Modelling and Design of ANN-based MPPT Controller of SEPIC Converter for SPV Application

An Artificial Neural Network (ANN) based Maximum Power Point Tracking (MPPT) algorithm fed Single Ended Primary Inductor Converter (SEPIC) is represented in this paper. For Solar photovoltaic (SPV) applications, as the output power depends on atmospheric conditions, MPPT is required for the successful extraction of maximum power. Steady-state and Small-signal modelling of the converter, in continuous current conduction mode, is analyzed. To improve the stability of the system, an Input Voltage Control (IVC) is developed with proper implementation of a PI-Compensator. Finally, a MATLAB simulation prototype, of 250W 48V, is created, and various voltage and current of the SEPIC converter's properties are verified. Additionally, the enhancement of ANN-MPPT performance is verified by comparison with other conventional MPPT techniques.