电源学报2024，Vol.22Issue(4)：192-199,8.DOI:10.13234/j.issn.2095-2805.2024.4.192
基于AG-MOPSO的含风电配电网无功优化
Reactive Power Optimization of Wind Power Distribution Network Based on AG-MOPSO
摘要
Abstract
Aimed at uncertainties in the output from grid-connected wind turbine,the scenario analysis method based on probability occurrence is adopted to transform the uncertainty model into a multi-scenario problem with different occurrence probabilities,and a reactive power optimization model with the goal of minimizing the active power loss and voltage deviation is established.In view of the poor diversity of Pareto frontiers obtained using the traditional methods,an adaptive grid multi-objective particle swarm optimization(AG-MOPSO)algorithm is proposed,which uses adaptive grids to obtain the density of particles in external archives,selects the global optimal particles and maintains the scale of the external storage library according to the density information as well as the betting mechanism,thus effectively ensuring the uniformity and diversity of the Pareto frontier distribution.This algorithm is used to perform reactive power optimization calculations on an IEEE 33-bus system with wind power,and it is also compared with the existing NSGA-Ⅱ algorithm.Results show that the Pareto frontier obtained using this algorithm is better,which verifies the feasibility of the proposed model and algorithm.关键词
场景分析/多目标无功优化/自适应网格/粒子群优化算法/Pareto前沿Key words
Scenario analysis/multi-objective reactive power optimization/adaptive grid/particle swarm optimization algorithm(PSO)/Pareto frontier分类
信息技术与安全科学引用本文复制引用
苏福清,匡洪海,钟浩..基于AG-MOPSO的含风电配电网无功优化[J].电源学报,2024,22(4):192-199,8.基金项目
国家自然科学基金资助项目(51977072) （51977072）
湖北省重点实验室开放基金资助项目(2019KJX06)This work is supported by National Natural Science Foundation under the grant 51977072 （2019KJX06）
Hubei Key Laboratory Open Fund under the grant 2019KJX06 （）
