Characterization of wind turbine flow through nacelle-mounted lidars: a review

S Letizia, P Brugger, N Bodini… - Frontiers in …, 2023 - frontiersin.org
This article provides a comprehensive review of the most recent advances in the planning,
execution, and analysis of inflow and wake measurements from nacelle-mounted wind …

Augmenting insights from wind turbine data through data-driven approaches

C Moss, R Maulik, GV Iungo - Applied Energy, 2024 - Elsevier
Data-driven techniques can enable enhanced insights into wind turbine operations by
efficiently extracting information from turbine data. This work outlines a data-driven strategy …

[HTML][HTML] Overview of preparation for the American WAKE ExperimeNt (AWAKEN)

P Moriarty, N Bodini, S Letizia, A Abraham… - Journal of Renewable …, 2024 - pubs.aip.org
The American WAKE ExperimeNt (AWAKEN) is a multi-institutional field campaign focused
on gathering critical observations of wind farm–atmosphere interactions. These interactions …

Profiling wind LiDAR measurements to quantify blockage for onshore wind turbines

C Moss, M Puccioni, R Maulik, C Jacquet… - Wind …, 2024 - Wiley Online Library
Flow modifications induced by wind turbine rotors on the incoming atmospheric boundary
layer (ABL), such as blockage and speedups, can be important factors affecting the power …

Blockage and speedup in the proximity of an onshore wind farm: A scanning wind LiDAR experiment

M Puccioni, CF Moss, C Jacquet… - Journal of Renewable and …, 2023 - pubs.aip.org
To maximize the profitability of wind power plants, wind farms are often characterized by
high wind turbine density leading to operations with reduced turbine spacing. As a …

Effects of wind shear and thrust coefficient on the induction zone of a porous disk: A wind tunnel study

WU Ahmed, GV Iungo - Wind Energy, 2024 - Wiley Online Library
Neglecting the velocity reduction in the induction zone of wind turbines can lead to
overestimates of power production predictions, and, thus, of the annual energy production …

Modeling Wind Turbine Performance and Wake Interactions with Machine Learning

C Moss, R Maulik, GV Iungo - arXiv preprint arXiv:2212.01483, 2022 - arxiv.org
Different machine learning (ML) models are trained on SCADA and meteorological data
collected at an onshore wind farm and then assessed in terms of fidelity and accuracy for …

PLEASE CITE THIS ARTICLE AS DOI: 10.1063/5.0157937

M Puccioni, CF Moss, C Jacquet, GV Iungo - pubs.aip.org
With 13.4 GW of new capacity installed in 2021 in the US 1, wind energy is playing a major
31 role in the transition towards the net-zero emission goal by 20502. However, the …

[PDF][PDF] Ressourceneffizienz in der Windenergie

L Alhrshy, A Gagel, A Lippke, L Vogt, C Jauch, P Kloft - opac.dbu.de
Kurzfassung Im Rahmen des Forschungsprojekts „Ressourceneffizienz in der Windenergie
“verfolgt das Institut für Windenergietechnik (WETI) an der Hochschule Flensburg in …