Abstract

In our study, we present a new Smart Control-Driven Asymmetric Multilevel Inverter (SCDAMLI) which is aimed to minimize the quantity of power semiconductor switches and maximize the quantity of levels of the output voltages. The inverter overcomes major issues of efficient and quality power conversion especially in systems of renewable energy as well as in the application of electric vehicles (EV). The suggested cross-structured architecture greatly reduces the number of components by optimizing switch set-up to make the system small and less expensive. A boost converter coupled with an improved ANFIS-based Maximum Power Point Tracking (MPPT) algorithm is utilized in order to make a solar photovoltaic (PV) module as efficient as possible in terms of energy recovery. Although multilevel inverters have advantages of a better power quality, it is known to have reliability issues due to total harmonic distortion (THD) and complicated circuitry. The SCDAMLI eliminates these shortcomings by providing 23 output voltage levels with asymmetric DC sources, providing better performance with fewer components. The inverter switching is controlled by an intelligent Teaching Learning Based Optimization (TLBO) algorithm, which guarantees good quality of voltage output and has a much lower THD. Under varying operating conditions, the system performance is assessed using the MATLAB/SIMULINK. It has been found that with the addition of an appropriately designed LC output filter, the inverter output meets IEEE standard 519 harmonic requirements, and hence is suitable in grid-connected renewable energy and electric vehicle systems.

Keywords

Asymmetric Multilevel Inverter, Reduced Switch Topology, ching–Learning-Based Optimization (TLBO), ANFIS-Based MPPT, Smart Control Strategies, Renewable Energy Integration,

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References

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