Next Article in Journal
The Influence of Output Variability from Renewable Electricity Generation on Net Energy Calculations
Next Article in Special Issue
Implementation and Control of a Residential Electrothermal Microgrid Based on Renewable Energies, a Hybrid Storage System and Demand Side Management
Previous Article in Journal / Special Issue
A Load Fluctuation Characteristic Index and Its Application to Pilot Node Selection
Article Menu

Export Article

Open AccessArticle
Energies 2014, 7(1), 130-149;

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

Department of Electrical Engineering and Information Technology, University of Napoli Federico II, Naples 80125, Italy
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)
Full-Text   |   PDF [331 KB, uploaded 17 March 2015]


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. View Full-Text
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 3.0).

Share & Cite This Article

MDPI and ACS Style

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.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top