含有光伏集群和储能型不间断电源集群的数据中心优化运行OACSTPCD
Optimal operation of Internet Data Center with PV and energy storage type of UPS clusters
数据中心存在大量不间断电源,众多不间断电源存在资源闲置浪费,使用率低以及存在数据中心如何利用众多不间断电源实现最优经济调度等问题.在此背景下,以绿色数据中心为研究对象,基于EUPS提出一种绿色数据中心三层优化框架.首先,在EUPS个体层,提出一种基于共享机制小生境理念的EUPS集群分类方法,实现EUPS集群的聚合管理;然后,在聚合层层提出EUPS聚合层的优化调度模型以及备电功能下的可调度充放电功率模型,使得绿色数据中心在保证备电功能的同时实现聚合层的优化调度,提升可再生能源利用率和供电充裕性;在绿色数据中心经济调度层,建立包含多目标多约束的数据中心最小综合成本模型,采用基于量子行为粒子群优化算法对模型进行求解.最后,开展三个场景的研究以及聚合层容量对绿色数据中心最优经济调度的影响研究,验证了本文所提三层优化框架和所提模型的经济性和有效性.
With the development of green data centers,a large number of Uninterruptible Power Supply(UPS)resources in Internet Data Center(IDC)are becoming idle assets owing to their low utilization rate.The revitalization of these idle UPS resources is an urgent problem that must be addressed.Based on the energy storage type of the UPS(EUPS)and using renewable sources,a solution for IDCs is proposed in this study.Subsequently,an EUPS cluster classification method based on the concept of shared mechanism niche(CSMN)was proposed to effectively solve the EUPS control problem.Accordingly,the classified EUPS aggregation unit was used to determine the optimal operation of the IDC.An IDC cost minimization optimization model was established,and the Quantum Particle Swarm Optimization(QPSO)algorithm was adopted.Finally,the economy and effectiveness of the three-tier optimization framework and model were verified through three case studies.
陈满;赵宇鑫;李毓烜;彭鹏;唐西胜
优化框架储能型不间断电源基于小生境的集群聚合方法量子行为粒子群优化算法
Three-tier optimization frameworkEnergy storage type of the UPSEUPS cluster classification methodQuantum Particle Swarm Optimization
《全球能源互联网（英文）》 2024 (001)
61-70 / 10
This work was supported by the Key Technology Projects of the China Southern Power Grid Corporation(STKJXM20200059)and the Key Support Project of the Joint Fund of the National Natural Science Foundation of China(U22B20123).
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