All Outputs (2)

Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning (2021)
Journal Article
Fan. (2022). Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning. Energy, https://doi.org/10.1016/j.energy.2021.121958

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 learning algorithm Rainbow Deep Q-Networks is used to control a battery... Read More about Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning.

Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraints (2021)
Journal Article
Samende, & Fan. (2021). Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraints. Astronomical Journal, https://doi.org/10.48550/arXiv.2108.09053

In this paper, we investigate an energy cost minimization problem for prosumers participating in peer-to-peer energy trading. Due to (i) uncertainties caused by renewable energy generation and consumption, (ii) difficulties in developing an accurate... Read More about Multi-Agent Deep Deterministic Policy Gradient Algorithm for Peer-to-Peer Energy Trading Considering Distribution Network Constraints.