Power System
Power systems research focuses on ensuring the reliable and efficient operation of electricity grids, addressing challenges posed by increasing renewable energy integration and evolving consumption patterns. Current research emphasizes developing accurate and computationally efficient models for forecasting, optimization (e.g., optimal power flow), and anomaly detection, often employing deep learning architectures like graph neural networks, transformers, and diffusion models, alongside physics-informed approaches. These advancements are crucial for improving grid stability, security, and resilience, enabling more effective integration of renewable sources and facilitating the transition to a sustainable energy future.
Papers
Digital Twin-Empowered Voltage Control for Power Systems
Jiachen Xu, Yushuai Li, Torben Bach Pedersen, Yuqiang He, Kim Guldstrand Larsen, Tianyi Li
PowerMamba: A Deep State Space Model and Comprehensive Benchmark for Time Series Prediction in Electric Power Systems
Ali Menati, Fatemeh Doudi, Dileep Kalathil, Le Xie