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Development a partially observable Markov decision processes-based intelligent assistant for power grids using Monte Carlo tree search
conference contribution
posted on 2023-05-23, 14:29 authored by Tomin, NV, Kurbatsky, V, Michael NegnevitskyMichael NegnevitskyAutonomous control systems will make much ”smarter” used automatic controls of modern power grids, as well as partially or completely replace the system operator, which may not be able sometimes to adequately respond to critical conditions due to psychological stress. Development of such systems can be solved by Monte-Carlo tree search algorithm that simulate ahead into the future, evaluate future states, and back-up those evaluations to the root of a search tree. We use the formalism of POMDPs (Partially Observable Markov Decision Processes) as the core of an intelligent assistant for power system control and dispatch. We demonstrate the feasibility of the approach to resolve the voltage and reactive power control in substation.
History
Publication title
Proceedings of the 10th International Scientific Symposium on Electrical Power EngineeringEditors
M Kolcun, I Kolcunova, J KurimskyPagination
389-393ISBN
9781510888715Department/School
School of EngineeringPublisher
Technical University of KosicePlace of publication
Stara Lesna, SlovakiaEvent title
10th International Scientific Symposium on Electrical Power Engineering, ELEKTROENERGETIKA 2019Event Venue
Stara Lesna, SlovakiaDate of Event (Start Date)
2019-09-16Date of Event (End Date)
2019-09-18Rights statement
Copyright 2019 ElsevierRepository Status
- Restricted