An improved MPPT controller for photovoltaic system using fuzzy logic-particle swarm optimization

Aji Akbar Firdaus, Riky Tri Yunardi, Eva Inaiyah Agustin


Photovoltaic (PV) is a renewable source of electrical energy. Because PV can convert solar energy into electrical energy. However, the level of PV power efficiency is less good. To get Maximum Power Point (MPP) from PV, Maximum Power Point Tracking (MPPT) is needed. There are several methods to adjust the duty cycle of MPPT. In this paper, the duty cycle is controlled by Fuzzy Logic-Particle Swarm Optimization (FL-PSO) to get optimal MPP with the small ripple and oscillation from MPPT. From the simulation results, the values of output current, voltage, and power from the boost converter are 3.464 A, 183.6 V, and 637.7 W, respectively. The ripple of output power from PV with FL-PSO is 69.5 W. The time required by Fuzzy Logic-PSO reaches MPP is 0.354 s. The results of the proposed algorithm are compared with the PSO method. The results show that the MPPT technique using Fuzzy Logic-PSO indicates better performance and faster than the PSO method.


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