Comparative Study of DC-DC Converters in PV Systems Using Fuzzy Logic MPPT Algorithm
Digant Rastogi, Manika Jain, Mini Sreejeth
Abstract
In today's time, conventional methods of energy production based on fossil fuels are not sustainable to fulfil the global energy needs since they are the major contributors to global warming. To tackle such issues, renewable energy resources for energy generation are being adopted universally. Solar energy is at the forefront of renewable energy production. However, irregular solar irradiation and varying ambient temperature are limiting the widespread use of Photovoltaic (PV) systems. DC-DC Converters act as the most suitable option for DC voltage regulation and high efficiency for renewable energy resources to overcome these constraints. A PV system consists of a PV Array connected to a DC-DC Converter. The PV array exhibits a maximum power peak in its P-V characteristics. Hence, for greater efficiency the system is operated at this maximum power point by using Maximum Power Point Tracking (MPPT) algorithm. This paper examines the Fuzzy Logic Control (FLC) technique for driving the system at MPPT. A DC-DC converter must be selected as needed in the system. In this paper, a detailed comparative analysis of five popular DC-DC converters-boost, cascaded buck-boost, cuk, Single Ended Primary Inductance Converter (SEPIC) and zeta converter working with the FLC based MPPT method has been accomplished. Each converter is designed and then simulated in MATLAB/Simulink.