A MULTIPORT NON-ISOLATED DC-DC CONVERTER FOR HYBRID ENERGY SOURCES BY USING ANN CONTROLLER

The purpose of this paper is to develop a multiport non-isolated DC-DC converter by using an Artificial Neural Network (ANN) based controlling algorithm. In the existing works, various multiport converter and controlling algorithms are developed for improving the power quality and regulating the voltage of hybrid energy storage systems. Still, some of the models are difficult to understand and require an increased component, high power loss, and reduced efficiency. Therefore, the proposed work intends to develop an ANN-based multiport converter, which helps to regulate the voltage according to the desired level properly. Moreover, this converter has many inputs that are connected and operated simultaneously. The hybrid energy sources considered in this work are solar Photovoltaic (PV) cells, wind, and fuel cells. These sources are connected in parallel, and their output is fed to the non-isolated converter as a single input. Since the input sources fluctuate, their output voltage does not maintain a constant value. In order to maintain the constant outputs, an ANN-based controlling algorithm is deployed in this paper, which helps to boost the level of output voltage properly. In addition to that, the Maximum Peak Point Tracking (MPPT) controlling method is utilized to obtain the maximum energy from the input DC source. Then, a rechargeable battery utilizes the backup supply for power generation. During simulation, the whole system is implemented and tested by using the MATLAB/Simulink platform. The obtained results reveal that the ANN-based controlling technique could efficiently reduce the spikes and maintain the constant output at all times.