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计及家用电器电热特性的分散式电采暖集群经济低碳调控策略 被引量:7

Economy Low-carbon Control Strategy of Decentralized Electric Heating Cluster Considering Electrical and Thermal Characteristics of Household Appliances
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摘要 我国正逐步制定和完善能源系统用户侧的降碳政策,住宅电采暖系统运行面临新的发展契机与挑战。为提升电采暖系统运行中电热能源利用率,实现采暖用能环节经济低碳化运行,以碳税定价政策作为环境成本价格背景,提出考虑家用电器电热特性的分散式电采暖集群经济低碳调控策略。首先,以电器设备运行中的电热特性作为分类依据,对室内电器运行情况进行分类聚合预测,并计算电器运行热增益作为采暖热源的补充。其次,根据分散式电采暖用户建筑和采暖设备热力学特性,构建电采暖“经济-低碳”运行优化模型,采用显式模型预测控制(explicit model predictive control,EMPC)技术对模型进行求解。最后,通过算例仿真对比分析可知,所提调控策略可用于分散式采暖用户集群的实时调控,实现电采暖系统运行经济性、低碳化目标。 Carbon reduction policies on the user side of the energy system in China is gradually formulating and improving,and the operation of residential electric heating systems is facing new development opportunities and challenges.In order to improve the utilization of electric heating energy in the operation of electric heating system and realize the economic and low-carbon operation of heating energy,this paper used the carbon tax pricing policy as the environmental cost price background,and propose d a decentralized electric heating cluster economic low-carbon regulation that takes into account the electrical and thermal characteristics of household appliances.First,the electrical heating characteristics of electrical equipment are used as a classification basis to classify and aggregate the operating conditions of indoor electrical appliances,and the electrical operating heat gain was calculated as a supplement to the heating source.Secondly,according to the thermodynamic characteristics of decentralized electric heating users’buildings and heating equipment,an electric heating"economy-low carbon"operation optimization model was constructed,and the explicit model predictive control(EMPC)technology was used to solve the model.Finally,through the comparison and analysis of simulation examples,it can be seen that the regulation strategy proposed in this paper can be used for real-time regulation of distributed heating user clusters to achieve the economic and low-carbon operation of the electric heating system.
作者 张虹 王明晨 白洋 张茜 於炜人 刘旭 ZHANG Hong;WANG Mingchen;BAI Yang;ZHANG Qian;YU Weiren;LIU Xu(Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology(Northeast Electric Power University),Ministry of Education,Jilin 132012,Jilin Province,China;State Grid Jilin Power Supply Company,Jilin 132000,Jilin Province,China;State Grid Haerbin Power Supply Company,Harbin 150040,Heilongjiang Province,China;State Grid Zhejiang Power Supply Company,Yongkang 321300,Zhejiang Province,China)
出处 《中国电机工程学报》 EI CSCD 北大核心 2022年第11期4013-4026,共14页 Proceedings of the CSEE
基金 国家自然科学基金项目(51777027) 吉林省教育厅科学研究项目(JJKH20210093KJ)。
关键词 碳达峰 电采暖 分散式电采暖用户集群 负荷分类聚合预测 显式模型预测控制 carbon peaking electric heating decentralized electric heating user cluster load classification and aggregation prediction explicit model predictive control
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