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Application of Multi-agent Particle Swarm Algorithm in Distribution Network Reconfiguration

机译:多主体粒子群算法在配电网重构中的应用

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An improved algorithm based on Multiagent particle swarm (MAS) is proposed to solve the distribution network reconfiguration problem in this paper. The approach is a combination of the learning, competition and cooperation mechanism of multi-agent technology and the strategies of Particle swarm optimization (PSO) algorithm. Using the Von Neumann topology structure in PSO algorithm, each particle represents an agent; each agent not only competes and cooperates with its neighborhood, but also absorbs the evolutionary mechanism of PSO algorithm, so as to share the information with the agent of global optimal. The rules of particle renovating reduce unfeasible solution in the process of particle renovating, and it is able to converge to global optimal accurately and quickly. Test on the IEEE 16-node, 32-node and 69-node system shows both a rapid convergence and a good robustness of this proposed approach.
机译:针对配电网重构问题,提出了一种基于多主体粒子群算法的改进算法。该方法是多智能体技术的学习,竞争和协作机制与粒子群优化(PSO)算法策略的结合。使用PSO算法中的冯·诺依曼拓扑结构,每个粒子代表一个代理;每个智能体不仅与其邻域进行竞争与协作,而且还吸收了PSO算法的进化机制,从而与全局最优智能体共享信息。粒子更新规则减少了粒子更新过程中不可行的解决方案,能够准确,快速地收敛到全局最优。在IEEE 16节点,32节点和69节点系统上的测试表明,该方法具有快速收敛性和良好的鲁棒性。

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