On the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants
Monitoring of solar photovoltaic power plants is an essential task that could enable efficient operation and maintenance. Active control and regular maintenance will enhance the photovoltaic plant's output performance and helps in reasonable or better returns on the investments made. The proces...
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| Format: | Article |
| Language: | English |
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Elsevier
2018
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| Online Access: | http://umpir.ump.edu.my/id/eprint/23915/1/On%20the%20technologies%20empowering%20drones%20for%20intelligent%20monitoring.pdf |
| _version_ | 1825812525895122944 |
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| author | ManojKumar, Nallapaneni Sudhakar, K. Mahendran, Samykano Jayaseelan, V. |
| author_facet | ManojKumar, Nallapaneni Sudhakar, K. Mahendran, Samykano Jayaseelan, V. |
| author_sort | ManojKumar, Nallapaneni |
| collection | UMP |
| description | Monitoring of solar photovoltaic power plants is an essential task that could enable efficient operation and maintenance. Active control and regular maintenance will enhance the photovoltaic plant's output performance and helps in reasonable or better returns on the investments made. The process of monitoring is done by conducting manual inspections, but due to technological advancements, the manual checks were replaced by intelligent systems, centralized control, and monitoring systems, surveillance cameras, robotics, drones, etc. Drones are becoming more suitable for the solar industry due to a wide range of surveillance capability, long range inspection, efficient data logging capability, easy to control and access from the central level, etc. In this paper, the role of drones in solar photovoltaic power plants, and scope for enabling intelligence and automation in drones for the active monitoring and data logging is discussed. Various types drones and their configurations along with the dynamics are also considered. A study on the technologies behind the drone intelligence and automation were identified and discussed. From this study, it was found that Recognition Technologies (RT), Artificial Intelligence (AI), and Machine Learning (ML) could empower the drones and make the monitoring of large-scale solar power plants easier. This study could help the developers and researcher who are working on intelligent drones for specialist care of massive solar parks, unaccessible remote solar plants, etc. |
| first_indexed | 2024-03-06T12:30:28Z |
| format | Article |
| id | UMPir23915 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:30:28Z |
| publishDate | 2018 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | UMPir239152019-01-23T02:18:11Z http://umpir.ump.edu.my/id/eprint/23915/ On the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants ManojKumar, Nallapaneni Sudhakar, K. Mahendran, Samykano Jayaseelan, V. TJ Mechanical engineering and machinery Monitoring of solar photovoltaic power plants is an essential task that could enable efficient operation and maintenance. Active control and regular maintenance will enhance the photovoltaic plant's output performance and helps in reasonable or better returns on the investments made. The process of monitoring is done by conducting manual inspections, but due to technological advancements, the manual checks were replaced by intelligent systems, centralized control, and monitoring systems, surveillance cameras, robotics, drones, etc. Drones are becoming more suitable for the solar industry due to a wide range of surveillance capability, long range inspection, efficient data logging capability, easy to control and access from the central level, etc. In this paper, the role of drones in solar photovoltaic power plants, and scope for enabling intelligence and automation in drones for the active monitoring and data logging is discussed. Various types drones and their configurations along with the dynamics are also considered. A study on the technologies behind the drone intelligence and automation were identified and discussed. From this study, it was found that Recognition Technologies (RT), Artificial Intelligence (AI), and Machine Learning (ML) could empower the drones and make the monitoring of large-scale solar power plants easier. This study could help the developers and researcher who are working on intelligent drones for specialist care of massive solar parks, unaccessible remote solar plants, etc. Elsevier 2018 Article PeerReviewed pdf en cc_by_nc_nd_4 http://umpir.ump.edu.my/id/eprint/23915/1/On%20the%20technologies%20empowering%20drones%20for%20intelligent%20monitoring.pdf ManojKumar, Nallapaneni and Sudhakar, K. and Mahendran, Samykano and Jayaseelan, V. (2018) On the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants. Procedia Computer Science, 133. pp. 585-593. ISSN 1877-0509. (Published) https://doi.org/10.1016/j.procs.2018.07.087 https://doi.org/10.1016/j.procs.2018.07.087 |
| spellingShingle | TJ Mechanical engineering and machinery ManojKumar, Nallapaneni Sudhakar, K. Mahendran, Samykano Jayaseelan, V. On the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants |
| title | On the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants |
| title_full | On the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants |
| title_fullStr | On the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants |
| title_full_unstemmed | On the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants |
| title_short | On the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants |
| title_sort | on the technologies empowering drones for intelligent monitoring of solar photovoltaic power plants |
| topic | TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/23915/1/On%20the%20technologies%20empowering%20drones%20for%20intelligent%20monitoring.pdf |
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