Operation Risk Assessment of Power System Considering Spatiotemporal Distribution of Source-Load Under Extreme Weather

With the increasing access capacity of new energy, the impact of extreme weather on source–load is intensifying, threatening the balance of supply and demand in the power system. Aiming at the systemic risks caused by the uncertainty and volatility of the spatiotemporal distribution of source–load under extreme weather conditions, this paper proposes a new method for power system operation risk assessment considering the spatiotemporal distribution of source–load under extreme weather. Firstly, the influence of various meteorological factors on the output and load of new energy under extreme weather is studied, and the meteorological sensitivity model of source–load is established. Secondly, aiming at the problem of limited historical data of extreme weather scenarios, this paper proposes a method for generating annual operation scenarios of power systems considering extreme weather: using Gaussian process regression to reconstruct extreme weather scenarios, and fusing them into typical meteorological year series through quantile incremental mapping method, forming meteorological scenarios with both typical characteristics and extreme events, and combining the source-load model to obtain the system operation scenario. Thirdly, a new power system risk assessment model considering the impact of extreme weather is established, and the risk indicators such as load shedding, line overlimit, and wind and solar curtailment on a long-term scale are evaluated by using the daily operation simulation in the annual operation scenario of the system. Finally, the IEEE 24-node System is used to analyze the numerical examples, which show that the proposed method provides a quantitative risk assessment framework for the power system to cope with extreme weather, which is helpful to improve the resilience and reliability of the system.