Titre :

Advanced methods of identification of sea-breeze and low-level jet events from near ground measurements with specific implication for energy production by offshore wind farms

Auteur(s) :

Roy, Sayahnya [Auteur]
Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 [LOG]
Sentchev, Alexei [Auteur]
Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 [LOG]
Augustin, Patrick [Auteur]
Laboratoire de Physico-Chimie de l'Atmosphère [LPCA]
Fourmentin, Marc [Auteur]
Laboratoire de Physico-Chimie de l'Atmosphère [LPCA]

Titre de l’ouvrage :

Trends in Renewable Energies Offshore – Guedes Soares (Ed.)

Éditeur :

CRC Press

Lieu de publication :

London

Date de publication :

2022-10-03

ISBN :

9781003360773

Résumé en anglais : [en]

Since an uniform high-speed wind is required for maximum power production, it is important to survey the meteorological phenomena which can boost up or down the power production by offshore wind turbines. The study is ...
Lire la suite >Since an uniform high-speed wind is required for maximum power production, it is important to survey the meteorological phenomena which can boost up or down the power production by offshore wind turbines. The study is focused on developing and validation of advanced methods of detection of such mete-orological phenomena. In situ measurements were performed at an experimental site located in Dunkirk, northern France. The wind variability was measured by Sonic anemometer during a period starting from 11th January 2018 to 18th December 2019. Automatic detection algorithms have been developed to detect sea-breeze (SB) and nocturnal low-level jet (NLLJ) events from Sonic anemometer measurements near ground. The SB detection is based on a recurrent neural network algorithm (RNN). The accuracy of event identifica-tion by this network is 95%. We found 67 and 78 SB days in 2018 and 2019 respectively. NLLJ detection al-gorithms developed, using wavelet transformation methods, show a better performance than other existing methods. A total of 192 and 168 NLLJ days were found in 2018 and 2019 respectively. The wind speed was found higher during the nighttime for NLLJ than for non-NLLJ days, which can increase the peak power pro-duction up to 40 times, compared to normal days. To evaluate the skill of detection algorithms based on ane-mometer measurements, simultaneous Sonic and lidar wind measurements have been done at site for 86-day long period. The wind speed and turbulence kinetic energy were computed from Sonic anemometer and com-pared to the lidar measurements. The comparison suggests that the point measurements by Sonic anemometer can be very useful for the algorithms of automatic detection of meteorological events.Lire moins >

Langue :

Anglais

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Laboratoire d'Océanologie et de Géosciences (LOG) - UMR 8187

Source :

Harvested from HAL