Spatiotemporal Complementary Characteristics of Large-Scale Wind Power, Photovoltaic Power, and Hydropower

• Published in: Sustainability Vol. 14; no. 15; p. 9273
• Main Authors: Wang, Songkai, Jia, Rong, Luo, Chang, An, Yuan, Guo, Pengcheng
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2022
• Subjects: Alternative energy sources; Complementarity; Correlation analysis; Energy resources; Energy sources; Evaluation; Hydroelectric power; Normal distribution; Photovoltaics; Power plants; Random variables; Renewable energy sources; Renewable resources; Statistical analysis; Sustainability; Time series; Wind power
• ISSN: 2071-1050; 2071-1050
• DOI: 10.3390/su14159273

With the increasing proportion of renewable energy in power generation, the mixed utilization of multiple renewable energy sources has gradually become a new trend. Using the natural complementary characteristics of wind power, photovoltaic, and hydropower to evaluate the complementary potential of various energy sources has become a hot issue in the research of mixed utilization. Given that traditional complementarity research can only assess the complementarity between two energy sources, this paper proposes a method to simultaneously determine the complementarity between three large-scale renewable energy sources. Firstly, a three-dimensional vector represents the complementary characteristic combination of any two energy sources. The complementary characteristics of the three energy sources were obtained by finding the optimal solution for the three-dimensional vector. Finally, power stations were selected, located in different spatial areas on the world’s largest renewable energy base in Qinghai, China, as the research object to analyze and verify the complementary characteristics of wind-power–photovoltaic-power–hydropower at different spatiotemporal scales. The results show significant differences in the complementary characteristics of different time scales. The farther the spatial distance between different power stations, the stronger their complementarity. The best complementary index on the monthly and daily scales was improved by 8.49% and 6.51%. This study provides a new focus for the future evaluation of the complementary utilization potential of large-scale joint renewable energy in different world regions.