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Title: Controller design for PMSG wind turbine
Authors: Peng, Di.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineering
Issue Date: 2011
Abstract: 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.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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