Coordinating various controllable distributed resources to reduce network losses is crucial to the secure and economical operation of modern power systems. This paper proposes a bi-level optimization model for power s...
详细信息
Coordinating various controllable distributed resources to reduce network losses is crucial to the secure and economical operation of modern power systems. This paper proposes a bi-level optimization model for power system loss reduction based on "source-grid-load-storage" coordinated optimization. The upper level aims to minimize the total annual planning cost of the system, determining the location and capacity of distributed photovoltaic systems, energy storage devices, and electric vehicle charging stations. The lower level aims to minimize the load curve smoothness and node voltage deviation of the distribution network, optimizing intraday operation strategies. For this complex optimization problem, this paper designs a particle swarm optimization (PSO) algorithm with adaptive weights and improved evolutionary strategies. The simulation results of case studies demonstrate that the proposed method has significant loss reduction effects in distribution networks of various scales and complexities. The algorithm performance comparison results show that the improved particle swarm algorithm outperforms traditional algorithms in terms of solution quality and computational efficiency, providing an effective solution for the coordinatedoptimization of "source-grid-load-storage".
暂无评论