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1.西安交通大学电气工程学院,陕西省西安市 710049
2.国网甘肃省电力公司电力科学研究院,甘肃省兰州市 730070
帅轩越(1998—),男,硕士研究生,主要研究方向:配电网优化运行、博弈论及其优化方法。E-mail:sxysxy@xjtu.edu.cn
王秀丽(1961—),女,通信作者,博士,教授,博士生导师,主要研究方向:电力系统规划、电力市场等。E-mail:xiuliw@mail.xjtu.edu.cn
吴雄(1986—),男,博士,副教授,博士生导师,主要研究方向:微电网能量管理、电力市场等。E-mail:wuxiong@mail.xjtu.edu.cn
收稿日期:2021-05-18,
修回日期:2021-08-09,
网络出版日期:2021-09-01,
纸质出版日期:2021-10-10
移动端阅览
帅轩越,王秀丽,吴雄等.计及电热需求响应的共享储能容量配置与动态租赁模型[J].电力系统自动化,2021,45(19):24-32.
SHUAI Xuanyue,WANG Xiuli,WU Xiong,et al.Shared Energy Storage Capacity Allocation and Dynamic Lease Model Considering Electricity-Heat Demand Response[J].Automation of Electric Power Systems,2021,45(19):24-32.
帅轩越,王秀丽,吴雄等.计及电热需求响应的共享储能容量配置与动态租赁模型[J].电力系统自动化,2021,45(19):24-32. DOI: 10.7500/AEPS20210518003.
SHUAI Xuanyue,WANG Xiuli,WU Xiong,et al.Shared Energy Storage Capacity Allocation and Dynamic Lease Model Considering Electricity-Heat Demand Response[J].Automation of Electric Power Systems,2021,45(19):24-32. DOI: 10.7500/AEPS20210518003.
为了科学合理地配置共享储能系统的参数、减少不必要的投资建设成本,提出一种计及电热综合需求响应的共享储能容量优化配置模型。首先,介绍了共享储能的运营模式,并分析了以往研究中共享储能模型的不足,进而提出共享储能动态容量租赁模型。其次,针对一类电-热综合能源微网进行建模。在此基础上,提出计及电热综合需求响应下共享储能容量配置的双层优化模型,其中上层目标函数为共享储能的收益最大,下层目标函数为多微网的总运行成本最小。进一步,给出模型的算法求解流程,并基于纳什议价方法对不同微网的利益进行分配。最后,在MATLAB平台上进行算例分析,验证所提模型的可行性与有效性。结果表明:所提容量租赁模型能为各微网分配最优容量,避免了以往模型中出现的用户侧功率交互现象,更贴合实际应用场景。
In order to scientifically and rationally configure the parameters of the shared energy storage system and reduce the unnecessary investment and construction costs
this paper proposes a model for the optimal allocation of shared energy storage capacity that takes into account the comprehensive demand response of electricity and heat. Firstly
the operation mode of shared energy storage is introduced
and the shortcomings of the shared energy storage model in previous studies are analyzed. And then a dynamic capacity lease model of the shared energy storage is proposed. Secondly
a type of electricity-heat integrated energy microgrid is modelling. On this basis
this paper proposes a bi-level optimization model for the allocation of shared energy storage capacity with consideration of the integrated electricity-heat demand response. The upper objective function is to maximize the income of shared energy storage
and the lower objective function is to minimize the total operation costs of multiple microgrids. Furthermore
an algorithm solution process of the model is given
and the profit of different microgrids are allocated based on the Nash bargaining method. Finally
a numerical example is analyzed on the MATLAB platform to verify the feasibility and effectiveness of the proposed model. The results show that the proposed capacity lease model can allocate optimal capacity for each microgrid
avoiding the user-side power interaction phenomenon in the previous model
which is more suitable for actual application scenarios.
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