电力需求侧管理2026，Vol.28Issue(2)：77-85,9.DOI:10.3969/j.issn.1009-1831.2026.02.012
计及用户低碳需求响应行为的动态碳排放因子预测方法
Dynamic carbon emission factor prediction method considering user low-carbon demand response behavior
摘要
Abstract
In view of the current problem of lack of key guiding signals for low-carbon energy consumption on the user side,a dynamic car-bon emission factor prediction method taking into account the low-carbon demand response behavior on the user side is proposed.First,a us-er dynamic electricity carbon emission factor calculation model is constructed based on the carbon emission flow theory,and a carbon emis-sion factor data pool is constructed in combination with system operation simulation.Second,a low-carbon energy consumption response be-havior model for power users facing dynamic carbon emission factors is constructed,and a dynamic carbon emission factor prediction meth-od taking into account the low-carbon demand response behavior on the user side is proposed.Carbon emission factor prediction is carried out based on LSTM neural network,and effective prediction of node-level dynamic carbon emission factors for a given system based on arbi-trary source and load input is achieved.Finally,a case analysis is carried out based on a PJM-5 node power system and a 36-node power sys-tem with a high proportion of renewable energy,which verifies the effectiveness of the proposed method in predicting node-level electricity carbon emission factors taking into account the user's low-carbon demand response.关键词
碳排放因子/低碳需求响应/长短期记忆神经网络/动态碳排放因子预测Key words
carbon emission factor/low carbon demand response/long short-term memory neural networks/dynamic carbon emission fac-tor prediction分类
信息技术与安全科学引用本文复制引用
李鹏,戚凯,张培强,张世旭,闫志兴,庞柯成,朱晓辉,张宁..计及用户低碳需求响应行为的动态碳排放因子预测方法[J].电力需求侧管理,2026,28(2):77-85,9.基金项目
许继电气重大科技攻关项目(2024G307) （2024G307）
国家自然科学基金项目(52477103) （52477103）
