A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions
<p>This article presents a comparative analysis of the latest swarm-based optimization approaches under partial shading conditions (PSCs) for maximum power point tracking (MPPT) in photovoltaic (PV) systems. The swarm-based MPPT algorithms are stochastic meta-heuristic approaches that have bec...
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| مؤلفون آخرون: | , , , , |
| منشور في: |
2022
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| الموضوعات: | |
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| _version_ | 1864513548313427968 |
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| author | Muhammad Shahid Wasim (16883984) |
| author2 | Muhammad Amjad (6613673) Salman Habib (16524330) Muhammad Abbas Abbasi (12883826) Abdul Rauf Bhatti (12463263) S.M. Muyeen (15746160) |
| author2_role | author author author author author |
| author_facet | Muhammad Shahid Wasim (16883984) Muhammad Amjad (6613673) Salman Habib (16524330) Muhammad Abbas Abbasi (12883826) Abdul Rauf Bhatti (12463263) S.M. Muyeen (15746160) |
| author_role | author |
| dc.creator.none.fl_str_mv | Muhammad Shahid Wasim (16883984) Muhammad Amjad (6613673) Salman Habib (16524330) Muhammad Abbas Abbasi (12883826) Abdul Rauf Bhatti (12463263) S.M. Muyeen (15746160) |
| dc.date.none.fl_str_mv | 2022-04-08T09:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1016/j.egyr.2022.03.175 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/A_critical_review_and_performance_comparisons_of_swarm-based_optimization_algorithms_in_maximum_power_point_tracking_of_photovoltaic_systems_under_partial_shading_conditions/29046227 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Electrical engineering Electronics, sensors and digital hardware Information and computing sciences Artificial intelligence Swarm optimization Global maximum power point Partial shading Photovoltaic |
| dc.title.none.fl_str_mv | A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p>This article presents a comparative analysis of the latest swarm-based optimization approaches under partial shading conditions (PSCs) for maximum power point tracking (MPPT) in photovoltaic (PV) systems. The swarm-based MPPT algorithms are stochastic meta-heuristic approaches that have become very popular recently in various applications owing to the drawbacks of conventional MPPT algorithms under different operating conditions. A comprehensive review of the recent research on these algorithms is carried out particularly focusing on the PSCs. The advantages, disadvantages, applications, computational efficiency, and stability of these algorithms are critically surveyed in detail. Moreover, to analyze the comparative performance of the swarm-based algorithms, a special case study is conducted in the MATLAB/Simulink environment for a solar-powered DC load with a boost converter. The performance of seven swarm-based MPPT techniques is evaluated in this case study in terms of their settling time, convergence speed, overshoot, and efficiency under different levels of PSCs. The statistical analysis for 30 simulation runs shows that under heavier shading conditions, the grasshopper optimization algorithm (GOA) and salp swarm algorithm (SSA) outperform other swarm-based MPPT algorithms. It is envisaged that this work will be a one-stop source of guidance for researchers working in the field of MPP optimization under PSCs.</p><h2>Other Information</h2> <p> Published in: Energy Reports<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.egyr.2022.03.175" target="_blank">https://dx.doi.org/10.1016/j.egyr.2022.03.175</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_6f34067aab3239deb22156c8c4f0f325 |
| identifier_str_mv | 10.1016/j.egyr.2022.03.175 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/29046227 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditionsMuhammad Shahid Wasim (16883984)Muhammad Amjad (6613673)Salman Habib (16524330)Muhammad Abbas Abbasi (12883826)Abdul Rauf Bhatti (12463263)S.M. Muyeen (15746160)EngineeringElectrical engineeringElectronics, sensors and digital hardwareInformation and computing sciencesArtificial intelligenceSwarm optimizationGlobal maximum power pointPartial shadingPhotovoltaic<p>This article presents a comparative analysis of the latest swarm-based optimization approaches under partial shading conditions (PSCs) for maximum power point tracking (MPPT) in photovoltaic (PV) systems. The swarm-based MPPT algorithms are stochastic meta-heuristic approaches that have become very popular recently in various applications owing to the drawbacks of conventional MPPT algorithms under different operating conditions. A comprehensive review of the recent research on these algorithms is carried out particularly focusing on the PSCs. The advantages, disadvantages, applications, computational efficiency, and stability of these algorithms are critically surveyed in detail. Moreover, to analyze the comparative performance of the swarm-based algorithms, a special case study is conducted in the MATLAB/Simulink environment for a solar-powered DC load with a boost converter. The performance of seven swarm-based MPPT techniques is evaluated in this case study in terms of their settling time, convergence speed, overshoot, and efficiency under different levels of PSCs. The statistical analysis for 30 simulation runs shows that under heavier shading conditions, the grasshopper optimization algorithm (GOA) and salp swarm algorithm (SSA) outperform other swarm-based MPPT algorithms. It is envisaged that this work will be a one-stop source of guidance for researchers working in the field of MPP optimization under PSCs.</p><h2>Other Information</h2> <p> Published in: Energy Reports<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.egyr.2022.03.175" target="_blank">https://dx.doi.org/10.1016/j.egyr.2022.03.175</a></p>2022-04-08T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.egyr.2022.03.175https://figshare.com/articles/journal_contribution/A_critical_review_and_performance_comparisons_of_swarm-based_optimization_algorithms_in_maximum_power_point_tracking_of_photovoltaic_systems_under_partial_shading_conditions/29046227CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/290462272022-04-08T09:00:00Z |
| spellingShingle | A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions Muhammad Shahid Wasim (16883984) Engineering Electrical engineering Electronics, sensors and digital hardware Information and computing sciences Artificial intelligence Swarm optimization Global maximum power point Partial shading Photovoltaic |
| status_str | publishedVersion |
| title | A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions |
| title_full | A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions |
| title_fullStr | A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions |
| title_full_unstemmed | A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions |
| title_short | A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions |
| title_sort | A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions |
| topic | Engineering Electrical engineering Electronics, sensors and digital hardware Information and computing sciences Artificial intelligence Swarm optimization Global maximum power point Partial shading Photovoltaic |