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Title: EXARL-PARS: Parallel Augmented Random Search Using Reinforcement Learning at Scale for Applications in Power Systems

Conference ·

Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Advanced Scientific Computing Research (SC-21)
DOE Contract Number:
SC0012704
OSTI ID:
2204148
Report Number(s):
BNL-224923-2023-COPA
Resource Relation:
Conference: e-Energy '23: The 14th ACM International Conference on Future Energy Systems, Orlando FL USA, 6/20/2023 - 6/23/2023
Country of Publication:
United States
Language:
English

References (11)

Implicit - integration dynamics simulation with the GridPACK framework conference July 2021
An analysis of previous blackouts in the world: Lessons for China׳s power industry journal February 2015
Decision Tree-Based Preventive and Corrective Control Applications for Dynamic Security Enhancement in Power Systems journal August 2010
Adaptive Power System Emergency Control Using Deep Reinforcement Learning journal March 2020
Accelerated Derivative-Free Deep Reinforcement Learning for Large-Scale Grid Emergency Voltage Control journal January 2022
Deep Reinforcement Learning for Autonomous Driving: A Survey journal January 2021
Reinforcement learning in robotics: A survey journal August 2013
An Efficient Optimal Control Method for Open-Loop Transient Stability Emergency Control journal July 2017
Blackout Prevention in the United States, Europe, and Russia journal November 2005
GridPACKTM: A framework for developing power grid simulations on high-performance computing platforms journal October 2015
Applications of reinforcement learning in energy systems journal March 2021