Controller design for PMSG wind turbine

In recent years, world energy crisis is getting serious. Much new energy is found to take the position of fossil fuels. Wind power has become more and more popular all over the world because it is renewable, clean and plentiful. At the same time it products no greenhouse gas emissions during operat...

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Main Author: Peng, Di.
Other Authors: Wang Youyi
Format: Final Year Project
Language:English
Published: 2011
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Online Access:http://hdl.handle.net/10356/44763
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-447632023-07-07T17:59:02Z Controller design for PMSG wind turbine Peng, Di. Wang Youyi School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering In recent years, world energy crisis is getting serious. Much new energy is found to take the position of fossil fuels. Wind power has become more and more popular all over the world because it is renewable, clean and plentiful. At the same time it products no greenhouse gas emissions during operation. However, there are some limitations in wind power. The wind speed is changing with the time and that lead to (1) the varying output power and (2) unstable output frequency. The higher the wind speed is and the more output power the wind turbine creates. Now the second question has been well solved by AC-DC controller while the optimal solution of the first question is still not found. In this report, a control strategy is proposed to make the wind turbine working in the optimal condition and guarantee the stable output adapt to the variation of wind speed. In this control strategy, rotor rate and pitch angle are controlled to make the output power maximum when the wind speed is low and maintain the output power in rated value when the wind speed is high. This control method is based on Extreme Learning Machine (ELM). In addition, the learning algorithm is chosen the Single-hidden Layer Feedforward neural Networks (SLFN) which randomly chooses hidden nodes and analytically determines the output weights of SLFNs. It tends to provide good generalization performance at extremely fast learning speed. The whole work has been conducted though MATLAB and the results are shown and conclusions are given in the last part of paper. Bachelor of Engineering 2011-06-03T07:49:01Z 2011-06-03T07:49:01Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/44763 en Nanyang Technological University 80 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
Peng, Di.
Controller design for PMSG wind turbine
description In recent years, world energy crisis is getting serious. Much new energy is found to take the position of fossil fuels. Wind power has become more and more popular all over the world because it is renewable, clean and plentiful. At the same time it products no greenhouse gas emissions during operation. However, there are some limitations in wind power. The wind speed is changing with the time and that lead to (1) the varying output power and (2) unstable output frequency. The higher the wind speed is and the more output power the wind turbine creates. Now the second question has been well solved by AC-DC controller while the optimal solution of the first question is still not found. In this report, a control strategy is proposed to make the wind turbine working in the optimal condition and guarantee the stable output adapt to the variation of wind speed. In this control strategy, rotor rate and pitch angle are controlled to make the output power maximum when the wind speed is low and maintain the output power in rated value when the wind speed is high. This control method is based on Extreme Learning Machine (ELM). In addition, the learning algorithm is chosen the Single-hidden Layer Feedforward neural Networks (SLFN) which randomly chooses hidden nodes and analytically determines the output weights of SLFNs. It tends to provide good generalization performance at extremely fast learning speed. The whole work has been conducted though MATLAB and the results are shown and conclusions are given in the last part of paper.
author2 Wang Youyi
author_facet Wang Youyi
Peng, Di.
format Final Year Project
author Peng, Di.
author_sort Peng, Di.
title Controller design for PMSG wind turbine
title_short Controller design for PMSG wind turbine
title_full Controller design for PMSG wind turbine
title_fullStr Controller design for PMSG wind turbine
title_full_unstemmed Controller design for PMSG wind turbine
title_sort controller design for pmsg wind turbine
publishDate 2011
url http://hdl.handle.net/10356/44763
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