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iEnergy 2022, 1(2): 170-187 https://doi.org/10.23919/IEN.2022.0021
Review | Open Access | Issue | Published: 15 July 2022

Quantum computing in power systems

Show Author's Information Yifan Zhou1,  Zefan Tang2,  Nima Nikmehr1,  Pouya Babahajiani1,  Fei Feng1,  Tzu-Chieh Wei3,  Honghao Zheng4,  Peng Zhang1,2( )
Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY 11794, USA
Interdisciplinary Science Department, Brookhaven National Laboratory, Upton, NY 11973, USA
CN Yang Institute for Theoretical Physics and Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY 11794, USA
Smart Grid and Technology, Commonwealth Edison, Oakbrook, IL 60523, USA
Keywords:
Quantum computing, power system, variational quantum algorithms, quantum optimization, quantum machine learning, quantum security
Cite this article:
Zhou Y, Tang Z, Nikmehr N, et al. Quantum computing in power systems. iEnergy, 2022, 1(2): 170-187. https://doi.org/10.23919/IEN.2022.0021
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Abstract Full text About this article

Electric power systems provide the backbone of modern industrial societies. Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems. However, today’s power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources, as well as managing huge volumes of data accordingly. These unprecedented challenges call for transformative analytics to support the resilient operations of power systems. Recently, the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations. Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems, which may lead to ultra-scalable and efficient power grid analytics. This paper reviews the newly emerging application of quantum computing techniques in power systems. We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives, including static analysis, transient analysis, stochastic analysis, optimization, stability, and control. We thoroughly discuss the related quantum algorithms, their benefits and limitations, hardware implementations, and recommended practices. We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era. Finally, we discuss challenges and future research directions. This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids.


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About this article

Quantum computing in power systems

Show Author's information Yifan Zhou1, Zefan Tang2, Nima Nikmehr1, Pouya Babahajiani1, Fei Feng1, Tzu-Chieh Wei3, Honghao Zheng4, Peng Zhang1,2( )
Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY 11794, USA
Interdisciplinary Science Department, Brookhaven National Laboratory, Upton, NY 11973, USA
CN Yang Institute for Theoretical Physics and Department of Physics and Astronomy, Stony Brook University, Stony Brook, NY 11794, USA
Smart Grid and Technology, Commonwealth Edison, Oakbrook, IL 60523, USA

Abstract

Electric power systems provide the backbone of modern industrial societies. Enabling scalable grid analytics is the keystone to successfully operating large transmission and distribution systems. However, today’s power systems are suffering from ever-increasing computational burdens in sustaining the expanding communities and deep integration of renewable energy resources, as well as managing huge volumes of data accordingly. These unprecedented challenges call for transformative analytics to support the resilient operations of power systems. Recently, the explosive growth of quantum computing techniques has ignited new hopes of revolutionizing power system computations. Quantum computing harnesses quantum mechanisms to solve traditionally intractable computational problems, which may lead to ultra-scalable and efficient power grid analytics. This paper reviews the newly emerging application of quantum computing techniques in power systems. We present a comprehensive overview of existing quantum-engineered power analytics from different operation perspectives, including static analysis, transient analysis, stochastic analysis, optimization, stability, and control. We thoroughly discuss the related quantum algorithms, their benefits and limitations, hardware implementations, and recommended practices. We also review the quantum networking techniques to ensure secure communication of power systems in the quantum era. Finally, we discuss challenges and future research directions. This paper will hopefully stimulate increasing attention to the development of quantum-engineered smart grids.

Keywords: Quantum computing, power system, variational quantum algorithms, quantum optimization, quantum machine learning, quantum security

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Received: 03 June 2022
Revised: 10 June 2022
Accepted: 21 June 2022
Published: 15 July 2022
Issue date: June 2022

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© The author(s) 2022

Acknowledgements

Acknowledgements

This work was supported in part by the Advanced Grid Modeling Program under U.S. Department of Energy’s Office of Electricity under Agreement No. 37533 (P.Z.), in part by Stony Brook University’s Office of the Vice President for Research through a Quantum Information Science and Technology Seed Grant (P.Z.), and in part by the National Science Foundation under Grant No. PHY 1915165 (T.-C.W.). We would like to acknowledge the Brookhaven National Laboratory operated IBM-Q Hub. This research also used resources of the Oak Ridge Leadership Computing Facility, which is a U.S. Department of Energy Office of Science User Facility supported under Contract DE-AC05-00OR22725.

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