Solar radiation forecasting using MARS, CART, M5, and random forest model: A case study for India
Solar radiation is a critical requirement for all solar power plants. As it is a time-varying quantity, the power output of any solar power plant is also time variant in nature. Hence, for the prediction of probable electricity generation for a few days in advance, for any solar power plant, forecas...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2019-10-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844019363522 |
| _version_ | 1818265253664784384 |
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| author | Rachit Srivastava A.N. Tiwari V.K. Giri |
| author_facet | Rachit Srivastava A.N. Tiwari V.K. Giri |
| author_sort | Rachit Srivastava |
| collection | DOAJ |
| description | Solar radiation is a critical requirement for all solar power plants. As it is a time-varying quantity, the power output of any solar power plant is also time variant in nature. Hence, for the prediction of probable electricity generation for a few days in advance, for any solar power plant, forecasting solar radiation a few days into the future is vital. Hourly forecasting for a few days in advance may help a utility or ISO in the bidding process. In this study, 1-day-ahead to 6-day-ahead hourly solar radiation forecasting was been performed using the MARS, CART, M5 and random forest models. The data required for the forecasting were collected from a solar radiation resource setup, commissioned by an autonomous body of the Government of India in Gorakhpur, India. From the results, it was determined that, for the present study, the random forest model provided the best results, whereas the CART model presented the worst results among all four models considered. |
| first_indexed | 2024-12-12T19:47:52Z |
| format | Article |
| id | doaj.art-07318c55573d48a2976f6a38dfb06b29 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-12-12T19:47:52Z |
| publishDate | 2019-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-07318c55573d48a2976f6a38dfb06b292022-12-22T00:14:03ZengElsevierHeliyon2405-84402019-10-01510e02692Solar radiation forecasting using MARS, CART, M5, and random forest model: A case study for IndiaRachit Srivastava0A.N. Tiwari1V.K. Giri2Corresponding author.; Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur 273010, Uttar Pradesh, IndiaDepartment of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur 273010, Uttar Pradesh, IndiaDepartment of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur 273010, Uttar Pradesh, IndiaSolar radiation is a critical requirement for all solar power plants. As it is a time-varying quantity, the power output of any solar power plant is also time variant in nature. Hence, for the prediction of probable electricity generation for a few days in advance, for any solar power plant, forecasting solar radiation a few days into the future is vital. Hourly forecasting for a few days in advance may help a utility or ISO in the bidding process. In this study, 1-day-ahead to 6-day-ahead hourly solar radiation forecasting was been performed using the MARS, CART, M5 and random forest models. The data required for the forecasting were collected from a solar radiation resource setup, commissioned by an autonomous body of the Government of India in Gorakhpur, India. From the results, it was determined that, for the present study, the random forest model provided the best results, whereas the CART model presented the worst results among all four models considered.http://www.sciencedirect.com/science/article/pii/S2405844019363522Electrical engineeringEnergyApplied computingM5CARTGlobal solar radiation forecasting |
| spellingShingle | Rachit Srivastava A.N. Tiwari V.K. Giri Solar radiation forecasting using MARS, CART, M5, and random forest model: A case study for India Heliyon Electrical engineering Energy Applied computing M5 CART Global solar radiation forecasting |
| title | Solar radiation forecasting using MARS, CART, M5, and random forest model: A case study for India |
| title_full | Solar radiation forecasting using MARS, CART, M5, and random forest model: A case study for India |
| title_fullStr | Solar radiation forecasting using MARS, CART, M5, and random forest model: A case study for India |
| title_full_unstemmed | Solar radiation forecasting using MARS, CART, M5, and random forest model: A case study for India |
| title_short | Solar radiation forecasting using MARS, CART, M5, and random forest model: A case study for India |
| title_sort | solar radiation forecasting using mars cart m5 and random forest model a case study for india |
| topic | Electrical engineering Energy Applied computing M5 CART Global solar radiation forecasting |
| url | http://www.sciencedirect.com/science/article/pii/S2405844019363522 |
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