Solving DC power flow problems using quantum and hybrid algorithms

被引:10
|
作者
Gao, Fang [1 ]
Wu, Guojian
Guo, Suhang
Dai, Wei
Shuang, Feng [1 ]
机构
[1] Guangxi Univ, Guangxi Key Lab Intelligent Control & Maintenance, Nanning 530004, Peoples R China
基金
中国国家自然科学基金;
关键词
DC power flow; Quantum algorithm; Hybrid algorithm; Qubit resources; INSPIRED EVOLUTIONARY ALGORITHM; GENETIC ALGORITHM; REAL; DISPATCH;
D O I
10.1016/j.asoc.2023.110147
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Power flow calculation plays an important role in planning, operation, and control of the power system. The quantum HHL algorithm can achieve theoretical exponential speedup over classical algorithms on DC power flow calculation. Since the qubit resources in the Noisy Intermediate-scale Quantum (NISQ) era are limited, it is important to discuss the performance considering this limitation. The phase estimation of DC power flow problems is imperfect. This work is carried out under the assumption of imperfect phase estimation. The performance of the HHL algorithm is systematically investigated with different accuracy and redundant qubits. In order to further reduce the required qubit resources, a hybrid quantum-classical algorithm is proposed. By comparing errors of the HHL and hybrid algorithms in the DC power flow calculation of the PJM 5-bus system, it is found that the hybrid algorithm can achieve comparable precision with fewer qubits than HHL by increasing the number of phase estimation modules, which may make the hybrid algorithm a feasible route in the NISQ era. (c) 2023 Elsevier B.V. All rights reserved.
引用
收藏
页数:11
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