Quantitative Evaluation Method for Regional Variations in Electricity Supply-Demand Balance Fluctuation by Weather Forecast Error

This paper introduces a data-driven method to evaluate regional variations in electricity supply-demand (S&D) balance fluctuations caused by weather forecast errors (WFE). Since renewable energy (RE) sources, such as solar and wind, are highly sensitive to weather conditions, effective grid stability management requires a comprehensive understanding of regional disparities in S&D imbalances caused by WFE. In this study, we use the imbalance unit price (IUP), which reflects the cost of correcting deviations between planned and actual electricity supply, as an indicator of regional S&D balance. The proposed two-stage causal inference approach utilizes doubly robust estimation to calculate the average treatment effects (ATEs) of WFE on IUPs and employs multivariate linear regression to quantify the impact of each region’s power mix on IUP fluctuations. By analyzing how each region’s power mix and demand influence ATE variations using historical data from 52 regions in Japan, we demonstrate the significant impact of local weather conditions on grid stability. Our findings reveal substantial regional differences in IUP fluctuations driven by RE generation capacities, particularly solar and wind power. This study emphasizes the importance of considering regional factors in optimizing grid operations.