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Power System Fault Diagnosis with Quantum Computing and Efficient Gate Decomposition
Power system fault diagnosis is crucial for identifying the location and causes of faults and providing decision-making support for power dispatchers.
Applying Large Language Models to Power Systems: Potential Security Threats
Applying large language models (LLMs) to modern power systems presents a promising avenue for enhancing decision-making and operational efficiency.
Cyber-physical interdependent restoration scheduling for active distribution network via ad hoc wireless communication
This paper proposes a post-disaster cyber-physical interdependent restoration scheduling (CPIRS) framework for active distribution networks (ADN) where the simultaneous damages on cyber and physical networks are considered.
Fed-NILM: A Federated Learning-based Non-Intrusive Load Monitoring Method for Privacy-Protection
However, inadequate load data and the risk of power consumer privacy breaches may be encountered by local data owners during the NILM model training.
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