On Modelling of Edge Datacentre Microgrid for Participation in Smart Energy InfrastructuresShow others and affiliations
2022 (English)In: IEEE Open Journal of the Industrial Electronics Society, ISSN 2644-1284, Vol. 3, p. 50-64Article in journal (Refereed) Published
Abstract [en]
Datacentres are becoming a sizable part of the energy system and are one of the biggest consumers of the energy grid. The so-called “Green Datacentre” is capable of not only consuming but also producing power, thus becoming an important kind of prosumers in the electric grid. Green datacentres consist of a microgrid with a backup uninterrupted power supply and renewable generation, e.g., using photovoltaic panels. As such, datacentres could realistically be important participants in demand/response applications. However, this requires reconsidering their currently rigid control and automation systems and the use of simulation models for online estimation of the control actions impact. This paper presents such a microgrid simulation model modelled after a real edge datacentre. A case study consumption scenario is presented for the purpose of validating the developed microgrid model against data traces collected from the green edge datacentre. Both simulation and real-time validation tests are performed to validate the accuracy of the datacentre model. Then the model is connected to the automation environment to be used for the online impact estimation and virtual commissioning purposes.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2022. Vol. 3, p. 50-64
Keywords [en]
Biological system modeling, Cooling, Data models, Load modeling, Microgrids, Renewable energy sources, Uninterruptible power systems, Automation, Biological systems, Electric power transmission networks, Online systems, Photovoltaic cells, Renewable energy resources, Datacenter, Energy grids, Energy infrastructures, Energy systems, Microgrid, Renewable energy source, Simulation model, Smart energies, Virtual reality
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:ri:diva-59104DOI: 10.1109/OJIES.2021.3138537Scopus ID: 2-s2.0-85122278310OAI: oai:DiVA.org:ri-59104DiVA, id: diva2:1651852
2022-04-132022-04-132023-05-25Bibliographically approved