7 citations · 19 across the 8 of their papers we have counts for
4 papers · 1 filter
Adapting Surprise Minimizing Reinforcement Learning Techniques for Transactive Control
William Arnold, Tarang Srivastava, Lucas Spangher +2
Optimizing prices for energy demand response requires a flexible controller with ability to navigate complex environments. We propose a reinforcement learning controller with surpr…
Offline-Online Reinforcement Learning for Energy Pricing in Office Demand Response: Lowering Energy and Data Costs
Doseok Jang, Lucas Spangher, Manan Khattar +3
Our team is proposing to run a full-scale energy demand response experiment in an office building. Although this is an exciting endeavor which will provide value to the community,…
Using Meta Reinforcement Learning to Bridge the Gap between Simulation and Experiment in Energy Demand Response
Doseok Jang, Lucas Spangher, Manan Khattar +2
Our team is proposing to run a full-scale energy demand response experiment in an office building. Although this is an exciting endeavor which will provide value to the community,…
Selling Renewable Utilization Service to Consumers via Cloud Energy Storage
Yu Yang, Utkarsha Agwan, Guoqiang Hu +1
This paper proposes a cloud energy storage (CES) model for enabling local renewable integration of building consumers (BCs). Different from most existing third-party based ES shari…