Prognostics and health management of wind energy infrastructure systems

C Yüce, O Gecgel, O Doğan… - … -ASME Journal of …, 2022 - asmedigitalcollection.asme.org
The improvements in wind energy infrastructure have been a constant process throughout
many decades. There are new advancements in technology that can further contribute …

A state-of-the-art review on wind power deterministic prediction

Z Tian - Wind Engineering, 2021 - journals.sagepub.com
With the continuous growth of wind power access capacity, the impact of intermittent and
volatile wind power generation on the grid is becoming more and more obvious, so the …

Wind power prediction using ensemble learning-based models

J Lee, W Wang, F Harrou, Y Sun - IEEE access, 2020 - ieeexplore.ieee.org
Wind power is one of the most potential energies and the major available renewable energy
sources. Precisely predicting wind power production is essential for the management and …

Bayesian CNN-BiLSTM and vine-GMCM based probabilistic forecasting of hour-ahead wind farm power outputs

M Zou, N Holjevac, J Đaković, I Kuzle… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
The importance of the accurate forecasting of power outputsof wind-based generation
systems is increasing, as their contributions to the total system generation are rising …

[HTML][HTML] Icing detection and prediction for wind turbines using multivariate sensor data and machine learning

F Ye, AA Ezzat - Renewable Energy, 2024 - Elsevier
Adverse weather events can significantly compromise the availability and economics of a
wind farm. This paper focuses on rotor icing detection, which constitutes a major challenge …

Overall equipment effectiveness as a metric for assessing operational losses in wind farms: a critical review of literature

KPB Sathler, K Salonitis, A Kolios - International Journal of …, 2023 - Taylor & Francis
To become more competitive, less dependent on financial support and more attractive for
investors, wind energy needs to reduce its final cost of energy. According to Levelized Cost …

Probabilistic forecasting of wind turbine icing related production losses using quantile regression forests

J Molinder, S Scher, E Nilsson, H Körnich, H Bergström… - Energies, 2020 - mdpi.com
A probabilistic machine learning method is applied to icing related production loss forecasts
for wind energy in cold climates. The employed method, called quantile regression forests, is …

[HTML][HTML] Skill and potential economic value of forecasts of ice accretion on wind turbines

L Strauss, S Serafin… - Journal of Applied …, 2020 - journals.ametsoc.org
Skill and Potential Economic Value of Forecasts of Ice Accretion on Wind Turbines in:
Journal of Applied Meteorology and Climatology Volume 59 Issue 11 (2020) Jump to …

Convolutional neural network with dual inputs for time series ice prediction on rotor blades of wind turbines

M Kreutz, AA Alla, K Varasteh, JH Ohlendorf, M Lütjen… - Procedia CIRP, 2021 - Elsevier
Downtimes due to ice formation on rotor blades reduce the economic efficiency of wind
turbines. An accurate ice prediction is required to operate active de-icing measures such as …

Ice prediction for wind turbine rotor blades with time series data and a deep learning approach

M Kreutz, AA Alla, M Lütjen, JH Ohlendorf… - Cold Regions Science …, 2023 - Elsevier
Reducing ice formation on wind turbine rotor blades is mandatory to increase the economic
viability of wind energy in cold regions. In our research, we propose a predictive anti-icing …