Year: 2025
Type: conference-paper
Abstract: Recent advances in Foundation Models allow leveraging rich, multimodal context to enhance performance in a variety of tasks.The management of modern energy systems including renewable energy generation and batteries is a control problem that is inherently context-sensitive due to the complex interplay of future energy demand, electricity prices, energy generation from wind, solar, and other sources.This presents new challenges in model training with existing narrow data sets, and context design.In this contribution we present the Open In-Context Energy Management Platform (OpenCEM), which will provide a rich, open data set of energy system management time series, event information, user-generated context, and a simulator through a public API to evaluate the performance of control algorithms and to provide quality feedback for user-supplied context.The data is obtained from an on-campus PV installation with batteries.
Authors: Yikai Lu, Tinko Sebastian Bartels, Ruixiang Wu, Fanzeng Xia, Xudong Wang, Yifei Wu, Haoxiang Yang, Tongxin Li
Institution: Chinese University of Hong Kong, Shenzhen
Language: English
Topic: Smart Grid Energy Management
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4411345779