Data mining techniques for performance analysis of onshore wind farms-Reference-Cited by-同舟云学术

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Data mining techniques for performance analysis of onshore wind farms

Published:2015-06 Issue: Volume:148 Page:220-233
ISSN:0306-2619
Container-title:Applied Energy
language:en
Short-container-title:Applied Energy

Author:

Astolfi Davide,Castellani Francesco,Garinei Alberto,Terzi Ludovico

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Mechanical Engineering,General Energy,Building and Construction

Reference38 articles.

1. Robust filtering for the characterization of wind turbines: improving its operation and maintenance;Sainz;Energy Convers Manage,2009

2. Optimization of wind turbine energy and power factor with an evolutionary computation algorithm;Kusiak;Energy,2010

3. Prediction, operations, and condition monitoring in wind energy;Kusiak;Energy,2013

4. Wind speed and wind energy forecast through Kalman filtering of numerical weather prediction model output;Cassola;Appl Energy,2012

5. Short-term wind speed forecasting with markov-switching model;Song;Appl Energy,2014

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1. Probabilistic assessment of wind power plant energy potential through a copula-deep learning approach in decision trees;Heliyon;2024-04

2. Overall equipment effectiveness as a metric for assessing operational losses in wind farms: a critical review of literature;International Journal of Sustainable Energy;2023-03-24

3. A two-stage anomaly decomposition scheme based on multi-variable correlation extraction for wind turbine fault detection and identification;Applied Energy;2022-09

4. A new hybrid model based on secondary decomposition, reinforcement learning and SRU network for wind turbine gearbox oil temperature forecasting;Measurement;2021-06

5. Influence of atmospheric stability on wind farm performance in complex terrain;Applied Energy;2021-01

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