Abstract
Data centers are one of the biggest energy consumers in the ICT sector. Their cooling system accounts for almost half of the overall data center energy demand. Thus, the flexibility in shifting energy demand of the cooling systems in data centers could be a great asset for data center operators. The amount of flexibility and how it can be maximized are important yet open problems, due to the several stochastic processes involved. In this paper, we propose a novel methodology that allows data center operators to compute the flexibility of the cooling system by modeling it as an Energy Storage System (ESS). To enable such a mapping, the temperature set-points of the cooling systems must be expressed by a recursive formulation. To this end, based on thermodynamic concepts, in this paper we derive a recursive formulation for the temperature of the cooling systems and verify it empirically through a real-world data set. We then sketch (as our future work) how this mapping can be used to compute the flexibility of the cooling systems which can be efficiently leveraged during demand-response periods.
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Notes
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Please note that we use t as the time notation in a continuous-time model and k in a discrete-time model.
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Basmadjian, R., Ghiassi-Farrokhfal, Y., Vishwanath, A. (2018). Hidden Storage in Data Centers: Gaining Flexibility Through Cooling Systems. In: German, R., Hielscher, KS., Krieger, U. (eds) Measurement, Modelling and Evaluation of Computing Systems. MMB 2018. Lecture Notes in Computer Science(), vol 10740. Springer, Cham. https://doi.org/10.1007/978-3-319-74947-1_5
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DOI: https://doi.org/10.1007/978-3-319-74947-1_5
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