Research on the identification and early warning method system of uncertain elements in power supply and demand

To address the multi-cycle and cross-system transmission characteristics of power supply and demand risks in the construction of the new power system, this paper proposes a set of identification framework and early warning method systems for uncertain elements of power supply and demand covering multiple dimensions of economy, society, and climate. By constructing a risk element classification model with a four-level time scale of long-term cycle, year, month, and day, the core influencing factors such as economic fluctuations, policy adjustments, fuel supply, and extreme weather were identified, and a cascade early warning index system was designed. Based on the system dynamics method, the causal feedback loop of power supply and demand and the stock-flow model were established. The dynamic evolution path of the power supply and demand gap was analyzed, and a risk early warning method system based on leading indicators-evolution analysis-early warning and prediction was proposed. This research provides theoretical support and decision-making tools for the dynamic risk assessment and early warning of the power system.