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

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

doi:10.1109/ECCE50734.2022.9948058

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

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

Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Scopus citations

Abstract

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 language	English (US)
Title of host publication	2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728193878
DOIs	https://doi.org/10.1109/ECCE50734.2022.9948058
State	Published - 2022
Event	2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 - Detroit, United States Duration: Oct 9 2022 → Oct 13 2022

Publication series

Name	2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022

Conference

Conference	2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
Country/Territory	United States
City	Detroit
Period	10/9/22 → 10/13/22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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

Access to Document

10.1109/ECCE50734.2022.9948058

Cite this

Jing, H., Wang, Y., Li, Y., Du, L., & Wu, Z. (2022). Quantum Approximate Optimization Algorithm-Enabled DER Disturbance Analysis of Networked Microgrids. In 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 (2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ECCE50734.2022.9948058

@inproceedings{84040884d75c4d5b892254573b661e96,

title = "Quantum Approximate Optimization Algorithm-Enabled DER Disturbance Analysis of Networked Microgrids",

abstract = "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.",

author = "Hang Jing and Ye Wang and Yan Li and Liang Du and Ziping Wu",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 ; Conference date: 09-10-2022 Through 13-10-2022",

year = "2022",

doi = "10.1109/ECCE50734.2022.9948058",

language = "English (US)",

series = "2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Jing, H, Wang, Y, Li, Y, Du, L & Wu, Z 2022, Quantum Approximate Optimization Algorithm-Enabled DER Disturbance Analysis of Networked Microgrids. in 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022. 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022, Institute of Electrical and Electronics Engineers Inc., 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022, Detroit, United States, 10/9/22. https://doi.org/10.1109/ECCE50734.2022.9948058

Quantum Approximate Optimization Algorithm-Enabled DER Disturbance Analysis of Networked Microgrids. / Jing, Hang; Wang, Ye; Li, Yan et al.
2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Jing, Hang

AU - Wang, Ye

AU - Li, Yan

AU - Du, Liang

AU - Wu, Ziping

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

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M3 - Conference contribution

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BT - 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

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

Abstract

Publication series

Conference

UN SDGs

All Science Journal Classification (ASJC) codes

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