Processing speed in seconds.
<div><p>Accurately simulating photovoltaic (PV) modules requires precise parameter extraction, a complex task due to the nonlinear nature of these systems. This study introduces the Mother Tree Optimization with Climate Change (MTO-CL) algorithm to address this challenge by enhancing par...
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2025
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| _version_ | 1852022315248779264 |
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| author | Mouncef El Marghichi (17328361) |
| author2 | Abdelilah Hilali (20485529) Abdelkhalek Chellakhi (20827008) Mohamed Makhad (20485535) Azeddine Loulijat (17328370) Najib El Ouanjli (13825678) Abdelhak Essounaini (20827011) Vikash Kumar Saini (20827014) Ameena Saad Al-Sumaiti (12659860) |
| author2_role | author author author author author author author author |
| author_facet | Mouncef El Marghichi (17328361) Abdelilah Hilali (20485529) Abdelkhalek Chellakhi (20827008) Mohamed Makhad (20485535) Azeddine Loulijat (17328370) Najib El Ouanjli (13825678) Abdelhak Essounaini (20827011) Vikash Kumar Saini (20827014) Ameena Saad Al-Sumaiti (12659860) |
| author_role | author |
| dc.creator.none.fl_str_mv | Mouncef El Marghichi (17328361) Abdelilah Hilali (20485529) Abdelkhalek Chellakhi (20827008) Mohamed Makhad (20485535) Azeddine Loulijat (17328370) Najib El Ouanjli (13825678) Abdelhak Essounaini (20827011) Vikash Kumar Saini (20827014) Ameena Saad Al-Sumaiti (12659860) |
| dc.date.none.fl_str_mv | 2025-03-04T18:33:34Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0318575.t005 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Processing_speed_in_seconds_/28534965 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biotechnology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified various solar modules seven alternative methods mother tree optimization mean squared error complex task due across different irradiances 7 &# 215 10 ^&# 8722 remaining solutions ). pv system modeling results demonstrate mto incorporating climate change enhancing parameter estimation cl &# 8217 2 &# 215 diode photovoltaic systems solar pv three parameter estimation climate change suboptimal solutions diode model study introduces slight adjustments robust tool refreshing 20 novel approach nonlinear nature inspired adaptations including st40 exploitation allows electrical parameters accurate extraction 86 mw 40 mw |
| dc.title.none.fl_str_mv | Processing speed in seconds. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <div><p>Accurately simulating photovoltaic (PV) modules requires precise parameter extraction, a complex task due to the nonlinear nature of these systems. This study introduces the Mother Tree Optimization with Climate Change (MTO-CL) algorithm to address this challenge by enhancing parameter estimation for a solar PV three-diode model. MTO-CL improves optimization performance by incorporating climate change-inspired adaptations, which affect two key phases: elimination (refreshing 20% of suboptimal solutions) and distortion (slight adjustments to 80% of remaining solutions). This balance between exploration and exploitation allows the algorithm to dynamically and effectively identify optimal parameters. Compared to seven alternative methods, MTO-CL shows superior performance in parameter estimation for various solar modules, including ST40 and SM55, across different irradiances and temperatures. It achieves exceptionally low Root Mean Square Error (RMSE) values from 0.0025A to 0.0165A and Mean Squared Error (MSE) values between 6.2 × 10^−6 and 2.7 × 10^−4, while also significantly minimizing power errors, ranging from 22.86 mW to 239.40 mW. These results demonstrate MTO-CL’s effectiveness in improving the accuracy and reliability of PV system modeling, offering a robust tool for enhanced solar energy applications.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_f8f41dbbbab26e4c2e4c2eb334b9a47b |
| identifier_str_mv | 10.1371/journal.pone.0318575.t005 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28534965 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Processing speed in seconds.Mouncef El Marghichi (17328361)Abdelilah Hilali (20485529)Abdelkhalek Chellakhi (20827008)Mohamed Makhad (20485535)Azeddine Loulijat (17328370)Najib El Ouanjli (13825678)Abdelhak Essounaini (20827011)Vikash Kumar Saini (20827014)Ameena Saad Al-Sumaiti (12659860)BiotechnologySpace ScienceBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedvarious solar modulesseven alternative methodsmother tree optimizationmean squared errorcomplex task dueacross different irradiances7 &# 21510 ^&# 8722remaining solutions ).pv system modelingresults demonstrate mtoincorporating climate changeenhancing parameter estimationcl &# 82172 &# 215diode photovoltaic systemssolar pv threeparameter estimationclimate changesuboptimal solutionsdiode modelstudy introducesslight adjustmentsrobust toolrefreshing 20novel approachnonlinear natureinspired adaptationsincluding st40exploitation allowselectrical parametersaccurate extraction86 mw40 mw<div><p>Accurately simulating photovoltaic (PV) modules requires precise parameter extraction, a complex task due to the nonlinear nature of these systems. This study introduces the Mother Tree Optimization with Climate Change (MTO-CL) algorithm to address this challenge by enhancing parameter estimation for a solar PV three-diode model. MTO-CL improves optimization performance by incorporating climate change-inspired adaptations, which affect two key phases: elimination (refreshing 20% of suboptimal solutions) and distortion (slight adjustments to 80% of remaining solutions). This balance between exploration and exploitation allows the algorithm to dynamically and effectively identify optimal parameters. Compared to seven alternative methods, MTO-CL shows superior performance in parameter estimation for various solar modules, including ST40 and SM55, across different irradiances and temperatures. It achieves exceptionally low Root Mean Square Error (RMSE) values from 0.0025A to 0.0165A and Mean Squared Error (MSE) values between 6.2 × 10^−6 and 2.7 × 10^−4, while also significantly minimizing power errors, ranging from 22.86 mW to 239.40 mW. These results demonstrate MTO-CL’s effectiveness in improving the accuracy and reliability of PV system modeling, offering a robust tool for enhanced solar energy applications.</p></div>2025-03-04T18:33:34ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0318575.t005https://figshare.com/articles/dataset/Processing_speed_in_seconds_/28534965CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/285349652025-03-04T18:33:34Z |
| spellingShingle | Processing speed in seconds. Mouncef El Marghichi (17328361) Biotechnology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified various solar modules seven alternative methods mother tree optimization mean squared error complex task due across different irradiances 7 &# 215 10 ^&# 8722 remaining solutions ). pv system modeling results demonstrate mto incorporating climate change enhancing parameter estimation cl &# 8217 2 &# 215 diode photovoltaic systems solar pv three parameter estimation climate change suboptimal solutions diode model study introduces slight adjustments robust tool refreshing 20 novel approach nonlinear nature inspired adaptations including st40 exploitation allows electrical parameters accurate extraction 86 mw 40 mw |
| status_str | publishedVersion |
| title | Processing speed in seconds. |
| title_full | Processing speed in seconds. |
| title_fullStr | Processing speed in seconds. |
| title_full_unstemmed | Processing speed in seconds. |
| title_short | Processing speed in seconds. |
| title_sort | Processing speed in seconds. |
| topic | Biotechnology Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified various solar modules seven alternative methods mother tree optimization mean squared error complex task due across different irradiances 7 &# 215 10 ^&# 8722 remaining solutions ). pv system modeling results demonstrate mto incorporating climate change enhancing parameter estimation cl &# 8217 2 &# 215 diode photovoltaic systems solar pv three parameter estimation climate change suboptimal solutions diode model study introduces slight adjustments robust tool refreshing 20 novel approach nonlinear nature inspired adaptations including st40 exploitation allows electrical parameters accurate extraction 86 mw 40 mw |