Wind Power Estimation Algorithm Using Artificial Neural Networks Case Study: Eregli
| dc.contributor.author | Cetinkaya, Nurettin | |
| dc.contributor.author | Yapici, Hamza | |
| dc.date.accessioned | 2024-02-23T14:45:21Z | |
| dc.date.available | 2024-02-23T14:45:21Z | |
| dc.date.issued | 2014 | |
| dc.department | NEÜ | en_US |
| dc.description | 6th International Conference on Electronics, Computers and Artificial Intelligence (ECAI) -- OCT 23-25, 2014 -- Pitesti, ROMANIA | en_US |
| dc.description.abstract | By the global warming and decreasing fossil fuel, alternative energy sources are looked for future and protecting environment. In the recent years, many studies are made about wind power whereby deteriorating environment will be regarded. This study prefers artificial neural network (ANN) algorithm to estimate electrical energy output of wind turbines can be constructed. Although many environmental effects such as wind speed, air density or temperature influence wind turbines installation, ANN estimates electrical energy and power output in the minimum cost. The wind turbine parameters of three manufacturers have been chosen so as to train ANN. For the structure of ANN, 1 hidden layer and 26 neurons have been set. Data in this work have been measured at Eregli terrain in Konya, Turkey. This daily data have been taken between January 2013 and February 2014. | en_US |
| dc.description.sponsorship | IEEE,IEEE Romania sect,IEEE Ind Appl Soc | en_US |
| dc.identifier.isbn | 978-1-4799-5479-7 | |
| dc.identifier.issn | 2378-7147 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12452/17370 | |
| dc.identifier.wos | WOS:000380489500022 | en_US |
| dc.indekslendigikaynak | Web of Science | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.ispartof | Proceedings Of The 2014 6th International Conference On Electronics, Computers And Artificial Intelligence (Ecai) | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Ann | en_US |
| dc.subject | Annual Electrical Energy Estimation | en_US |
| dc.subject | Power Plant Structure | en_US |
| dc.subject | Wind Turbine | en_US |
| dc.title | Wind Power Estimation Algorithm Using Artificial Neural Networks Case Study: Eregli | en_US |
| dc.type | Conference Object | en_US |
