Hybrid Energy Integration via ZETA Converter and ANN Assisted MPPT for Enhanced System Reliability

A sensible way to fulfill the increasing need for energy while reducing its environmental impact is to include Renewable Energy Sources (RES), such as solar and wind power, into hybrid energy systems. By optimizing the technoeconomics of such systems with the use of a Zeta converter and Artificial Neural Network (ANN) assisted Maximum Power Point Tracking (MPPT), the study aims to increase overall system dependability. The Zeta converter is used to raise the photovoltaic (PV) panel's output voltage. Under a variety of environmental circumstances, the ANN-assisted MPPT method is used to extract power from solar panels. The proposed work simulated through the use of Matlab Platform. According to the findings, the proposed system with the Zeta converter and ANNassisted MPPT performs better than traditional systems in terms of energy output and cost-effectiveness. The viability of large-scale implementation is shown by the economic analysis, which shows a good return on investment. In order to optimize hybrid renewable energy systems and create robust and sustainable energy infrastructures, this research highlights the potential of sophisticated power electronic converters and intelligent control algorithms. The efficiency achieved with the Zeta converter is 92.5 % and tracing efficiency of the ANN based MPPT is 93 %.