关键词: 新型农村电网, 分布式光伏, 充电设施, 选址定容, 多目标优化, 改进粒子群算法

Abstract: Facing the dual challenges of high penetration of distributed photovoltaic (PV) generation and surging electric vehicle (EV) charging demand in Hunan’s new-type rural distribution networks, this paper proposes a phased collaborative optimization model integrating siting, sizing, and operational verification, which explicitly accounts for voltage quality, network loss, PV accommodation, and reactive power optimization. The proposed model decouples planning decisions from operational simulations: the upper-level layer minimizes the total annual social cost, including operating costs, user time costs, and PV curtailment penalties; the lower-level layer performs reactive power verification for the planning schemes by minimizing network losses and voltage deviations. To achieve efficient solution under rural dispersed load scenarios, an integrated strategy combining dynamic partitioning with multi-objective normalization is adopted, and an improved particle swarm optimization algorithm is introduced for iterative optimization. A case study is conducted on a newly planned rural area in a county of Hunan Province. The optimization results show that when five charging stations are constructed, the total annual social cost reaches its minimum of 5.2945 million CNY. After the lower-level reactive power optimization, the system active power loss is reduced by 36.28%, the maximum voltage deviation decreases by 58.8%, and the local PV accommodation capacity is significantly enhanced.

Key words: new-type rural power grid, distributed photovoltaic, charging facilities, site selection and capacity determination, multi-objective optimization, improved particle swarm algorithm