Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7159624 | Energy Conversion and Management | 2017 | 11 Pages |
Abstract
Wind and solar energy are two kinds of renewable energy resources with huge potential. Complementarity research between wind and solar resources is quite important for the efficient use of them due to their uncertainty and stochastic volatility. In this paper, the current situation of wind and solar photovoltaic power development in China is firstly introduced. Secondly, the dependence model of wind-sun energy is established by combining copula approach and the Gaussian kernel function, which is a kind of nonparametric kernel density estimation. The copula approach can characterize the dependence structure between the variables so completely that the Kendall's rank correlation coefficient Ï calculated from the model above is more accurate. The wind-sun complementarity maps of various regions in China for the whole year and four seasons are further built by using the k-means clustering algorithm with Ï as the regionalization indicator. At last, the study analyzes spatial and temporal distribution features of wind-sun complementarity. The results are as following: in spatial dimension of China, Category I (-0.95<Ï⩽-0.80) concentrates in the northwest of China; Category II (-0.80<Ï⩽-0.60) diffuses in the north, west and a few coastal regions; Category III (-0.60<Ï⩽-0.30) is dispersed in the eastern, southwestern and western regions; Category IV (-0.30<Ï⩽0.10) is mostly in the central and southeastern regions. In general, the northwestern and northern regions are more likely to adopt the concept of wind-sun complementarity. In temporal dimension, wind-sun complementarity in spring and summer is superior to that in autumn and winter. The maps have a certain reference significance for renewable resources develop-planning and management in China.
Keywords
Related Topics
Physical Sciences and Engineering
Energy
Energy (General)
Authors
Lanjing Xu, Zhiwei Wang, Yanfeng Liu,