Optimization of Solar Panel Deployment Using Machine Learning
In this work, we proposed a mechanism for topology reconfiguration or optimization of photovoltaic (PV) arrays using machine learning-assisted techniques. The study takes into concern several topologies that includes series parallel topology, parallel topology, bridge link topology, honeycomb topolo...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Journal of Photoenergy |
| Online Access: | http://dx.doi.org/10.1155/2022/7249109 |
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| _version_ | 1832565822859509760 |
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| author | Shoaib Kamal P. S. Ramapraba Avinash Kumar Bikash Chandra Saha M. Lakshminarayana S. Sanal Kumar Anitha Gopalan Kuma Gowwomsa Erko |
| author_facet | Shoaib Kamal P. S. Ramapraba Avinash Kumar Bikash Chandra Saha M. Lakshminarayana S. Sanal Kumar Anitha Gopalan Kuma Gowwomsa Erko |
| author_sort | Shoaib Kamal |
| collection | DOAJ |
| description | In this work, we proposed a mechanism for topology reconfiguration or optimization of photovoltaic (PV) arrays using machine learning-assisted techniques. The study takes into concern several topologies that includes series parallel topology, parallel topology, bridge link topology, honeycomb topology, and total cross tied. The artificial neural network-based topology reconfiguration strategy allows for optimal working conditions for PV arrays. With this, machine learning-assisted topology reconfiguration or optimal solar panel deployment enables the proposed mechanism to achieve higher degree of testing accuracy precision, recall, and f-measure under standard ideal condition. |
| format | Article |
| id | doaj-art-e882e7183910461c89fb71467e1028f3 |
| institution | Kabale University |
| issn | 1687-529X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Photoenergy |
| spelling | doaj-art-e882e7183910461c89fb71467e1028f32025-02-03T01:06:35ZengWileyInternational Journal of Photoenergy1687-529X2022-01-01202210.1155/2022/7249109Optimization of Solar Panel Deployment Using Machine LearningShoaib Kamal0P. S. Ramapraba1Avinash Kumar2Bikash Chandra Saha3M. Lakshminarayana4S. Sanal Kumar5Anitha Gopalan6Kuma Gowwomsa Erko7Department of Electronics and Communication EngineeringDepartment of Electrical and Electronics EngineeringDepartment of Electrical and Electronics EngineeringDepartment of Electrical and Electronics EngineeringDepartment of Electronics and Communication EngineeringDepartment of InstrumentationDepartment of Electronics and Communication EngineeringDepartment of Mechanical EngineeringIn this work, we proposed a mechanism for topology reconfiguration or optimization of photovoltaic (PV) arrays using machine learning-assisted techniques. The study takes into concern several topologies that includes series parallel topology, parallel topology, bridge link topology, honeycomb topology, and total cross tied. The artificial neural network-based topology reconfiguration strategy allows for optimal working conditions for PV arrays. With this, machine learning-assisted topology reconfiguration or optimal solar panel deployment enables the proposed mechanism to achieve higher degree of testing accuracy precision, recall, and f-measure under standard ideal condition.http://dx.doi.org/10.1155/2022/7249109 |
| spellingShingle | Shoaib Kamal P. S. Ramapraba Avinash Kumar Bikash Chandra Saha M. Lakshminarayana S. Sanal Kumar Anitha Gopalan Kuma Gowwomsa Erko Optimization of Solar Panel Deployment Using Machine Learning International Journal of Photoenergy |
| title | Optimization of Solar Panel Deployment Using Machine Learning |
| title_full | Optimization of Solar Panel Deployment Using Machine Learning |
| title_fullStr | Optimization of Solar Panel Deployment Using Machine Learning |
| title_full_unstemmed | Optimization of Solar Panel Deployment Using Machine Learning |
| title_short | Optimization of Solar Panel Deployment Using Machine Learning |
| title_sort | optimization of solar panel deployment using machine learning |
| url | http://dx.doi.org/10.1155/2022/7249109 |
| work_keys_str_mv | AT shoaibkamal optimizationofsolarpaneldeploymentusingmachinelearning AT psramapraba optimizationofsolarpaneldeploymentusingmachinelearning AT avinashkumar optimizationofsolarpaneldeploymentusingmachinelearning AT bikashchandrasaha optimizationofsolarpaneldeploymentusingmachinelearning AT mlakshminarayana optimizationofsolarpaneldeploymentusingmachinelearning AT ssanalkumar optimizationofsolarpaneldeploymentusingmachinelearning AT anithagopalan optimizationofsolarpaneldeploymentusingmachinelearning AT kumagowwomsaerko optimizationofsolarpaneldeploymentusingmachinelearning |