Enhancing the maximum power of wind turbine using artificial neural network
Bashar Mohammed Salih, Khaleel Nawafal, Safwan Assaf Hamoodi
Abstract
Wind energy conversion systems (WECS) now play a significant role in meeting the world's energy needs. Several different approaches are used to try to increase the reliability of these renewable energy systems. Smart systems are designed to be more proactive to improve the performance of renewable energy equipment. Artificial neural networks (ANNs) have a variety of applications, including controlling renewable energy systems. Using optimal torque control (OTC) system based prediction techniques, a controller to monitor a maximum point of wind turbine output power (MPPT) is designed and modeled in this paper. MATLAB/Simulink package tools for neural networks are also used to design the controller and simulate it to achieve the necessary results and to obtain an appropriate analysis for the controller. The results show that the ANN is more active and delivers better output than the traditional controller.
Keywords
Artificial neural network; Maximum power point tracking controller fourth; Optimal torque control method; Wind turbine
DOI:
https://doi.org/10.11591/eei.v12i5.5019
Refbacks
There are currently no refbacks.
This work is licensed under a
Creative Commons Attribution-ShareAlike 4.0 International License .
<div class="statcounter"><a title="hit counter" href="http://statcounter.com/free-hit-counter/" target="_blank"><img class="statcounter" src="http://c.statcounter.com/10241695/0/5a758c6a/0/" alt="hit counter"></a></div>
Bulletin of EEI Stats
Bulletin of Electrical Engineering and Informatics (BEEI) ISSN: 2089-3191, e-ISSN: 2302-9285 This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU) .