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A Multi-Agent Clustering-based Approach for the Distributed Planning of Wind Generators

机译：一种基于多智能聚类的群体，用于风力发电机的分布式规划

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In this paper, a new approach for the distributed planning of the wind distributed generators (DGs) in active distribution networks and microgrids is proposed. First, an electrical distance matrix (EDM) is obtained for the distribution system. Having obtained the EDM, a maximization problem is formulated and solved for the optimal clustering of the network. In the second stage, agents are assigned to each cluster, and a multi-objective optimization problem (MOOP) is formulated for optimal planning of wind DGs and assigned to a head agent; the objective functions in the MOOP are equal to the number of agents, and the objective function of an agent is composed of annual energy losses. A voltage improvement index for each cluster is also calculated to measure the improvement in the voltage profile. IEEE 37-node test feeder and two test cases are taken into account for the study. The results show that the losses are reduced in each cluster, and the voltage profile is also enhanced at the same time.
机译：在本文中，提出了一种新的激活分布网络和微电网中的风分布发生器（DGS）的分布式规划方法。首先，为分配系统获得电距离矩阵（EDM）。获得了EDM，制定了最大化问题并解决了网络的最佳聚类。在第二阶段，代理被分配给每个群集，并且配制了多目标优化问题（MOOP）以获得风力DG的最佳规划并分配给头代理; MOOP中的目标功能等于药剂的数量，并且代理的目标函数由年度能量损失组成。还计算每个集群的电压改进索引以测量电压分布的改进。考虑到IEEE 37节点测试馈线和两个测试用例。结果表明，每个簇中的损耗降低，并且电压曲线也同时增强。

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