TY - GEN
T1 - Quantum Approximate Optimization Algorithm-Enabled DER Disturbance Analysis of Networked Microgrids
AU - Jing, Hang
AU - Wang, Ye
AU - Li, Yan
AU - Du, Liang
AU - Wu, Ziping
N1 - Publisher Copyright:
© 2022 IEEE.
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.
UR - http://www.scopus.com/inward/record.url?scp=85144083825&partnerID=8YFLogxK
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U2 - 10.1109/ECCE50734.2022.9948058
DO - 10.1109/ECCE50734.2022.9948058
M3 - Conference contribution
AN - SCOPUS:85144083825
T3 - 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
BT - 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
Y2 - 9 October 2022 through 13 October 2022
ER -
