Power Quality Improvement in Grid Connected PV System using Fuzzy Logic Controller based Maximum Power Point Tracing(MPPT)

Abstract

The expansion of the spread of solar photovoltaic power generation systems is fraught with challenges related to the low efficiency and performance of these systems in light of the change in the surrounding weather conditions and the disturbances associated with the loads, which weakens the electrical energy productivity of these photovoltaic systems due to energy loss. To overcome and reduce these challenges as much as possible, it is considered the use of controllers that track the maximum power point of photovoltaic systems is the ideal solution to increase their efficiency and improve the quality of their electrical power, in order to obtain the maximum productive capacity from these systems, and this will be reflected in achieving an optimum benefit from the available solar energy and thus reducing the loss of unused energy in the absence of the control system.This paper presents a study, analysis and simulation of the actual behaviour of the grid-connected solar photovoltaic system model by means of the (MATLAB/Simulink_R2018a) program. The performance of Fuzzy Logic Controller is then evaluated to track the path of the maximum power point, and its work is based on tracking techniques that use the direct control method to control the operating cycle of the DC commutator, which in turn performs by feeding the inverter with the maximum output power from the solar photovoltaic system.A tracking technology was selected that relies on the method of artificial intelligence, which is the technique (fuzzy logic controller), and a fuzzy logic controller of the type (Mamdani) was used. The most suitable for tracking the maximum power point at the steady state of the Grid and under constant and changing weather conditions, as well as choosing the most appropriate controller when transient disturbances occur in the Grid under constant weather conditions only. The results proved the effectiveness of the fuzzy logic controller, and it had good performance in tracking the maximum power point in terms of achieving more stability, reducing error and settling time.