@Article{ee.2025.060810,
AUTHOR = {Caifeng Wen, Feifei Xue, Hongliang Hao, Edwin E. Nyakilla, Ning Yang, Yongsheng Wang, Yuwen Zhang},
TITLE = {Research on Wind-Solar Complementarity Rate Analysis and Capacity Configuration Based on COPULA-IMOPSO},
JOURNAL = {Energy Engineering},
VOLUME = {122},
YEAR = {2025},
NUMBER = {4},
PAGES = {1511--1529},
URL = {http://www.techscience.com/energy/v122n4/60185},
ISSN = {1546-0118},
ABSTRACT = {This paper presents a new capacity planning method that utilizes the complementary characteristics of wind and solar power output. It addresses the limitations of relying on a single metric for a comprehensive assessment of complementarity. To enable more accurate predictions of the optimal wind-solar ratio, a comprehensive complementarity rate is proposed, which allows for the optimization of wind-solar capacity based on this measure. Initially, the Clayton Copula function is employed to create a joint probability distribution model for wind and solar power, enabling the calculation of the comprehensive complementarity rate. Following this, a joint planning model is developed to enhance the system’s economy and reliability. The goal is to minimize total costs, load deficit rates, and curtailment rates by applying an Improved Multi-Objective Particle Swarm Optimization algorithm (IMOPSO). Results show that when the proportion of wind power reaches 70%, the comprehensive complementarity rate is optimized. This optimization leads to a 14.83% reduction in total costs and a 9.27% decrease in curtailment rates. Compared to existing studies, this paper offers a multidimensional analysis of the relationship between the comprehensive complementarity rate and the optimal wind-solar ratio, thereby improving predictive accuracy and providing a valuable reference for research on the correlation between wind and solar power.},
DOI = {10.32604/ee.2025.060810}
}