Single-Ended Primary Inductor Converter (SEPIC) Converter, DC-DC Boost, and Cuk Converters with a Self-Guided Reimanuian Residual Network: Optimisation of Solar Energy

Finding solutions to reduce emissions of carbon dioxide, which is a toxic gas that produces negative changes on a worldwide scale, is the difficulty that the greenhouse effect faces in the present day. Solar power, which takes advantage of a solar array system that is made up of a variety of components, is one of the environmentally beneficial energy sources. The Maximum Power Point Tracker (MPPT), which ensures that the system generates the most amount of electricity possible, is an essential component of this system. The Insulated Gate Bipolar Transistor (IGBT), which modifies the system's resistance, receives a signal from the MPPT via a Pulse Width Modulator (PWM). The Perturbation and Observation (P&O) algorithm was utilized by conventional controllers; however, it was unable to cope with the rapid changes that occurred in the environment. The new Self-guided Reimannian residual network (SGRRNN) controller produced to enhances efficiency by rapidly adjusting to alterations. The hyperparameters of SGRRNN is optimized using the Energy Valley Optimizer to improve the efficiency. Boost, Cuk, and Single-Ended Primary Inductor Converter (SEPIC) converters are the three DC-DC converters that are compared in this work with the SGRRNN controller on the basis of three data sets consisting of 104, 201, and 1001 respectively. This outcomes in an increase in the effectiveness of solar photovoltaic (PV) systems, with the SGRRNN controller obtaining a peak efficiency of 96.2275% when that controller is integrated with a DC-DC Boost converter.