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ABSTRACT
This paper explicates a standalone solar photovoltaic system design to track maximum power by utilising intelligent adaptive control algorithms. Conventional MPPT algorithms are not efficient enough to follow the maximum power variable irradiation and temperature conditions. Therefore, an intelligent algorithm has been required to extract the maximum power in a standalone PV system. The present paper incorporates adaptive intelligent maximum power point tracking (MPPT) method adaptive neuro-fuzzy inference system (ANFIS) techniques to extract maximum voltage and power. The fuzzy logic controller (FLC) has been implemented to analyse the performance compared to the ANFIS method. Because of the utilisation of conventional techniques, the point of maximum power gets oscillated in a low irradiance level and the values move between forward and backwards but do not have a fixed value. The used ANFIS method takes all the possibility values from 0 to 1, increasing efficiency. The efficiency of the ANFIS-based MPPT method is 90% more accurate than those of other conventional methods, which has been presented in the paper. For the remote monitoring of the obtained voltage, current and power, internet of things (IoT) features have been incorporated into the considered standalone PV system. The presented standalone PV system has been experimentally verified and validated for the efficiency evaluation of the proposed ANFIS algorithm.
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No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Santanu Kumar Dash
Santanu Kumar Dash has received the Ph.D. degree in Electrical Engineering from National Institute of Technology Rourkela, India in 2019. His research interest include power quality, grid connected systems, distributed generations and embedded system application for power converter control. He is currently working as Senior Assistant Professor in TIFAC-CORE Research Center, Vellore Institute of Technology, India.
Priyanka Garg
Priyanka Garg has received the M.Tech degree from VNRVJIET, Hyderabad. Her expertise include embedded systems, Internet of Things, Embedded controllers. She has published many research papers in international conferences. She is also an industrial expert in Artificial Intelligence for development of industry level controllers.
Soumya Mishra
Soumya Mishra has received the Ph.D. degree in electrical engineering at the National Institute of Technology Rourkela, Odisha, India. His research interests include power system, custom power devices, active power filtering, modeling and control of PV systems.
Suprava Chakraborty
Dr. Suprava Chakraborty had completed Ph.D. in Electrical Engineering (Solar Photovoltaic) from IIT(ISM) Dhanbad in 2016. She is currently working as Assistant Professor in the TIFAC-CORE Research Center at VIT, Vellore. She is having 3 years’ experience as Research Scientist and in -charge of Advanced Solar Photovoltaic Lighting System Laboratory at National Institute of Solar Energy (An Autonomous Institute of Ministry of New and Renewable Energy, Govt. of India), Gurgaon, India. She completed her M.Tech in Energy Technology from Tezpur University and B.Tech in Electrical Engineering from West Bengal University of Technology.
Devaraj Elangovan
Dr. Devaraj Elangovan received the B.E. degree in electrical and electronics engineering from Madras University, Tamilnadu, India in 2003. the M.Tech degree in power electronics and drives from Sri Venkateswara college of Engineering (Anna University), Tamilnadu, India, in 2005, and the Ph.D degree in analysis, design and implementation of high gain dc–dc converters for fuel cell applications from the Vellore Institute of Technology, University, Vellore in 2016. Now he is an Associate Professor and Deputy Director -Technology Information Forecasting and Assessment Council (TIFAC) VIT Vellore.