Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea
The Agrophotovoltaic (APV) system is a novel concept in the field of Renewable Energy Systems. This system enables the generation of solar energy via photo-voltaic (PV) modules above crops, to mitigate harmful impact on food production. This study aims to develop a performance evaluation model for a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/14/20/6724 |
| _version_ | 1797514720208486400 |
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| author | Sojung Kim Sumin Kim |
| author_facet | Sojung Kim Sumin Kim |
| author_sort | Sojung Kim |
| collection | DOAJ |
| description | The Agrophotovoltaic (APV) system is a novel concept in the field of Renewable Energy Systems. This system enables the generation of solar energy via photo-voltaic (PV) modules above crops, to mitigate harmful impact on food production. This study aims to develop a performance evaluation model for an APV system in a temperate climate region, such as South Korea. To this end, both traditional electricity generation models (solar radiation-based model and climate-based model) of PV modules and two major machine learning (ML) techniques (i.e., polynomial regression and deep learning) have been considered. Electricity generation data was collected via remote sensors installed in the APV system at Jeollanam-do Agricultural Research and Extension Services in South Korea. Moreover, economic analysis in terms of cost and benefit of the subject APV system was conducted to provide information about the return on investment to farmers and government agencies. As a result, farmers, agronomists, and agricultural engineers can easily estimate performance and profit of their APV systems via the proposed performance model. |
| first_indexed | 2024-03-10T06:35:39Z |
| format | Article |
| id | doaj.art-6b491369cf234bf6a43d316fbe8514dd |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T06:35:39Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-6b491369cf234bf6a43d316fbe8514dd2023-11-22T18:07:47ZengMDPI AGEnergies1996-10732021-10-011420672410.3390/en14206724Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South KoreaSojung Kim0Sumin Kim1Industrial and Systems Engineering, Dongguk University-Seoul, Seoul 04620, KoreaDepartment of Environmental Horticulture & Landscape Architecture, College of Life Science & Biotechnology, Dankook University, Cheonan-si 31116, KoreaThe Agrophotovoltaic (APV) system is a novel concept in the field of Renewable Energy Systems. This system enables the generation of solar energy via photo-voltaic (PV) modules above crops, to mitigate harmful impact on food production. This study aims to develop a performance evaluation model for an APV system in a temperate climate region, such as South Korea. To this end, both traditional electricity generation models (solar radiation-based model and climate-based model) of PV modules and two major machine learning (ML) techniques (i.e., polynomial regression and deep learning) have been considered. Electricity generation data was collected via remote sensors installed in the APV system at Jeollanam-do Agricultural Research and Extension Services in South Korea. Moreover, economic analysis in terms of cost and benefit of the subject APV system was conducted to provide information about the return on investment to farmers and government agencies. As a result, farmers, agronomists, and agricultural engineers can easily estimate performance and profit of their APV systems via the proposed performance model.https://www.mdpi.com/1996-1073/14/20/6724Agrophotovoltaicphotovoltaicrenewable energyenergy systemmachine learning |
| spellingShingle | Sojung Kim Sumin Kim Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea Energies Agrophotovoltaic photovoltaic renewable energy energy system machine learning |
| title | Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea |
| title_full | Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea |
| title_fullStr | Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea |
| title_full_unstemmed | Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea |
| title_short | Performance Estimation Modeling via Machine Learning of an Agrophotovoltaic System in South Korea |
| title_sort | performance estimation modeling via machine learning of an agrophotovoltaic system in south korea |
| topic | Agrophotovoltaic photovoltaic renewable energy energy system machine learning |
| url | https://www.mdpi.com/1996-1073/14/20/6724 |
| work_keys_str_mv | AT sojungkim performanceestimationmodelingviamachinelearningofanagrophotovoltaicsysteminsouthkorea AT suminkim performanceestimationmodelingviamachinelearningofanagrophotovoltaicsysteminsouthkorea |