Clustering analysis of typical scenarios of island power supply system by using cohesive hierarchical clustering based K-Means clustering method. (November 2021)

• Record Type: Journal Article
• Authors: Niu, Geng; Ji, Yu; Zhang, Zhihui; Wang, Wenbo; Chen, Jikai; Yu, Peng
• Is Part Of: Energy reports. Volume 7(2021)Supplement 6
• Page Start: 250
• Page End: 256
• Publication Date: 2021-11
• Subjects: Island power supply system -- Scenario analysis -- Clustering analysis -- Cohesive hierarchical clustering -- K-means clustering; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2021.08.049
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: Scenario analysis plays an important role in the planning and operation of the island power supply system. In this paper, a cohesive hierarchical clustering based K-means clustering method is proposed and used for clustering analysis of typical scenarios of island power supply systems. At first, the source and load characteristics of a typical island power supply system are analyzed. Then, three characteristic indexes to distinguish island types are proposed which can achieve the feature extraction of typical scenarios of island power supply systems. On this basis, the cohesive hierarchical clustering based K-means clustering method is proposed for the clustering analysis of typical scenarios of the island power supply system. A case study is made to verify the effectiveness of the proposed method. The case study results indicate that the proposed method can effectively classify different islands into several types, and the features of the typical scenarios of each type of island are analyzed.