Workload and energy management of geo-distributed datacenters considering demand response programs

• Published in: Sustainable energy technologies and assessments 2023-02, Vol.55, p.102851, Article 102851
• Main Authors: Zhao, Mengmeng, Wang, Xiaoying, Mo, Junrong
• Format: Article
• Language: English
• Subjects: Demand response programs; Energy management; Geo-distributed datacenters; OPRS; Smart grid system; Workload management
• ISSN: 2213-1388
• DOI: 10.1016/j.seta.2022.102851

Datacenters usually consume huge energy and their workload can be adjusted dynamically, which makes them become good potential participants of demand response (DR) programs in the smart grid system. To overcome the drawbacks of centralization and enable fault-tolerance of a single datacenter, geographically distributed datacenters could be connected by a wide-area network to build up an integrated infrastructure, upon which multiple datacenter workloads could be balanced by taking advantage of space–time electricity price differences to reduce electricity costs. Particularly, when geo-distributed datacenters participate into DR programs, in order to obtain more economic benefits and to help achieve the load control objectives issued by the grid, it is necessary to consider a variety of external and internal conditions to optimize the workload and energy management strategy. Aiming at this problem, we propose an optimal power regulation scheduling method (OPRS) to simultaneously manage workload and energy consumption in geo-distributed datacenters, which comprehensively considers various factors including variation of electricity prices, operating costs, renewable energy constraints, and DR requirements. On the basis of the conventional computer room air conditioner system, additional devices are also incorporated into the architecture for datacenter cooling, including a solar-powered absorption cooling system and a chilled liquid storage system. Based on such framework, the OPRS method not only uses local renewable energy to reduce the energy consumption of the datacenter, but also can reduce the operating cost of the geo-distributed datacenters by leveraging the difference of electricity prices between time and space. Second, the method increases the frequency of uninterruptible power supply (UPS) usage and thus enhances the flexibility of datacenter power regulation. Furthermore, the OPRS method manages the workload by jointly considering task reassignment and delayed scheduling according to specific DR programs, thereby helping to maintain the stability of the regional power grid system. Experimental evaluation results show that, compared with other alternative strategies, the OPRS method can reduce the total operating cost by 19.52 %–66.96 %. Furthermore, the detailed analysis of the power regulation process illustrates that the OPRS method can also achieve better management of datacenter power consumption in the demand response stage.