Performance enhancement of multi-port bidirectional DC-DC converter using resilient backpropagation neural network method

The world's energy consumption has been growing at an exponential rate. Traditional energy sources such as coal, oil, and gas must be replaced by renewable energy sources which are readily available and non-polluting. The combined solar photovoltaic and hybrid systems have several advantages including consistent output power during the daytime and at night. Three significant parts of a hybrid energy system are the power generation system, energy storage (batteries) and power conditioning modules. A new multi-port DC-DC power converter is proposed in this research to deal with the intermittent nature and slow responsiveness of renewable energy applications. In addition to the energy storage unit, the proposed converter incorporates a DC-DC converter, and the suggested circuit incorporates several renewable energy sources. When the primary energy supply is unavailable, battery storage devices store extra power and discharge it to meet peak power demand. The load is connected to two input ports and one output port in a three-port converter. The two input ports, namely photovoltaic and battery storage systems, are coupled to the first and second ports. This research work is based on the split-type secondary port for hybrid energy systems. The secondary port consists of both energy storage and solar energy source and both are switched alternatively using a bi-directional switching topology. The improvements in voltage boost ratio, output power and efficiency are presented in the proposed work. By regulating the Maximum Power Point Tracking, Resilient Back Propagation and Adaptive Neuro-Fuzzy Interference (ANFIS) approaches are utilised to harvest maximum power from the photovoltaic system (MPPT). The suggested hybrid energy system uses an isolated converter topology to isolate the input from the load. The Adaptive Neuro-Fuzzy Controller is realized using the Back Propagation Method which obtains a good result in voltage transfer ratio and net efficiency. •Proposed improvements in voltage boost ratio, output power and efficiency.•Resilient Back Propagation and Adaptive Neuro-Fuzzy Interference (ANFIS) method are used for mining extreme power from photo-voltaic system by controlling Maximum Power Point Tracking (MPPT) Switch.•Proposed isolated converter topology for hybrid energy system.•Discussed the importance of a three-port converter for standalone applications.•Proposed to reduce the inductor current settling time.