Photovoltaic power data analysis using hierarchical clustering

Photovoltaic is attracting attention as one of the renewable energy sources that replace existing fossil fuel-based power generation. Photovoltaic power generation data clustering is becoming increasingly popular because it allows us to identify PV systems without extensive analysis and simulation. Generally, clustering method of PV power data analyzes only the meaning of each cluster, so it is difficult to grasp the similarity between clusters. In this paper, clustering of PV power data through hierarchical clustering algorithm is performed to calculate the relationship between clusters. The hierarchical clustering method was used to analyze the similarity of PV power data between clusters. As a result, PV power data were classified into seasonal clusters and defective clusters.