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Optimal placement and sizing of distributed generation in radial distribution system using K-means clustering method

机译:基于K均值聚类的径向配电系统中分布式发电的最优布置和尺寸确定。

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Distributed generations play important role for power quality such as losses reduction, voltage profile and reliability improvement. However on its implementation, to obtain optimal solution installation DG have to be planned properly. Hence, it is important to determine optimal location and size of DG during the planning of active distribution system to achieve minimum losses. This paper proposes the DG placement and sizing technique using K-Means Clustering method. Clustering based technique is used to determine optimal location of DG based on Loss Sensitivity Factor (LSF) and bus voltage. Once optimal location is obtained then analytical approach is used to determine optimal size of DG. The proposed method is tested on IEEE 33 bus and 69 bus radial distribution system to verify its performance on obtaining optimal DG placement and sizing for losses reduction. The result on IEEE 33 bus system shows that the proposed method obtain 87,5% losses reduction, better than 76,77% loss reduction obtained by LSF priority list method. While result on IEEE 69 bus system shows that the proposed method obtain 69,84% losses reduction, better than 65,95% loss reduction obtained by LSF priority list method.
机译:分布式发电对电能质量起着重要作用,例如降低损耗,改善电压分布和提高可靠性。但是,在实施时,必须正确计划DG以获得最佳解决方案安装。因此,重要的是在有源配电系统的规划过程中确定DG的最佳位置和大小,以实现最小的损失。本文提出了使用K-Means聚类方法的DG放置和大小调整技术。基于聚类的技术用于基于损耗敏感度因子(LSF)和总线电压确定DG的最佳位置。一旦获得最佳位置,则使用分析方法确定DG的最佳尺寸。该方法在IEEE 33总线和69总线径向分配系统上进行了测试,以验证其在获得最佳DG位置和确定尺寸以减少损耗方面的性能。在IEEE 33总线系统上的结果表明,所提出的方法可减少87.5%的损耗,优于通过LSF优先级列表方法获得的76.7%的损耗。而在IEEE 69总线系统上的结果表明,该方法可减少69.84%的损耗,优于LSF优先级列表方法可减少65.95%的损耗。

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