Based on the Bi-level Optimization Framework for Site Selection and Capacity Determination of Renewable Energy Distribution Network Nodes

To address the planning-operation coordination optimization problem of high-proportion renewable energy integration into the distribution network, this paper proposes a node location and capacity determination method based on a bi-level optimization framework and the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm. The upper-level model aims to minimize equipment investment costs and operating costs, determining the installation locations and quantities of wind turbines, photovoltaics, and energy storage. The lower-level model optimizes power scheduling under the given configuration, minimizing voltage deviation and curtailment of wind and solar power. Through simulation verification on the IEEE 33-node system, the results show that the proposed method can generate Pareto-optimal configuration schemes, significantly reduce operating and investment costs, and ensure the safe operation of the power grid.