DocumentCode :
666944
Title :
Stochastic programming of vehicle to building interactions with uncertainty in PEVs driving for a medium office building
Author :
Cardoso, Ghendy ; Stadler, Mark ; Chehreghani Bozchalui, Mohammad ; Sharma, Ritu ; Marnay, Chris ; Barbosa-Povoa, A. ; Ferrao, P.
Author_Institution :
Inst. Super. Tecnico, Tech. Univ. of Lisbon, Lisbon, Portugal
fYear :
2013
fDate :
10-13 Nov. 2013
Firstpage :
7648
Lastpage :
7653
Abstract :
The large scale penetration of electric vehicles (EVs) will introduce technical challenges to the distribution grid, but also carries the potential for vehicle-to-grid services. Namely, if available in large enough numbers, EVs can be used as a distributed energy resource (DER) and their presence can influence optimal DER investment and scheduling decisions in microgrids. In this work, a novel EV fleet aggregator model is introduced in a stochastic formulation of DER-CAM [1], an optimization tool used to address DER investment and scheduling problems. This is used to assess the impact of EV interconnections on optimal DER solutions considering uncertainty in EV driving schedules. Optimization results indicate that EVs can have a significant impact on DER investments, particularly if considering short payback periods. Furthermore, results suggest that uncertainty in driving schedules carries little significance to total energy costs, which is corroborated by results obtained with the stochastic formulation of the problem.
Keywords :
buildings (structures); distributed power generation; electric vehicles; energy resources; stochastic programming; EV fleet aggregator model; PEV; distributed energy resource; distribution grid; electric vehicles; medium office building; microgrids; optimization tool; short payback periods; stochastic formulation; stochastic programming; vehicle to building interactions; vehicle to grid services; Density estimation robust algorithm; Electricity; Investment; Microgrids; Schedules; Stochastic processes; System-on-chip; distributed energy resources; driving patterns; electric storage; electric vehicles; microgrids; 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.2013.6700407
Filename :
6700407
Link To Document :
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