Electric Power ›› 2025, Vol. 58 ›› Issue (5): 52-61.DOI: 10.11930/j.issn.1004-9649.202410088

• Carbon Governance • Previous Articles     Next Articles

A Forecasting Method for Provincial-level Energy Supply and Demand under Carbon Quota Constraint

LI Yan1(), ZHAO Xin1, XUE Wanlei1, TAN Xiandong2, LIU Zhifan1, LIU Zhilin2()   

  1. 1. Economic & Technology Research Institute, State Grid Shandong Electric Power Company, Jinan 250021, China
    2. State Grid Energy Research Institute Co., Ltd., Beijing 102209, China
  • Received:2024-10-28 Online:2025-05-30 Published:2025-05-28
  • Supported by:
    This work is supported by Science and Technology Project of State Grid Shandong Electric Power Company (Study on the Energy Transformation Path and Effect Evaluation of Shandong Province under the Target of Carbon Peak and Carbon Neutralization, No.520625210017).

Abstract:

Energy is the foundation of national economy and the main field for carbon reduction, and its future development of energy supply and demand has a significant impact on constructing the new energy systems and achieving the carbon peak and carbon neutralization targets. Considering multiple factors such as economic and social development status, energy consumption characteristics of each province, an indicator system for carbon quota allocation is constructed, encompassing aggregate and relative metrics, and balancing equity with efficiency, and a provincial-level energy supply-demand forcasting method under carbon quota constraints is proposed to achieve comprehensive balance analysis and prediction of primary and secondary energy of different varieties and industries covering the entire process. Based on China's carbon peak target in 2030, an empirical analysis is carried out with Shandong Province as an example to verify the effectiveness of the proposed method, which provides a reference for different provinces in carbon emissions control and energy transformation.

Key words: energy supply and demand, carbon quotas, fairness and efficiency, synthetic forecasting