Power systems are complex cyber-physical systems requiring sophisticated control and decision-making capabilities for reliable, efficient, and secure operations. Ensuring safety is critical, given the potential for widespread disruptions if operational constraints are violated in this critical infrastructure. Reinforcement learning (RL) presents a promising data-driven approach to developing intelligent control policies, but deploying RL necessitates new methods that can respect safety constraints through safe exploration, constrained optimization, and stability guarantees.

To bring together the diverse community of Safe RL and smart grid researchers together to steer discussions on challenges and perspectives of using RL for smart grid applications, we propose the Safe RL Workshop for Smart Grid Control and Operations. The sessions will focus on the progress and challenges in safe RL, emphasizing its application to the complex cyber-physical systems of power grids. Discussions will delve into topics such as safety constraint satisfaction during exploration, optimization under constraints, stability guarantees, and the operational challenges of deploying RL in smart grids where reliability and security are extremely important. By concentrating on these areas, the workshop aims to highlight the unique requirements and solutions for safe RL deployment in power systems, moving towards the goal of achieving efficient, secure, and resilient grid operations.

• Workshop date: September 17, 2024

• Submission opens: May 28, 2024

• Submission deadline:  June 25, 2024 (AOE)

• Acceptance notification:  July 10, 2024

• Camera-ready and poster upload deadline: August 9, 2024