Energy Storage Optimal Planning Method Considering Generation-Storage Coordination for Local Consumption and Power Supply Reliability

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.