Quantum contingency analysis for power system steady-state security identification
Abstract Unprecedented extreme climate events cause devastating infrastructure outages within power systems. Comprehensive outage identification is essential for the identification of critical components to ensure the uninterrupted power supply in a secure manner to withstand extreme weather events....
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-98776-5 |
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| author | Fei Feng Yifan Zhou Mikhail A. Bragin Yacov A. Shamash Peng Zhang |
| author_facet | Fei Feng Yifan Zhou Mikhail A. Bragin Yacov A. Shamash Peng Zhang |
| author_sort | Fei Feng |
| collection | DOAJ |
| description | Abstract Unprecedented extreme climate events cause devastating infrastructure outages within power systems. Comprehensive outage identification is essential for the identification of critical components to ensure the uninterrupted power supply in a secure manner to withstand extreme weather events. Accurate outage identification, however, requires simulations of a large number of outage scenarios necessitating highly scalable computations thus challenging classical computing paradigms. Quantum computing provides a promising resolution by exploiting exponential scalability achieved through superposition and entanglement of voltage states. This paper devises a quantum contingency analysis (QCA) method to identify outage scenarios on Noisy Intermediate-Scale Quantum (NISQ) devices. Advanced quantum circuits incorporating Pauli-twirling, dynamic decoupling, and matrix-free measurement are designed to mitigate hardware-induced errors. A preconditioned hybrid method is devised to alleviate the computation burden of parameter optimization of quantum gates. Case studies identify line and generation outages via QCA in typical power systems. Our research underscores that quantum computing exhibits exponential scalability in identifying power grid outages and critical components. |
| format | Article |
| id | doaj-art-5627e9797e094681a0aa2d7ced3eaf42 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-5627e9797e094681a0aa2d7ced3eaf422025-08-20T02:11:22ZengNature PortfolioScientific Reports2045-23222025-04-0115111110.1038/s41598-025-98776-5Quantum contingency analysis for power system steady-state security identificationFei Feng0Yifan Zhou1Mikhail A. Bragin2Yacov A. Shamash3Peng Zhang4Department of Electrical Engineering, SUNY Maritime CollegeDepartment of Electrical and Computer Engineering, Stony Brook UniversityDepartment of Electrical and Computer Engineering, University of ConnecticutDepartment of Electrical and Computer Engineering, Stony Brook UniversityDepartment of Electrical and Computer Engineering, Stony Brook UniversityAbstract Unprecedented extreme climate events cause devastating infrastructure outages within power systems. Comprehensive outage identification is essential for the identification of critical components to ensure the uninterrupted power supply in a secure manner to withstand extreme weather events. Accurate outage identification, however, requires simulations of a large number of outage scenarios necessitating highly scalable computations thus challenging classical computing paradigms. Quantum computing provides a promising resolution by exploiting exponential scalability achieved through superposition and entanglement of voltage states. This paper devises a quantum contingency analysis (QCA) method to identify outage scenarios on Noisy Intermediate-Scale Quantum (NISQ) devices. Advanced quantum circuits incorporating Pauli-twirling, dynamic decoupling, and matrix-free measurement are designed to mitigate hardware-induced errors. A preconditioned hybrid method is devised to alleviate the computation burden of parameter optimization of quantum gates. Case studies identify line and generation outages via QCA in typical power systems. Our research underscores that quantum computing exhibits exponential scalability in identifying power grid outages and critical components.https://doi.org/10.1038/s41598-025-98776-5 |
| spellingShingle | Fei Feng Yifan Zhou Mikhail A. Bragin Yacov A. Shamash Peng Zhang Quantum contingency analysis for power system steady-state security identification Scientific Reports |
| title | Quantum contingency analysis for power system steady-state security identification |
| title_full | Quantum contingency analysis for power system steady-state security identification |
| title_fullStr | Quantum contingency analysis for power system steady-state security identification |
| title_full_unstemmed | Quantum contingency analysis for power system steady-state security identification |
| title_short | Quantum contingency analysis for power system steady-state security identification |
| title_sort | quantum contingency analysis for power system steady state security identification |
| url | https://doi.org/10.1038/s41598-025-98776-5 |
| work_keys_str_mv | AT feifeng quantumcontingencyanalysisforpowersystemsteadystatesecurityidentification AT yifanzhou quantumcontingencyanalysisforpowersystemsteadystatesecurityidentification AT mikhailabragin quantumcontingencyanalysisforpowersystemsteadystatesecurityidentification AT yacovashamash quantumcontingencyanalysisforpowersystemsteadystatesecurityidentification AT pengzhang quantumcontingencyanalysisforpowersystemsteadystatesecurityidentification |