袁博,张天翔,王逸飞

• 1:国网河北电力有限公司经济技术研究院
• 2:东南大学电气工程学院

摘要(Abstract)：

随着国家碳达峰与碳中和战略推进，在未来几年新能源将大量并网。同时，由于新能源发电的不可控性，单纯依靠传统可控机组的调节方式可能产生大量弃风弃光现象，需要利用用户侧大规模分布式资源促进新能源消纳。然而，目前在面向新能源消纳的大规模用户需求响应方面研究较少。为此，提出了一种考虑大规模用户负荷准线需求响应的电力系统运行决策模型。该模型将各负荷节点可以有效消纳新能源出力的理想负荷曲线形状定义为负荷准线，该负荷准线通过综合考虑发电机对负荷节点动态贡献比例、系统运行情况以及新能源预测评估得到。将负荷准线公开发布后用户在激励补贴影响下权衡利弊自愿调整用电行为，使实际负荷曲线的形状趋近于所属节点负荷准线，从而实现大规模用户侧可控资源与新能源侧不可控资源的消纳平衡。该模型降低了大规模用户需求响应时过高的通信与控制成本，同时使系统运行成本大幅降低，促进新能源并网的消纳。并且，提出一种新的用户响应效果评价指标，可以有效提高激励补贴计算的公平性。

关键词(KeyWords)： 新能源消纳;需求响应;负荷准线;激励补贴;碳达峰;碳中和;光伏发电;风力发电

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(52007032)

作者(Author): 袁博,张天翔,王逸飞

DOI: 10.13928/j.cnki.wrahe.2022.12.016

参考文献(References)：

• [1] 葛毅，陈佳铭，朱永康，等.考虑广义需求侧资源的江苏“十四五”电源规划[J].电力需求侧管理，2021,23(2):4-9.GE Yi,CHEN Jiaming,ZHU Yongkang,et al.Power generation planning considering generalized demand?side resources of Jiangsu province in the 14th Five-Year Plan period [J].Power Demand Side Management,2021,23(2):4-9.
• [2] 王俐英，曾鸣，赵嘉欣，等.计及电力需求响应的多能源协同系统优化运行研究[J].电力工程技术，2021,40(1):2-9.WANG Liying,ZENG Ming,ZHAO Jiaxin,et al.Optimal operation of multi-energy collaborative system considering electricity demand response[J].Electric Power Engineering Technology,2021,40(1):2-9.
• [3] 刘军会，刘鑫，李虎军，等.国外需求响应市场化实施模式及启示[J].电力需求侧管理，2021,23(2):95-100.LIU Junhui,LIU Xin,LI Hujun,et al.Marketization implementation mode and enlightenment of foreign demand response participating in electricity[J].Power Demand Side Management,2021,23(2):95-100.
• [4] ZHENGQI C,YINGYUN S,XIN A,et al.Integrated demand response characteristics of industrial park:a review[J].Journal of Modern Power Systems and Clean Energy,2020,8(1):15-26.
• [5] 陈宏，赖春艳.我国电力能源需求响应发展现状与展望[J].电力与能源，2021,42(1):87-90.CHEN Hong,LAI Chunyan.Present situation and prospect of China′s power demand response development[J].Power & Energy,2021,42(1):87-90.
• [6] 高赐威，李倩玉，李扬.基于dlc的空调负荷双层优化调度和控制策略[J].中国电机工程学报，2014,34(10):1546-1555.GAO Ciwei,LI Qianyu,LI Yang.Bi-level optimal dispatch and control strategy for air-conditioning load based on direct load control[J].Proceedings of the CSEE,2014,34(10):1546-1555.
• [7] 胡晓青.空调负荷参与电力系统需求响应的建模及控制策略研究[D].南京：东南大学，2017.HU Xiaoqing.Research On Modeling And Control Strategy For Air Conditioning Loads To Participate In Demand Response In Power System[D].Nanjing:School of Electrical Engineering,Southeast University,2017.
• [8] 周欣怡，齐先军，吴红斌，等.提高需求响应可靠性的储能优化配置研究[J].电力系统保护与控制，2021,49(2):107-114.ZHOU Xinyi,QI Xianjun,WU Hongbin,et al.Research on optimal allocation of energy storage to improve the reliability of demand response[J].Power System Protection and Control,2021,49(2):107-114.
• [9] 王颖杰，詹红霞，杨孝华，等.考虑综合需求响应的电热系统调度[J].电力工程技术，2021,40(1):17-24.WANG Yingjie,ZHAN Hongxia,YANG Xiaohua,et al.Optimal dispatching strategy of combined heat and power systemconsidering integrated demand response [J].Electric Power Engineering Technology,2021,40(1):17-24.
• [10] ZENG Fangdi,BIE Zhaohong,LIU Shiyu,et al.Trading model combining electricity,heating and cooling under multi-energy demand response[J].Journal of Modern Power Systems and Clean Energy,2020,8(1):133-141.
• [11] CAO Yuwei,WANG Liying,JIANG Shigong,et al.Optimal operation of cold-heat-electricity multi- energy collaborative system based on price demand response[J].Global Energy Interconnection,2020,3(5):430-441.
• [12] FANG Chen,ZHAO Xiaojin,XU Qin,et al.Aggregator- based demand response mechanism for electric vehicles participating in peak regulation in valley time of receiving-end power grid[J].Global Energy Interconnection,2020,3(5):453-463.
• [13] 许信义.电力市场动态需求响应建模与优先级排序研究[D].吉林：东北电力大学，2020.XU Xinyi.Modeling and Prioritizing Dynamic Demand Response Programs in the Electricity Markets[D].Jilin:School of Electrical Engineering,Northeast Electric Power University,2020.
• [14] 徐弘升，陆继翔，杨志宏，等.基于深度强化学习的激励型需求响应决策优化模型[J].电力系统自动化，2021,45(14):97-103.XU Hongsheng,LU Jixiang,YANG Zhihong,et al.Decision optimization model of incentive demand response based on deep reinforcement learning[J].Automation of Electric Power Systems,2021,45(14):97-103.
• [15] 洪奕，刘瑜俊，徐青山，等.基于积分制和分时电价的电动汽车混合型精准需求响应策略[J].电力自动化设备，2020,40(11):106-116.HONG Yi,LIU Yujun,XU Qingshan,et al.Hybrid targeted demand response strategy of electric vehicles based on integral system and time-of-use electricity price[J].Electric Power Automation Equipment,2020,40(11):106-116.
• [16] 牛文娟，王磊，李扬.需求响应项目中用户基线负荷计算方法及其应用[J].东南大学学报(自然科学版),2014,44(3):556-560.NIU Wenjuan,WANG Lei,LI Yang.Calculation method and application of customer baseline load in demand response project[J].Journal of Southeast University(Natural Science Edition),2014,44(3):556-560.
• [17] 王啸峰，苏慧玲，宋天立，等.基于负荷细分的差异化用户基线负荷预测[J].电力工程技术，2018,37(6):33-38.WANG Xiaofeng,SU Huiling,SONG Tianli,et al.Differential Customer baseline load forecasting based on load subdivision[J].Electric Power Engineering Technology,2018,37(6):33-38.
• [18] 刘顺桂，杨佳驹，王磊.考虑用户用电特性的基线负荷计算方法[J].电力需求侧管理，2016,18(3):17-22.LIU Shungui,YANG Jiaju,WANG Lei.Baseline load calculation with considering customer different electrical characteristics[J].Power Demand Side Management,2016,18(3):17-22.
• [19] 曹琛.考虑用户舒适度及用户基线负荷的需求侧负荷控制策略研究[D].西安：西安理工大学，2020.CAO Chen.Research on Demand Side Load Control Strategy Considering User Comfort and User Baseline Load[D].Xian:Xi’an University of Technology,2020.
• [20] 邱革非，何超，骆钊，等.考虑新能源消纳及需求响应不确定性的配电网主从博弈经济调度[J].电力自动化设备，2021,41(6):66-74.QIU Gefei,HE Chao,LUO Zhao,et al.Economic dispatch of Stackelberg game in distribution network considering new energy consumption and uncertainty of demand response[J].Electric Power Automation Equipment,2021,41(6):66-74.
• [21] 范帅，郏琨琪，王芬，等.基于负荷准线的大规模需求响应[J].电力系统自动化，2020,44(15):19-27.FAN Shuai,JIA Kunqi,WANG Fen,et al.Large-scale demand response based on customer directrix load[J].Automation of Electric Power Systems,2020,44(15):19-27.
• [22] FAN S,LI Z,YANG L,et al.Customer directrix load-based large-scale demand response for integrating renewable energy sources[J].Electric Power Systems Research,2020,181(C):106175.
• [23] ARUN S L,SELVAN M P.Smart residential energy management system for demand response in buildings with energy storage devices[J].Frontiers in Energy,2019,13(4):715-730.
• [24] SAEED A,SAYYAD N,MEHDI A.Multi-objective short-term scheduling of active distribution networks for benefit maximization of DisCos and DG owners considering demand response programs and energy storage system[J].Journal of Modern Power Systems and Clean Energy,2018,6(1):95-106.
• [25] 曾璐琨.需求侧聚合负荷协同控制策略研究[D].北京：华北电力大学(北京),2019.ZENG Lukun.Research on Collaborative Control Strategy of Demand-side Aggregated Loads[D].Beijing:School of Electrical and Electronic Engineering,North China Electric Power University,2019.
• [26] XIAO Hao,PEI Wei,DONG Zuomin,et al.Bi-level planning for integrated energy systems incorporating demand response and energy storage under uncertain environments using novel metamodel[J].CSEE Journal of Power and Energy Systems,2018,4(2):155-167.