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 language | English (US) |
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Title of host publication | 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 926-930 |
Number of pages | 5 |
ISBN (Electronic) | 9781509045457 |
DOIs | |
State | Published - Apr 19 2017 |
Event | 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 - Washington, United States Duration: Dec 7 2016 → Dec 9 2016 |
Other
Other | 2016 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2016 |
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Country | United States |
City | Washington |
Period | 12/7/16 → 12/9/16 |
Keywords
- Demand Response
- Energy Storage
- Load Aggregation
- Load Shifting
- Reserve Capacity
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications