Optimal coordinated management of integrated electricity-heat-computation systems in geographically distributed data centers
Lingfang Yang,
Xianqing Chen,
Xiaolun Fang and
Qiang Yang
Energy, 2025, vol. 332, issue C
Abstract:
The rapid development of the data center (DC) industry has made it increasingly important to prioritize energy efficiency in DCs. This paper studies the cooperative dispatch of workload and energy supply equipment for geo-distributed green DCs, in which various forms of energy flow, i.e. electricity flow, heat flow and data flow, are considered. An integrated electricity-heat-computation system model is constructed, which considers diverse flexible operating characteristics of DCs, including waste heat recovery systems (WHRSs), the thermal inertia of indoor air, different types of energy supply equipment, and the spatial-temporal flexibility of computational workloads. To achieve significant environmental and economic performance, a model predictive control (MPC) based two-stage coordinated scheduling strategy is proposed, which consists of a day-ahead scheduling stage and an intra-day online dispatch stage. During the day-ahead stage, the pre-scheduling plan is obtained, while in the intra-day stage, the MPC online rolling optimization method is applied to reduce the negative impact caused by operational uncertainties of computational workloads and renewable energy sources (RESs). The proposed solution is extensively assessed through a case study, and the numerical results confirm its effectiveness and benefits in terms of economic cost, RES accommodation, CO2 emission mitigation and power usage effectiveness (PUE).
Keywords: Data center; Real-time workload; Delay-tolerant workload; Waste heat recovery; Model predictive control; Renewable energy source (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544225028749
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:332:y:2025:i:c:s0360544225028749
DOI: 10.1016/j.energy.2025.137232
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().