Correlation Analysis between Photovoltaic Power Generation Efficiency and Meteorological Impact Factors Based on Clustering Algorithm

Abstract

Cluster analysis is a multivariate statistical method, which can find similar or different types of things in the same sample data for comparison. In this paper, the correlation analysis between photovoltaic power generation (PVPG) and meteorological factors is carried out based on clustering method. In order to improve the accuracy of prediction, this paper uses Matlab software to design a cluster analysis system to do a detailed study on the correlation between PVPG efficiency and meteorological factors. This paper mainly uses qualitative and quantitative analysis, principal component analysis and data comparison to compare the positive and negative correlation between meteorological factors and PVPG. The experimental data shows that the irradiance has a stronger relationship with the efficiency of PVPG, and the correlation is more than 0.3. The analysis results of the clustering algorithm show that the temperature and sunshine are the most important factors affecting the efficiency of the photovoltaic power generation, which need to be considered and optimized in the design and operation of the photovoltaic power generation system. At the same time, factors such as wind speed and humidity also need to be included in the monitoring and control category of the photovoltaic power generation system, so as to ensure the stability and reliability of the system.