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Found 5 papers, 2 papers with code
Learning and Optimization for Price-based Demand Response of Electric Vehicle Charging
Thus, to model and optimize EV charging, it is important for charging station operator to model the PBDR patterns of EV customers by precisely predicting charging demands given price signals.
Large Foundation Models for Power Systems
Foundation models, such as Large Language Models (LLMs), can respond to a wide range of format-free queries without any task-specific data collection or model training, creating various research and application opportunities for the modeling and operation of large-scale power systems.
Laxity-Aware Scalable Reinforcement Learning for HVAC Control
Demand flexibility plays a vital role in maintaining grid balance, reducing peak demand, and saving customers' energy bills.
Learning a Multi-Agent Controller for Shared Energy Storage System
Deployment of shared energy storage systems (SESS) allows users to use the stored energy to meet their own energy demands while saving energy costs without installing private energy storage equipment.
Learning Task-Aware Energy Disaggregation: a Federated Approach
We consider the problem of learning the energy disaggregation signals for residential load data.
