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1.浙江大学电气工程学院,浙江省杭州市 310027
2.国网浙江省电力有限公司,浙江省杭州市 310007
3.国网浙江省电力有限公司电力科学研究院,浙江省杭州市 310014
吕挺(1997—),男,硕士研究生,主要研究方向:电力市场、需求侧响应。E-mail:lvting_ee@zju.edu.cn
张智(1994—),男,博士研究生,主要研究方向:电力市场、需求侧响应。E-mail:zhangzhi_ee@zju.edu.cn
芦鹏飞(1993—),男,工程师,主要研究方向:需求侧响应、有序用电。E-mail:845293550@qq.com
林振智(1979—),男,通信作者,博士,教授,博士生导师,主要研究方向:电力系统态势感知、电力大数据、电力市场与需求侧管理、综合能源系统规划与运行。E-mail:linzhenzhi@zju.edu.cn
收稿:2022-03-27,
修回:2022-09-01,
网络出版:2022-11-30,
纸质出版:2023-10-10
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吕挺,张智,芦鹏飞等.考虑用户信用的虚拟聚合商需求响应交易机制[J].电力系统自动化,2023,47(19):44-52.
LYU Ting,ZHANG Zhi,LU Pengfei,et al.Demand Response Transaction Mechanism for Virtual Load Aggregator Considering User Credit[J].Automation of Electric Power Systems,2023,47(19):44-52.
吕挺,张智,芦鹏飞等.考虑用户信用的虚拟聚合商需求响应交易机制[J].电力系统自动化,2023,47(19):44-52. DOI: 10.7500/AEPS20220327001.
LYU Ting,ZHANG Zhi,LU Pengfei,et al.Demand Response Transaction Mechanism for Virtual Load Aggregator Considering User Credit[J].Automation of Electric Power Systems,2023,47(19):44-52. DOI: 10.7500/AEPS20220327001.
新型电力系统中
用户侧可调负荷等灵活资源将广泛参与电网互动,促进源网荷弹性平衡。为此,文中提出面向工商业可调负荷资源的虚拟聚合商需求响应模式,通过基于用户信用的响应补贴机制实现用户侧可调负荷集聚,并构建了用户响应补贴双层优化模型。上层模型以虚拟聚合商参与需求响应收益最大为目标,通过优化补贴信用系数实现用户响应收益最大;下层模型中用户以计及舒适度损失的效益最大化为目标,调整自身响应行为。算例分析选取了典型用户对所提机制和模型进行验证,结果表明,所提出的需求响应交易机制有效规范了用户的响应行为,信用作用下虚拟聚合商与用户形成了激励相容的效果,有利于需求响应目标精确达成。
Flexible resources such as user-side adjustable load will widely participate in the interaction of the power grid and promote the elastic balance of source-grid-load in the new power system. Thus
a demand response mode of the virtual load aggregators is proposed for the industrial and commercial adjustable load resources
in which the aggregation of user-side adjustable load resources is realized by the response subsidy mechanism based on user credit
and the bi-level optimization model for the user response subsidy is constructed. In the upper level
the maximization of benefits of the virtual load aggregators participating in the demand response is taken as the objective function
and the subsidy credit coefficient is optimized to maximize the response benefits of users. In the lower level
the maximization of benefits of the users with their comfort loss considered is taken as the objective function
and users adjust their response behavior. Verification results of a case study on selected typical users illustrate that the proposed demand response transaction mechanism can effectively regulate the user response behavior
and the effect of credit creates incentive compatibility between the virtual load aggregator and the users
which is conducive to the accurate achievement of the demand response target.
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