An Experimental Estimation of Hybrid ANFIS-PSO-Based MPPT for PV Grid Integration Under Fluctuating Sun Irradiance

• Published in: IEEE systems journal Vol. 14; no. 1; pp. 1218 - 1229
• Main Authors: Priyadarshi, Neeraj, Padmanaban, Sanjeevikumar, Holm-Nielsen, Jens Bo, Blaabjerg, Frede, Bhaskar, Mahajan Sagar
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: adaptive neuro-fuzzy inference system–particle swarm optimization (ANFIS–PSO); Adaptive systems; Algorithms; Ant colony optimization; Artificial neural networks; Circuits; Computer architecture; Control algorithms; Converters; Estimation; Fuzzy logic; fuzzy logic control (FLC); Fuzzy systems; Hybrid power systems; Impedance matching; Inverters; Irradiance; Mathematical model; Maximum power point trackers; maximum power point tracking (MPPT); Maximum power tracking; Particle swarm optimization; photovoltaic (PV) system; Photovoltaic cells; Space vector modulation; space vector modulation hysteresis current controller (SVMHCC); Sun; Tracking control; Zeta converter

To enhance the photovoltaic (PV) power-generation conversion, maximum power point tracking (MPPT) is the foremost constituent. This article introduces an adaptive neuro-fuzzy inference system-particle swarm optimization (ANFIS-PSO)-based hybrid MPPT method to acquire rapid and maximal PV power with...