Makale detayı · 2023
Assessing the impact of wave model calibration in the uncertainty of wave energy estimation
Dergi
Elsevier BVISSN 0960-1481
ISSN kaydı başka bir dergiye işaret ediyor; ad YÖKSİS kaydından.
- Yıl
- 2023
- Tür
- article
Veri kaynağı ayrımı
- YÖKSİS YÖKSİS makale kaydı
- YÖKSİS dergi adı Elsevier BV
- Katalog eşleşmesi (ISSN) Renewable Energy
- OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)
Özet
OpenAlex · İngilizce
The accuracy of estimated sea conditions, specifically wave height and peak/average wave periods, affects the estimation of electrical energy production from wave energy converters. This study investigates the uncertainty in wave energy harvesting estimated by the SWAN wave model and determines possible improvements by adjusting the model's tunable parameters. Three different wave energy converters (OEBuoy, WaveBob, and Pontoon) and ten different locations along the Atlantic coast of the Iberian Peninsula are used in the study. The SWAN model is calibrated using the ST6 term package based on both wave height and peak period wave parameters. Different wave hindcast data produced by different model settings are used to estimate the wave energy produced by the wave energy converters at ten buoy locations and compared to wave energy produced estimated based on wave observations. The study finds that the physical settings of the SWAN model have a considerable influence on the uncertainty in the estimation of the power output produced by the device. The best-fitting calibrated model improved the mean energy output value of all locations compared to the SWAN default settings. The study concludes that adjusting the SWAN model parameters can improve the accuracy of the estimation of the energy output.
Konular
Atıflar
OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.
26 atıf
OpenAlex cited_by_count (önbellek / veritabanı)
Yerel katalogda bu makaleye atıf yapan 3 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).
- Development of a multi-criteria decision-making tool for combined offshore wind and wave energy site selection 2025
- Wave energy resource classification based on multivariate clustering for the Mediterranean and Black Sea 2025
- Wave energy resource classification based on multivariate clustering for the Mediterranean and Black Sea 2025