TY - GEN
T1 - Interoperation Analysis of Reconfigurable Networked Microgrids through Quantum Approximate Optimization Algorithm
AU - Jing, Hang
AU - Wang, Ye
AU - Li, Yan
N1 - Funding Information:
The author would like to thank Dr. Rui Chao at Duke University for the detailed discussion on the QAOA algorithm. Y.W. is supported by DOE BES award de-sc0019449 (quantum algorithm analysis).
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The maximum power exchange section is playing an important role in analyzing the interoperation of network microgrids. Mathematically, the problem is formulated into a weighted Max-Cut problem, which is non-deterministic polynomial-time hard (NP-hard). A Quantum Approximate Optimization Algorithm (QAOA) is introduced in this paper to search the approximate maximum power exchange sections in networked microgrids. QAOA is a hybrid quantum-classical algorithm, which uses a classical optimizer to train a parametrized quantum circuit. Layer number and angle parameters of the quantum circuit are discussed, which highly impact the performance of QAOA. Numerical examples on a typical reconfigurable networked microgrid system test and verify the effectiveness of QAOA in getting the maximum power exchange sections. This quantum computing implementation sheds light on the development of quantum algorithms to resolve the challenges in power systems that are hard to solve by classical computers.
AB - The maximum power exchange section is playing an important role in analyzing the interoperation of network microgrids. Mathematically, the problem is formulated into a weighted Max-Cut problem, which is non-deterministic polynomial-time hard (NP-hard). A Quantum Approximate Optimization Algorithm (QAOA) is introduced in this paper to search the approximate maximum power exchange sections in networked microgrids. QAOA is a hybrid quantum-classical algorithm, which uses a classical optimizer to train a parametrized quantum circuit. Layer number and angle parameters of the quantum circuit are discussed, which highly impact the performance of QAOA. Numerical examples on a typical reconfigurable networked microgrid system test and verify the effectiveness of QAOA in getting the maximum power exchange sections. This quantum computing implementation sheds light on the development of quantum algorithms to resolve the challenges in power systems that are hard to solve by classical computers.
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U2 - 10.1109/PESGM48719.2022.9916769
DO - 10.1109/PESGM48719.2022.9916769
M3 - Conference contribution
AN - SCOPUS:85128676434
T3 - IEEE Power and Energy Society General Meeting
BT - 2022 IEEE Power and Energy Society General Meeting, PESGM 2022
PB - IEEE Computer Society
T2 - 2022 IEEE Power and Energy Society General Meeting, PESGM 2022
Y2 - 17 July 2022 through 21 July 2022
ER -
