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)

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)