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Exact quantum algorithm for unit commitment optimization based on partially connected quantum neural networks |
| Jian Liu(刘键)2,†, Xu Zhou(周旭)1,3,6,†,‡, Zhuojun Zhou(周卓俊)2, and Le Luo(罗乐)1,4,5 |
1 School of Physics and Astronomy, Sun Yat-Sen University, Zhuhai 519082, China;
2 QUDOOR Co., Ltd., Hefei 230000, China;
3 QUDOOR Co., Ltd., Beijing 100089, China;
4 Shenzhen Research Institute of Sun Yat-Sen University, Shenzhen 518057, China;
5 Guangdong Provincial Key Laboratory of Quantum Metrology and Sensing, Sun Yat-Sen University, Zhuhai 519082, China;
6 Yangtze Delta Industrial Innovation Center of Quantum Science and Technology, Suzhou 215000, China |
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Abstract The quantum hybrid algorithm has recently become a very promising and speedy method for solving larger-scale optimization problems in the noisy intermediate-scale quantum (NISQ) era. The unit commitment (UC) problem is a fundamental problem in the field of power systems that aims to satisfy the power balance constraint with minimal cost. In this paper, we focus on the implementation of the UC solution using exact quantum algorithms based on the quantum neural network (QNN). This method is tested with a ten-unit system under the power balance constraint. In order to improve computing precision and reduce network complexity, we propose a knowledge-based partially connected quantum neural network (PCQNN). The results show that exact solutions can be obtained by the improved algorithm and that the depth of the quantum circuit can be reduced simultaneously.
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Received: 02 December 2024
Revised: 14 July 2025
Accepted manuscript online: 28 July 2025
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PACS:
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03.67.Ac
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(Quantum algorithms, protocols, and simulations)
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03.67.Lx
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(Quantum computation architectures and implementations)
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88.50.Mp
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(Electricity generation, grid integration from wind)
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45.10.Db
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(Variational and optimization methods)
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| Fund: This work was supported in part by the China Postdoctoral Science Foundation (Grant No. 2023M740874). |
Corresponding Authors:
Xu Zhou
E-mail: zhoux359@mail.sysu.edu.cn
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Cite this article:
Jian Liu(刘键), Xu Zhou(周旭), Zhuojun Zhou(周卓俊), and Le Luo(罗乐) Exact quantum algorithm for unit commitment optimization based on partially connected quantum neural networks 2025 Chin. Phys. B 34 100303
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