Universiti Teknologi Malaysia Institutional Repository

Adaptive neuro fuzzy inference systems based maximum power point tracking for a photovoltaic system connected to a grid

Mohammed, Karam Khairullah and Buyamin, Salinda and Mekhilef, Saad and Rosmin, Norzanah and Shamsudin, Mohamad Amir (2022) Adaptive neuro fuzzy inference systems based maximum power point tracking for a photovoltaic system connected to a grid. In: 3rd International Conference on Control, Instrumentation and Mechatronics Engineering, CIM 2022, 2 March 2022 - 3 March 2022, Virtual, Online.

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Official URL: http://dx.doi.org/10.1007/978-981-19-3923-5_32

Abstract

This paper presented an adaptive neuro fuzzy inference system (ANFIS) for photovoltaic (PV) connected to the grid system for fast and precise maximum power point tracking (MPPT) in various weather conditions. Due to the high cost of sensors and the inaccuracy of irradiance readings, this study suggested an ANFIS approach for tracking maximum power without irradiance and voltage sensors. Instead, it relied on an equation to estimate the irradiance value. The generated power by PV is converted to the grid via a voltage source converter (VSC). MATLAB/SIMULINK has been used to simulate the proposed controller. As per simulation results, the proposed method was shown to be effective in all of the tested cases. A comparison with particle swarm optimization algorithm (PSO) and Perturb and Observe (P&O) has been provided to assess the efficacy of the proposed method. The results demonstrated the efficacy of the proposed technique by providing a rapid and precise tracking in 0.02 s with high efficiency.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:ANFIS MPPT, maximum power point tracking, PV system
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Faculty of Engineering - School of Electrical
ID Code:100697
Deposited By: Yanti Mohd Shah
Deposited On:30 Apr 2023 08:48
Last Modified:30 Apr 2023 08:48

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