Control of wind turbine power and vibration with a data-driven approach

Renewable Energy

Volumn 43, Issue , 2012, Pages 73-82

  Kusiak, Andrew ^a   Zhang, Zijun ^a  

^a UNIVERSITY OF IOWA   (United States)

Author keywords

Data mining; Drive train acceleration; Particle swarm optimization; Tower acceleration; Turbine control; Turbine vibration

Indexed keywords

ACCELERATION PARAMETERS; ANTICIPATORY CONTROL; CONTROL OF WIND TURBINES; DATA MINING ALGORITHM; DATA-DRIVEN APPROACH; DATA-DRIVEN MODEL; OPTIMIZATION CONTROL; PARTICLE SWARM; PARTICLE SWARM OPTIMIZATION ALGORITHM; PREDICTION ACCURACY; TURBINE CONTROL; TWO PARAMETER; WIND FARM;

ACCELEROMETERS; ALGORITHMS; ELECTRIC UTILITIES; PARTICLE SWARM OPTIMIZATION (PSO); WIND POWER; WIND TURBINES;

DATA MINING;

ACCURACY ASSESSMENT; ALGORITHM; CONTROL SYSTEM; DATA MINING; OPTIMIZATION; VIBRATION; WIND TURBINE;

EID: 84856527344     PISSN: 09601481     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.renene.2011.11.024     Document Type: Article

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