A novel approach to investigate the effects of global warming and exchange rate on the solar power plants
| dc.contributor.author | Gurturk, Mert | |
| dc.contributor.author | Ucar, Ferhat | |
| dc.contributor.author | Erdem, Murat | |
| dc.date.accessioned | 2026-08-12T18:07:10Z | |
| dc.date.issued | 2022 | |
| dc.department | Fırat Üniversitesi | |
| dc.description.abstract | The present study proposes novel approaches to concepts such as risk assessment and investment management in investments in solar power plants. In this context, 11 cities in Turkey have been taken into consideration for solar energy investment. Global warming is also one of the current issues on the World's agenda. The monthly impact of global warming has been investigated for 5 years using a deep learning model, and the effects of global warming on cost have been determined within the scope of this study. Concerning the outputs of the designed deep learning-based temperature-forecasting model, it was observed that the gain values might decrease between 5.98% and 3.74% due to the possible global warming effects in 2025e2030. Also, changes in the US$/TL ratio put solar energy investors in a difficult position. The Turkish government issued a Presidential Decree numbered 3453 on January 30, 2021, to offer a solution to this situation. The profit-loss situation of solar energy investments was investigated with the issued support policy and fixed price-purchasing policy. It has been observed that the fixed price policy is not sustainable and the new support system partially protects the solar energy investor. . (c) 2021 Elsevier Ltd. All rights reserved. | |
| dc.identifier.doi | 10.1016/j.energy.2021.122344 | |
| dc.identifier.issn | 0360-5442 | |
| dc.identifier.issn | 1873-6785 | |
| dc.identifier.orcid | 0000-0003-0380-5704 | |
| dc.identifier.orcid | 0000-0003-0287-1881 | |
| dc.identifier.scopus | 2-s2.0-85117385148 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.uri | https://doi.org/10.1016/j.energy.2021.122344 | |
| dc.identifier.uri | https://hdl.handle.net/11508/62597 | |
| dc.identifier.volume | 239 | |
| dc.identifier.wos | WOS:000711163800009 | |
| dc.identifier.wosquality | Q1 | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.language.iso | en | |
| dc.publisher | Pergamon-Elsevier Science Ltd | |
| dc.relation.ispartof | Energy | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.snmz | KA_WoS_20260511 | |
| dc.subject | PV | |
| dc.subject | Solar energy | |
| dc.subject | Solar power plant | |
| dc.subject | Global warming | |
| dc.subject | Deep learning | |
| dc.title | A novel approach to investigate the effects of global warming and exchange rate on the solar power plants | |
| dc.type | Article |







