Current Practices of Solar Photovoltaic Panel Cleaning System and Future Prospects of Machine Learning Implementation
Solar Photovoltaic System (SPV) is one of the growing green energy sources having immense penetration in the national grid as well as the off-grid around the globe. Regardless of different solar insolation level at various regions of the world, SPV performance is also affected by several factors: co...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9146654/ |
| _version_ | 1818616705888288768 |
|---|---|
| author | Nasib Khadka Aayush Bista Binamra Adhikari Ashish Shrestha Diwakar Bista Brijesh Adhikary |
| author_facet | Nasib Khadka Aayush Bista Binamra Adhikari Ashish Shrestha Diwakar Bista Brijesh Adhikary |
| author_sort | Nasib Khadka |
| collection | DOAJ |
| description | Solar Photovoltaic System (SPV) is one of the growing green energy sources having immense penetration in the national grid as well as the off-grid around the globe. Regardless of different solar insolation level at various regions of the world, SPV performance is also affected by several factors: conversion efficiency of PV cell technology, ambient temperature and humidity, soiling and seasonal/weather patterns. The rise in PV cell temperature and soiling is found to be detrimental issues regarding power plant performance and life expectancy leading alterations in the levelised cost of energy (LCoE). In this paper, authors present a short glance about factors affecting the performance of photovoltaic modules and re-discuss their usability in cleaning intervention decision-making models. With some highlights on the essence of cleaning to mitigate the soiling issues in PV power plants, this paper presents the existing cleaning techniques and practices along with their evaluations. The need for an optimal cleaning intervention by using advanced scientific tools rather than by visual inspection is drawing the attention of PV experts. The authors finally suggest a schematic of a decision-making model which involves the use of probable parameters, data processing techniques and machine learning tools. The implementation of data science and machine learning in a solar PV panel cleaning system could be a remarkable advancement in the field of renewable energy. |
| first_indexed | 2024-12-16T16:54:03Z |
| format | Article |
| id | doaj.art-edc20dd17293433cbe3f857d96d1ddbc |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T16:54:03Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-edc20dd17293433cbe3f857d96d1ddbc2022-12-21T22:23:56ZengIEEEIEEE Access2169-35362020-01-01813594813596210.1109/ACCESS.2020.30115539146654Current Practices of Solar Photovoltaic Panel Cleaning System and Future Prospects of Machine Learning ImplementationNasib Khadka0https://orcid.org/0000-0002-6808-1551Aayush Bista1Binamra Adhikari2Ashish Shrestha3https://orcid.org/0000-0001-7915-7729Diwakar Bista4Brijesh Adhikary5Department of Electrical and Electronics Engineering, Kathmandu University, Dhulikhel, NepalDepartment of Electrical and Electronics Engineering, Kathmandu University, Dhulikhel, NepalDepartment of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, SK, CanadaDepartment of Electrical and Electronics Engineering, Kathmandu University, Dhulikhel, NepalDepartment of Electrical and Electronics Engineering, Kathmandu University, Dhulikhel, NepalDepartment of Electrical and Electronics Engineering, Kathmandu University, Dhulikhel, NepalSolar Photovoltaic System (SPV) is one of the growing green energy sources having immense penetration in the national grid as well as the off-grid around the globe. Regardless of different solar insolation level at various regions of the world, SPV performance is also affected by several factors: conversion efficiency of PV cell technology, ambient temperature and humidity, soiling and seasonal/weather patterns. The rise in PV cell temperature and soiling is found to be detrimental issues regarding power plant performance and life expectancy leading alterations in the levelised cost of energy (LCoE). In this paper, authors present a short glance about factors affecting the performance of photovoltaic modules and re-discuss their usability in cleaning intervention decision-making models. With some highlights on the essence of cleaning to mitigate the soiling issues in PV power plants, this paper presents the existing cleaning techniques and practices along with their evaluations. The need for an optimal cleaning intervention by using advanced scientific tools rather than by visual inspection is drawing the attention of PV experts. The authors finally suggest a schematic of a decision-making model which involves the use of probable parameters, data processing techniques and machine learning tools. The implementation of data science and machine learning in a solar PV panel cleaning system could be a remarkable advancement in the field of renewable energy.https://ieeexplore.ieee.org/document/9146654/Solar photovoltaicsgreen energyperformancesoilingcleaning systemmachine learning |
| spellingShingle | Nasib Khadka Aayush Bista Binamra Adhikari Ashish Shrestha Diwakar Bista Brijesh Adhikary Current Practices of Solar Photovoltaic Panel Cleaning System and Future Prospects of Machine Learning Implementation IEEE Access Solar photovoltaics green energy performance soiling cleaning system machine learning |
| title | Current Practices of Solar Photovoltaic Panel Cleaning System and Future Prospects of Machine Learning Implementation |
| title_full | Current Practices of Solar Photovoltaic Panel Cleaning System and Future Prospects of Machine Learning Implementation |
| title_fullStr | Current Practices of Solar Photovoltaic Panel Cleaning System and Future Prospects of Machine Learning Implementation |
| title_full_unstemmed | Current Practices of Solar Photovoltaic Panel Cleaning System and Future Prospects of Machine Learning Implementation |
| title_short | Current Practices of Solar Photovoltaic Panel Cleaning System and Future Prospects of Machine Learning Implementation |
| title_sort | current practices of solar photovoltaic panel cleaning system and future prospects of machine learning implementation |
| topic | Solar photovoltaics green energy performance soiling cleaning system machine learning |
| url | https://ieeexplore.ieee.org/document/9146654/ |
| work_keys_str_mv | AT nasibkhadka currentpracticesofsolarphotovoltaicpanelcleaningsystemandfutureprospectsofmachinelearningimplementation AT aayushbista currentpracticesofsolarphotovoltaicpanelcleaningsystemandfutureprospectsofmachinelearningimplementation AT binamraadhikari currentpracticesofsolarphotovoltaicpanelcleaningsystemandfutureprospectsofmachinelearningimplementation AT ashishshrestha currentpracticesofsolarphotovoltaicpanelcleaningsystemandfutureprospectsofmachinelearningimplementation AT diwakarbista currentpracticesofsolarphotovoltaicpanelcleaningsystemandfutureprospectsofmachinelearningimplementation AT brijeshadhikary currentpracticesofsolarphotovoltaicpanelcleaningsystemandfutureprospectsofmachinelearningimplementation |