Title: Red deer optimisation based asymmetrical reduced switch MLI with low switching loss and minimum voltage harmonics

Authors: Rupali Mohanty; Debashis Chatterjee; Swati Suman

Addresses: Department of Electrical Engineering, Jadavpur University, 700032, Kolkata, India ' Department of Electrical Engineering, Jadavpur University, 700032, Kolkata, India ' Department of Electrical Engineering, Jadavpur University, 700032, Kolkata, India

Abstract: In this research, an improved reduced multilevel inverter (MLI) design with a single active voltage source and the lowest possible power switches is proposed. Asymmetrical voltage sources power this reduced MLI using series capacitors connected to a single photo voltaic (PV) module. Due to the use of a minimal number of switching devices and input voltage sources, this MLI design also can be appropriate for integrating PV sources with low voltage grids. The constraints of the cascade H-bridge MLI and traditional two-level inverter have been overcome by the offered approach due to low switching loss and minimum switching stress. The variable capacitance ratio with respect to a reference value and the required switching pulses is calculated using a new metaheuristic technique called red deer optimisation (RDO) algorithm. The total harmonics distortion (THD) of the MLI output voltage has been reduced by this technique to 3.52%. To demonstrate the usefulness of the RDO method, its performance was compared to that of particle swarm optimisation (PSO) and Grey Wolf optimisation (GWO). In addition to simulation and experiment, the usefulness and productivity of this reduced MLI have been supported by these results.

Keywords: reduced H-bridge multilevel inverter; ML; red deer optimisation algorithm; RDO; total harmonics distortion; THD; asymmetrical voltage supply; modulation index; voltage grading.

DOI: 10.1504/IJPELEC.2024.137805

International Journal of Power Electronics, 2024 Vol.19 No.3/4, pp.261 - 284

Received: 25 Dec 2022
Accepted: 06 Apr 2023
Published online: 05 Apr 2024 *

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