Scalable Grid-Aware Dynamic Matching using Deep Reinforcement Learning

no code implementations • 31 Jan 2023 • Majid Majidi, Deepan Muthirayan, Masood Parvania, Pramod P. Khargonekar

The central agent then solves an optimal power flow problem with the IHRs as the nodes, with their active power flow and reactive power {capacities}, and grid constraints to scalably determine the final flows such that matched power can be delivered to the extent the grid constraints are satisfied.

reinforcement-learning Reinforcement Learning (RL)

Cyber-Resilient Frequency Control of Power Grids with Energy Storage Systems

no code implementations • 25 Jul 2022 • Jairo Giraldo, Masood Parvania

The integration of synchronous generators and energy storage systems operated through communication networks introduces new challenges and vulnerabilities to the electric grid, where cyber attacks can corrupt sensor measurements or control inputs and interrupt functions such as frequency regulation.

Dynamic Matching Markets in Power Grid: Concepts and Solution using Deep Reinforcement Learning

no code implementations • 12 Apr 2021 • Majid Majidi, Deepan Muthirayan, Masood Parvania, Pramod P. Khargonekar

This paper proposes an alternative to bulk load flexibility options for managing uncertainty in power markets: a reinforcement learning based dynamic matching market.

reinforcement-learning Reinforcement Learning (RL)