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.

Original languageEnglish (US)
Title of host publication2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages926-930
Number of pages5
ISBN (Electronic)9781509045457
DOIs
StatePublished - Apr 19 2017
Event2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States
Duration: Dec 7 2016Dec 9 2016

Other

Other2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016
CountryUnited States
CityWashington
Period12/7/1612/9/16

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Keywords

  • Demand Response
  • Energy Storage
  • Load Aggregation
  • Load Shifting
  • Reserve Capacity

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

Cite this

Hreinsson, K., Scaglione, A., & Vittal, V. (2017). Aggregate load models for demand response: Exploring flexibility. In 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings (pp. 926-930). [7905978] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2016.7905978