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Energies 2014, 7(1), 130-149; doi:10.3390/en7010130

Optimal Sizing of Battery Storage Systems for Industrial Applications when Uncertainties Exist

1,* , 2
1 Department of Electrical Engineering and Information Technology, University of Napoli Federico II, Naples 80125, Italy 2 Department of Electrical Engineering and Information, University of Cassino and Southern Lazio, Cassino 03043, Italy
* Author to whom correspondence should be addressed.
Received: 21 October 2013 / Revised: 11 December 2013 / Accepted: 27 December 2013 / Published: 3 January 2014
(This article belongs to the Special Issue Smart Grids: The Electrical Power Network and Communication System)
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Demand response (DR) can be very useful for an industrial facility, since it allows noticeable reductions in the electricity bill due to the significant value of energy demand. Although most industrial processes have stringent constraints in terms of hourly active power, DR only becomes attractive when performed with the contemporaneous use of battery energy storage systems (BESSs). When this option is used, an optimal sizing of BESSs is desirable, because the investment costs can be significant. This paper deals with the optimal sizing of a BESS installed in an industrial facility to reduce electricity costs. A four-step procedure, based on Decision Theory, was used to obtain a good solution for the sizing problem, even when facing uncertainties; in fact, we think that the sizing procedure must properly take into account the unavoidable uncertainties introduced by the cost of electricity and the load demands of industrial facilities. Three approaches provided by Decision Theory were applied, and they were based on: (1) the minimization of expected cost; (2) the regret felt by the sizing engineer; and (3) a mix of (1) and (2). The numerical applications performed on an actual industrial facility provided evidence of the effectiveness of the proposed procedure.
Keywords: smart grid; demand response; storage systems; sizing; decision theory smart grid; demand response; storage systems; sizing; decision theory
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Carpinelli, G.; di Fazio, A.R.; Khormali, S.; Mottola, F. Optimal Sizing of Battery Storage Systems for Industrial Applications when Uncertainties Exist. Energies 2014, 7, 130-149.

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