity, while the inner layer utilizes a particle swarm optimization (PSO) algorithm integrated with MATPOWER for power flow calculations to refine daily operation strategies. The feasibility and effectiveness of the proposed method are validated through simulations on the IEEE 33-node system using Matlab.