The accuracy of power system measurements directly affects the safe and stable operation of power grids. This study explores the application prospects of quantum sensing technology in power system measurements. The research first analyzes the limitations of traditional measurement techniques, such as electromagnetic interference sensitivity and measurement accuracy bottlenecks. It then introduces the basic principles of quantum sensing, including concepts like quantum entanglement and superposition states. Through theoretical analysis and numerical simulations, the study assesses the potential advantages of quantum sensors in current, voltage, and magnetic field measurements. Results show that quantum magnetometers offer significant improvements in accuracy and interference resistance for current measurements. The study also discusses the application of quantum optical technology in high-voltage measurements, demonstrating its unique advantages in improving measurement dynamic range. However, quantum sensing technology still faces challenges in practical applications, such as technological maturity and cost. To address these issues, the research proposes a phased implementation strategy and industry-academia collaboration model. Finally, the study envisions future directions combining quantum sensing with artificial intelligence. This research provides a theoretical foundation for innovative upgrades in power system measurement technology.
References
[1]
Degen, C.L., Reinhard, F. and Cappellaro, P. (2017) Quantum sensing. Reviews of Modern Physics, 89, Article 035002. https://doi.org/10.1103/revmodphys.89.035002
[2]
Bao, X.H., Reingruber, J., Dietrich, P., Rui, J., Dück, A., Strassel, T. and Pan, J.W. (2020) Efficient and Long-Lived Quantum Memory with Cold Atoms Inside a Ring Cavity. Nature Physics, 16, 1169-1174.
[3]
Rondin, L., Tetienne, J., Hingant, T., Roch, J., Maletinsky, P. and Jacques, V. (2014) Magnetometry with Nitrogen-Vacancy Defects in Diamond. Reports on Progress in Physics, 77, Article 056503. https://doi.org/10.1088/0034-4885/77/5/056503
[4]
Meyer, H.M., Stockill, R., Steiner, M., Le Gall, C., Matthiesen, C., Clarke, E., et al. (2015) Direct Photonic Coupling of a Semiconductor Quantum Dot and a Trapped Ion. Physical Review Letters, 114, Article 123001. https://doi.org/10.1103/physrevlett.114.123001
[5]
Li, Z., Liu, H., Zhao, J., Bi, T. and Yang, Q. (2021) Fast Power System Event Identification Using Enhanced LSTM Network with Renewable Energy Integration. IEEE Transactions on Power Systems, 36, 4492-4502. https://doi.org/10.1109/tpwrs.2021.3064250
[6]
Wang, Y., Liu, D. and Ding, Y. (2019) An Intelligent System for Improving Measurement Accuracy of Power Quality Disturbances Using Quantum Genetic Algorithm and Dual Neural Networks. IEEE Transactions on Industrial Informatics, 15, 4569-4579.
[7]
Zhang, J., Xie, X. and Poor, H.V. (2022) A Review of Quantum Sensing for Power System Monitoring. IEEE Transactions on Smart Grid, 13, 107-121.
[8]
Li, Z., Zhao, N., Qi, B. and Lo, H.K. (2021) Experimental Demonstration of Quantum-Enhanced Power System State Estimation. npj Quantum Information, 7, 1-8.
[9]
Huang, H., Wu, D., Fan, D. and Zhu, X. (2020) Superconducting Quantum Computing: A Review. Science China Information Sciences, 63, 1-32. https://doi.org/10.1007/s11432-020-2881-9
[10]
Giovannetti, V., Lloyd, S. and Maccone, L. (2011) Advances in Quantum Metrology. Nature Photonics, 5, 222-229. https://doi.org/10.1038/nphoton.2011.35
[11]
Dorninger, D. and Länger, H. (2018) Quantum Measurements Generating Structures of Numerical Events. Journal of Applied Mathematics and Physics, 6, 982-996. https://doi.org/10.4236/jamp.2018.65085
[12]
Saleh, S.A. (2016) Statistical Mechanics for Weak Measurements and Quantum Inseparability. Journal of Quantum Information Science, 6, 10-15. https://doi.org/10.4236/jqis.2016.61002
[13]
Chen, K., Wang, L., Zhang, J., Chen, S. and Zhang, S. (2023) Semantic Learning for Analysis of Overlapping LPI Radar Signals. IEEE Transactions on Instrumentation and Measurement, 72, 1-15. https://doi.org/10.1109/tim.2023.3242013
