Fopid Controllers Based Forward DC to DC Converter With Modified Osprey Optimization Algorithm for MPPT of PV System Under Partial Shading Conditions

Everywhere, electric power is needed for a variety of functions and tasks. Creating electric power through renewable resources, like solar energy, is a practical way to solve a lot of issues. Typically, photovoltaic modules use solar radiation to generate electricity. To guarantee maximum usage or optimal efficiency, a photovoltaic system must be equipped with a maximum power point tracking converter (MPPTC). In this paper, a DC to DC forward converter is chosen to function as MPPTC. For MPPTC under uniform sun irradiances, a variety of traditional methods are available, such as incremental conductance, perturb, and observe. However, trees, shade, dust, birds, clouds, and other factors will cause photovoltaic modules - of which many are coupled to make a power production unit - to receive non-uniform irradiances. The system enters a partial shading condition (PSC) as a result of this event. Conventional algorithms may be failed to approach the maximum utilization point to increase energy extraction under PSC. Therefore, to operate the power unit at its optimal usage under the situation of PSC, an optimization method is needed. In this study on MPPTC, an optimization method called the “Modified Osprey Optimization Algorithm (MOOA)” is designed to gather more energy during PSCs. This research also compares MOOA, Modified Invasive Weed Optimization (MIWO), Modified Grey Wolf Optimization (MGWO), and Whale Optimization Algorithm (WOA). OPALRT technology is used to create the Hardware-in-the-Loop, which gathers diverse outcomes for analysis under different operations.