2019/05/02 by Akshay Ajagekar, Fengqi You · 2 citations
Computer Science · Energy · Engineering · Mathematics · Physics and Astronomy · #Algorithm #Computational science #Computer engineering #Computer science #Distributed computing #Mathematical optimization #Mathematics #Microgrid Control and Optimization #Optimization problem #Photovoltaic System Optimization Techniques #Quantum #Quantum Computing Algorithms and Architecture #Quantum algorithm #Quantum computer #Theoretical computer science #math.OC #quant-ph
paper · pdf · doi:10.1016/j.energy.2019.04.186
published as Energy, Volume 179, Pages 76-89 (2019)
openalex publication_date 2019/05/02 · arxiv created 2020/02/29 · arxiv updated 2020/03/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.