Design and Comparison of Performance of DFIG Based Wind Turbine with PID Controller, Fuzzy Controller, Artificial Neural Network and Model Predictive Controller

K. Naresh; P. Reddy; P. Sujatha

Research Article

Design and Comparison of Performance of DFIG Based Wind Turbine with PID Controller, Fuzzy Controller, Artificial Neural Network and Model Predictive Controller

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@ARTICLE{10.4108/eai.29-6-2021.170251,
    author={K. Naresh and P. Umapathi Reddy and P. Sujatha},
    title={Design and Comparison of Performance of DFIG Based Wind Turbine with PID Controller, Fuzzy Controller, Artificial Neural Network and Model Predictive Controller},
    journal={EAI Endorsed Transactions on Energy Web},
    volume={9},
    number={37},
    publisher={EAI},
    journal_a={EW},
    year={2021},
    month={6},
    keywords={Multimode control strategy, PI controller, Fuzzy controller, Artificial neural network, Model predictive controller},
    doi={10.4108/eai.29-6-2021.170251}
}

K. Naresh
P. Umapathi Reddy
P. Sujatha
Year: 2021
Design and Comparison of Performance of DFIG Based Wind Turbine with PID Controller, Fuzzy Controller, Artificial Neural Network and Model Predictive Controller
EW
EAI
DOI: 10.4108/eai.29-6-2021.170251

K. Naresh¹^,*, P. Umapathi Reddy², P. Sujatha³

1: Research Scholar, EEE Department, JNTUA Ananthapuramu, Ananthapuramu, Andhra Pradesh- India- 515002
2: Professor, EEE Department, SVEC- Thirupati, Andhra Pradesh- India- 517102
3: Professor, EEE Department, JNTUA Ananthapuramu, Ananthapuramu, Andhra Pradesh-India- 515002

*Contact email: Naresh5kelothu@gmail.com

Abstract

The everyday benefits of environmentally friendly power sources urges to build their use to the bigger degree of whichwind energy is the most accessible asset. This paper presents the plan of multimode hang control methodology based variable speed wind power age framework. The multimode hang control procedure improves the framework to work regarding the network framework and furthermore in the independent method of activity. The multimode control methodology utilizes the DC connect voltage regulator to control the DC interface capacitor voltage for working the framework side converter and current regulator to control current and force of the rotor side converter. The control methodology is investigated with the customary regulator like PI regulator, astute regulators like Fuzzy regulator, fake neural organization (ANN) and model prescient regulator (MPC) which predicts the future factors. A correlation has been performed with the previously mentioned various sorts of regulators based breeze power age framework regarding various boundaries. This paper likewise includes examination of various experiments with the previously mentioned regulators. The examination of various experiments with various regulators has been performed utilizing MATLAB 2013a and every one of the outcomes are checked.

Keywords: Multimode control strategy, PI controller, Fuzzy controller, Artificial neural network, Model predictive controller

Received: 2021-04-30
Accepted: 2021-06-18
Published: 2021-06-29
Publisher: EAI

: http://dx.doi.org/10.4108/eai.29-6-2021.170251

Copyright © 2021 K. Naresh et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.