A Buck-Boost-Flyback integrated converter for grid-connected wind-photovoltaic battery energy storage system using hybrid optimization assisted model

The power demand has increased dramatically in the modern era, which has caused a rapid exhaustion of fossil resources. Consequently, RES are used as input sources by the energy processor. Nowadays, power converters used in renewable energy sources like solar, wind, and fuel cells are commonplace for producing electricity for a load. A single fly-back converter and two buck-boost converters are combined into a single power switch with a single-phase layout to create the Buck-Boost-Fly Back Integrated Converter (BBFIC). Despite having the characteristics of buck-boost and fly-back converters, it avoids the problem of inverted voltage polarization and recycles the energy stored in the leaked inductor without the need for additional active clamp circuits. Additionally, for grid-connected gadgets, the BBFIC raises the voltage of the photovoltaic (PV) module to extremely high rates. The goal of this research is to provide an innovative structure for grid-tied PV-wind-BESS systems that increase the voltage gain of the BBFIC. It is intended to improve the converter's duty cycle to increase the voltage gain of the BBFIC. To achieve precise optimization, this study uses a hybridized technique called the Reminiscence-Insisted Sand Cat Swarm Optimization Approach (RI-SCS), which combines the principles of the Sand Cat Swarm Optimization Algorithm (SCSO) and the Crow Search Optimization Algorithm (CSA) for optimal results. In instance 2, the approach had chosen for irradiation pattern 1 works better with lower error rates than conventional HBA, AQO, CSO, and SCS designs, respectively, by 0.15 %, 0.08 %, 0.28 %, and 0.07 %. Finally, the experimental outcomes reveal the superiority of the suggested strategy with the number of metrics.