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1.华南理工大学电力学院,广东省广州市 510641
2.香港理工大学电机及电子工程学系,香港 999077
Received:24 April 2024,
Revised:2024-07-19,
Published Online:06 August 2024,
Published:25 September 2024
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文淅宇,朱继忠,李盛林等.基于时空协同的多数据中心虚拟电厂低碳经济调度策略[J].电力系统自动化,2024,48(18):56-65.
WEN Xiyu,ZHU Jizhong,LI Shenglin,et al.Low-carbon Economic Dispatch for Multiple Data Center Virtual Power Plant Based on Spatio-Temporal Collaboration[J].Automation of Electric Power Systems,2024,48(18):56-65.
文淅宇,朱继忠,李盛林等.基于时空协同的多数据中心虚拟电厂低碳经济调度策略[J].电力系统自动化,2024,48(18):56-65. DOI: 10.7500/AEPS20240424007.
WEN Xiyu,ZHU Jizhong,LI Shenglin,et al.Low-carbon Economic Dispatch for Multiple Data Center Virtual Power Plant Based on Spatio-Temporal Collaboration[J].Automation of Electric Power Systems,2024,48(18):56-65. DOI: 10.7500/AEPS20240424007.
数据中心因其负荷具有时空双尺度可调特性,可被视为庞大且极具潜力的新型需求响应资源,是虚拟电厂的行业案例。然而,在以往数据中心经济调度的研究中,环境效益和租户的计算体验未得到充分考虑,需求响应后的执行效果评估多被忽略。对此,提出基于时空协同的多数据中心低碳经济调度策略。首先,对数据中心工作负载的时空可调特性进行精细化建模,明晰需求响应和可再生能源消纳的具体实现路径。其次,量化租户对需求响应的满意度以保证用户侧服务体验,并在目标函数中引入碳交易成本以引导源侧减碳。最后,在中国广东电力市场日前邀约需求响应模式下,使用典型数据中心数据进行算例分析。仿真结果表明,所提方案能够有效激发数据中心灵活资源的时空调节潜力,在实现整体经济性提升的同时兼顾环境效益和租户满意度。
The data center
due to its adjustable load at both spatial and temporal scales
can be regarded as a huge and highly potential new demand response resource
and is an industrial case of virtual power plants. However
in existing studies of data center economic dispatch
environmental benefits and computing experience for renters have not been fully considered
and the evaluation of execution effectiveness after demand response has been mostly neglected. Thus
a low-carbon economic dispatch scheme for multiple data centers based on spatio-temporal collaboration is proposed. Firstly
the spatio-temporal adjustable characteristics of data center workloads are modeled to clarify the specific realization path of demand response and renewable energy accommodation. Secondly
the renter satisfaction for demand response is quantified to ensure the user-side service experience. The carbon trading cost is introduced into the objective function to guide the source side in reducing carbon emissions. Finally
the case study is conducted using typical data of data center in the day-ahead invitation demand response mode in Guangdong electricity market
China. Simulation results show that the proposed scheme can effectively stimulate the spatio-temporal regulation potential for flexible resources of data centers and achieve overall economic improvement while considering environmental benefits and renter satisfaction.
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