Dynamics Analysis of Microgrids Integrated with EV Charging Stations based on Quantum Approximate Optimization Algorithm

Hang Jing, Ye Wang, Yan Li, Liang Du, Ziping Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

A Quantum Approximate Optimization Algorithm (QAOA) is introduced in this paper to analyze the impact of electric vehicle (EV) charging stations on the dynamic operations of microgrids via exploring the maximum power sections in the system. Mathematically, the problem is formulated into a weighted Max-Cut problem. To efficiently address this NP hard problem, quantum computing is leveraged through finding the maximum energy state of the problem's Hamiltonian based on adiabatic theorem. Numerical examples test and verify the effectiveness of QAOA in getting the microgrid system's maximum power sections considering the integration of EV charging stations. This quantum computing will shed light on the development of quantum algorithms for power systems to resolve the challenges that are hard to solve by using classical computers.

Original languageEnglish (US)
Title of host publication2022 IEEE Transportation Electrification Conference and Expo, ITEC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages574-578
Number of pages5
ISBN (Electronic)9781665405607
DOIs
StatePublished - 2022
Event2022 IEEE Transportation Electrification Conference and Expo, ITEC 2022 - Anaheim, United States
Duration: Jun 15 2022Jun 17 2022

Publication series

Name2022 IEEE Transportation Electrification Conference and Expo, ITEC 2022

Conference

Conference2022 IEEE Transportation Electrification Conference and Expo, ITEC 2022
Country/TerritoryUnited States
CityAnaheim
Period6/15/226/17/22

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Transportation

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