A New Effective APEAO Algorithm Assisted Positive Output-Super Lift Luo Converter with PV-Wind Energy System

Abstract

The importance of renewable energy resources in the energy province necessitates the use of photovoltaic (PV) and wind systems to power brushless DC (BLDC) motors for applications such as water pumping and automobiles. In this research, an optimized MPPT-based positive output super-lift Luo converter (PO-SLLC) is presented for a hybrid power system with a BLDC motor to overcome the constraints of ordinary DC–DC converters. The Luo converter produces a positive output voltage which aids in achieving a high power density with fewer ripples in the voltage and current profile. The output voltage grows in geometric progression, increasing the converter’s efficiency, according to its mathematical model. Adjustment parameter enhanced Aquila optimization (APEAO) is used to optimize the duty cycle of the PO-SLLC from the MPPT controller and the controller parameters of the PI controller of the wind system. The proposed system’s behavior for variations in irradiation patterns with constant load torque is simulated in MATLAB/Simulink. The settling time and overshoot obtained with the proposed optimized controller are compared to those obtained with other optimization controllers, such as ant colony optimization (ACO), genetic algorithm (GA), Aquila optimization (AO), advanced version of harmony search algorithm (2N[Formula: see text][Formula: see text][Formula: see text]1-HSA) and opposition based quantum bat algorithm (OQBA) and it is demonstrated that the proposed APEAO optimized controller has good dynamic performance.