<b>Forecasting China’s Nuclear Power Generation to 2030: An ARIMA Model-Based Trend Analysis</b>

作者：Yutao Luo, Yinzi Shao, Bowen Zhang, Peng Liu, Shida Liu, Zhongyuan Yuan, Shijing Sang · 发表于：Engineering Frontiers · 年份：2025 · DOI：10.71411/ef.2025.v1i1.939 · 被引用次数：2 · 研究领域：Energy Load and Power Forecasting、Forecasting Techniques and Applications、Integrated Energy Systems Optimization

This study employs an Autoregressive Integrated Moving Average (ARIMA) model to conduct time series analysis and forecasting of China's nuclear power generation, aiming to provide quantitative basis for medium-term energy planning. Utilizing 279 monthly observations from May 2000 to July 2025, the research systematically evaluated 131 model specifications through an extended automatic ARIMA model selection procedure within the parameter space of p∈[0,6], d∈[0,2], and q∈[0,6]. Based on the Akaike Information Criterion (AIC), ARIMA(4,2,5) was selected as the optimal model with an AIC value of 2170.56. Model diagnostics revealed a root mean square error (RMSE) of 11.38 units, mean absolute percentage error (MAPE) of 9.86%, and Ljung-Box test p-value of 0.0911, indicating that the model adequately captures the autocorrelation structure in the data. Forecast results show that China's nuclear power generation will increase from 430.00 hundred million kWh in August 2025 to 618.81 hundred million kWh in December 2030, with a total growth rate of 43.91% over the forecast period and an average annual growth rate of 8.11%. This model provides a reliable quantitative forecasting tool for China's future nuclear power development planning.