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Analyzing The Potential Of Genetic Algorithm For Maximum Power Point Tracking In Wind Energy Conversion System In Malaysia

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dc.contributor.authorNasrullah Bin Isninen_US
dc.date.accessioned2023-05-03T15:02:54Z
dc.date.available2023-05-03T15:02:54Z
dc.date.issued2019-10
dc.description.abstractWith the world is greatly concerns on the environmental pollution and the greenhouse gasses effect, the popularity of the renewable energy is greatly increasing. Hydro power, wind and solar energy, as example of the most discussed renewable energy resources have become more popular. The renewable energy resources are penetrating the country energy generation by slowly replacing the coal and fossil fuels as the main energy generation resources. The wind energy has become a popular choice of the renewable energy resources as it does not pollute the environment and the wind energy is abundantly available. With the increase of popularity, there are many researches is done in order to extract the maximum power from the wind energy. In this paper, a maximum power point tracking for the wind turbine is proposed which is the indirect speed control. A genetic algorithm is used to further optimised the control strategy by finding the optimised variable for the controller. The proposed control strategy is used to regulate the frequency of the rotor current to control the rotor speed of the Doubly-Fed Induction Generator (DFIG) to extract maximum power of the wind turbine. the simulation of this project is done in MATLAB/Simulink software. The proposed MMPT technique is able to extract the maximum power and with GA optimisation, the system respond can achieve a response with 1.336 second faster.en_US
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/20497
dc.language.isoenen_US
dc.subjectMPPTen_US
dc.subjectWind Energyen_US
dc.subjectGenetic Algorithmen_US
dc.titleAnalyzing The Potential Of Genetic Algorithm For Maximum Power Point Tracking In Wind Energy Conversion System In Malaysiaen_US
dspace.entity.typePublication
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