Abstract
China is a broad territory country. There are significant differences in the terrain, climate, and other environmental factors between different provinces, which affect wind power generation. In order to better analyze the situation of wind power generation in Chinese provinces, this paper uses the functional clustering analysis to classify the monthly data of wind power generation in 30 Chinese provinces from March 2013 to October 2019. The empirical results of this paper show that the wind energy generation in Chinese provinces can be divided into three categories, and the results are consistent with the actual situation. In this paper, functional clustering analysis is used to analyze monthly data, compared with the traditional clustering analysis to analyze annual data which are obtained by accumulated monthly data. Higher-dimensional data can be used for analysis to reduce information loss. Moreover, data can be viewed as functions, and more information can be mined by analyzing derivative functions, and so on. The analysis of wind energy generation has certain guiding significance for the development and utilization of renewable energy.
Highlights
With the growing size of the world economy, world energy consumption continues to increase
This paper uses the method of functional clustering analysis to study the wind power generation in different Chinese provinces and classifies the wind power generation situation in China
Based on the above reasons, we say that we use Functional data analysis (FDA) method which can more effectively analyze the wind power generation situation in different Chinese provinces, and provide suggestions for the development and utilization of wind power resources in China
Summary
With the growing size of the world economy, world energy consumption continues to increase. Due to the shortage of oil, natural gases, and other nonrenewable energy, and the increasing serious environmental problems, like air pollution, acid rain, and the greenhouse effect, the use of wind power generation has attracted increasing attention. Functional data analysis (FDA) is the general name of the method for analyzing functional data (Ramsay, 1982). This paper uses the method of functional clustering analysis to study the wind power generation in different Chinese provinces and classifies the wind power generation situation in China. Based on the above reasons, we say that we use FDA method which can more effectively analyze the wind power generation situation in different Chinese provinces, and provide suggestions for the development and utilization of wind power resources in China
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