LAPSE:2018.0909
Published Article
LAPSE:2018.0909
Optimal Power Management Strategy for Energy Storage with Stochastic Loads
November 27, 2018
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.
Keywords
Energy Storage, flywheel, Optimization, power management, RTG crane, stochastic loads
Suggested Citation
Pietrosanti S, Holderbaum W, Becerra VM. Optimal Power Management Strategy for Energy Storage with Stochastic Loads. (2018). LAPSE:2018.0909
Author Affiliations
Pietrosanti S: School of Systems Engineering, University of Reading, Whiteknights, Reading RG6 6AY, UK [ORCID]
Holderbaum W: School of Systems Engineering, University of Reading, Whiteknights, Reading RG6 6AY, UK [ORCID]
Becerra VM: School of Engineering, University of Portsmouth, Anglesea Road, Portsmouth PO1 3DJ, UK
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Journal Name
Energies
Volume
9
Issue
3
Article Number
E175
Year
2016
Publication Date
2016-03-09
Published Version
ISSN
1996-1073
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Original Submission
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PII: en9030175, Publication Type: Journal Article
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LAPSE:2018.0909
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doi:10.3390/en9030175
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Nov 27, 2018
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CC BY 4.0
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Nov 27, 2018
 
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Original Submitter
Calvin Tsay
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