基于多情景组合的我国电能替代潜力预测与实施路径研究  

Research on the Potential Prediction and Implementation Path of Electric Energy Substitution in China Based on Mutiple Scenario Combinations

作　　者：王博[1,3] 王灿 张洪秩 李浩[2,3] 王兆华[2,3] WANG Bo;WANG Can;ZHANG Hongzhi;LI Hao;WANG Zhaohua(School of Management,Beijing Institute of Technology,Bejing 100081,China;School of Economics,Beijing Institute of Technology,Beijing 100081,China;Digital Economy and Policy Intelligentization Key Laboratory of Ministry of Industry and Information Technology,Beijing Institute of Technology,Beijing 100081,China)

机构地区：[1]北京理工大学管理学院,北京100081 [2]北京理工大学经济学院,北京100081 [3]北京理工大学数字经济与政策智能工业和信息化部重点实验室,北京100081

出　　处：《工程管理科技前沿》2025年第1期19-27,共9页Frontiers of Science and Technology of Engineering Management

基　　金：北京市社会科学基金资助项目(21GLC057)。

摘　　要：本文基于对数平均迪式指数法探究家庭和产业部门电力消费驱动因素的异质性,并结合分解结果扩展电力负荷预测模型,将智能化程度、电气化政策等我国新时期电力需求变化关键影响因素纳入模型,研判中国化共享社会经济路径(SSPs)与典型浓度路径(RCPs)的组合情景下我国电能替代水平。研究结果发现:(1)短期看家庭部门驱动因素的作用效果总体小于产业部门,两部门的能源强度效应和能源结构效应都将对电力增长发挥重要驱动作用;(2)我国未来电力需求增长空间广、情景差异大,2060年,可持续发展(SSP1-RCP1.9)情景下我国用电量达14.97万亿千瓦时,高化石能源依赖(SSP5-RCP8.5)情景下电力需求量达16.87万亿千瓦时,历史模式发展(SSP2-RCP4.5)情景下用电量仅为SSP5-RCP8.5情景的3/4。电力需求发展路径研判为未来能源系统转型、低碳政策制定提供科学支撑。The electrification of end-use energy and the clean production of electricity have become pivotal strategies for China to address the dual challenges of climate change and achieving its commitments to carbon peaking and neutrality.However,as the process of electric energy substitution deepens and the share of new energy sources characterized by random and intermittent fluctuations grows,China's power system faces increasing challenges related to economic efficiency,operational security,and overall stability.These challenges necessitate a comprehensive understanding of medium-and long-term electricity demand trends,as well as the impact of factors such as electrification,urbanization,and technological progress.Such understanding is critical for managing supply-demand uncertainties,supporting a stable energy transition,and planning for the rational deployment of low-or zero-carbon power generation capacity.This paper analyzes the drivers of China's electricity demand between 2001 and 2019 using the Logarithmic Mean Divisia Index(LMDI) method.Considering that residential electricity demand is mainly affected by demographic characteristics,income levels,technological advances,and climatic conditions,while the drivers of industrial sector electricity demand mainly include economic development,industrial structure,and technological advances,this paper further explores the heterogeneity of the drivers of electricity consumption in the household and industrial sectors.The analysis reveals that the effect of household sector drivers is generally smaller than that of the industrial sector,and the energy intensity effect and energy structure effect of both sectors will play an important driving role in electricity growth.For the industrial sector,the economic scale effect is the main driver of electricity consumption growth in 2001—2019.For the household sector,the household income improvement effect promotes the shift of residential energy use from traditional domestic energy to cleaner and more convenient electricity,wh

关 键 词：电力需求预测 驱动因素解析 扩展电力负荷预测模型 SSP-RCP情景框架 

分 类 号：F426.61[经济管理—产业经济]