Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system
The paper presents a new multiple scenario multi-objective salp swarm optimization (MS-MOSS) algorithm to optimally size a standalone PV system. An accurate estimation of the number of PV modules and storage battery is crucial as it affects the system reliability and cost. Three scenarios have been...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2020
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| Online Access: | http://psasir.upm.edu.my/id/eprint/86860/ http://psasir.upm.edu.my/id/eprint/86860/1/Multiple%20scenarios%20multi.pdf |
| _version_ | 1848860306213699584 |
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| author | Ridha, Hussein Mohammed Gomes, Chandima Hizam, Hashim Mirjalili, Seyedali |
| author_facet | Ridha, Hussein Mohammed Gomes, Chandima Hizam, Hashim Mirjalili, Seyedali |
| author_sort | Ridha, Hussein Mohammed |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The paper presents a new multiple scenario multi-objective salp swarm optimization (MS-MOSS) algorithm to optimally size a standalone PV system. An accurate estimation of the number of PV modules and storage battery is crucial as it affects the system reliability and cost. Three scenarios have been presented focusing on Pareto optimal solutions by minimizing two conflicting objectives. Loss of load probability (LLP) and life-cycle cost (LLC) are considered to obtain the Pareto front. The iterative method is employed for validation of the superiority results of the proposed MS-MOSS algorithm. The results show that the scenarios are able to find Pareto optimal configuration at a high level of accuracy and at a very low cost. The proposed three scenarios are faster than iterative approach approximately by 158, 194.2, and 141.6 times, respectively. The third scenario outperforms other scenarios in terms of coverage and convergence of the distribution of solution to the Pareto front. As a conclusion, The MS-MOSS algorithm is found to be very effective in sizing of SAPV system. |
| first_indexed | 2025-11-15T12:43:08Z |
| format | Article |
| id | upm-86860 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T12:43:08Z |
| publishDate | 2020 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-868602021-11-22T02:42:39Z http://psasir.upm.edu.my/id/eprint/86860/ Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system Ridha, Hussein Mohammed Gomes, Chandima Hizam, Hashim Mirjalili, Seyedali The paper presents a new multiple scenario multi-objective salp swarm optimization (MS-MOSS) algorithm to optimally size a standalone PV system. An accurate estimation of the number of PV modules and storage battery is crucial as it affects the system reliability and cost. Three scenarios have been presented focusing on Pareto optimal solutions by minimizing two conflicting objectives. Loss of load probability (LLP) and life-cycle cost (LLC) are considered to obtain the Pareto front. The iterative method is employed for validation of the superiority results of the proposed MS-MOSS algorithm. The results show that the scenarios are able to find Pareto optimal configuration at a high level of accuracy and at a very low cost. The proposed three scenarios are faster than iterative approach approximately by 158, 194.2, and 141.6 times, respectively. The third scenario outperforms other scenarios in terms of coverage and convergence of the distribution of solution to the Pareto front. As a conclusion, The MS-MOSS algorithm is found to be very effective in sizing of SAPV system. Elsevier 2020-06 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/86860/1/Multiple%20scenarios%20multi.pdf Ridha, Hussein Mohammed and Gomes, Chandima and Hizam, Hashim and Mirjalili, Seyedali (2020) Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system. Renewable Energy, 153. pp. 1330-1345. ISSN 0960-1481; ESSN: 1879-0682 https://www.sciencedirect.com/science/article/abs/pii/S0960148120302020 10.1016/j.renene.2020.02.016 |
| spellingShingle | Ridha, Hussein Mohammed Gomes, Chandima Hizam, Hashim Mirjalili, Seyedali Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system |
| title | Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system |
| title_full | Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system |
| title_fullStr | Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system |
| title_full_unstemmed | Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system |
| title_short | Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system |
| title_sort | multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system |
| url | http://psasir.upm.edu.my/id/eprint/86860/ http://psasir.upm.edu.my/id/eprint/86860/ http://psasir.upm.edu.my/id/eprint/86860/ http://psasir.upm.edu.my/id/eprint/86860/1/Multiple%20scenarios%20multi.pdf |