Forecasting China’s Electric Power Digitalization Scale Using a Unified New-information-Priority Accumulating Generation Operator

In an era of rapid technological evolution, China’s electric power industry is undergoing a significant transformation toward digitalization. Accordingly, accurately forecasting this digitalization scale is crucial for strategic planning and policy-making. However, traditional forecasting methods often struggle to keep pace with the sector’s dynamic changes and sparse data. Addressing this need, our study introduces the Unified New Information Accumulating Generation Operator (UNAGO), integrated into the Discrete Grey Model (DGM (1,1)), to enhance forecasting accuracy. UNAGO can effectively handle the complexities of the rapidly evolving sectors often characterized by limited data. It prioritizes new information within data sequences, offering a more nuanced and adaptable accumulating weights structure compared to traditional AGOs. For comparison purposes, UNAGO is contrasted to five previously proposed AGO techniques. The results indicate UNAGO’s superior prediction accuracy with 4.24% and 1.66% out-of-sample MAPE values. Applying the UNAGO-DGM (1,1) model, we forecasted the scale of electric power digitalization in China from 2021 to 2025. The model projects a substantial growth from 414 billion Yuan in 2021 to 643.23 billion Yuan by 2025. To conclude, the results not only advance the theoretical aspects of the grey prediction model but also offer practical insights for stakeholders in China’s electric power sector. The model’s predictions serve as a valuable tool for informed decision-making, guiding strategic planning, investment, technological innovation, and policy formulation in a sector poised for significant digital transformation.