Automated time series based grid extension planning using a coupled agent based simulation and genetic algorithm approach

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CIRED 2019 - 1142.pdf (400.66 KB)

Paper number

1142

Working Group Number

Conference name

CIRED 2019

Conference date

3-6 June 2019

Conference location

Madrid, Spain

Peer-reviewed

Yes

Short title

Convener

Authors

Hiry, Johannes, TU Dortmund university - Institute of Energy Systems- Energy Efficiency and Energy Economics, Germany
Kittl, Chris, TU Dortmund university - Institute of Energy Systems Energy Efficiency and Energy Economics, Germany
Römer, Christian, TU Dortmund University / Institute of Energy Systems Energy Efficiency and Energy Economics, Germany
Rehtanz, Christian, TU Dortmund university - Institute of Energy Systems Energy Efficiency and Energy Economics, Germany
Schimmeyer, Sebastian, intulion solutions GmbH, Germany
Willmes, Lars, intulion solutions GmbH, Germany

Abstract

In recent years, the distribution grid planning process has faced the big challenge to integrate renewable energy sources in its planning methodology while preserving a secure and stable provision of electricity. With the currently observable efforts to electrify human mobility all around the world, another new challenge arises for the planning and operation of distribution grids. To address these challenges and to leverage the opportunities that are accompanied by them, new methods for the planning of distribution grids as well as planning decision-supportive approaches and algorithms are needed. The presented approach contributes to the described demands by means of a coupled approach, using both distribution grid time series as well as a genetic algorithm to support decision making in the planning process considering not only new assets for grid reinforcements and extensions but also smart-grid and operational opportunities. 

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Keywords

Publisher

AIM

Date

2019-06-03

Published in

CIRED 2019 Conference

Permanent link to this record

https://cired-repository.org/handle/20.500.12455/317
http://dx.doi.org/10.34890/548

ISSN

2032-9644

ISBN

978-2-9602415-0-1