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This study proposes a new isolated intelligent adjustable buck-boost (IIABB) converter with an intelligent control strategy that is suitable for regenerative energy systems with unsteady output voltages. It also serves as a reliable voltage source for loads such as battery systems, microgrids, etc. In addition, the hill climbing (HC) maximum power point tracking (MPPT) algorithm can be utilized with this innovative IIABB converter to capture the MPP and then enhance system performance. In this converter, five inductors (LA, LB, LC, LD, and LE) and four power MOSFETs (SA, SB, SC, and SD) are used in the proposed novel isolated intelligent adjustable buck-boost (IIABB) converter to adjust the applied voltage across the load side. It also has a constant, stable output voltage. The new IIABB converter is simulated and verified using MATLAB R2021b, and the performances of the proposed IIABB converter and conventional SEPIC converter are compared. The solar photovoltaic module output voltages of 20 V, 30 V, and 40 V are given as inputs to the proposed IIABB converter, and the total output voltage of the proposed converter is 48 V. In the new IIABB converter, the duty cycle of the power MOSFET has a small variation. The proposed IIABB converter has an efficiency of 92~99%. On the other hand, in the conventional SEPIC converter, the duty cycle of a power MOSFET varies greatly depending on the relationship between the output and input voltage, which deteriorates the efficiency of the converter. As a result, this research contributes to the development of a novel type of IIABB converter that may be employed in renewable energy systems to considerably increase system performance and reduce the cost and size of the system.

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The multilevel inverters (MLIs) are capable of handling large quantities of power and generating high-quality output voltages. Consequently, the size of the filters is reduced, and the circuitry is simplified. As a result, they have a diverse range of uses in the industrial sector, especially in smart grids. The input voltage boosting feature is required to utilize the MLI with renewable energy. In addition, a large number of components are required to attain higher output voltage levels, which increases the cost of the circuit and weight. A variety of MLI topologies have been identified to reduce losses, device quantity, and device ratings. The selective harmonic elimination (SHE) approaches reduce distinct lower order harmonics by computing the ideal switching angles. This research presents a nine–level Packed E–Cell (PEC–9) inverter that uses selective harmonic elimination to eliminate total harmonic distortion. In order to calculate the best switching angle, the reptile search algorithm (RSA) is implemented in this paper, a nature–inspired metaheuristic algorithm inspired by the hunting behavior of the crocodile. The hunting behavior of crocodiles is implemented in two main steps: the first is encircling, which is accomplished by belly walking or high walking, and the second is hunting, which is accomplished by hunting cooperation or hunting coordination. In this technique, nonlinear transcendental equations have been solved. The simulation was run in the MATLAB R2021b software environment. The simulation results suggest that the RSA outperforms the other metaheuristic algorithms. Furthermore, the simulation result was validated on a hardware setup using DSP–TMS320F28379D in the laboratory.