Online Learning for Robust Voltage Control Under Uncertain Grid Topology
Author:
Affiliation:
1. Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA, USA
2. Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA
Funder
Caltech Resnick Sustainability Institute
two Caltech/Amazon AWS AI4Science Fellowships
National Science Foundation
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
https://ieeexplore.ieee.org/ielam/5165411/10643567/10486962-aam.pdf
Reference55 articles.
1. A Survey on Power System Blackout and Cascading Events: Research Motivations and Challenges
2. A Survey of Frequency and Voltage Control Ancillary Services—Part I: Technical Features
3. Fast Local Voltage Control Under Limited Reactive Power: Optimality and Stability Analysis
4. A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems
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1. Fractional-order transfer Q-learning based on modal decomposition and convolutional neural networks for voltage control of smart grids;Advanced Engineering Informatics;2024-10
2. Distributed MPC-Based Voltage Control for Active Distribution Networks Considering Uncertainty of Distributed Energy Resources;Electronics;2024-07-12
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