Mayfly Optimization Approach Based Photovoltaic Supplied SRM Driven Water Pumping System Under Partial Shading Conditions

Water pumping systems play a crucial role in sustaining human life by addressing essential needs such as drinking water, agricultural irrigation, and various industrial processes. Implementing renewable energy sources, particularly standalone water pumping models supplied by Photovoltaic (PV) technology, can offer a more efficient solution for water supply across diverse regions. In numerous instances, the presence of several water pumping units is crucial to meet the demand. This research focuses on two water pumping systems that are managed by a shared PV system and a common converter. The switched reluctance motor (SRM) is especially distinguished for its outstanding performance for these applications, where the role of an electric motor is vital for effective water pumping. The adoption of PV-fed SRM in place of batteries allows the system to reduce costs and maintenance associated with battery operation. To enhance regulation, sensorless speed control and a sliding mode control (SMC) have been integrated. Partial shading is a common occurrence in PV systems, which can adversely affect power generation. The maximum power point under partial shading conditions (PSCs) may not be accurately estimated using the Perturbed and Observe (P&O) approach alone. The combination of the Mayfly algorithm and the P&O method has the potential to enhance efficiency in the management of PSCs. This research examines the effectiveness of maximum power point tracking (MPPT) across different PSC scenarios, and it contrasts the findings with those derived from the Modified Grey Wolf Optimizer (MGWO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA). The integration of the recommended MPPT algorithm into SMC could transform the converter into an effective MPPT operation. Further proposed control methodology utilized TS-Fuzzy controller to achieve effective operation. Hardware-in-the-loop (HIL) testing has been used to verify the effectiveness of the suggested method on the OPAL-RT platform.