Reinforcement Learning for Electricity Network Operation

2020/03/16 by Adrian Kelly, Aïdan O'Sullivan, Kelly, Adrian +5 · 1 citation
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Electrical engineering #I.2 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimal Power Flow Distribution #Reinforcement Learning in Robotics #Signal Processing (eess.SP) #Smart Grid Energy Management #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2003.07339

openalex publication_date 2020/03/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper presents the background material required for the Learning to Run Power Networks Challenge. The challenge is focused on using Reinforcement Learning to train an agent to manage the real-time operations of a power grid, balancing power flows and making interventions to maintain stability. We present an introduction to power systems targeted at the machine learning community and an introduction to reinforcement learning targeted at the power systems community. This is to enable and encourage broader participation in the challenge and collaboration between these two communities.

Citations

• Introducing machine learning for power system operation support

Cited by

• Power Grid Control with Graph-Based Distributed Reinforcement Learning

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• PowRL: A Reinforcement Learning Framework for Robust Management of Power Networks
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