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1.华北电力大学电气与电子工程学院,北京市102206
2.需求侧多能互补优化与供需互动技术北京市重点实验室(中国电力科学研究院有限公司),北京市 100085
祁兵(1965—),男,硕士,教授,博士生导师,主要研究方向:电力节能、需求响应相关技术。E-mail:bellqi@sina.com
曹望璋(1993—),男,博士研究生,主要研究方向:需求侧管理相关技术。E-mail:120192101048@ncep u.edu.cn
李彬(1983—),男,通信作者,博士,副教授,主要研究方向:电力通信、电气信息技术。E-mail:direfish@163.com
收稿:2021-11-14,
修回:2022-04-08,
网络出版:2022-07-19,
纸质出版:2022-11-10
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祁兵,曹望璋,李彬等.计及负载特征及响应特性的多数据中心双层优化模型[J].电力系统自动化,2022,46(21):30-41.
QI Bing,CAO Wangzhang,LI Bin,et al.Bi-level Optimization Model of Multiple Data Centers Considering Workload Features and Response Characteristics[J].Automation of Electric Power Systems,2022,46(21):30-41.
祁兵,曹望璋,李彬等.计及负载特征及响应特性的多数据中心双层优化模型[J].电力系统自动化,2022,46(21):30-41. DOI: 10.7500/AEPS20211114001.
QI Bing,CAO Wangzhang,LI Bin,et al.Bi-level Optimization Model of Multiple Data Centers Considering Workload Features and Response Characteristics[J].Automation of Electric Power Systems,2022,46(21):30-41. DOI: 10.7500/AEPS20211114001.
多个数据中心可通过工作负载(计算需求)的调节利用不同地域微网的资源,从而达到经济运行的目的。然而,负载的调节需要考虑IT用户的影响,在以往研究中IT用户多被忽略,且并未以合适的激励引导其参与数据中心的优化。对此,提出一种计及负载特征及IT用户响应特性的多数据中心双层优化模型。首先,文中从可转移和可削减两个特征对数据中心负载进行分类。其次,基于主从博弈建立双层优化,下层模型考虑负载特征及IT用户响应特性,目标为IT用户的效益。上层模型考虑微网资源的约束,目标为数据中心的整体成本。最后,通过启发式算法和线性规划相结合的方法求解出数据中心的运行方案。仿真结果表明,所提的优化模型考虑了负载的响应特性,能以激励引导IT用户参与数据中心的负荷优化,在微网环境下降低多个数据中心的整体成本。
Multiple data centers can utilize microgrid resources in different regions through the adjustment of workload (i.e.
calculation demand)
thereby achieving the purpose of economic operation. However
the adjustment of workload needs to consider the effect of IT users. In existing studies
IT users are almost neglected
and they are not motivated with appropriate incentives to participate in the optimization of data centers. Thus
a bi-level optimization model of multiple data centers considering features of workload and response characteristics of IT users is proposed. Firstly
this paper classifies data center workloads into two classes: transferable workload and reducible workload. Secondly
a bi-level optimization model based on the Stackelberg’s game theory is established. The lower-level model considers the features of workload and response characteristics of IT users
where the optimization goal is the benefit of IT users. The upper-level model considers the constraints of microgrids
and the goal is the total cost of the data centers. Finally
the operation plans of the data centers are optimized by the combination of heuristic algorithm and linear optimization technique. The simulation results show that the proposed optimization model takes into account the response characteristics of IT users while motivating them to participate in the load optimization of data centers. This model also reduces the total cost of data centers in the microgrid environment.
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