[HTML][HTML] Reinforcement learning-driven local transactive energy market for distributed energy resources

S Zhang, D May, M Gül, P Musilek - Energy and AI, 2022‏ - Elsevier
Local energy markets are emerging as a tool for coordinating generation, storage, and
consumption of energy from distributed resources. In combination with automation, they …

The impact of battery storage on power flow and economy in an automated transactive energy market

S Zhang, P Musilek - Energies, 2023‏ - mdpi.com
This article explores the use of battery energy storage in a transactive energy approach for a
heavily solar-penetrated community. We hypothesize that the efficient market interactions …

A game-theoretic approach for charging demand management of electric vehicles during system overload

A Hussain, P Musilek - 2021 IEEE Electrical Power and Energy …, 2021‏ - ieeexplore.ieee.org
To manage the charging demand of electric vehicles (EVs) under maximum power limit
constraints, a single-leader-multi-follower Stackelberg game theory-based solution …

Utility-scale energy storage system for load management under high penetration of electric vehicles: A marginal capacity value-based sizing approach

A Hussain, P Musilek - Journal of Energy Storage, 2022‏ - Elsevier
To determine a trade-off between the battery energy storage system (BESS) size and
corresponding benefits in managing the load of distribution systems under high penetration …

Utility-scale energy storage system for managing EV load in connected distribution circuits

A Hussain, K Gerasimov, C Chapelsky, P Musilek - IET Conference …, 2022‏ - IET
Increased penetration of electric vehicles (EVs) may exacerbate the residential peaks in
distribution circuits due to the coincidence of the residential and EV peak loads. Meanwhile …

{Multi-Agent Deep Reinforcement Learning for Autonomous Energy Coordination in Demand Response Methods for Residential Distribution Networks

P Atrazhev - 2023‏ - era.library.ualberta.ca
In the field of collaborative learning and decision-making, this thesis aims to explore the
effects of individual and joint rewards on the performance and coordination of agents in …