Maximum power point tracking in PV system using intelligence based P&O technique and hybrid cuk converter

The requirement for renewable energy sources is very high in recent years due to the acute energy crisis. Photovoltaic power is regarded as a chief source of energy in several countries with high solar power density. The main obstruction for reach of solar PV systems is their low efficiency and high capital cost. Therefore, controlling Maximum Power Point Tracking (MPPT) for the solar array has become an essential aspect in a PV generation as Maximum Power Point (MPP) changes with the solar radiation and temperature. In this paper, Perturbation and Observation (P&O) algorithm is used for maximum power point tracking as it has the potential to adjust the solar array reference voltage to attain maximum power point. P&O system has certain limitation which is overcome in this paper with the utilization of fuzzy based P&O. But, this produces oscillations in voltage conversion. To overcome this difficulty, a better converter should be used in voltage conversion. Cuk converter is one of the existing efficient converters in PV systems. One of main drawback in cuk converter is more duty cycles are required for better conversion and some oscillations will persist in voltage conversion. To overcome these drawbacks, hybrid boost mode cuk converter is used in this paper. In hybrid boost mode cuk converter, step up structure is used which will result in better conversion ratio and better damping of oscillations. The main advantage of this proposed system is that the efficiency of the hybrid boost mode cuk converter is increased. The system is simulated under different climatic conditions. The simulation model of controller is built in MATLAB / Simulink background, and the simulation result shows the reduction in oscillations and improvement in power conversion.