Complementarity Analysis and Evaluation of Renewable Energy Stations based on Mixed-Copula Model

Multi-energy complementarity is an effective way to improve the utilization capacity for renewable energy sources in the grid. Correlation analyses on the power of different new energy units are the key to evaluating their complementary degree. Compared with traditional linear analytical methods, Copula functions can well capture the nonlinear tail correlation between random variables. In order to describe the complementary characteristics of renewable energy stations, this paper introduces the mixed-Copula theory to construct the two-dimensional dependence structure model of renewable energy output. A stochastic scenario generation method based on the acceptance-rejection sampling is proposed to simulate the power subject to the Copula correlation. In addition, combined with the conditional probability in the upper and lower tail intervals, a complementarity evaluation index is developed to describe the coupling degree of the power from different renewable energy plants. The comparison with the existing index verifies the effectiveness of the proposed evaluation method.