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DOE OSTI · 1889652

Quantum-Inspired Power System Reliability Assessment

Nikmehr, Nima·Zhang, Peng
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Abstract

To enable an in-depth study of power system operation and planning, the assessment of standard reliability indices is inevitable. The Monte Carlo Simulation (MCS) approach is a broadly used method in replacing the analytical methods in reliability indices assessment. The accuracy of MCS, however, highly depends on the sampling size, and hence, a complicated system with large number of components requires a large sampling size and daunting computational effort. To address this shortcoming, we, in this paper attempt to take advantage of potentials of the quantum computing (QC) for power system reliability assessment by realizing the following contributions: 1) an innovative quantum model designed for reliability assessment; 2) a quantum circuit that achieves the quadratic speed up compared to the classical MCS method; 3) an efficient quantum amplitude estimation (QAE) algorithm to accurately evaluate the reliability indices. The accuracy and efficacy of the quantum reliability method are extensively verified and demonstrated on both radial and mesh distribution systems.

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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATIONComputational modelingDistribution systemsOptimizationPower system reliabilityQuantum amplitude estimationQuantum circuitQuantum computingQubitReliabilityReliability assessment

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Nikmehr, Nima, Zhang, Peng. 2022-09-05. Quantum-Inspired Power System Reliability Assessment. https://doi.org/10.1109/tpwrs.2022.3204393

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