System Dynamics Simulation and Dynamic Evolution Analysis of Heterogeneous Electricity Demand Scenarios in Hebei Province Under the Dual-Carbon Context

Under the “Dual-Carbon” goals, conventional regional electricity demand forecasting methods struggle with the changes in socioeconomic and energy consumption patterns. This paper proposes an innovative method integrating System Dynamics (SD) and Ridge Regression. A detailed SD model comprising four subsystems–socioeconomic, electricity, steel industry, and energy is built to depict complex interrelations. Ridge Regression optimizes its accuracy. Using Hebei Province as an example, the model forecasts electricity demand across different “Dual-Carbon” scenarios. The novelty resides in the SD-Ridge Regression combination and its capacity to capture dynamic demand, offering crucial decision-making support for “Dual-Carbon” achievement and contributing to regional energy planning and carbon reduction strategies.