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电网技术 2008, 32(24) 55-59 DOI:
ISSN: 1000-3673 CN: 11-2410/TM |
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| 电力系统 |
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基于免疫粒子群算法的电力系统无功优化 |
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鲁忠燕 邓集祥 汪永红 |
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东北电力大学 电气工程学院，吉林省 吉林市 132012 |
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摘要：
为提高粒子群优化(particle swarm optimization，PSO)算法的收敛性能，将免疫算法(immunity algorithms，IA)的免疫信息处理机制引入到标准粒子群算法，形成一种新的优化算法，即免疫粒子群算法。该算法将免疫算法的免疫记忆和自我调节机制引入PSO，并采用基于粒子浓度机制的多样性保持策略；同时，用免疫算法的"接种疫苗"和"免疫选择"来指导搜索过程。改进后的算法可以很好的保持优化过程中粒子群的多样性，抑制优化过程中出现的退化现象，保证算法的收敛精度和收敛速度。IEEE 30节点系统算例仿真表明，IA-PSO算法与标准PSO算法相比，能够及时跳出局部最优得到全局最优解，且收敛速度快、精度高。 |
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关键词：
免疫算法(IA)
粒子群优化算法(PSO)
免疫粒子群算法(IA-PSO)
无功优化
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Reactive Power Optimization Based on Particle Swarm Optimization Algorithm with Immunity |
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LU Zhong-yan DENG Ji-xiang WANG Yong-hong |
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School of Electrical Engineering，Northeast Dianli University，Jilin 132012，Jilin Province，China |
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Abstract:
To improve the convergence performance of particle swarm optimization(PSO) algorithm, the immunological memory and self-regulation mechanism are led into standard PSO to form particle swarm optimization algorithm with immunity. In the proposed algorithm the diversity holding strategy based on particle concentration mechanism is adopted, meanwhile the vaccination and immunoselection in immune algorithm are used to guide the search process. The improved PSO can hold the diversity of swarm during the optimization process, and eliminate the degeneration phenomenon occurring in the optimization process, thus both convergence accuracy and convergence speed of the improved algorithm can be ensured. The simulation of IEEE 30-bus system that is taken as case study is simulated and the simulation results show that comparing with standard PSO algorithm, the proposed PSO algorithm with immunity possesses following advantages such as high convergence speed, accurate and the ability of getting rid of local optima in time to achieve global optimal solution, etc. |
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Keywords:
immunity algorithm(IA)
particle swarm optimization algorithm(PSO)
particle swarm optimization algorithm with immunity(IA-PSO)
reactive power optimization
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收稿日期 2007-10-22 修回日期 1900-01-01 网络版发布日期 |
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DOI: |
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基金项目:
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通讯作者: 鲁忠燕 |
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作者简介: |
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作者Email: luzhongyan0312@163.com |
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