A load control method for small data centers participating in demand response programs |
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| Affiliation: | 1. Department of Electrical Engineering, Tatung University, No. 40, Sec. 3, Zhongshan N. Rd., Taipei 104, Taiwan;2. Graduate Institute of Communication Engineering, Tatung University, No. 40, Sec. 3, Zhongshan N. Rd., Taipei 104, Taiwan;3. Smart Network System Institute, Institute for Information Industry, 7F, No. 133, Sec. 4, Minsheng E. Rd., Taipei 105, Taiwan;1. Centre of New Energy Systems, Department of Electrical, Electronic and Computer Engineering, University of Pretoria, South Africa;2. Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, United Kingdom;2. RWE Deutschland AG, Kruppstraße 5, 45128 Essen, Germany;1. DEIB, Politecnico di Milano, via Ponzio 34/5, 20133 Milano, Italy;2. LRI, Paris-Sud University, Bat. 650, rue Noetzlin, 91405 Orsay, France;3. IUF, Institut Universitaire de France, France;4. LIPADE, Paris Descartes University, 45 rue des Saints Peres, 75270 Paris, France |
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| Abstract: | This paper presents a load control method for small data centers, which are rarely studied although they account for more than 50% of all data centers. The method utilizes the data network and the electrical network to control power usage for participation in demand response (DR) programs, which are regarded as the killer applications of the emerging smart grid (SG). Traditional data center power management often directly manipulates energy usage, which may be ineffective or impractical for small data centers due to their limited resources. Both the SG and the data centers are considered to be the cyber-physical systems (CPSs). This article proposes an approach that performs the data center DR load management through the cyberspaces of the SG and the targeted data center. The proposed method instructs the workload dispatcher to select the best-suited algorithm when a DR event is issued. Additionally, this method also adjusts the temperature set-points of the air conditioners. The simulation result shows that this approach can achieve a 30% power reduction for DR. |
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| Keywords: | Smart grid Smart meter Demand response Data center Cyber-physical system |
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