汤卓凡,王奎,赵建立,王开让,郑庆荣
TANG Zhuofan,WANG Kui,ZHAO Jianli,WANG Kairang,ZHENG Qingrong

• 1:国网上海市电力公司
• 2:上海市智能电网需求响应重点实验室
• 3:国网电力科学研究院武汉能效测评有限公司
• 4:国网电力科学研究院有限公司

摘要(Abstract)：

随着我国“双碳”目标的推进，新能源大规模接入使得电力系统供需平衡问题日益突出，空调负荷的需求响应能力是解决该问题的重要手段之一。我国空调负荷参与需求响应的激励机制并不完善，无法调动用户参与电网互动的积极性。首先，基于空调负荷特性，汲取国内外空调负荷参与需求响应的发展经验，分析我国在空调负荷参与需求响应方面所面临的挑战。然后，根据电力市场机制完善度、关键技术成熟度和用户接受度3个维度的发展程度，将空调负荷参与电网灵活互动分为起步阶段、过渡阶段和成熟阶段，并提出不同阶段面向空调负荷的需求响应激励机制。最后，针对不同阶段的激励机制提出配套的实施建议。
With the advancement of China's dual carbon goals, the large-scale integration of new energy sources has exacerbated the supply-demand balance in power systems. The demand response capability of air-conditioning loads is one of the crucial means for addressing this issue. However, the incentive mechanisms for air-conditioning loads participating in demand response in China are still underdeveloped, limiting user engagement in grid interaction. This paper first analyzes the challenges China faces in this area by examining the characteristics of airconditioning loads and drawing insights from both domestic and international demand response practices. It then categorizes the stages of air-conditioning loads participating in grid flexibility into initiation, transition, and maturity phases, based on the development levels of electricity market mechanisms, key technologies, and user acceptance.For each stage, different demand response incentive mechanisms are proposed, along with specific implementation recommendations tailored to each phase.

关键词(KeyWords)： 空调负荷;需求响应;激励机制;电力市场;负荷管理
air-conditioning loads;demand response;incentive mechanism;electricity markets;load management

Abstract:

Keywords:

基金项目(Foundation): 国家电网有限公司总部科技项目（5400-202340383A-2-3-XG）

作者(Author): 汤卓凡,王奎,赵建立,王开让,郑庆荣
TANG Zhuofan,WANG Kui,ZHAO Jianli,WANG Kairang,ZHENG Qingrong

DOI: 10.19585/j.zjdl.202502003

参考文献(References)：

• [1]孟凯.空调负荷的需求响应机制研究[D].郑州：郑州大学，2018.MENG Kai.Research on demand response mechanism of air conditioning load[D]. Zhengzhou:Zhengzhou University,2018.
• [2]宋梦.空调负荷参与电力系统调控关键技术研究[D].南京：东南大学，2018.SONG Meng.Research on key technologies of air conditioning loads participating in power system dispatch and control[D].Nanjing:Southeast University,2018.
• [3]吴桐，惠红勋，张洪财.商业建筑空调系统参与城市电网负荷调控综述[J].中国电力，2023,56(7):1-11.WU Tong,HUI Hongxun,Hongcai. Review of commercial air conditioners for participating in urban grid regulation[J].Electric Power,2023,56(7):1-11.
• [4]宿皓.基于负荷不确定性的建筑需求响应优化控制策略研究[D].天津：天津大学，2020.SU Hao. Research on building demand response control strategy based on load uncertainty[D]. Tianjin:Tianjin University,2020.
• [5]吉用丽.空调负荷参与电网辅助服务关键技术研究[D].南京：东南大学，2022.JI Yongli.Research on key technologies of air conditioning loads participating in auxiliary service of power system[D].Nanjing:Southeast University,2022.
• [6] JI Yongli,XU Qingshan. Frequency regulation support from aggregation of air conditioners based on the trigger value local update strategy[J].IET Generation,Transmission&Distribution,2020,14(16):3150-3160.
• [7]张鑫洋，孟庆龙，李辉，等.集中空调系统需求响应潜力分析[J].电力需求侧管理，2023,25(6):57-62.ZHANG Xinyang,MENG Qinglong,LI Hui,et al.Analysis of demand response potential of central air-conditioning system[J]. Power Demand Side Management,2023,25(6):57-62.
• [8]汤江晖，苏子云，王迎秋，等.考虑5G宏基站空调负荷参与需求响应的潜力分析[J].电力需求侧管理，2022,24(6):77-83.TANG Jianghui,SU Ziyun,WANG Yingqiu,et al.Potential analysis of 5G macro base station’s air conditioning load participating in demand response[J].Power Demand Side Management,2022,24(6):77-83.
• [9]程杰，谢昕怡，杨鑫源，等.需求侧资源聚合参与调峰的双层优化模型研究[J].武汉大学学报（工学版），2024,57(3):338-347.CHENG Jie,XIE Xinyi,YANG Xinyuan,et al.Research on two-level optimization model of demand side resource aggregation participating in peak shaving[J]. Engineering Journal of Wuhan University,2019,57(3):338-347.
• [10]胡志勇，郭雪丽，王爽，等.考虑响应意愿的电动汽车群-空调集群需求响应策略研究[J].电力系统保护与控制，2023,51(15):109-119.HU Zhiyong,GUO Xueli,WANG Shuang,et al.Demand response strategy for electric vehicles and air conditioners considering response willingness[J]. Power System Protection and Control,2023,51(15):109-119.
• [11]丁胜，徐承美，饶尧，等.楼宇空调需求响应实时控制仿真与实践研究[J].电力需求侧管理，2022,24(6):91-98.DING Sheng,XU Chengmei,RAO Yao,et al.Simulation and practice on demand response real-time control of building air conditioning[J].Power Demand Side Management,2022,24(6):91-98.
• [12]康靖，李雨桐，郝斌，等.多联机空调柔性负荷参与电力系统需求响应的实证研究[J].供用电，2022,39(8):39-46.KANG Jing,LI Yutong,HAO Bin,et al.Empirical study on flexible load of multi connected air conditioning participating in power system demand response[J].Distribution&Utilization,2022,39(8):39-46.
• [13]刘衣萍，于鹤洋，王晨旭，等.考虑用户行为的居民空调负荷需求响应[J].浙江电力，2023,42(3):1-8.LIU Yiping,YU Heyang,WANG Chenxu,et al.Demand response of residential air conditioning load based on user behavior[J].Zhejiang Electric Power,2023,42(3):1-8.
• [14]张天伟，谢畅，王蓓蓓，等.美国商业建筑空调负荷控制策略及其在自动需求响应系统中的整合应用[J].电力需求侧管理，2016,18(6):60-64.ZHANG Tianwei,XIE Chang,WANG Beibei,et al.The commercial building air conditioning load control strategies and its comprehensive application in automated demand response system of the U.S[J].Power Demand Side Management,2016,18(6):60-64.
• [15] DA FONSECA A L A, CHVATAL K M S,FERNANDES R A S. Thermal comfort maintenance in demand response programs:a critical review[J]. Renewable and Sustainable Energy Reviews,2021,141(8):110847.
• [16]曾麟，谭娟，向运鲲，等.面向新型电力系统的负荷聚合商功能界定及其需求响应流程[J].科技风，2022,(16):82-84.ZENG Lin,TAN Juan,XIANG Yun,et al.Function definition and demand response process of load aggregator for new power system[J]. Technology Wind,2022,(16):82-84.
• [17]文福拴，林鸿基，胡嘉骅.需求响应的商业机制与市场框架初探[J].电力需求侧管理，2019,21(1):4-9.WEN Fushuan,LIN Hongji,HU Jiahua.A preliminary investigation on commercial mechanism and market framework for demand response[J].Power Demand Side Management,2019,21(1):4-9.
• [18]刘巍峰.新型电力系统的紧急需求响应机制研究[D].扬州：扬州大学，2023.LIU Weifeng. Research on emergency demand response mechanism of new power system[D]. Yangzhou:Yangzhou University,2023.
• [19]张杰，高广玲，张智晟.需求响应参与电力系统调频的模糊控制策略[J].广东电力，2020,33(3):64-71.ZHANG Jie,GAO Guangling,ZHANG Zhisheng. Fuzzy control strategy of demand response participating in power system frequency modulation[J]. Guangdong Electric Power,2019,33(3):64-71.
• [20]刘淳，王仕俊，赵燕玲，等.区块链技术在虚拟电厂交易中的应用综述[J].电力建设，2023,44(4):130-144.LIU Chun,WANG Shijun,ZHAO Yanling,et al.Review of the application of blockchain technology in virtual power plant transactions[J].Electric Power Construction,2023,44(4):130-144.
• [21]舒征宇，朱凯翔，王灿，等.考虑碳交易的虚拟电厂日前电力市场竞价策略[J].电力工程技术，2024,43(5):58-68.SHU Zhengyu,ZHU Kaixiang,WANG Can,et al.Virtual power plants participating in day-ahead electricity market bidding strategy considering carbon trading[J]. Electric Power Engineering Technology,2024,43(5):58-68.
• [22]徐慧慧，田云飞，缪猛，等.计及碳交易和需求响应的虚拟电厂低碳经济调度[J].智慧电力，2023,51(8):1-7.XU Huihui,TIAN Yunfei,MIAO Meng,et al.Low carbon economy dispatch of virtual power plants considering carbon trading and demand response[J]. Smart Power,2023,51(8):1-7.
• [23]刘亚鑫，蔺红.计及碳交易与条件风险值的虚拟电厂竞价策略[J].电力工程技术，2023,42(6):179-188.LIU Yaxin,LIN Hong.Bidding strategy of virtual power plant considering carbon trading and conditional value at risk[J].Electric Power Engineering Technology,2023,42(6):179-188.
• [24]高建伟，黄宁泊，高芳杰，等.基于改进信息间隙决策理论的考虑决策者风险态度的社区虚拟电厂经济-能源-环境调度策略选择[J].电力建设，2024,45(3):39-57.GAO Jianwei,HUANG Ningbo,GAO Fangjie,et al.Selection of economics-energy-environment scheduling strategy for a community virtual power plant considering decision-makers'risk attitudes based on improved information gap decision theory[J].Electric Power Construction,2024,45(3):39-57.
• [25]杨悦，宋良泰.考虑用户需求响应的空调负荷日前-实时聚合调控[J].全球能源互联网，2023,6(5):529-537.YANG Yue,SONG Liangtai.Day ahead and real time aggregate regulation of air conditioning load on demand response[J]. Journal of Global Energy Interconnection,2023,6(5):529-537.
• [26]贾乾罡，陈思捷，严正，等.基于区块链的空调负荷用电权分配：模式与方法[J].中国电机工程学报，2020,40(11):3393-3401.JIA Qiangang,CHEN Sijie,YAN Zheng,et al.Blockchainenabled power usage quotas allocation method for air conditioning loads[J]. Proceedings of the CSEE,2020,40(11):3393-3401.
• [27]周磊，朱明杰，张政，等.针对空调聚合负荷的作用时段差别化尖峰电价机制设计[J].电力需求侧管理，2019,21(3):11-16.ZHOU Lei,ZHU Mingjie,ZHANG Zheng,et al.Design of progressive time differentiated peak pricing mechanism for aggregated air-conditioning load[J]. Power Demand Side Management,2019,21(3):11-16.
• [28]朱峰.空调负荷需求响应特性及其调控策略研究[D].南京：东南大学，2016.ZHU Feng. Research on demand response characteristic and control strategy of air conditioning load[D].Nanjing:Southeast University,2016.
• [29]薛凯.住宅房间空调器使用群体特征及其用能预测方法研究[D].重庆：重庆大学，2022.XUE Kai.Characteristic of residential room air conditioners usage groups and its energy demand prediction method[D].Chongqing:Chongqing University,2022.
• [30]林慧婕，顾琳琳，张宇峰.面向城市楼宇群的温控类柔性负荷优化调度控制方法[J].自动化与仪器仪表，2023(11):150-153.LIN Huijie,GU Linlin,ZHANG Yufeng. Optimal dispatching control method of temperature control flexible load for urban buildings[J]. Automation&Instrumentation,2023(11):150-153.
• [31]姜婷玉，李亚平，江叶峰，等.温控负荷提供电力系统辅助服务的关键技术综述[J].电力系统自动化，2022,46(11):191-207.JIANG Tingyu,LI Yaping,JIANG Yefeng,et al.Review on key technologies for providing auxiliary services to power system by thermostatically controlled loads[J]. Automation of Electric Power Systems,2022,46(11):191-207.
• [32]熊成燕，孟庆龙，奚源.基于交易控制的空调系统电力需求响应策略进展及建议[J].电力需求侧管理，2021,23(06):91-95.XIONG Chengyan, MENG Qinglong, XI Yuan. Development and suggestions of electricity demand response strategies for air-conditioning systems based on transactive control[J]. Power Demand Side Management, 2021, 23(6):91-95.
• [33]孔赟，潘棋，王蓓蓓，等.空调自动需求响应控制策略在美国商业建筑中的应用案例分析[J].电力需求侧管理，2017,19(1):60-64.KONG Yun,PAN Qi,WANG Beibei,et al.The performance analysis of automated demand response control strategies for air conditionings adopted in American commercial buildings[J]. Power Demand Side Management,2017,19(1):60-64.
• [34] MCANANY J.2023 Demand response operations markets activity report:January 2024[R].PJM Demand Side Response Operations,2023. https：//www. pjm. com/-/media/markets-ops/dsr/2023-demand-response-activityreport.ashx.
• [35] HWANG H,YOON A,YOON Y,et al. Demand response of HVAC systems for hosting capacity improvement in distribution networks:a comprehensive review and case study[J].Renewable and Sustainable Energy Reviews,2023,187:113751.
• [36]李彬，陈京生，李德智，等.我国实施大规模需求响应的关键问题剖析与展望[J].电网技术，2019,43(2):694-704.LI Bin,CHEN Jingsheng,LI Dezhi,et al. Analysis and prospect of key issues in China’s demand response for further large scale implementation[J].Power System Technology,2019,43(2):694-704.
• [37]杨旭英，周明，李庚银.智能电网下需求响应机理分析与建模综述[J].电网技术，2016,40(1):220-226.YANG Xuying,ZHOU Ming,LI Gengyin. Survey on demand response mechanism and modeling in smart grid[J].Power System Technology,2016,40(1):220-226.
• [38]祁琪，石富岭，陈宋宋，等.居民负荷参与电力系统调控关键技术综述与展望[J].电网技术，2024,48(2):809-818.QI Qi,SHI Fuling,CHEN Songsong,et al. Review and prospect of key technologies for residential loads participating in power system dispatch and control[J].Power System Technology,2024,48(2):809-818.
• [39]赵晓东，王娟，邓良辰，等.电力市场化改革下我国需求响应价格形成机制研究[J].价格理论与实践，2024(2):142-147.ZHAO Xiaodong,WANG Juan,DENG Liangchen,et al.Study on the price formation mechanism of demand response under the electricity market reform in China[J].Price:Theory&Practice,2024(2):142-147.
• [40]范帅，危怡涵，何光宇，等.面向新型电力系统的需求响应机制探讨[J].电力系统自动化，2022,46(7):1-12.FAN Shuai,WEI Yihan,HE Guangyu,et al. Discussion on demand response mechanism for new power systems[J].Automation of Electric Power Systems,2022,46(7):1-12.
• [41]孟琰，肖居承，洪居华，等.计及需求响应不确定性的节点负荷准线：概念与模型[J].电力系统自动化，2023,47(13):28-39.MENG Yan,XIAO Jucheng,HONG Juhua,et al. Nodal customer directrix load considering demand response uncertainty:concept and model[J]. Automation of Electric Power Systems,2023,47(13):28-39.
• [42]陆旦宏，李思琦，杨婷，等.中央空调负荷精细化调控双层优化技术研究[J].电力需求侧管理，2024,26(1):23-30.LU Danhong,LI Siqi,YANG Ting,et al.Research on refined regulation for two-layer optimization technology of central air-conditioning load[J]. Electric Power Demand Side Management,2024,26(1):23-30.
• [43]石坤，李德智，杨斌，等.面向市场化的智能楼宇互动调控技术[J].电力科学与技术学报，2017,32(3):114-120.SHI Kun,LI Dezhi,YANG Bin,et al.Market oriented interactive control technology for intelligent building[J].Journal of Electric Power Science and Technology,2017,32(3):114-120.
• [44] CORBIN C D,MAKHMALBAF A,HUANG S,et al.Transactive control of commercial build ding HVAC systems[R].Richland WA,USA:Pacific Northwest National Laboratory,2016.
• [45] RAMDASPALLI S, PIPATTANASOMPORN M,KUZLU M,et al. Transactive control for efficient operation of commercial buildings[C]//2016 IEEE PES Innovative Smart Grid Technologies Conference Europe(ISGT-Europe).Ljubljana,Slovenia:IEEE,2016:1-5.