大电网负荷建模需要将众多的变电站聚合成几类,然后再针对每一类建立负荷模型.为解决传统层次聚类方法中聚类树状图倾斜的问题,本文提出了一种公平层次聚类方法.首先,基于基尼系数定义了公平指标;然后,提出了一种基于公平指标的层次聚类方法;最后,利用轮廓系数及t-SNE二维平面图对聚类结果进行评价.实际大电网负荷变电站聚类算例表明,本文提出的公平层次聚类方法可以有效解决树状图倾斜的问题,具有较高的准确度.“,”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.