Multi-objective collaborative optimization of active distribution network operation based on improved particle swarm optimization algorithm

被引:0
|
作者
Sun, Shumin [1 ]
Yu, Peng [1 ]
Xing, Jiawei [1 ]
Wang, Yuejiao [1 ]
Yang, Song [1 ]
机构
[1] State Grid Shandong Elect Power Res Inst, Jinan 250002, Peoples R China
来源
SCIENTIFIC REPORTS | 2025年 / 15卷 / 01期
关键词
Improved particle swarm optimization; Active distribution network; Distribution network operation; Multi-objective; Collaborative optimization;
D O I
10.1038/s41598-025-90907-2
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
ADN (Active distribution network) is easily disturbed during its operation, resulting in problems such as power supply quality degradation and operation safety deterioration. Therefore, the research and simulation of multi-objective collaborative optimization of ADN operation based on improved particle swarm optimization algorithm are proposed. An objective function of multi-objective collaborative optimization configuration for ADN operation is constructed. According to this objective function, the improved particle swarm optimization algorithm is used to optimize the collaborative optimization configuration, and the population particles are mutated, and the obtained result is the optimal energy storage capacity configuration result of power system. The architecture of the simulation platform for cooperative operation of ADN is constructed, and the load grades of distribution system are divided. Based on the hierarchical management of loads in distributed systems, multi-objective collaborative optimization of ADN operating voltage in both frequency and time domains has been achieved. The experimental results show that during peak periods, the system's load capacity is only twice that of before optimization or other situations, achieving stable power supply for peak power demand. Multi-objective collaborative optimization in frequency domain and time domain has the best effect. Under the conditions of reactive power and active power, the multi-objective collaborative optimization method of ADN operation has good results.
引用
收藏
页数:14
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