Contents I. Introduction
Inverters are inevitable in various applications that require AC power, such as solar power systems, wind turbines, electric vehicles, and grid-tied power systems. Multilevel inverter allows for the acquisition of staircase output voltage through a combination of DC voltage sources [1]. Reducing particular lower-order odd harmonics with the help of selective harmonic elimination (SHE) process., the required fundamental output can be produced. The advantages of SHE are low switching loss, small filter size, and the absence of harmonic interfer-ence, making it a very suitable technique for high-voltage applications [2]. Analytical methods are usually employed to solve SHE equations and calculate the switching angles. The main advantage of SHE is the capacity to adjust switching pulse angles in inverters to diminish lower-order selected harmonics. Because of nonlinear transcendental equations of output waveform, it is difficult to calculate switching pulse angles. Popular Newton-Raphson (N-R) method [3] can be employed to determine solutions for nonlinear transcendental equations. However, these methods necessitate highly precise initial approximations that can accurately depict the solution pattern. Alternatively, the resultant theory [4] method can be utilized for harmonic suppression, but this technique has certain drawbacks, such as complexity and high computational time. Overall, while there are multiple methods available for inverter design, each comes with its own merits and limitations. Evolutionary algorithms have been proven to be effective in finding solutions for eliminating low order-harmonics. Some commonly used evolutionary algorithms in the literature include Genetic algorithms, Particle Swarm Optimization, Bee Algorithm(BA), and Red Deer Algorithm(RDA) [5]. GA and PSO are simple and effective algorithms for finding optimal solutions to complex problems.
