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强电磁工程与新技术国家重点实验室(华中科技大学),湖北省武汉市 430074
吴云芸(1997—),女,硕士研究生,主要研究方向:数据中心能量管理、储能规划、输电网规划等。E-mail:wuyunyun_scu@163.com
方家琨(1985—),男,博士,教授,博士生导师,主要研究方向:电力制氢制气、综合能源传输、多物理场偏微分方程约束的优化理论等。E-mail:jfa@hust.edu.cn
艾小猛(1986—),男,通信作者,博士,副教授,博士生导师,主要研究方向:新能源特性分析与建模、新能源并网优化规划与运行、储能规划与优化、负荷侧管理、综合能源市场等。E-mail:xiaomengai@hust.edu.cn
收稿:2022-07-25,
修回:2022-10-12,
网络出版:2022-12-12,
纸质出版:2023-04-10
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吴云芸,方家琨,艾小猛等.计及需求响应的数据中心联盟共享储能规划[J].电力系统自动化,2023,47(7):42-50.
WU Yunyun,FANG Jiakun,AI Xiaomeng,et al.Shared Energy Storage Planning for Data Center Alliance Considering Demand Response[J].Automation of Electric Power Systems,2023,47(7):42-50.
吴云芸,方家琨,艾小猛等.计及需求响应的数据中心联盟共享储能规划[J].电力系统自动化,2023,47(7):42-50. DOI: 10.7500/AEPS20220725003.
WU Yunyun,FANG Jiakun,AI Xiaomeng,et al.Shared Energy Storage Planning for Data Center Alliance Considering Demand Response[J].Automation of Electric Power Systems,2023,47(7):42-50. DOI: 10.7500/AEPS20220725003.
为避免数据中心单独配置储能出现储能利用率低、经济效益差等问题,提出一种计及需求响应的数据中心联盟共享储能规划方法,能够考虑不同场景下各数据中心对储能需求的差异性和互补性,在降低储能投资成本的同时发挥储能最大效能。首先,提出了数据中心联盟共享储能运营模式,包括不同场景间共享储能使用容量分配、成本分摊和基于纳什议价的利益分配方法,保障联盟内各个体的利益。其次,考虑批处理负荷、机房空调参与需求响应,建立数据中心房间级能量管理模型,结合共享储能配置约束,以联盟集体利益最大化为目标,构建计及需求响应的数据中心联盟共享储能规划模型。为使得规划结果能够应对多种运行场景,提出共享储能规划场景集选取方法。最后,设置了4个对比算例验证所提方法的有效性。
The separate configuration of energy storage in the data centers may lead to low utilization of energy storage and poor economic benefits. Given the above background
a shared energy storage planning approach for the data center alliance considering demand response is proposed
which can take into account the difference and complementarity of energy storage requirements of each data center in different operation scenarios
and maximize the energy storage efficiency while reducing investment cost. Firstly
an operation mode of shared energy storage for the data center alliance is proposed
including the sharing of energy storage capacity
the allocation of investment cost and the distribution method of profit based on Nash bargaining among different scenarios
to guarantee the interest of the alliance members. Secondly
an energy management model at the level of data center room is established considering the participation of batch processing loads and computer room air conditioners in demand response. Next
combined with configuration constraints of shared energy storage
a shared energy storage planning model for the data center alliance considering demand response is established with the goal of maximizing the collective interests of the alliance. A selection method of scenario set for shared energy storage planning is proposed to enable the planning results to cope with a variety of operation scenarios. Finally
four comparative cases are set to verify the effectiveness of the proposed method.
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