Implementing GA-ANFIS for Maximum Power Point Tracking in PV System

Alireza Rezvani; Maziar Izadbakhsh; Majid Gandomkar  and Saeed Vafaei

doi:10.17485/ijst/2015/v8i10/51832

Article

Implementing GA-ANFIS for Maximum Power Point Tracking in PV System

VIEWS 1901
PDF 204

Abstract
Full-Text HTML
Full-Text PDF
How to Cite

Indian Journal of Science and Technology

DOI: 10.17485/ijst/2015/v8i10/51832

Year: 2015, Volume: 8, Issue: 10, Pages: 982–991

Original Article

Implementing GA-ANFIS for Maximum Power Point Tracking in PV System

Alireza Rezvani ^{1 *}, Maziar Izadbakhsh¹ , Majid Gandomkar² and Saeed Vafaei ²

¹Young Researchers and Elite Club, Saveh Branch, Islamic Azad University, Saveh, Iran; alireza.rezvani.saveh@gmail.com

²Department of Electrical Engineering, Saveh Branch, Islamic Azad University, Saveh, Iran

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Nowadays, it has been a developing consideration towards utilization of photovoltaic (PV) system. This paper proposes the Adaptive Neuro-Fuzzy Inference System (ANFIS) and an integrated offline Genetic Algorithm (GA) to track the PV power based on different circumstances due to the various climate changes. Training data in ANFIS are optimized by GA. The proposed controller is accomplished and studied applying Matlab/Simulink software. The results show minimal error of Maximum Power Point (MPP), Optimal Voltage (Vmpp ) and superior capability of the suggested method in MPP tracking.

Keywords: ANFIS, GA, MPPT, Photovoltaic System