Fractional Order PID Controller Design for Maximum Power Point Tracking of Dynamic Loaded PV System

Abstract

PV installations and systems running under variable irradiation and temperature, produce a variance in its output voltage, resulting in control challenges. The constant output voltage from such systems despite the variations in the produced voltage and load is maintained by employing a DC converter. This paper presents the design of a maximum power point tracking (MPPT) on DC converter controller for a system. Fractional Order Proportional-Integral-Derivative (FOPID) and Proportional-Integral-Derivative (PID) controllers have been implemented to the system converter as a proposed control approach. Particle Swarm Optimization (PSO) is used as optimization technique for determining the optimal parameters of (FOPID & PID) controllers for tracking the output voltage from trained Adaptive Neuro Fuzzy Inference System (ANFIS) that is corresponding to maximum power generated from (PV) module. The PV system with the dynamic load is modeled and simulated by using the MATLAB/Simulink environment. The system performance is displayed in the form of a family of curves under different operating conditions. a result of the additional power gathered from the modules [3]. This study presents the design of a maximum power point tracking MPPT controller on the DC converter for a dynamic loaded PV system. As a control technique, the optimal PID (PID) and a fractional order PID (FO-PID) controllers are proposed. The introduced MPPT method employs an Adaptive Neuro Fuzzy Inference System (ANFIS). The system converter will be controlled by the proposed controllers. The parameters of both PID & FO-PID controllers have been optimized using the Particle Swarm Optimization PSO method to track the output voltage from the ANFIS unit which will be equivalent to the maximum power generated by the PV module. The PV system with the dynamic load is modeled and simulated using the MATLAB/Simulink environment. A family of curves are used to illustrate the system performance under various operating conditions This work presents a model of photovoltaic PV array supplying a dynamic load as a DC motor via DC– DC converter. PID & FOPID controllers are used for tracking the voltage Vmpp corresponding to the maximum power point Pmpp of the PV array. The desired value for Vmpp of the PV has been generated from a trained Adaptive Fuzzy Inference System ANFIS. Particle swarm optimization PSO is used as the optimization technique for determining the optimal parameters of both the PID and the FOPID controllers for maximum power point tracking MPPT of the PV system. The overall system is modeled and simulated by Simulink in MATLAB program. FOPID controller was more efficient in improving the response characteristics as well as reducing the steady state-error, rise time, settling time and maximum overshoot.