@inproceedings{cb9ca21de2bc4196a1636c6d36c839a9,
title = "Aggregate load models for demand response: Exploring flexibility",
abstract = "This paper describes new aggregate load models of batteries, electric vehicles (EVs) and deferrable appliances (DAs), for use in demand response (DR). Compared to other models that have previously appeared in the literature, the low order models we propose aggregate large populations of devices that share certain parameters. The models also reveal various characteristics of populations of DR devices, such as aggregate energy demand, flexibility and ramping potential. We further look at the different ways the aggregate model consumes energy, identify strategies that bound all others in terms of stored energy and use those to predict the future feasible operating region.",
keywords = "Demand Response, Energy Storage, Load Aggregation, Load Shifting, Reserve Capacity",
author = "Kari Hreinsson and Anna Scaglione and Vijay Vittal",
note = "Funding Information: This research is sponsored by ARPA-E grant DWS1103 as well as Landsvirkjun Energy Research Fund and The Leifur Eirksson Foundation. Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 ; Conference date: 07-12-2016 Through 09-12-2016",
year = "2017",
month = apr,
day = "19",
doi = "10.1109/GlobalSIP.2016.7905978",
language = "English (US)",
series = "2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "926--930",
booktitle = "2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings",
}