A review of safe reinforcement learning methods for modern power systems
Due to the availability of more comprehensive measurement data in modern power systems,
there has been significant interest in developing and applying reinforcement learning (RL) …
there has been significant interest in developing and applying reinforcement learning (RL) …
Spatiotemporal Deep Learning for Power System Applications: A Survey
M Saffari, M Khodayar - IEEE Access, 2024 - ieeexplore.ieee.org
Understanding spatiotemporal correlations in power systems is crucial for maintaining grid
stability, reliability, and efficiency. By discerning connections between spatial and temporal …
stability, reliability, and efficiency. By discerning connections between spatial and temporal …
Rethinking Safe Policy Learning for Complex Constraints Satisfaction: A Glimpse in Real-Time Security Constrained Economic Dispatch Integrating Energy Storage …
Reinforcement learning (RL) for real-time security constrained economic dispatch (RT-
SCED) problems have been the subject of significant research interest in recent years …
SCED) problems have been the subject of significant research interest in recent years …
Physics-Informed Reinforcement Learning for Real-Time Optimal Power Flow with Renewable Energy Resources
Z Wu, M Zhang, S Gao, ZG Wu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The serious uncertainties from the extensive integration of renewable energy generations
put forward a higher real-time requirement for power system dispatching. To provide …
put forward a higher real-time requirement for power system dispatching. To provide …
Approximating energy market clearing and bidding with model-based reinforcement learning
Energy market rules should incentivize market participants to behave in a market and grid
conform way. However, they can also provide incentives for undesired and unexpected …
conform way. However, they can also provide incentives for undesired and unexpected …
Robust Optimal Control of Electric Vehicles Charging for Stochastic and Differentially Private Demand
This paper presents a comprehensive stochastic optimization model that seamlessly
integrates aggregate electric vehicle (EV) charging demand response with power grid …
integrates aggregate electric vehicle (EV) charging demand response with power grid …
[PDF][PDF] Distributed Optimization and Learning: A Paradigm Shift for Power Systems
A Al-Tawaha, E Cibaku, SW Park, J Lavaei, M Jin - lavaei.ieor.berkeley.edu
This survey provides a comprehensive overview of recent advances in distributed
optimization and machine learning for power systems, particularly focusing on optimal …
optimization and machine learning for power systems, particularly focusing on optimal …
[PDF][PDF] Research Field: Power System Stability and Operation
MSJ Bao, MSM Wältermann, MSS Uhlenbrock - ie3.etit.tu-dortmund.de
Decentralized energy resources (DERs) have increased tremendously in the past few years,
which leads to the need of sophisticated operational schemes in power systems. With the …
which leads to the need of sophisticated operational schemes in power systems. With the …