针对高比例分布式新能源接入给配电网带来的节点电压越限风险、反向潮流过载、供电可靠性下降等耦合问题，提出一种计及源储协同面向就地消纳与供电可靠性的储能优化规划方法。构建以年化综合成本(含储能投资、新能源弃电惩罚等)、节点电压波动性与净负荷波动性综合最优为目标的储能优化规划模型；采用改进型多目标粒子群优化算法求解该非凸非线性模型，通过自适应惯性权重与基于动态密集距离的非劣解集更新策略规避早熟收敛与局部最优陷阱问题。基于IEEE 33节点配网模型的仿真结果表明：相较于“新能源合理弃电”方案，“配储+新能源合理弃电”方案的新能源消纳率提升约12%，年度综合成本降低约5.6%；相较于“配储”方案，其年度综合成本降低约7.5%。

To address the interconnected challenges of bus voltage limit violations, reverse power flow overloading, and deteriorated power supply reliability caused by high-penetration distributed renewable energy integration, this paper proposes an energy storage optimal planning method considering generation-storage coordination for local consumption and power supply reliability. An energy storage optimal planning model is established, aiming to minimize the annualized comprehensive cost (including energy storage investment and renewable curtailment penalties) while optimizing voltage fluctuation and net load fluctuation. The non-convex nonlinear model is solved using an improved multi-objective particle swarm optimization algorithm. By incorporating an adaptive inertia weight mechanism and a dynamic crowding distance-based non-dominated solution set update strategy, the algorithm effectively avoids premature convergence and local optima traps. Simulation results based on the IEEE 33-bus distribution network demonstrate that the “storage configuration + reasonable curtailment of renewable energy” scheme increases renewable energy local utilization by 12% and reduces annualized comprehensive cost by 5.6% compared to the “reasonable curtailment of renewable energy” scheme, while achieving a 7.5% cost reduction compared to the “storage configuration” scheme alone.