PowerWeb Lecture: “Combining Deep Reinforcement Learning and Mathematical Optimization for Scalable Decision Making in Power Distribution Systems”

30 May 2023 12:45 till 13:30 | Add to my calendar

By: Masood Parvania, Associate Professor and Director of Utah Energy and Power Innovation Center (U-EPIC), University of Utah.

Date: Tuesday 30 May 2023
Time: 12:45-13:30 (free lunch from 12:15)
Location: Faculty of EWI, Mekelweg 4 (Chip Hall)
Moderator: Dr Francesco Lombardi

Register here: registration form.

Abstract: The operation of power distribution systems has grown from passive and manual applications to include making complex decisions in real-time to facilitate the operation of large number of distributed energy resources for various applications. The limitations of mathematical optimization techniques in making scalable real-time decisions under uncertainty, has brought attention to techniques such as deep reinforcement learning (DRL) that has the potential to revolutionize the operation and enable further automation in power distribution systems. This talk will introduce a model that combines DRL with mathematical optimization for real-time operation applications in power distribution systems. This model brings the best of DRL and mathematical optimization, enabling the scalable and automated decision making in real-time while ensuring the physical feasibility of decisions in power distribution systems


Short bio of the presenter: Dr. Masood Parvania is the Director of Utah Energy and Power Innovation Center, and Associate Professor of Electrical and Computer Engineering, at the University of Utah. His research interests include the operation, economics and resilience of power and energy systems, and modeling and operation of interdependent critical infrastructures. Dr. Parvania serves as an Associate Editor for the IEEE Transactions on Power Systems and the IEEE Power Engineering Letters.