Abstract: Accurately forecasting thermal power generation is essential for China’s sustainable energy planning and green development. This paper proposes a novel multivariable time-delay grey model to forecast China’s thermal power generation from 2025 to 2030. The proposed model combines time-delay effects and dummy variables to capture the complex, nonlinear relationships between thermal power generation and economic drivers under conditions of limited data. By optimizing parameters with the Aquila Optimizer, the proposed model achieves improved adaptability and forecasting accuracy. The proposed model’s fitting MAPE is 0.58%, and the test MAPE is 0.29%, outperforming other comparison models. The forecasting results indicate that China’s thermal power generation may grow unstably through 2030. The growth rate may slow due to the increasing integration of renewable energy sources and the implementation of carbon neutrality policies. It offers referenceable and foresight insights for the Chinese government to support energy security management and future sustainable development.

Key words: Multivariable grey model, Time-delay, Dummy variables, Thermal power generation forecasting