Optimization Method of Energy Consumption for Thermoelectric Coupling System in Smart Energy Community Considering Demand Response

Zesheng HU; Jun LU; Rui HUANG; Mouhai LIU; Zhiqiang XU; Yun WANG

doi:10.7500/AEPS20190712014

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Optimization Method of Energy Consumption for Thermoelectric Coupling System in Smart Energy Community Considering Demand Response

Basic Research | 更新时间：2025-06-16

- Optimization Method of Energy Consumption for Thermoelectric Coupling System in Smart Energy Community Considering Demand Response
- Automation of Electric Power Systems Vol. 44, Issue 12, Pages: 22-30(2020)
- 作者机构：
  
  1. 华北电力大学电气与电子工程学院，北京市 102206
  2. 国网湖南省电力有限公司供电服务中心（计量中心），湖南省长沙市 410004
  3. 国网湖南省电力有限公司经济技术研究院，湖南省长沙市 410004
- 作者简介：
- 基金信息：
  
  State Grid Corporation of China
- DOI：10.7500/AEPS20190712014
  CLC：
- Received：12 July 2019，
  
  Revised：2019-10-15，
  
  Published Online：13 April 2020，
  
  Published：25 June 2020
- 稿件说明：
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胡泽升,陆俊,黄瑞等.计及需求响应的智慧能源小区热电耦合系统用能优化方法[J].电力系统自动化,2020,44(12):22-30.

HU Zesheng,LU Jun,HUANG Rui,et al.Optimization Method of Energy Consumption for Thermoelectric Coupling System in Smart Energy Community Considering Demand Response[J].Automation of Electric Power Systems,2020,44(12):22-30.
胡泽升,陆俊,黄瑞等.计及需求响应的智慧能源小区热电耦合系统用能优化方法[J].电力系统自动化,2020,44(12):22-30. DOI： 10.7500/AEPS20190712014.

HU Zesheng,LU Jun,HUANG Rui,et al.Optimization Method of Energy Consumption for Thermoelectric Coupling System in Smart Energy Community Considering Demand Response[J].Automation of Electric Power Systems,2020,44(12):22-30. DOI： 10.7500/AEPS20190712014.

摘要

针对智慧能源小区热电耦合系统中能量间纵向转换和用能负荷横向搬移的协同用能优化问题，通过负荷侧需求响应用能精细化建模，提出一种计及需求响应的热电耦合系统用能优化方法。在分析典型热电耦合系统结构框架基础上，通过用能负荷分类及其用能响应过程的数学建模，建立了含热电耦合系统的能源供给侧与用能负荷侧的能量枢纽方程，实现了用能负荷响应与能源供给之间能量转换的量化描述；其次将用能负荷的需求响应程度表示为可转移负荷参与比和可转换负荷参与比，建立了系统运行成本最小的热电耦合系统用能最优化模型，并提出了灵活尺度多次参与用能优化的模型求解方法。最后，算例结果表明，在高可转移负荷参与比和低可转换负荷参与比时，在降低供给侧峰值段负荷的同时使系统总成本降低，实现了热电耦合系统用能最优化运行。

Abstract

Aiming at the synergy optimization problem of longitudinal transition between energy and lateral shift of energy consumption for thermoelectric coupling system in smart energy community

this paper proposes an optimization method of energy consumption considering thermoelectric coupling system of demand response through refined modeling of energy consumption for demand response on load side. Based on the analysis of the structural framework of typical thermoelectric coupling system

the energy hub (EH) equation between energy supply side

energy consumption on load side containing thermoelectric coupling system is established by the mathematical modeling of load classification and response process for energy consumption. And the quantitative description of energy conversion between load response of energy consumption and energy supply is realized. Then

the demand response degree of load for energy consumption is expressed as the participation ratio of the transformable load and the shiftable load. The optimization model of energy consumption is established with the lowest system operation cost. A model solution method with flexible scale and participation of multiple demand responses is proposed for the optimization of energy consumption.The results of experiments show that the peak of load on supply side and the total system cost can be reduced at the same time with high shiftable load participation ratio and low transformable load participation ratio

which achieves the optimal operation of the thermoelectric coupling system.

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references

国家电网有限公司 . 关于新时代改革“再出发”加快建设世界一流能源互联网企业的意见 [EB/OL].[ 2019-01-21 ]. http://m.tanpaifang.com/article/62904.html http://m.tanpaifang.com/article/62904.html .

State Grid Corporation of China . Review on the new era of reform “re-start” to accelerate the construction of world-class Energy Internet companies [EB/OL]. [ 2019-01-21 ]. http://m.tanpaifang.com/article/62904.html http://m.tanpaifang.com/article/62904.html .

程浩忠 , 胡枭 , 王莉 , 等 . 区域综合能源系统规划研究综述 [J]. 电力系统自动化 , 2019 , 43 ( 7 ): 2 - 13 .

CHENG Haozhong , HU Xiao , WANG Li , et al . Review on research of regional integrated energy system planning [J]. Automation of Electric Power Systems , 2019 , 43 ( 7 ): 2 - 13 .

孙秋野 , 王冰玉 , 黄博南 , 等 . 狭义能源互联网优化控制框架及实现 [J]. 中国电机工程学报 , 2015 , 35 ( 18 ): 4571 - 4580 .

SUN Qiuye , WANG Bingyu , HUANG Bonan , et al . The optimization control and implementation for the special energy internet [J]. Proceedings of the CSEE , 2015 , 35 ( 18 ): 4571 - 4580 .

DE PAOLA A , ORTOLANI M , LO RE G , et al . Intelligent management systems for energy efficiency in buildings [J]. ACM Computing Surveys , 2014 , 47 ( 1 ): 1 - 38 .

李更丰 , 别朝红 , 王睿豪 , 等 . 综合能源系统可靠性评估的研究现状及展望 [J]. 高电压技术 , 2017 , 43 ( 1 ): 114 - 121 .

LI Gengfeng , BIE Zhaohong , WANG Ruihao , et al . Research status and prospects on reliability evaluation of integrated energy system [J]. High Voltage Engineering , 2017 , 43 ( 1 ): 114 - 121 .

郝然 , 艾芊 , 朱宇超 , 等 . 基于能源集线器的区域综合能源系统分层优化调度 [J]. 电力自动化设备 , 2017 , 37 ( 6 ): 171 - 178 .

HAO Ran , AI Qian , ZHU Yuchao , et al . Hierarchical optimal dispatch based on energy hub for regional integrated energy system [J]. Electric Power Automation Equipment , 2017 , 37 ( 6 ): 171 - 178 .

徐筝 , 孙宏斌 , 郭庆来 . 综合需求响应研究综述及展望 [J]. 中国电机工程学报 , 2018 , 38 ( 24 ): 7194 - 7205 .

XU Zheng , SUN Hongbin , GUO Qinglai . Review and prospect of integrated demand response [J]. Proceedings of the CSEE , 2018 , 38 ( 24 ): 7194 - 7205 .

张伊宁 , 何宇斌 , 晏鸣宇 , 等 . 计及需求响应与动态气潮流的电-气综合能源系统优化调度 [J]. 电力系统自动化 , 2018 , 42 ( 20 ): 1 - 10 .

ZHANG Yining , HE Yubin , YAN Mingyu , et al . Optimal dispatch of integrated electricity-natural gas system considering demand response and dynamic natural gas flow [J]. Automation of Electric Power Systems , 2018 , 42 ( 20 ): 1 - 10 .

ZHANG C , XU Y , DONG Z Y , et al . Robust operation of microgrids via two-stage coordinated energy storage and direct load control [J]. IEEE Transactions on Power Systems , 2017 , 32 ( 4 ): 2858 - 2868 .

LI R , CHEN L J , YUAN T J , et al . Optimal dispatch of zero-carbon-emission micro Energy Internet integrated with non-supplementary fired compressed air energy storage system [J]. Journal of Modern Power Systems and Clean Energy , 2016 , 4 ( 4 ): 566 - 580 .

王珺 , 顾伟 , 陆帅 , 等 . 结合热网模型的多区域综合能源系统协同规划 [J]. 电力系统自动化 , 2016 , 40 ( 15 ): 17 - 24 .

WANG Jun , GU Wei , LU Shuai , et al . Cooperative planning of multi-region integrated energy system combined with heat network model [J]. Automation of Electric Power Systems , 2016 , 40 ( 15 ): 17 - 24 .

朱承治 , 陆帅 , 周金辉 , 等 . 基于电-热分时间尺度平衡的综合能源系统日前经济调度 [J]. 电力自动化设备 , 2018 , 38 ( 6 ): 138 - 143 .

ZHU Chengzhi , LU Shuai , ZHOU Jinhui , et al . Day-ahead economic dispatch of integrated energy system based on electricity and heat balance in different time scales [J]. Electric Power Automation Equipment , 2018 , 38 ( 6 ): 138 - 143 .

徐航 , 董树锋 , 何仲潇 , 等 . 基于多能互补的电/热综合需求响应 [J]. 电网技术 , 2019 , 43 ( 2 ): 480 - 489 .

XU Hang , DONG Shufeng , HE Zhongxiao , et al . Electro-thermal comprehensive demand response based on multi-energy complementarity [J]. Power System Technology , 2019 , 43 ( 2 ): 480 - 489 .

郭尊 , 李庚银 , 周明 , 等 . 计及综合需求响应的商业园区能量枢纽优化运行 [J]. 电网技术 , 2018 , 42 ( 8 ): 2439 - 2448 .

GUO Zun , LI Gengyin , ZHOU Ming , et al . Optimal operation of energy hub in business park considering integrated demand response [J]. Power System Technology , 2018 , 42 ( 8 ): 2439 - 2448 .

陆俊 , 朱炎平 , 彭文昊 , 等 . 计及用电行为聚类的智能小区互动化需求响应方法 [J]. 电力系统自动化 , 2017 , 41 ( 17 ): 113 - 120 .

LU Jun , ZHU Yanping , PENG Wenhao , et al . Interactive demand response method of smart community considering clustering of electricity consumption behavior [J]. Automation of Electric Power Systems , 2017 , 41 ( 17 ): 113 - 120 .

BAHRAMI S , SHEIKHI A . From demand response in smart grid toward integrated demand response in smart energy hub [J]. IEEE Transactions on Smart Grid , 2016 , 7 ( 2 ): 650 - 658 .

王毅 , 张宁 , 康重庆 . 能源互联网中能量枢纽的优化规划与运行研究综述及展望 [J]. 中国电机工程学报 , 2015 , 35 ( 22 ): 5669 - 5681 .

WANG Yi , ZHANG Ning , KANG Chongqing . Review and prospect of optimal planning and operation of energy hub in energy internet [J]. Proceedings of the CSEE , 2015 , 35 ( 22 ): 5669 - 5681 .

张东霞 , 苗新 , 刘丽平 , 等 . 智能电网大数据技术发展研究 [J]. 中国电机工程学报 , 2015 , 35 ( 1 ): 2 - 12 .

ZHANG Dongxia , MIAO Xin , LIU Liping , et al . Research on development strategy for smart grid big data [J]. Proceedings of the CSEE , 2015 , 35 ( 1 ): 2 - 12 .

COMINOLA A , GIULIANI M , PIGA D , et al . A hybrid signature-based iterative disaggregation algorithm for non-intrusive load monitoring [J]. Applied Energy , 2017 , 185 : 331 - 344 .

门向阳 , 曹军 , 王泽森 , 等 . 能源互联微网型多能互补系统的构建与储能模式分析 [J]. 中国电机工程学报 , 2018 , 38 ( 19 ): 5727 - 5737 .

MEN Xiangyang , CAO Jun , WANG Zesen , et al . The constructing of multi-energy complementary system of energy internet microgrid and energy storage model analysis [J]. Proceedings of the CSEE , 2018 , 38 ( 19 ): 5727 - 5737 .

CHUA K J , CHOU S K , YANG W M . Advances in heat pump systems: a review [J]. Applied Energy , 2010 , 87 : 3611 - 3624 .

NGUYEN H T , MUHS J W , PARVANIA M . Assessing impacts of energy storage on resilience of distribution systems against hurricanes [J]. Journal of Modern Power Systems and Clean Energy , 2019 , 7 ( 4 ): 731 - 740 .

Commercial and residential hourly load profiles for all TMY 3 locations in the United States [EB/OL]. [ 2013-07-02 ]. https://openei.org/datasets/dataset/commercial-and-residential-hourly-load-profiles-for-all-tmy3-locations-in-the-united-states https://openei.org/datasets/dataset/commercial-and-residential-hourly-load-profiles-for-all-tmy3-locations-in-the-united-states .

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