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Fair hierarchical clustering of substations based on Gini coefficient

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摘要 For the load modeling of a large power grid,the large number of substations covered by it must be segregated into several categories and,thereafter,a load model built for each type.To address the problem of skewed clustering tree in the classical hierarchical clustering method used for categorizing substations,a fair hierarchical clustering method is proposed in this paper.First,the fairness index is defined based on the Gini coefficient.Thereafter,a hierarchical clustering method is proposed based on the fairness index.Finally,the clustering results are evaluated using the contour coefficient and the t-SNE two-dimensional plane map.The substations clustering example of a real large power grid considered in this paper illustrates that the proposed fair hierarchical clustering method can effectively address the problem of the skewed clustering tree with high accuracy.
出处 《Global Energy Interconnection》 EI CAS CSCD 2021年第6期576-586,共11页 全球能源互联网(英文版)
基金 supported by the Major Science and Technology Project of Yunnan Province entitled“Research and Application of Key Technologies of Power Grid Operation Analysis and Protection Control for Improving Green Power Consumption”(202002AF080001) the China South Power Grid Science and Technology Project entitled“Research on Load Model and Modeling Method of Yunnan Power Grid”(YNKJXM20180017).
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