DocumentCode :
667015
Title :
Uncertainty in the flexibility of aggregations of demand response resources
Author :
Mathieu, Johanna L. ; Gonzalez Vaya, Marina ; Andersson, Goran
Author_Institution :
Power Syst. Lab., ETH Zurich, Zürich, Switzerland
fYear :
2013
fDate :
10-13 Nov. 2013
Firstpage :
8052
Lastpage :
8057
Abstract :
Aggregations of demand response resources can provide a variety of services to the power grid. To utilize them effectively, for both planning problems and real-time control, we must estimate their flexibility. However, flexibility estimates are uncertain because of issues such as model error and forecasting error. In this paper, we present a model of uncertain flexibility and describe the many causes of uncertainty. We conduct two case studies, one for electric vehicle aggregations and one for air conditioner aggregations, in order to show specific examples that illustrate the causes and magnitude of uncertainty. We find that uncertainty can be very large for small load aggregations, when models do not capture enough of the underlying dynamics, or when forecasts of other quantities, such as ambient conditions, are bad. Although the focus of the paper is on understanding uncertainty, we also briefly discuss how one might use knowledge of uncertainty distributions in planning problems to derive closer-to-optimal results.
Keywords :
air conditioning; electric vehicles; power grids; power system parameter estimation; power system planning; air conditioner aggregations; demand response resource aggregations; electric vehicle aggregations; forecasting error; model error; planning problems; power grid; real-time control; uncertainty distributions; Aggregates; Atmospheric modeling; Batteries; Computational modeling; Load modeling; Real-time systems; Uncertainty; demand response; electric vehicles; energy storage; load management; load modeling; reduced order systems; stochastic systems; uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location :
Vienna
ISSN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2013.6700479
Filename :
6700479
Link To Document :
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