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

O. Penangsang, D. F. U. Putra, Taufani Kurniawan
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引用次数: 4

Abstract

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.
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基于k -均值聚类方法的径向配电系统中分布式发电的最优布局和规模
分布式电源在降低损耗、提高电压分布和可靠性等电能质量方面发挥着重要作用。然而,在实施过程中,为了获得最优的解决方案,必须对DG进行适当的规划。因此,在主动式配电系统规划中,确定DG的最优位置和最优规模以实现最小的损耗是非常重要的。本文提出了一种基于k均值聚类方法的DG放置和分级技术。采用基于聚类的技术,基于损耗敏感系数和母线电压确定DG的最佳位置。一旦确定了最优位置,则采用解析法确定DG的最优尺寸。在IEEE 33总线和69总线径向配电系统上进行了测试,验证了该方法在获得最佳DG布局和尺寸以降低损耗方面的性能。在ieee33总线系统上的实验结果表明,该方法比LSF优先级表法的损耗降低率达到87.5%,优于LSF优先级表法的76.77%。在ieee69总线系统上的实验结果表明,该方法比LSF优先级表法减少了65.95%的损耗,降低了69.84%的损耗。
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