Enhancing the accuracy of China's electricity consumption forecasting through economic cycle division: An MSAR-OPLS scenario analysis

• Published in: Energy (Oxford) 2024-04, Vol.293, p.130618, Article 130618
• Main Authors: Xie, Pinjie, Shu, Yalin, Sun, Feihu, Pan, Xianyou
• Format: Article
• Language: English
• Subjects: Economic cycles; Electricity consumption; Markov switching autoregression; OPLS; Scenario analysis
• ISSN: 0360-5442
• DOI: 10.1016/j.energy.2024.130618

Accurate electricity consumption (EC) forecasting is vital for ensuring efficient energy supply and underpinning long-term economic stability. Prior research has often overlooked the intricate interplay between the nuanced dynamics of economic growth and EC. In contrast, this study innovatively incorporates the economic cycle into the analytical framework of EC, providing a more comprehensive perspective. Firstly, we construct the MSAR-OPLS two-step model to discern the factors influencing EC across various cycles. We select the most fitting stabilization cycle as the foundation for forecasting. By integrating both dynamic and static scenario analyses, we offer a comprehensive and precise evaluation of future EC trends. This study ensures both the reliability and accuracy of our forecasts. Projections suggest that China's EC will escalate to 11,780 billion kWh by 2030, reflecting an average annual growth rate of 3.96% from 2023 to 2030. Furthermore, through rigorous robustness and sensitivity analyses, the study validates the forecast's accuracy. Beyond emphasizing the role of economic phases in ensuring energy security, this research furnishes policymakers with insights on embedding foresightful elements into strategic economic and energy planning. •Electricity consumption forecasting is a precondition for power planning.•Include economic cycles in electricity consumption forecasting.•Combine dynamic analysis to establish static forecasts for multiple scenarios.•Prevent power shortages or surpluses through influencing factors identification.