Quantum Approximate Optimization Algorithm-Enabled DER Disturbance Analysis of Networked Microgrids

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

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

3 Scopus citations


The Quantum Approximate Optimization Algorithm (QAOA) is applied to Networked Microgrids (NMs) in this paper to search for the maximum power exchange section, which is playing an essential role in operating NMs. Mathematically, obtaining the maximum power section is to solve a Max-Cut problem over the modeling graph of NMs. Considering the integration and fluctuations of Distributed Energy Resources (DERs), the maximum power section will change frequently. To efficiently get the section, QAOA provides a powerful solution by leveraging quantum resources. The performance of QAOA highly depends on the critical parameters of quantum circuits. We find the designed parameters for QAOA are still effective under wide range change of output power of energy resources. Tests on a typical NMs system verify the effectiveness of the QAOA method in efficiently searching for the maximum power sections of NMs.

Original languageEnglish (US)
Title of host publication2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728193878
StatePublished - 2022
Event2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 - Detroit, United States
Duration: Oct 9 2022Oct 13 2022

Publication series

Name2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022


Conference2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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