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Application of Deep Learning Methods in Monitoring and Optimization of Electric Power Systems

arXiv 2309.00498 ↗First posted 1 Sep 2023cs.LG cs.SY eess.SYcited by 0

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Abstract (arXiv)

This PhD thesis thoroughly examines the utilization of deep learning techniques as a means to advance the algorithms employed in the monitoring and optimization of electric power systems. The first major contribution of this thesis involves the application of graph neural networks to enhance power system state estimation. The second key aspect of this thesis focuses on utilizing reinforcement learning for dynamic distribution network reconfiguration. The effectiveness of the proposed methods is affirmed through extensive experimentation and simulations.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 23 of its 174 references that are in the map. First posted on arXiv 1 Sep 2023.

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23 of 174 references.

References · 23

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11 more
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