Maximum power from wind energy system using fuzzy controller

Mohammed, Walaa; Kamal, Elkhatib; Sobaih, Abdul Azim

doi:10.1109/icenco.2015.7416329

Cited by 1 publication

(1 citation statement)

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“…The system also provides robust performance [102][103][104] for system parameter variation and any external disturbances and provides better stability [105].…”

Section: Fuzzy Logic Controlmentioning

confidence: 99%

Review on control techniques and methodologies for maximum power extraction from wind energy systems

Kumar

Saravanan

Padmanaban

et al. 2018

IET Renewable Power Generation

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This review study focuses on various methods and technologies used in past and present for obtaining maximum output power from a wind energy conversion system. There are plenty of solution for maximum power point (MPP), but the problem lies in the effective choice made among them and it needs the expert knowledge on every technique for picking up the best MPP method as every method on its own has some advantages and disadvantages. A comparison has been made among various MPP methods in terms of convergence time, efficiency, training, complexity and wind measurement. Here, different MPP tracking (MPPT) algorithms are classified based on wind speed measurement (WSR) and without WSR models. In this study, from the literature, a novel maximum electrical power tracking (MEPT) and maximum mechanical power tracking (MMPT) methods are compared with state-of-the-art MPPT algorithms. On basis of the results obtained from the literature available, the MEPT algorithm has fast convergence rate of 15 ms; on the other hand, optimal relation-based method is having large convergence rate of 364 ms and less efficient. A case study has been considered for performance validation, and MEPT and MMPT are having a good response for dynamic variation in wind speed.

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“…The system also provides robust performance [102][103][104] for system parameter variation and any external disturbances and provides better stability [105].…”

Section: Fuzzy Logic Controlmentioning

confidence: 99%