A Study on Energy Production and Consumption Based on Seasonal ARIMA and REAO

Abstract

In the face of the global energy challenge, this study delves into the intricate landscape of energy dynamics within the rapidly evolving global economy and technological sphere. Recognizing energy as a pivotal driver of societal progress, we present a comprehensive evaluation and optimization model for China's energy sources, emphasizing economic, cost, electric energy, and environmental considerations. Employing time series models, specifically ARIMA and gray scale forecasting, we meticulously analyze wind and solar power generation, as well as overall power consumption. The results showcase nuclear power and hydropower as significant contributors to the energy landscape. Leveraging a linear programming model, we simulate and optimize the future energy development structure, considering constraints such as cost, energy, capacity, and carbon emissions. Our findings reveal the optimal quota contributions of thermal power, hydro power, nuclear power, wind power, and solar power as 13.7%, 14.2%, 17.6%, 54.5%, and 0%. Building upon these insights, we propose strategic recommendations for sustainable electric energy development. Emphasizing wind and solar energy's potential, we advocate for continued interest and increased support for technological advancements. Additionally, we call for the establishment of comprehensive power and energy development plans, integrating economic and environmental goals. To address imperfections in China's electricity tariff system, we recommend ongoing reforms aligned with market dynamics and environmental considerations.