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Found 7 papers, 0 papers with code
Mobile Energy Storage in Power Network: Marginal Value and Optimal Operation
This paper examines the marginal value of mobile energy storage, i. e., energy storage units that can be efficiently relocated to other locations in the power network.
Machine Learning for Smart and Energy-Efficient Buildings
In this work, we review the ways in which machine learning has been leveraged to make buildings smart and energy-efficient.
Electric Vehicle Battery Sharing Game for Mobile Energy Storage Provision in Power Networks
In this paper, we consider two types of EV drivers who may be willing to provide mobile storage service using their EVs: commuters taking a fixed route, and on-demand EV drivers who receive incentives from a transportation network company (TNC) and are willing to take any route.
Asset Participation and Aggregation in Incentive-Based Demand Response Programs
We develop a probabilistic model for the curtailment capability of these assets, and use it to derive analytic expressions for the optimal participation (i. e., promised curtailment) and profitability from the DR asset perspective.
Adapting Surprise Minimizing Reinforcement Learning Techniques for Transactive Control
Optimizing prices for energy demand response requires a flexible controller with ability to navigate complex environments.
Offline-Online Reinforcement Learning for Energy Pricing in Office Demand Response: Lowering Energy and Data Costs
Our team is proposing to run a full-scale energy demand response experiment in an office building.
Using Meta Reinforcement Learning to Bridge the Gap between Simulation and Experiment in Energy Demand Response
Our team is proposing to run a full-scale energy demand response experiment in an office building.
