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
相关论文
共 50 条
  • [41] Multi-objective particle swarm and genetic algorithm for the optimization of the LANSCE linac operation
    Pang, X.
    Rybarcyk, L. J.
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 2014, 741 : 124 - 129
  • [42] Research and Application of Multi-Objective Particle Swarm Optimization Algorithm Based on α-Stable Distribution
    Fan H.
    Zhan H.
    Cheng S.
    Mi B.
    Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University, 2019, 37 (02): : 232 - 241
  • [43] A simplified multi-objective particle swarm optimization algorithm
    Vibhu Trivedi
    Pushkar Varshney
    Manojkumar Ramteke
    Swarm Intelligence, 2020, 14 : 83 - 116
  • [44] Constrained Multi-objective Particle Swarm Optimization Algorithm
    Gao, Yue-lin
    Qu, Min
    EMERGING INTELLIGENT COMPUTING TECHNOLOGY AND APPLICATIONS, 2012, 304 : 47 - 55
  • [45] A particle swarm algorithm for multi-objective optimization problem
    Institute of Information Engineering, Xiangtan University, Xiangtan 411105, China
    Moshi Shibie yu Rengong Zhineng, 2007, 5 (606-611):
  • [46] Multi-Objective Mean Particle Swarm Optimization Algorithm
    Pei, Shengyu
    Zhou, Yongquan
    2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2010, : 3315 - 3319
  • [47] A simplified multi-objective particle swarm optimization algorithm
    Trivedi, Vibhu
    Varshney, Pushkar
    Ramteke, Manojkumar
    SWARM INTELLIGENCE, 2020, 14 (02) : 83 - 116
  • [48] Adaptive Multi-objective Particle Swarm Optimization algorithm
    Tripathi, P. K.
    Bandyopadhyay, Sanghamitra
    Pal, S. K.
    2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS, 2007, : 2281 - +
  • [49] Fault Reconfiguration in Distribution Networks Based on Improved Discrete Multimodal Multi-Objective Particle Swarm Optimization Algorithm
    Li, Xin
    Li, Mingyang
    Yu, Moduo
    Fan, Qinqin
    BIOMIMETICS, 2023, 8 (05)
  • [50] A parallel particle swarm optimization algorithm for multi-objective optimization problems
    Fan, Shu-Kai S.
    Chang, Ju-Ming
    ENGINEERING OPTIMIZATION, 2009, 41 (07) : 673 - 697