A Critical Review of Safe Reinforcement Learning Techniques in Smart Grid Applications
On the map: Deep reinforcement learning methods → RL for energy, networks and operations
Abstract (arXiv)
The high penetration of distributed energy resources (DERs) in modern smart power systems introduces unforeseen uncertainties for the electricity sector, leading to increased complexity and difficulty in the operation and control of power systems. As a cutting-edge machine learning technology, deep reinforcement learning (DRL) has been widely implemented in recent years to handle the uncertainty in power systems. However, in critical infrastructures such as power systems, safety issues always receive top priority, while DRL may not always meet the safety requirements of power system operators. The concept of safe reinforcement learning (safe RL) is emerging as a potential solution to overcome the shortcomings of conventional DRL in the operation and control of power systems. This study provides a rigorous review of the latest research efforts focused on safe RL to derive power system control policies while accounting for the unique safety requirements of power grids. Furthermore, this study highlights various safe RL algorithms applied in diverse applications within the power system sector, from single grid-connected power converters, residential smart homes, and buildings to large power distribution networks. For all methods outlined, a discussion on their bottlenecks, research challenges, and potential opportunities in the operation and control of power system applications is also presented. This review aims to support research in the area of safe RL algorithms, embracing smart power system operation with safety constraints amid high uncertainty from DERs.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in RL for energy, networks and operations, one of 15 directions in Deep reinforcement learning methods. Builds on 19 of its 92 references that are in the map. First posted on arXiv 24 Sep 2024.
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- 2022A Review of Safe Reinforcement Learning: Methods, Theory and Applicationscited by 181
- 2020Discovering Reinforcement Learning Algorithmscited by 77
- 2021A Review of Graph Neural Networks and Their Applications in Power Systemscited by 63
- 2021Action Set Based Policy Optimization for Safe Power Grid Managementcited by 21
- 2021Computationally Efficient Safe Reinforcement Learning for Power Systemscited by 20
- 2020Deep Learning for Biomedical Image Reconstruction: A Surveycited by 17
- 2020Safe Reinforcement Learning for Emergency LoadShedding of Power Systemscited by 8
- 2021Barrier Function-based Safe Reinforcement Learning for Emergency Control of Power Systemscited by 8
- 2022Contingency-constrained economic dispatch with safe reinforcement learningcited by 8
- 2022Safe reinforcement learning for multi-energy management systems with known constraint functionscited by 7
- 2021District Cooling System Control for Providing Operating Reserve based on Safe Deep Reinforcement Learningcited by 6
- 2021Understanding the Safety Requirements for Learning-based Power Systems Operationscited by 5
6 more
- 2022Coordinated Frequency Control through Safe Reinforcement Learningcited by 4
- 2022Reinforcement Learning for Distributed Transient Frequency Control with Stability and Safety Guaranteescited by 4
- 2023Networked Multiagent Safe Reinforcement Learning for Low-carbon Demand Management in Distribution Networkcited by 4
- 2023Multi-agent Deep Reinforcement Learning for Distributed Load Restorationcited by 3
- 2021Safe multi-agent deep reinforcement learning for joint bidding and maintenance scheduling of generation unitscited by 2
- 2021Safe Reinforcement Learning for Grid Voltage Controlcited by 1
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- 2024Safe Reinforcement Learning for Power System Control: A Review
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- 2024Implementing Deep Reinforcement Learning-Based Grid Voltage Control in Real-World Power Systems: Challenges and Insights
- 2024Safe Imitation Learning-based Optimal Energy Storage Systems Dispatch in Distribution Networks
- 2024Make Safe Decisions in Power System: Safe Reinforcement Learning Based Pre-decision Making for Voltage Stability Emergency Control
- 2025Safe Reinforcement Learning-based Automatic Generation Control
- 2024Reinforcement Learning-Based Approaches for Enhancing Security and Resilience in Smart Control: A Survey on Attack and Defense Methods
- 2025Optimizing Power Grid Topologies with Reinforcement Learning: A Survey of Methods and Challenges