Prediction, operations, and condition monitoring in wind energy
Recent developments in wind energy research including wind speed prediction, wind turbine control, operations of hybrid power systems, as well as condition monitoring and fault detection are surveyed. Approaches based on statistics, physics, and data mining for wind speed prediction at different tim...
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| Published in | Energy (Oxford) Vol. 60; pp. 1 - 12 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Kidlington
Elsevier Ltd
01.10.2013
Elsevier |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Recent developments in wind energy research including wind speed prediction, wind turbine control, operations of hybrid power systems, as well as condition monitoring and fault detection are surveyed. Approaches based on statistics, physics, and data mining for wind speed prediction at different time scales are reviewed. Comparative analysis of prediction results reported in the literature is presented. Studies of classical and intelligent control of wind turbines involving different objectives and strategies are reported. Models for planning operations of different hybrid power systems including wind generation for various objectives are addressed. Methodologies for condition monitoring and fault detection are discussed. Future research directions in wind energy are proposed.
•Models and methods applied in wind energy are discussed.•Typology of research models is developed.•Control, condition, and performance monitoring of wind turbine components are highlighted.•Future research directions are outlined. |
|---|---|
| AbstractList | Recent developments in wind energy research including wind speed prediction, wind turbine control, operations of hybrid power systems, as well as condition monitoring and fault detection are surveyed. Approaches based on statistics, physics, and data mining for wind speed prediction at different time scales are reviewed. Comparative analysis of prediction results reported in the literature is presented. Studies of classical and intelligent control of wind turbines involving different objectives and strategies are reported. Models for planning operations of different hybrid power systems including wind generation for various objectives are addressed. Methodologies for condition monitoring and fault detection are discussed. Future research directions in wind energy are proposed.
•Models and methods applied in wind energy are discussed.•Typology of research models is developed.•Control, condition, and performance monitoring of wind turbine components are highlighted.•Future research directions are outlined. Recent developments in wind energy research including wind speed prediction, wind turbine control, operations of hybrid power systems, as well as condition monitoring and fault detection are surveyed. Approaches based on statistics, physics, and data mining for wind speed prediction at different time scales are reviewed. Comparative analysis of prediction results reported in the literature is presented. Studies of classical and intelligent control of wind turbines involving different objectives and strategies are reported. Models for planning operations of different hybrid power systems including wind generation for various objectives are addressed. Methodologies for condition monitoring and fault detection are discussed. Future research directions in wind energy are proposed. |
| Author | Zhang, Zijun Verma, Anoop Kusiak, Andrew |
| Author_xml | – sequence: 1 givenname: Andrew surname: Kusiak fullname: Kusiak, Andrew email: andrew-kusiak@uiowa.edu organization: Department of Mechanical and Industrial Engineering, 3131 Seamans Center, The University of Iowa, Iowa City, IA 52242–1527, USA – sequence: 2 givenname: Zijun surname: Zhang fullname: Zhang, Zijun email: zijzhang@cityu.edu.hk organization: Department of Systems Engineering and Engineering Management, P6600, 6/F, Academic 1, City University of Hong Kong, Hong Kong Special Administrative Region – sequence: 3 givenname: Anoop surname: Verma fullname: Verma, Anoop email: anoopver@buffalo.edu organization: Department of Mechanical and Aerospace Engineering, University at Buffalo, NY 14260, USA |
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| Keywords | Condition monitoring and fault detection Wind energy Wind speed prediction Wind turbine control Control system Wind velocity Review Wind generator Component Monitoring |
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| SubjectTerms | Applied sciences Condition monitoring and fault detection Energy Exact sciences and technology monitoring Natural energy physics planning prediction statistics wind direction Wind energy wind power wind speed Wind speed prediction Wind turbine control wind turbines |
| Title | Prediction, operations, and condition monitoring in wind energy |
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