Solar-wind resource characteristics and optimal capacity allocation across China: insights from observations and reanalyses

Abstract

Accurate characterization of renewable energy variability, complementarity, and optimal capacity allocation is essential for power system planning, yet observational evidence and reanalysis performance to reproduce these characteristics remain poorly quantified. Using homogenized observations from 1980–2022, this study quantifies solar-wind resource intermittency, availability, and complementarity across China, and assesses the performance of European Center for Medium-Range Weather Forecasts Reanalysis, version 5 (ERA5), Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), and Japanese Meteorological Agency for Japanese 55 year Reanalysis (JRA-55) in reproducing these characteristics. A Compound Synergistic Cost Index is further developed to optimize solar-wind capacity allocation by jointly considering their characteristics and installation cost. Results show that wind energy exhibits higher intermittency (0.45–0.61) than solar energy (0.21–0.40), while hybrid systems significantly reduce intermittency to 0.20–0.37 and enhance resource availability. Strong solar-wind complementarity is concentrated in western China, where solar complementing wind dominates and has strengthened in recent decades, whereas wind complementing solar occurs primarily in Northeast China. Optimal capacity allocation reveals distinct regional patterns, with wind power accounting for 44.1% of installed capacity in Northeast China and solar power accounting for 79.4% and 70.6% in the Tibetan Plateau and Northwest China, respectively. Among reanalyses, ERA5 shows the most reliable overall representation of renewable energy characteristics, optimal solar-wind capacity allocation, and hybrid generation potential across most regions of China. Meanwhile, JRA-55 provides more accurate estimates of optimal capacity allocation in Northeast China and the Tibetan Plateau, whereas MERRA-2 better captures solar-wind complementarity at the daily scale in Northwest China. These findings provide an observational benchmark for evaluating reanalysis performance in representing renewable energy characteristics and optimizing hybrid solar-wind system design under varying climates.