IEEE Power Electronics Magazine - September 2020 - 66

Expert View

by Sitharthan Ramachandran

Applying AI in Power Electronics
for Renewable Energy Systems

he energy crisis is one of the
vital problems faced by the
world today. Due to the
increase in smart industries 4.0 and
household components, the electrical usage around the world has substantially increased the demand for
energy. Traditionally, nearly 72% of
the surplus energy demand has been
satisfied by conventional energy
resources and 28% by renewable
energy resources [1]. Because emission is considered as the preliminary
factor for the deteriorating environment, energy sectors have shifted
their focus towards renewable energy resources. With the advantage of
minimizing carbon pollution, renewable energy is a feasible solution to
make t he world safer and energy
proficient. It has been predicted that
45% of the load demand by 2024 will
be satisfied by renewable energy
resources and most of the increase
will likely come from solar, wind,
and hydropower [2].
The integration of renewable energy systems with the existing power
grid and energy storage are possible
only through a power electronic converter that has always presented
many challenges. However, a promising solution for obtaining optimal
performance out of the renewable
resources are developing an intelligent control strategy that can vary

Digital Object Identifier 10.1109/MPEL.2020.3012009
Date of current version: 15 September 2020

IEEE POWER ELECTRONICS MAGAZINE

The intelligent control strategy
the switching patterns of the power
also improves the integration of all
electronic converter depending on
m icro/macro renewable energ y
the load. Thus, effectively extracting
resources to build microgrid and
essential power from renewable enermanage distributed energy. The intelgy resources to obtain the maximum
ligent control strateamount of energy
gy enabled power
conversion. Advancelectronic convertes in artificial in The intelligent control
ers will play a vital
telligence (AI) such
strategy enabled power
role in solving the
a s deep neural netelectronic converters
quality and congesworks-IoT, and artiwill play a vital role in
tion issues in the
ficial neural network
solving the quality and
microgrid. The
blo ckc h a i n t e c h congestion issues in
power control in
niques are rapidly
energy harvesting
providing this intelthe microgrid.
multiple access sysligent control solutems w it h a n A I
tion to enhance the
algorithm has been developed in refoperation of power electronic conerence [4]. In this application, the
verters and, thereby, increase the perdeveloped intelligent algorithm conformance of the renewable energy
trols the power of the integrated
system by tracking the optimal
renewable energy sources and helps
power. For example, in a paper preto maintain its optimal performance
sented in the IEEE Transactions on
in battery and renewable resources.
Circuits and Systems, May 2020 [3],
The primary concern of the renewresearchers from the University of
able energy source integration is
Electronic Science and Technology of
improved safety and reliability. The
China, Chengdu, discuss an AI neural
development of AI and IoT has made
network-assisted maximum power
it possible to offer improved safety,
point tracking control for a solar enerefficiency, and reliability. The intelligy system. Applying the AI control
gent control strategy with IoT can
strategy, the researchers demonstrate
estimate the energy consumption
a solar energy harvesting system with
patterns, identify the energy leakage,
89.39% efficiency and a minimal
and ensure the health of the system.
tracking error of 0.01-0.5%. The study
For example, in the AI and IoT couclearly shows that the integration of
pled system the prognostic analysis
AI technique with power electronic
will gather the data from renewable
devices will increase the extraction
energy resources with the sensors to
of energy from renewable energy remonitor the wear and tear in the
sources with maximum efficiency.

z September 2020

IEEE Power Electronics Magazine - September 2020

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