research
∙
09/18/2023
Contract Design for V2G Smart Energy Trading
The transition to a net zero energy system necessitates development in a...
share
research
∙
08/26/2022
Battery and Hydrogen Energy Storage Control in a Smart Energy Network with Flexible Energy Demand using Deep Reinforcement Learning
Smart energy networks provide for an effective means to accommodate high...
research
∙
11/21/2021
Renewable energy integration and microgrid energy trading using multi-agent deep reinforcement learning
In this paper, multi-agent reinforcement learning is used to control a h...
research
∙
08/18/2021
A Review on Cybersecurity in Smart Local Energy Systems: Requirements, Challenges, and Standards
Smart local energy system (SLES) is considered as a promising pathway fa...
research
∙
06/10/2021
Data-driven battery operation for energy arbitrage using rainbow deep reinforcement learning
As the world seeks to become more sustainable, intelligent solutions are...
research
∙
05/27/2021
Federated Learning for Short-term Residential Energy Demand Forecasting
Energy demand forecasting is an essential task performed within the ener...
research
∙
12/14/2020
Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters
In this proposal paper we highlight the need for privacy preserving ener...
research
∙
04/24/2020
A Review of Privacy Preserving Federated Learning for Private IoT Analytics
The Internet-of-Things generates vast quantities of data, much of it att...
research
∙
04/24/2020
Federated learning with hierarchical clustering of local updates to improve training on non-IID data
Federated learning (FL) is a well established method for performing mach...
research
∙
10/29/2019