Taming uncertainty in distribution grid planning – A scenario-based methodology for the analysis of impact of electric vehicles.

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CIRED 2019 - 1955.pdf (442.48 KB)

Paper number

1955

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Conference name

CIRED 2019

Conference date

3-6 June 2019

Conference location

Madrid, Spain

Peer-reviewed

Yes

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Convener

Authors

Toffanin, Damiano, Adaptricity AG, Switzerland
Ulbig, Andreas, Adaptricity AG, Switzerland

Abstract

Investigating grid adequacy for future scenarios of electricity demand is a continuing concern among distribution grid planners and power system researchers. The wide-spread adoption of plug-in electric vehicles (PEVs) is connected with increased risks of line overloading or undervoltage events, because of the significant additional load associated at traditional peak loading times and a high coincidence factor of these new load types.Understanding the complexity of ensuring long-term adequacy of distribution grids, given the uncertainty associated to such game-changing trends, is vitally important to design reliable methods. This paper presents a scenario-based grid analysis and grid planning method using Monte Carlo simulations, that quantifies the likelihood of critical grid situations and can be used by grid planners to target actions such as grid upgrades and grid reconfigurations in advance. Overall, the aim is to achieve better cost-efficiency in grid planning by taming, e.g. reducing, planning uncertainties caused by changing grid usage patterns. The methodology can be applied to both medium- and low-voltage grids.The scenario-based grid planning method is designed to focus on voltage violation and component overloading (i.e. lines and transformers), given an uncoordinated penetration of new appliance types in the form of PEVs. The results can then be exploited as a starting point for the implementation of countermeasures.

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Publisher

AIM

Date

2019-06-03

Published in

CIRED 2019 Conference

Permanent link to this record

https://cired-repository.org/handle/20.500.12455/660
http://dx.doi.org/10.34890/882

ISSN

2032-9644

ISBN

978-2-9602415-0-1