1 code implementation • 2 Oct 2023 • Flora Charbonnier, Thomas Morstyn, Malcolm McCulloch
We fill these gaps with the open-access HEDGE tool which generates data sequences of energy data for several days in a way that is consistent for single homes, both in terms of profile magnitude and behavioural clusters.
no code implementations • 30 May 2023 • Flora Charbonnier, Bei Peng, Thomas Morstyn, Malcolm McCulloch
This paper investigates how deep multi-agent reinforcement learning can enable the scalable and privacy-preserving coordination of residential energy flexibility.
no code implementations • 7 Mar 2022 • Flora Charbonnier, Thomas Morstyn, Malcolm D. McCulloch
This paper proposes a novel scalable type of multi-agent reinforcement learning-based coordination for distributed residential energy.
no code implementations • 8 Feb 2022 • Flora Charbonnier, Thomas Morstyn, Malcolm McCulloch
This paper proposes a novel taxonomy of coordination strategies for distributed energy resources at the edge of the electricity grid, based on a systematic analysis of key literature trends.