Unlocking the potential: A review of artificial intelligence applications in wind energy

被引:1
|
作者
Dorterler, Safa [1 ]
Arslan, Seyfullah [1 ]
Ozdemir, Durmus [1 ]
机构
[1] Kutahya Dumlupinar Univ, Fac Engn, Dept Comp Engn, Kutahya, Turkiye
关键词
artificial intelligence; artificial neural network; machine learning; meta-heuristic algorithms; renewable energy; wind energy; wind turbine; MACHINE-LEARNING-MODELS; CONDITION-BASED MAINTENANCE; NEURAL-NETWORK; POWER PREDICTION; FUZZY-LOGIC; MULTIOBJECTIVE OPTIMIZATION; FAULT-DETECTION; TURBINE; SPEED; SYSTEM;
D O I
10.1111/exsy.13716
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a comprehensive review of the most recent papers and research trends in the fields of wind energy and artificial intelligence. Our study aims to guide future research by identifying the potential application and research areas of artificial intelligence and machine learning techniques in the wind energy sector and the knowledge gaps in this field. Artificial intelligence techniques offer significant benefits and advantages in many sub-areas, such as increasing the efficiency of wind energy facilities, estimating energy production, optimizing operation and maintenance, providing security and control, data analysis, and management. Our research focuses on studies indexed in the Web of Science library on wind energy between 2000 and 2023 using sub-branches of artificial intelligence techniques such as artificial neural networks, other machine learning methods, data mining, fuzzy logic, meta-heuristics, and statistical methods. In this way, current methods and techniques in the literature are examined to produce more efficient, sustainable, and reliable wind energy, and the findings are discussed for future studies. This comprehensive evaluation is designed to be helpful to academics and specialists interested in acquiring a current and broad perspective on the types of uses of artificial intelligence in wind energy and seeking what research subjects are needed in this field.
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页数:39
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