Complementary Characteristics Between Hydro-Solar-Wind Power Factors in the Upper Yellow River Region During 1979~2018

Jiongwei Cao, Xiang Li (), Huimin Zuo, Jingyang Wang and Lizhen Wang
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Jiongwei Cao: State Key Laboratory of Plateau Ecology and Agriculture, School of Civil Engineering, Qinghai University, Xining 810016, China
Xiang Li: State Key Laboratory of Plateau Ecology and Agriculture, School of Civil Engineering, Qinghai University, Xining 810016, China
Huimin Zuo: School of Hydraulic Engineering, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China
Jingyang Wang: State Key Laboratory of Basin Water Cycle Simulation and Regulation, China Institute of Resources and Hydropower Research, Beijing 100038, China
Lizhen Wang: State Key Laboratory of Plateau Ecology and Agriculture, School of Civil Engineering, Qinghai University, Xining 810016, China

Energies, 2025, vol. 18, issue 7, 1-25

Abstract: In this paper, we focus on the four provinces (Qinghai, Gansu, Ningxia, and Inner Mongolia) in the upper Yellow River region and conduct a quantitative analysis of the spatiotemporal distributions of the precipitation (P), shortwave radiation (R), and wind speed (W) from 1979 to 2018 using the China Meteorological Forcing Dataset. The complementarity of these power factors is analyzed across multiple time scales and resolutions. A complementarity coefficient is introduced by integrating three correlation coefficients to evaluate the interrelationship between pairs of power factors. Additionally, the probability density distributions of individual and pairs of power factors are examined at the Longyangxia Clean Energy Base in Qinghai Province. The complementarity coefficients between the P and R, P and W, and R and W exhibited significant variations across regions. The complementarity coefficients for P and R were negative, ranging from −0.019 to −0.029 at the 3 h resolution and from −0.384 to −0.429 at the daily resolution, indicating a strong complementarity at the longer temporal resolution. The complementarity coefficients for P and W were positive, ranging from 0.029 to 0.047 at the 3 h resolution and from 0.038 to 0.065 at the daily resolution, indicating a stable correlation at different resolutions. The complementarity coefficients for R and W changed from positive at the 3 h resolution to negative at the daily resolution, indicating that the correlation changes to complementarity at different resolutions. The annual joint probability density is highest for daily precipitation ranging from 276.0 to 304.4 mm, daily shortwave radiation between 1832.6 and 1847.5 kW/m 2 , and daily mean wind speed varying from 1.7 to 1.8 m/s.

Keywords: hydro-solar-wind power factors; spatiotemporal variations; complementarity coefficient; probability density distribution; copula function (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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