浏览全部资源
扫码关注微信
School of Electronics and Information Engineering, University of Science and Technology Liaoning, Liaoning Anshan 114051, China
Received：11 October 2025，
Revised：2025-11-10，
Published：25 April 2026
移动端阅览
LI Fang, LI Boqun, CUI Yang. Reactive Power Optimization of Power System Based on Improved Particle Swarm Optimization Algorithm[J]. Power Capacitor & Reactive Power Compensation, 2026, 47(2): 70-79.
LI Fang, LI Boqun, CUI Yang. Reactive Power Optimization of Power System Based on Improved Particle Swarm Optimization Algorithm[J]. Power Capacitor & Reactive Power Compensation, 2026, 47(2): 70-79. DOI： 10.14044/j.1674-1757.pcrpc.2026.02.008.
为提高电力系统无功优化的经济性与运行稳定性，提出了一种改进的粒子群算法（particle swarm optimization，PSO），用于实现配电网无功优化调度。以网损和运行成本最小为目标函数，构建包含传统电容器组与无功补偿器出力的无功优化模型。通过引入精英竞角领导策略与驱动扰动机制，增强算法全局搜索能力与收敛性能，并采用Sigmoid函数动态调整惯性权重，使粒子在解空间分布更为均匀，有效克服传统PSO易早熟收敛的缺陷。此外，定义一种特殊拥挤距离度量方式，保持解的分布性与多样性。在多模态多目标测试函数上的实验表明，该算法能够稳定获取大量分布均匀的帕累托最优解。基于IEEE 14节点系统的仿真验证进一步表明，所提方法在无功优化中具有明显优势，可提供多种分布均匀且多样化的无功补偿方案，显著降低网损并改善电压质量，为配电网优化运行提供有效决策支持。
For improving the economic performance and operation stability of reactive power optimization in power systems，an improved particle swarm optimization（PSO）algorithm is proposed to achieve reactive power optimization dispatching in distribution networks. Taking the minimum network loss and operating cost as the objective functions，a reactive power optimization model including the output of traditional capacitor bank and reactive power compensators is constructed. By introducing the elite competitive leadership strategy and the driving perturbation mechanism，the global search ability and convergence performance of the algorithm are enhanced. Moreover，the Sigmoid function is adopted to dynamically adjust the inertia weight and make the particle distribution in the solution space more uniform，which effectively overcomes the defect of premature convergence of traditional PSO. In addition，a special crowding distance measurement mode is defined，which can maintain the distribution and diversity of solutions. The experiments on multimodal and multi-objective test functions show that this algorithm can stably obtain a large number of uniformly distributed Pareto optimal solutions. The simulation verification based on the IEEE 14-node system further indicates that the proposed method has obvious advantages in reactive power optimization. It can provide a variety of uniformly distributed and diverse reactive power compensation schemes，significantly reduce network losses and improve voltage quality，as well as provide effective decision support for the optimal operation of distribution network.
李伟龙.基于改进PSO的配电网无功优化研究[J].电气开关，2024，62（6）：45-47.
LI Weilong. Research on reactive power optimization of distribution network based on improvedPSO[J]. Electric Switcher，2024，62（6）：45-47.
黄浩，黄咏乐，彭翔.电力系统无功优化的智能算法研究与应用[J].环境技术，2024，42（12）：210-213.
HUANG Hao，HUANG Yongle，PENG Xiang. Research and application of intelligent algorithms for reactive power optimization in power systems[J]. Environmental Technology，2024，42（12）：210-213.
周双喜，郑智，鲁宗相，等.基于多种群遗传算法的无功规划[J].电力系统及其自动化学报，2007，19（6）：66-71.
ZHOU Shuangxi，ZHENG Zhi，LU Zongxiang，et al. New reactive power planning based on the multiple-population genetic algorithm[J]. Proceedings of the CSU - EPSA， 2007，19（6）：66-71.
刘述奎，李奇，陈维荣，等.改进粒子群优化算法在电力系统多目标无功优化中应用[J].电力自动化设备， 2009，29（11）：31-36.
LIU Shukui，LI Qi，CHEN Weirong，et al. Multi-objective reactive power optimization based on modified particle swarm optimization algorithm[J].Electric Power Automation Equipment，2009，29（11）：31-36.
陈春萌，梁英，张舒捷.基于多策略自适应粒子群算法的电网无功优化[J].电力电容器与无功补偿，2020，41（4）：102-108.
CHEN Chunmeng，LIANG Ying，ZHANG Shujie. Reactive power optimization of power grid based on multi-strategy adaptive particle swarm optimization algorithm[J]. Power Capacitor & Reactive Power Compensation，2020，41（4）：102-108.
杨景明，侯新培，崔慧慧，等.基于融合多策略改进的多目标粒子群优化算法[J].控制与决策，2018，33（2）：226-234.
YANG Jingming，HOU Xinpei，CUI Huihui，et al. Improved multi-objectiive particle swarm optimzation algorithm based on integrating multiply strategies[J]. Control and Decision，2018，33（2）：226-234.
邹帅，姬嘉明，杨旭东，等.改进PSO算法在电力系统无功优化中的应用[J].信息与电脑（理论版），2021，33（24）：77-80.
ZOU Shuai，JI Jiaming，YANG Xudong，et al. Applica tion of improved PSO algorithm in power system reactive power optimization[J]. Information and Computers（Theoretical Edition），2021，33（24）：77-80.
张志成.基于鲸鱼算法的配电网无功补偿配置优化方法[J].电气技术与经济，2025（3）：214-216.
ZHANG Zhicheng. Reactive power compensation configuration optimization method for distribution networks based on whale algorithm[J]. Electrical Equipment and Economy， 2025（3）：214-216.
张虹，张泽熙，李亚洲，等.基于分布式信息交互的微电网多智能楼宇区间滚动P2P电能交易策略[J].电工技术学报，2025，40（13）：4292-4305.
ZHANG Hong，ZHANG Zexi，LI Yazhou，et al. A rolling P2P energy trading strategy based on distributed information interaction for multi-intelligent buildings in microgrids[J]. Transactions of China Electrotechnical Society ， 2025 ， 40（13）：4292-4305.
凌峰，郁从丽，袁一凡，等.基于改进遗传算法的低压配电网无功补偿自动优化方法[J].自动化应用，2024，65（15）：258-259.
LING Feng，YU Congli，YUAN Yifan，et al. Automatic optimization method of reactive power compensation of lowvoltage distribution network based on improved genetic algorithm[J]. Automation Application，2024，65（15）：258-259.
程玉，何之倬，王子畅，等.基于遗传算法的光储VSG控制系统无功优化策略[J].电力与能源，2025，46（2）：179-182.
CHENG Yu，HE Zhizhuo，WANG Zichang，et al. Reactive power optimization strategy for PV-storage VSG control system based on genetic algorithm[J]. Power & Energy， 2025，46（2）：179-182.
王琳语.一种基于改进PSO算法的配电网无功优化研究[J].东北电力技术，2025，46（4）：44-47.
WANG Linyu. Research on reactive power optimization of distribution network based on improved PSO algorithm[J]. Northeast Electric Power Technology，2025，46（4）：44-47.
许田阳，李文转，范凯迪，等.基于分层粒子群优化算法的用户侧电力调峰配置模型[J].电工技术，2023（5）：40-42.
XU Tianyang，LI Wenzhuan，FAN Kaidi，et al. User side power peak shaving configuration model based on hierarchical particle swarm optimization algorithm[J]. Electric Engineering，2023（5）：40-42.
熊军华，赵迪迪，刘国庆.基于多目标粒子群算法的配电网无功优化[J].电力电容器与无功补偿，2023，44（3）：26-32.
XIONG Junhua，ZHAO Didi，LIU Guoqing. Reactive power optimization of distribution network based on multi-ob jective particle swarm optimization[J]. Power Capacitor &Reactive Power Compensation，2023，44（3）：26-32.
窦迅，邓叶航，王顺江，等.基于改进多智能体深度确定策略梯度算法的配电网无功协调优化调度[J].电力自动化设备，2025，45（8）：79-86.
DOU Xun，DENG Yehang，WANG Shunjiang，et al. Reactive power coordination optimization scheduling of distribution network based on improved multi-agent deep deterministic policy gradient algorithm[J]. Electric Power Automation Equipment，2025，45（8）：79-86.
赵晶晶，朱炯达，刘帅，等.基于集群划分的配电网多时间尺度分布式有功-无功协同优化方法[J].电测与仪表， 2024，61（10）：57-66.
ZHAO Jingjing，ZHU Jiongda，LIU Shuai，et al. Multi-timescale distributed active and reactive power coordinated optimization method of distributed network based on cluster division[J]. Electrical Measurement & Instrumentation， 2024，61（10）：57-66.
傅国斌，孙海斌，王海亭，等.含高渗透率新能源电力系统多目标无功优化方法[J].高压电器，2025，61（5）：291-301.
FU Guobin，SUN Haibin，WANG Haiting，et al. Multi-objective reactive power optimization method for new energy power systems with high permeability[J]. High Voltage Apparatus，2025，61（5）：291-301.
杜晓东，李晓明，韩思宁，等.基于线性化潮流模型的配电网电压无功控制策略[J].电测与仪表，2024，61（4）：41-47.
DU Xiaodong，LI Xiaoming，HAN Sining，et al. Volt/var control strategy of distribution network based on linearized power flow model[J]. Electrical Measurement & Instrumentation，2024，61（4）：41-47.
丁璨，李江，袁召，等.基于MOPSO算法的超导限流器结构参数优化[J].高压电器，2024，60（11）：209-216.
DING Can，LI Jiang，YUAN Zhao，et al. Structural parameter optimization of superconducting current limiter based on MOPSO algorithm[J]. High Voltage Apparatus，2024， 60（11）：209-216.
乔立同，汪挺，刘剑宁，等.考虑源网荷储协调互动的配电网无功优化[J].电测与仪表，2024，61（5）：146-151.
QIAO Litong，WANG Ting，LIU Jianning，et al. Distribution network reactive power optimization considering generation network load storage interaction[J]. Electrical Measurement & Instrumentation，2024，61（5）：146-151.
蔡黎，向丽红，晏娟，等.引入PID反馈的SHAEKF算法估算电池SOC[J].电池，2024，54（1）：47-51.
CAI Li，XIANG Lihong，YAN Juan，et al. Introduction of SHAEKF algorithm with PID feedback for estimating batterySOC[J]. Dianchi（Battery Bimonthly），2024，54（1）：47-51.
吴桐.基于Q学习超启发算法的农村配电网无功补偿配置容量优化[J].电工技术，2025（11）：104-106.
WU Tong. Capacity optimization of reactive power compensation configuration in rural distribution networks based on Q-learning super heuristic algorithm[J]. Electric Engineering，2025（11）：104-106.
马凡烁，于惠钧，李嘉轩，等.基于改进红嘴蓝鹊优化算法的光储配电网无功优化方法[J].湖南电力，2025，45（3）：95-102.
MA Fanshuo，YU Huijun，LI Jiaxuan，et al. Reactive power optimization method of photovoltaic energy storage distribution network based on improved red-billed blue magpie optimization algorithm[J]. Hunan Electric Power，2025， 45（3）：95-102.
徐涛，李互刚，杨龙雨，等.注意力机制和多目标粒子群混合驱动的配电网无功优化[J].电网与清洁能源， 2024，40（7）：146-154.
XU Tao，LI Hugang，YANG Longyu，et al. Hybrid-driven reactive power optimization for distribution networks driven by attentional mechanisms and multi-objective particle swarms[J].Advances of Power System & Hydroelectric Engineering，2024，40（7）：146-154.
赵晏淇，李伯群，张春宇，等.基于改进海鸥优化算法的热连轧板带轧制规程优化[J].塑性工程学报，2024， 31（11）：97-104.
ZHAO Yanqi，LI Baiqun，ZHANG Chunyu，et al. Optimization of hot continuous rolled strip rolling schedule based on improved seagull optimization algorithm[J].Journal of Plasticity Engineering，2024，31（11）：97-104.
刘振超，苑迎春，王克俭，等.融合特征权重与改进粒子群优化的特征选择算法[J].计算机工程与科学，2024， 46（2）：282-291.
LIU Zhenchao，YUAN Yingchun，WANG Kejian，et al. Feature selection algorithm based on feature weights and improved particle swarm optimization[J]. Computer Engineering and Science，2024，46（2）：282-291.
杨铎烔，俞靖一，葛俊，等.海上风电场自适应多目标无功优化控制策略[J].电力工程技术，2024，43（3）：121-129.
YANG Duotong，YU Jingyi，GE Jun，et al. Adaptive multiobjective reactive power optimization control strategy for offshore wind farms[J]. Jiangsu Electrical Engineering，2024， 43（3）：121-129.
高金兰，刁楠，侯学才，等.基于改进粒子群算法的主动配电网无功优化[J].自动化技术与应用，2024，43（11）：19-23.
GAO Jinlan，DIAO Nan，HOU Xuecai，et al. Reactive power optimization of active distribution network based on improved particle swarm algorithm[J]. Techniques of Auto mation and Applications，2024，43（11）：19-23.
高家元，黄帅，姜飞，等.弱电网下基于比例权重的控制环参数自适应调整并网逆变器稳定性提升方法[J].电工技术学报，2024，39（24）：7846-7859.
GAO Jiayuan，HUANG Shuai，JIANG Fei，et al. Stability improvement method of grid-connected inverter based on proportional weight control loop parameters adaptive adjustment under weak grid[J]. Transactions of China Electrotechnical Society，2024，39（24）：7846-7859.
徐曼，丁然，王德胜，等.考虑风电场并网性能差异的风电集群有功控制策略优化[J].浙江电力，2024，43（10）：85-92.
XU Man，DING Ran，WANG Desheng，et al. Optimization of an active control strategy for wind farm clusters considering their integration performance difference[J]. Zhejiang Electric Power，2024，43（10）：85-92.
杨葆鑫，邢文奇，刘鹏飞，等.基于直流电压前馈的构网型光伏稳定性优化控制策略[J].高压电器，2024，60 （12）：213-222.
YANG Baoxin，XING Wenqi，LIU Pengfei，et al. Optimal control strategy of stability for grid-forming photovoltaic based on DC voltage feedforward[J]. High voltage apparatus，2024，60（12）：213-222.
龚凯，肖晃庆，张展，等.新能源并网换流器的自适应混合同步控制及其小信号稳定性分析[J].浙江电力，2024， 43（11）：3-14.
GONG Kai，XIAO Huangqing，ZHANG Zhan，et al. Adaptive hybrid synchronization control of grid-connected converters in renewable power plants and its small-signal stability analysis[J]. Zhejiang Electric Power，2024，43（11）：3-14.
徐婕，俞斌，白隆，等.基于前推回代法的含DG配电网无功优化[J].自动化与仪表，2024，39（11）：13-17.
XU Jie，YU Bin，BAI Long，et al. Reactive power optimization of distribution network with DG based on for-ward pushback generation method[J]. Automation & Instrumentation，2024，39（11）：13-17.
尚磊，唐王倩云，苏适，等.构网型无功补偿抑制新能源送端暂态过电压[J].电力工程技术，2024，43（2）：83-93.
SHANG Lei，TANG Wangqianyun，SU Shi，et al. Suppression of transient overvoltage in renewable energy transmission terminal by grid-forming based reactive power compensation[J]. Electric Power Engineering Technology，2024， 43（2）：83-93.
0
Views
0
下载量
0
CSCD
0
CNKI被引量
Publicity Resources
Related Articles
Related Author
Related Institution
陕公网安备 61010402000197