Multi-Spatiotemporal Power Source Planning for New Power Systems Considering Extreme Weathers

The large-scale integration of renewable energy sources has made power generation highly susceptible to climate variability, increasing operational risks within power systems. The growing frequency of extreme weather events has further intensified uncertainty and stochasticity, thereby elevating risks to supply security. To enhance the operational resilience of modern power systems under extreme weather conditions, this study proposes a multi-temporal and multi-spatial power supply planning model that explicitly incorporates the impacts of such events. First, the effects of extreme weather on the source–grid–load framework are analyzed, and a radiation attenuation model for the rainy season as well as a spatiotemporal evolution model for hurricanes are developed. Subsequently, a climate-dependent power output model is established, employing the Finkelstein–Schafer statistical method to construct a Typical Meteorological Year, which serves as input for the reliable power source modeling. Furthermore, a two-stage power supply planning model based on generation adequacy was established to optimize the location and capacity of various types of backup power sources. Case studies conducted on the IEEE 24-bus system demonstrate that optimized planning of thermal power units and energy storage systems can mitigate the overall power shortfall during extreme weather events, thereby improving the system’s ability to maintain a reliable electricity supply under adverse climate conditions.