Optimal Power Management Strategy for Energy Storage with Stochastic Loads
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-03-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/9/3/175 |
| _version_ | 1818011691448795136 |
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| author | Stefano Pietrosanti William Holderbaum Victor M. Becerra |
| author_facet | Stefano Pietrosanti William Holderbaum Victor M. Becerra |
| author_sort | Stefano Pietrosanti |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T06:10:49Z |
| format | Article |
| id | doaj.art-e8f40678360346299486e152edd43ec3 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-14T06:10:49Z |
| publishDate | 2016-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-e8f40678360346299486e152edd43ec32022-12-22T02:08:22ZengMDPI AGEnergies1996-10732016-03-019317510.3390/en9030175en9030175Optimal Power Management Strategy for Energy Storage with Stochastic LoadsStefano Pietrosanti0William Holderbaum1Victor M. Becerra2School of Systems Engineering, University of Reading, Whiteknights, Reading RG6 6AY, UKSchool of Systems Engineering, University of Reading, Whiteknights, Reading RG6 6AY, UKSchool of Engineering, University of Portsmouth, Anglesea Road, Portsmouth PO1 3DJ, UKIn 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.http://www.mdpi.com/1996-1073/9/3/175energy storagepower managementoptimizationstochastic loadsflywheelRTG crane |
| spellingShingle | Stefano Pietrosanti William Holderbaum Victor M. Becerra Optimal Power Management Strategy for Energy Storage with Stochastic Loads Energies energy storage power management optimization stochastic loads flywheel RTG crane |
| title | Optimal Power Management Strategy for Energy Storage with Stochastic Loads |
| title_full | Optimal Power Management Strategy for Energy Storage with Stochastic Loads |
| title_fullStr | Optimal Power Management Strategy for Energy Storage with Stochastic Loads |
| title_full_unstemmed | Optimal Power Management Strategy for Energy Storage with Stochastic Loads |
| title_short | Optimal Power Management Strategy for Energy Storage with Stochastic Loads |
| title_sort | optimal power management strategy for energy storage with stochastic loads |
| topic | energy storage power management optimization stochastic loads flywheel RTG crane |
| url | http://www.mdpi.com/1996-1073/9/3/175 |
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