no code implementations • 11 Oct 2023 • Gregory Palmer, Chris Parry, Daniel J. B. Harrold, Chris Willis
An overview of state-of-the-art approaches for scaling DRL to domains that confront learners with the curse of dimensionality, and; iv.)
no code implementations • 21 Nov 2021 • Daniel J. B. Harrold, Jun Cao, Zhong Fan
In this paper, multi-agent reinforcement learning is used to control a hybrid energy storage system working collaboratively to reduce the energy costs of a microgrid through maximising the value of renewable energy and trading.
no code implementations • 10 Jun 2021 • Daniel J. B. Harrold, Jun Cao, Zhong Fan
As the world seeks to become more sustainable, intelligent solutions are needed to increase the penetration of renewable energy.