Adaptive Maximum Power Tracking Control Technique for Wind Energy Conversion Systems

Abdelhameed, Esam H.; Hassan, Hanan M.

doi:10.1109/mepcon.2018.8635144

Cited by 8 publications

(2 citation statements)

References 13 publications

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“…The simulations carried out for confirming the effectiveness involve a mathematical model of the turbine itself. Usage of Maximum Power Point Tracking controller for generating control strategies are focused primarily on recent studies, which is evident due to the simplicity and potential of the system [ 65 ]. As DFIG has a low inertia response, they are used in most wind turbines.…”

Section: Present Trends In the Field Of Wecs And Scopes Of Improvementmentioning

confidence: 99%

Energy Conversion Strategies for Wind Energy System: Electrical, Mechanical and Material Aspects

et al. 2022

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Currently, about 22% of global electricity is being supplemented by different renewable sources. Wind energy is one of the most abundant forms of renewable energy available in the atmospheric environment due to different air-currents spread over the troposphere and stratosphere. The demand of modern wind energy conversion system (WECS) has increased to achieve a suitable alternate renewable energy source. In this paper, after a brief introduction, the classification of WECS is reviewed with attractive illustrations. The various mechanical materials and electrical components of WECS are discussed. The flow of power in WECS and its control strategies are also been described. The wind energy conversion is carried out with a suitable controlling mechanism for power grid integration. A maximum power-point tracking controller is an effective controlling method to extract the maximum possible power from the turbines. The present trends in WECS and the scope for improvement and future prospects are discussed. The materials used for both the blade and generator have been found to be key elements of wind turbines. Recycling of the polymer matrix composite materials are found to be a great threat to wind power plants, as well as to their supply chain industries.

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Section: Present Trends In the Field Of Wecs And Scopes Of Improvementmentioning

confidence: 99%

Energy Conversion Strategies for Wind Energy System: Electrical, Mechanical and Material Aspects

et al. 2022

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“…In this section, the performance of the proposed control strategy will be verified and compared with those results in [ 6 , 32 ].…”

Section: Simulationmentioning

confidence: 99%

Maximum Power Point Tracking Control for Non-Gaussian Wind Energy Conversion System by Using Survival Information Potential

Yin

Lai

Zhu

et al. 2022

Entropy

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In this paper, a wind energy conversion system is studied to improve the conversion efficiency and maximize power output. Firstly, a nonlinear state space model is established with respect to shaft current, turbine rotational speed and power output in the wind energy conversion system. As the wind velocity can be descried as a non-Gaussian variable on the system model, the survival information potential is adopted to measure the uncertainty of the stochastic tracking error between the actual wind turbine rotation speed and the reference one. Secondly, to minimize the stochastic tracking error, the control input is obtained by recursively optimizing the performance index function which is constructed with consideration of both survival information potential and control input constraints. To avoid those complex probability formulation, a data driven method is adopted in the process of calculating the survival information potential. Finally, a simulation example is given to illustrate the efficiency of the proposed maximum power point tracking control method. The results demonstrate that by following this method, the actual wind turbine rotation speed can track the reference speed with less time, less overshoot and higher precision, and thus the power output can still be guaranteed under the influence of non-Gaussian wind noises.

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Analysis of Wind Energy System Using Neural Network Controller

Vig,

Kumar

2024

Lecture Notes in Electrical Engineering

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Adaptive Maximum Power Tracking Control Technique for Wind Energy Conversion Systems

Cited by 8 publications

References 13 publications

Energy Conversion Strategies for Wind Energy System: Electrical, Mechanical and Material Aspects

Energy Conversion Strategies for Wind Energy System: Electrical, Mechanical and Material Aspects

Maximum Power Point Tracking Control for Non-Gaussian Wind Energy Conversion System by Using Survival Information Potential

Analysis of Wind Energy System Using Neural Network Controller

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