International journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN:2313-626X

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 Volume 5, Issue 2 (February 2018), Pages: 90-96

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 Original Research Paper

 Title: ANFIS-based PI controller for maximum power point tracking in PV systems

 Author(s): Hisham Hussein 1, *, Ali Aloui 1, Badr AlShammari 2

 Affiliation(s):

 1Department of Electronics Engineering, Community College, Ha’il University, Hai’l, Saudi Arabia
 2College of Engineering, Ha’il University, Hai’l, Saudi Arabia

 https://doi.org/10.21833/ijaas.2018.02.015

 Full Text - PDF          XML

 Abstract:

This paper presents a maximum power point tracking (MPPT) control system which is designed to increase the energy generation efficiency of Photovoltaic (PV) arrays. Usually Maximum power point tracking control system uses dc-to-dc converters to compensate for the output voltage of the PV array in order to keep the voltage at the value, which maximizes the output power. The purpose of the work is to develop an adaptive neuro-fuzzy inference system (ANFIS)-based proportional integral controller. The operating temperature and level of irradiance constitute inputs for the ANFIS controller, allowing it to determine the maximum available power that the PV array possesses. The error between the reference power from the ANFIS controller and the measured voltage and current of the PV array enables the proportional integral controller to generate the duty cycle. It is shown that ANFIS-based PI controller gives better performance criteria, unlike conventional techniques which usually give associations at steady state operating conditions. Eventually, the proposed MPPT control system based on ANFIS could provide better results than conventional techniques in terms of performance, accuracy and stability. 

 © 2017 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Adaptive neuro-fuzzy inference system, Maximum power point, Fuzzy logic, Neural networks

 Article History: Received 15 September 2017, Received in revised form 12 December 2017, Accepted 18 December 2017

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2018.02.015

 Citation:

 Hussein H, Aloui A, and AlShammari B (2018). ANFIS-based PI controller for maximum power point tracking in PV systems. International Journal of Advanced and Applied Sciences, 5(2): 90-96

 Permanent Link:

 http://www.science-gate.com/IJAAS/2018/V5I2/Hussein.html

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