  The purpose of this paper is to explore the applications of quantum computing
to energy systems optimization problems and discuss some of the challenges
faced by quantum computers with techniques to overcome them. The basic concepts
underlying quantum computation and their distinctive characteristics in
comparison to their classical counterparts are also discussed. Along with
different hardware architecture description of two commercially available
quantum systems, an example making use of open-source software tools is
provided as a first step for diving into the new realm of programming quantum
computers for solving systems optimization problems. The trade-off between
qualities of these two quantum architectures is also discussed. Complex nature
of energy systems due to their structure and large number of design and
operational constraints make energy systems optimization a hard problem for
most available algorithms. Problems like facility location allocation for
energy systems infrastructure development, unit commitment of electric power
systems operations, and heat exchanger network synthesis which fall under the
category of energy systems optimization are solved using both classical
algorithms implemented on conventional CPU based computer and quantum algorithm
realized on quantum computing hardware. Their designs, implementation and
results are stated. Additionally, this paper describes the limitations of
state-of-the-art quantum computers and their great potential to impact the
field of energy systems optimization.
