An extensive use of fossil fuel has led to an extreme increment of carbon footprint in the
world globally. Glaciers are melting on the earth’s poles due to the greenhouse effect. Many such
natural indications urge us to adopt renewable energy sources. In most cases, renewable power is
generated in electrical form, which does not suit the existing grid requirements. Cascaded H bridge
with multilevel inverter topology is promising in this context. The output of the multilevel inverter
is near to sinusoidal. It has added advantages of low device stress, no need for step-up transformers,
low common-mode voltage, near sinusoidal input current, low switching frequency, and reduced
harmonics. The direct output of Cascaded H bridge multilevel inverters may not be suitable for
many applications like integrating solar panel output with an existing grid where harmonic reduction
is necessary. Various modulation techniques are available like sinusoidal pulse width modulation,
space vector modulation, and selective harmonic elimination. Among the listed modulation techniques,
selective harmonic elimination can be implemented with the low switching frequency, and it
is suitable where low electromagnetic interference, low switching loss, and good power quality are
required. To reduce the harmonics, one must solve the non-linear transcendental output equations of
the cascaded H-bridge Multilevel inverter (CHB-MLI). Various Artificial Intelligent (AI) algorithms
are introduced, and researchers have worked on eliminating harmonics or minimizing Total Harmonics
Distortion (THD) from the output of CHB-MLI. This paper gives a review of the harmonic
reduction using some of the well-known explored AI algorithms. It also provides insight into some
of the unexplored algorithms in this area.
Harmonic Reduction of a Single-Phase Multilevel Inverter Using Genetic Algorithm and Particle Swarm Optimization
