Faculty of Electrical Engineering, Hamedan University of Technology,Hamedan, Iran
Abstract
In order to use photovoltaic cell effectively and improve its photoelectric conversion efficiency, the maximum power point of photovoltaic generation system should be tracked rapidly and stably. In this paper after comparison and analysis common methods used in controller of photovoltaic systems such as Fuzzy and P&O, proposed an approach combined from FLC and particle swarm optimization algorithm (PSO) as an appropriate method to achieve maximum power point tracking (MPPT). Indeed Fuzzy logic control can cope with photovoltaic system using heuristic knowledge rules, but tuning the control parameters is not straightforward. PSO performs an on-line haphazard global search for input and output scaling factors of a PD-type fuzzy controller. The objective function of the PSO algorithm has been defined to minimize slope of P-V curve. The simulation results in SIMULINK of MATLAB indicate that proposed method can effectively eliminate the power oscillation around MPP and raise stability and reach steady state of the system.
Imani, M., & Delavari, H. (2017). Tuning a PD-type Fuzzy Controller by Particle Swarm Optimization for Photovoltaic Systems to Achieve Maximum Power Point Tracking. Journal of Solar Energy Research, 2(2), 33-39.
MLA
M. Imani; H. Delavari. "Tuning a PD-type Fuzzy Controller by Particle Swarm Optimization for Photovoltaic Systems to Achieve Maximum Power Point Tracking". Journal of Solar Energy Research, 2, 2, 2017, 33-39.
HARVARD
Imani, M., Delavari, H. (2017). 'Tuning a PD-type Fuzzy Controller by Particle Swarm Optimization for Photovoltaic Systems to Achieve Maximum Power Point Tracking', Journal of Solar Energy Research, 2(2), pp. 33-39.
VANCOUVER
Imani, M., Delavari, H. Tuning a PD-type Fuzzy Controller by Particle Swarm Optimization for Photovoltaic Systems to Achieve Maximum Power Point Tracking. Journal of Solar Energy Research, 2017; 2(2): 33-39.
)