Multi-objective Particle Swarm Optimization Algorithm for Feeder Capacity Planning of Distribution Network Considering Dynamic Load

• Published in: 2023 3rd International Conference on New Energy and Power Engineering (ICNEPE) pp. 773 - 776
• Main Authors: Yin, Xiang, Liu, Jian, Cheng, Shi, Zang, Siqi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 24.11.2023
• Subjects: Adaptive systems; Capacity planning; Counting and dynamic load; Distribution network; Distribution networks; Feeder capacity; Heuristic algorithms; Multi-objective particle swarm; Optimization planning; Particle swarm optimization; Planning; Planning algorithm; Regulation
• DOI: 10.1109/ICNEPE60694.2023.10429172

The optimization proportion of distribution network feeder capacity cannot reach the expected standard, so this paper proposes a multi-objective Particle swarm optimization algorithm for distribution network feeder capacity considering dynamic load. The multi-objective method is used to expand the planning scope, the multi-objective Particle swarm optimization feeder capacity planning matrix is set, and the feeder capacity optimization planning calculation model under dynamic load is designed. The experimental results show that the final optimization rate of the feeder capacity in the distribution network can reach over 5, indicating that the designed directional planning algorithm has high measurement accuracy, strong pertinence, and controllable error under dynamic load conditions and has practical application value.