A novel metric for assessing wind and solar power complementarity based on three different fluctuation states and corresponding fluctuation amplitudes

Abstract

Assessing complementarity is a foundational work to combine wind and solar power to mitigate their fluctuations. Correlation coefficient is the most commonly used index to assess complementarity. But correlation coefficient mainly quantifies the synchronous and reverse correlations between wind and solar power. Moreover, it ignores the fluctuation amplitudes of wind and solar power, which would misestimate the complementarity. To address the issue, a novel complementarity index is proposed considering both the fluctuation states and corresponding fluctuation amplitudes. The present study firstly divides the fluctuations of wind and solar power into synchronous, reverse, and discrepancy fluctuation states. Then the degrees of the three different fluctuation states are obtained according to the score rules considering the fluctuation amplitudes. Finally, the novel complementarity index is jointly determined by these fluctuation degrees. Validation results show that the proposed index successfully avoids the misestimation scenarios caused by using correlation coefficient to assess complementarity. Then the proposed index is applied to analyze the complementarity of wind and solar power in China on hourly, daily, and monthly time scales. The complementarity index is generally −0.11–0 on the hourly time scale in most regions of Jilin, Heilongjiang, Liaoning, Inner Mongolia, northern Gansu, southern Xinjiang, and the North China Plain, showing greater complementarity than other onshore regions. But the complementarity index is generally 0–0.3 in most of the aforementioned regions on the monthly time scale, implying that the complementarity on the monthly time scale is smaller than that on the hourly time scale. The complementarity indices in most offshore regions are −0.1–0, −0.12–0 and −0.2–0, respectively, on the hourly, daily, and monthly time scales. Further analysis reveals that the complementarity between wind and solar power would be overestimated once the fluctuation amplitude is ignored. Additionally, the proposed complementarity index can be used to optimize the installed capacity ratio of wind and solar power in a hybrid system. The proposed complementarity metric contributes to a better and more accurate understanding of the complementarity between wind and solar power. Furthermore, the proposed metric can be readily applied to assess the complementarity of other renewable power generations.