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Open AccessEditor’s ChoiceArticle

Optimal Power Management Strategy for Energy Storage with Stochastic Loads

School of Systems Engineering, University of Reading, Whiteknights, Reading RG6 6AY, UK
School of Engineering, University of Portsmouth, Anglesea Road, Portsmouth PO1 3DJ, UK
Author to whom correspondence should be addressed.
Academic Editor: K. T. Chau
Energies 2016, 9(3), 175;
Received: 29 January 2016 / Revised: 29 February 2016 / Accepted: 3 March 2016 / Published: 9 March 2016
(This article belongs to the Special Issue Control of Energy Storage)
In this paper, a power management strategy (PMS) has been developed for the control of energy storage in a system subjected to loads of random duration. The PMS minimises the costs associated with the energy consumption of specific systems powered by a primary energy source and equipped with energy storage, under the assumption that the statistical distribution of load durations is known. By including the variability of the load in the cost function, it was possible to define the optimality criteria for the power flow of the storage. Numerical calculations have been performed obtaining the control strategies associated with the global minimum in energy costs, for a wide range of initial conditions of the system. The results of the calculations have been tested on a MATLAB/Simulink model of a rubber tyre gantry (RTG) crane equipped with a flywheel energy storage system (FESS) and subjected to a test cycle, which corresponds to the real operation of a crane in the Port of Felixstowe. The results of the model show increased energy savings and reduced peak power demand with respect to existing control strategies, indicating considerable potential savings for port operators in terms of energy and maintenance costs. View Full-Text
Keywords: energy storage; power management; optimization; stochastic loads; flywheel; RTG crane energy storage; power management; optimization; stochastic loads; flywheel; RTG crane
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Pietrosanti, S.; Holderbaum, W.; Becerra, V.M. Optimal Power Management Strategy for Energy Storage with Stochastic Loads. Energies 2016, 9, 175.

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