Photovoltaic (PV) power generation in China has experienced promising growth and it has become a significant sector of the power system in the near future. To further utilize the variable uncertain of PV resources, the generation resource assessment focusing on a high temporal resolution would greatly assist China in achieving its dramatic “dual carbon goals”. In this paper, the installed PV potential of every province in China is measured based on the radiation intensity and temperature data with a time step of 15 minutes. Power reliability and complementary through ultra-short-term PV prediction are assessed as well to better utilize PV power. It is indicated that China's PV power potential is 4567.0 TWh/year, as for the spatial distribution, Inner Mongolia and Xinjiang possess the largest PV potential in China, with power generation potential of 1281.6 TWh/year and 576.0 TWh/year, respectively. There are large monthly variations in the temporal availability of PV power generation in each province, with the difference between the highest availability and the lowest availability in every province generally being larger than 150%, and the PV output also fluctuates considerably during the day in different seasons in each province. To ensure power reliability and complementary in terms of designing PV-Energy Storage system, case study indicates that the optimal capacity ratio for hybrid energy storage capacity configuration is 38% for the battery and 62% for the supercapacitor.

The worldwide promotion of carbon-neutral policies is leading to a continuously growing percentage of electricity being derived from renewable energy, which makes it feasible to design power systems composed of 100% renewable energy in the future. The question of how to realize stable transmission for 100% renewable energy-integrating grids under different operating conditions needs to receive more attention. Voltage source converter-based high-voltage direct current (VSC-HVDC) technology is one of the prospective solutions for large-scale renewable energy integration due to its unique dominance in areas such as independent reactivity and active control. In this study, we design a novel, 100% renewable energy system through grid integration via a VSC-HVDC system structure and a control strategy. Unlike in other research, a mixed control strategy based on grid-forming control (PSL) and grid-following control (GFL) is developed to realize smooth switching in order to ensure secure transmission and consistent operation when the operating conditions of the 100% renewable energy-integrating grid changes. The simulation results indicate that the proposed system structure and control could stabilize renewable energy transmission under normal operation conditions and provide necessary grid support under different system disturbances.

Accurately decoding the climate sensitivity of electric vehicle (EV) charging demand is crucial but challenged by confounding socio-economic trends. This study establishes an explainable data-driven framework coupling an optimized eXtreme Gradient Boosting (XGBoost) model with Shapley Additive Explanations (SHAP) theory. Leveraging daily records across 11 Chinese cities (2023–2024) integrated with ERA5 data, we implement temporal linear interpolation to isolate weather shocks from macro trends. The model achieves a robust testing R2 of 0.74. Global attributions reveal ambient temperature as the primary climatic driver (5.8% contribution), presenting an asymmetric shallow U-shaped trajectory with an inflection threshold at 9.64°C. Weekends and holidays drive up demand for EV charging at public charging stations. Second-order interactions confirm population and charging station density as operational multipliers, peaking at a joint synergy value of 0.292. These findings provide actionable insights for smart grids, justifying climate-elastic dynamic tariffs and synchronized weekend buffering.

Accurately decoding the climate sensitivity of electric vehicle (EV) charging demand is crucial but challenged by confounding socio-economic trends. This study establishes an explainable data-driven framework coupling an optimized eXtreme Gradient Boosting (XGBoost) model with Shapley Additive Explanations (SHAP) theory. Leveraging daily records across 11 Chinese cities (2023–2024) integrated with ERA5 data, we implement temporal linear interpolation to isolate weather shocks from macro trends. The model achieves a robust testing R² of 0.74. Global attributions reveal ambient temperature as the primary climatic driver (5.8% contribution), presenting an asymmetric shallow U-shaped trajectory with an inflection threshold at 9.64°C. Weekends and holidays drive up demand for EV charging at public charging stations. Second-order interactions confirm population and charging station density as operational multipliers, peaking at a joint synergy value of 0.292. These findings provide actionable insights for smart grids, justifying climate-elastic dynamic tariffs and synchronized weekend buffering.

Accurately decoding the climate sensitivity of electric vehicle (EV) charging demand is crucial but challenged by confounding socio-economic trends. This study establishes an explainable data-driven framework coupling an optimized eXtreme Gradient Boosting (XGBoost) model with Shapley Additive Explanations (SHAP) theory. Leveraging daily records across 11 Chinese cities (2023–2024) integrated with ERA5 data, we implement temporal linear interpolation to isolate weather shocks from macro trends. The model achieves a robust testing R² of 0.74. Global attributions reveal ambient temperature as the primary climatic driver (5.8% contribution), presenting an asymmetric shallow U-shaped trajectory with an inflection threshold at 9.64°C. Weekends and holidays drive up demand for EV charging at public charging stations. Second-order interactions confirm population and charging station density as operational multipliers, peaking at a joint synergy value of 0.292. These findings provide actionable insights for smart grids, justifying climate-elastic dynamic tariffs and synchronized weekend buffering.