• Optimization models are developed for Wind-Solar-Storage-Transmission systems. • Data from 210 sites across North China over 87,600 h are utilized • Complementarity between wind and solar resources is examined. • Impacts of intermittency, heterogeneity, and uncertainty are analyzed. As thermal power is gradually phased out, renewable energy bases dominated by wind and solar power will require energy storage to replace the current practice of bundling renewables with thermal power for long-distance transmission. This transition raises a new challenge: determining the most cost-effective capacity configuration for Wind-Solar-Storage-Transmission (WSST) systems, which depends critically on regional wind and solar resource conditions. This study investigates the fundamental relationship between resource conditions and the optimal capacity configuration of renewable energy bases. To this end, 210 sites across five major power-exporting provinces in North China are selected as research subjects. Drawing on hourly wind and solar capacity factor data covering 87,600 h from 2014 to 2023, we develop both a basic optimization model and a scenario-based distributionally robust optimization model for WSST systems. These models are used to examine how renewable energy intermittency, regional heterogeneity, and resource uncertainty shape the cost-optimal capacity allocation of renewable energy bases. The results show that the installed capacities of wind and solar power are strongly correlated with their respective resource endowments and, beyond competing with each other, also exhibit pronounced complementarity. At current storage prices, not all renewable bases require energy storage; the key determinant is the wind-to-solar capacity factor ratio. Compared with wind, solar PV depends far more heavily on storage. In single-source scenarios, higher solar capacity factors correspond to greater storage requirements, with better solar resources further amplifying this demand, whereas wind power requires little to no storage regardless of resource conditions. In wind-solar complementary systems, storage capacity follows an inverted U-shaped pattern with respect to the wind-to-solar capacity factor ratio. Transmission capacity is primarily driven by wind resources, while solar conditions exert a comparatively minor influence. Given the higher uncertainty associated with wind power, explicitly accounting for resource variability generally leads to reduced wind capacity, increased solar PV capacity, unchanged storage, and lower transmission capacity.
Zhou et al. (Fri,) studied this question.