Improved Clamped Z-Source Converter with Optimized Maximum Power Point Tracker for Hybrid Renewable Energy Systems Based Energy Management System

Abstract

In light of the intermittent and seasonal nature of wind and solar energy, electrical systems are becoming more problematic to operate. The purpose of the work is to establish an energy storage system that helps to minimize such operational challenges, which are essential to improve grid stability and reliability. The tasks solved in the article to achieve the given goal are the following: incorporating an energy management system with the aid of improved converter and optimized maximum power point (MPPT) for (Photovoltaic) PV and PMSG (permanent magnet synchronous generator) based wind system. On comparing with conventional Z-source converters, a novel improved clamped Z-source converter, which is utilized in this work has high efficiency with low THD and it has the capacity to protect electrical circuits against damage caused by short circuits, overcurrent and overvoltage. The Pulse Width Modulation (PWM) rectifier is implemented to convert AC-DC supply obtained from the PMSG wind system. Firefly optimization with an aid of Radial Basis Function Neural Network (RBFNN) technique is employed as an MPPT system for extracting optimal power from photovoltaic system. The excess energy obtained from the hybrid sources are stored in the battery and it is controlled by the recurrent neural network (RNN) with the bidirectional converter. The overall developed system is executed in MATLAB software and the most important outcomes are demonstrated in terms of high efficiency with 91.2%, high tracking efficiency of 98.54% and reduced THD of 2.45% respectively. The significance of results obtained in this research lies in the advancement of renewable energy integration technologies. By overcoming the challenges associated with intermittent energy sources, the developed system contributes to the improvement of grid stability and reliability.