Ramadhani, Farah and Hussain, Mohammad Azlan and Mokhlis, Hazlie and Illias, Hazlee Azil (2021) Two-stage fuzzy-logic-based for optimal energy management strategy for SOFC/PV/TEG hybrid polygeneration system with electric charging and hydrogen fueling stations. Journal of Renewable and Sustainable Energy, 13 (2). ISSN 1941-7012, DOI https://doi.org/10.1063/5.0010832.
Full text not available from this repository.Abstract
Integration between supplies for stationary power and vehicles is potentially useful for increasing the efficiency and the reliability of energy generation systems. Solid oxide fuel cell is one matured technology, which is suitable for a polygeneration system and provides an integration of supply for stationary power and vehicles. However, a combination of solid oxide fuel cell with photovoltaic thermal and thermoelectric generation increases the complexity of a polygeneration system. The system needs a management strategy for dispatching the energies produced. Therefore, in this work, a fuzzy energy management strategy was applied for this polygeneration system by considering two different configurations: an off-grid system with electric vehicle supply and an on-grid system with hydrogen vehicle supply. A two-stage fuzzy energy management strategy considering optimization and management of multi-parameters of the polygeneration components was considered. The evaluation of the optimum fuzzy was analyzed based on energy, economic, and environmental criteria. From the results obtained, the optimal strategy increased the reliability, energy, and system cost savings by 22.05%, 22.4%, and 32.58%, respectively. Moreover, the optimum management reduced the power loss of the polygeneration system by about 48.82%, which was achieved by the configuration with electric vehicles supply and off-grid connection.
| Item Type: | Article |
|---|---|
| Funders: | Sumatra Institute of Technology [GBU45] |
| Uncontrolled Keywords: | Transient simulation; Demand response; Optimal design; Cell; Heat; Power; Optimization; Performance; Storage; Intelligence |
| Subjects: | Q Science > QC Physics T Technology > TP Chemical technology |
| Divisions: | Faculty of Engineering > Department of Chemical Engineering Faculty of Engineering > Department of Electrical Engineering Faculty of Science > Department of Physics |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 18 Apr 2022 00:42 |
| Last Modified: | 18 Apr 2022 00:42 |
| URI: | http://eprints.um.edu.my/id/eprint/26736 |
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