Publication
Validation of a methodology for post-construction Energy Yield Assessment of an operational wind farm
| datacite.subject.fos | Engenharia e Tecnologia | |
| datacite.subject.sdg | 09:Indústria, Inovação e Infraestruturas | |
| dc.contributor.author | Costa, M. | |
| dc.contributor.author | Rocha, T. | |
| dc.contributor.author | Mendonça, J. | |
| dc.contributor.author | Pilão, R. | |
| dc.contributor.author | Pinto, P. | |
| dc.date.accessioned | 2025-02-14T18:57:37Z | |
| dc.date.available | 2025-02-14T18:57:37Z | |
| dc.date.issued | 2024-06-26 | |
| dc.description.abstract | The uncertainty associated with the prospective Energy Yield Assessment (EYA) of a wind farm may be reduced by re estimating the energy yield after it enters normal operation. This study aims to validate a simple methodology for conducting post-construction EYA of an operational wind farm. The proposed methodology derives a linear relationship between a historical source of wind speed data and the observed wind farm production on a monthly basis. In a first stage, the impact of different data sources on the accuracy of the Long-Term energy yield estimate was assessed. Results suggest that the determination coefficient R 2 is a reliable indicator for selecting the most adequate source of historical wind speed data to be used in the Long-Term energy yield estimate. In a second stage, the model was validated from a statistical point of view by testing the premises of the linear regression model, namely the significance of the linear correlation (ANOVA test), and normally-distributed (Shapiro-Wilk test), non-self-correlated (Durbin-Watson), homoscedastic (Breusch-Pagan test) residuals. Results show these premises are verified for most test cases, indicating that the model is statistically robust that the model is statistically robust for most test cases. | eng |
| dc.identifier.citation | Costa, M., Rocha, T., Mendonça, J., Pilão, R., & Pinto, P. (2024). Validation of a methodology for post-construction Energy Yield Assessment of an operational wind farm. Renewable Energy and Power Quality Journal (RE&PQJ), 22. https://doi.org/10.52152/4102 | |
| dc.identifier.doi | 10.52152/4102 | |
| dc.identifier.issn | 2172-038 X | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/29534 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Elsevier | |
| dc.relation | Center for Innovation in Industrial Engineering and Technology | |
| dc.relation.hasversion | https://repqj.com/index.php/repqj/article/view/4118/3790 | |
| dc.rights.uri | N/A | |
| dc.subject | Wind energy | |
| dc.subject | post-construction Energy Yield Assessment | |
| dc.subject | linear regression | |
| dc.title | Validation of a methodology for post-construction Energy Yield Assessment of an operational wind farm | eng |
| dc.type | conference paper | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | Center for Innovation in Industrial Engineering and Technology | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04730%2F2020/PT | |
| oaire.citation.conferenceDate | 2024-06-26 | |
| oaire.citation.conferencePlace | Bilbao, Spain | |
| oaire.citation.title | 22nd International Conference on Renewable Energies and Power Quality (ICREPQ’24) | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| relation.isProjectOfPublication | cdbfce2f-6ff0-4d59-a7c6-96c99d52a570 | |
| relation.isProjectOfPublication.latestForDiscovery | cdbfce2f-6ff0-4d59-a7c6-96c99d52a570 |