4 citations · 5 across the 4 of their papers we have counts for
4 papers
The role of living laboratories in unlocking the potential of low-carbon energy technologies on the journey to net-zero
Zhong Fan, Jun Cao, Taskin Jamal +8
We demonstrate the potential role of one of the largest at scale multi-vector Smart Energy Network Demonstrator (SEND).
Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learning
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 maximi…
A Review on Cybersecurity in Smart Local Energy Systems: Requirements, Challenges, and Standards
Siyuan Dong, Jun Cao, Zhong Fan
Smart local energy system (SLES) is considered as a promising pathway facilitating a more effective and localised operation, benefited from the complex information and communicatio…
Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning
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. In this paper, the model-free deep reinforcement le…