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Generating worst-case scenarios by randomly distributing loads for risk assessment in low voltage residential electricity grids

Yang, Shangdan and Bergmann, Peggy and Derendorf, Karen and Schuldt, Frank and Maydell, Karsten von (2020) Generating worst-case scenarios by randomly distributing loads for risk assessment in low voltage residential electricity grids. In: esrel. Research Publishing, Singapore. 30th ESREL 2020, 1.-5. Nov 2020, Venedig, Italien and online.

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Abstract

In order to assess the capacity of low voltage electricity grids different grid operation cases are usually analyzed. These cases are used to identify weaknesses in the grid, evaluate the risks involved and subsequently facilitate the integration of new loads such as electric vehicles or heat pumps which are joining these grids in an increasing degree. This study suggests a random load allocation algorithm to create realistic worst-case scenarios for grid operation without the need for historical load data or reverting to load profiles. This is achieved by distributing loads asymmetrically across all three phases so that they comply with grid codes and burden the local transformer moderately. In this way, a multitude of feasible load scenarios is generated and evaluated. A metric is proposed to select those scenarios which lead to a critical operation state of the grid. The generated worst-case scenarios can be used to evaluate the potential capacity and risks of integrating new consumers into grids. This is demonstrated in a use case where electric vehicles are integrated into the investigated grid at half of all connection points. The Analysis shows that the grid is additionally stressed and the reinforcement of cables or charge management would be required to facilitate the safe operation of the grid with additional loads.

Item URL in elib:https://elib.dlr.de/138926/
Document Type:Conference or Workshop Item (Speech)
Title:Generating worst-case scenarios by randomly distributing loads for risk assessment in low voltage residential electricity grids
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Yang, ShangdanShangdan.Yang (at) dlr.deUNSPECIFIED
Bergmann, PeggyPeggy.Bergmann (at) dlr.deUNSPECIFIED
Derendorf, KarenKaren.Derendorf (at) dlr.deUNSPECIFIED
Schuldt, Frankfrank.schuldt (at) dlr.dehttps://orcid.org/0000-0002-4196-2025
Maydell, Karsten vonKarsten.Maydell (at) dlr.dehttps://orcid.org/0000-0003-0966-5810
Date:2020
Journal or Publication Title:esrel
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Editors:
EditorsEmailEditor's ORCID iD
Baraldi, PieroUNSPECIFIEDUNSPECIFIED
Di Maio, FrancescoUNSPECIFIEDUNSPECIFIED
Zio, EnricoUNSPECIFIEDUNSPECIFIED
Publisher:Research Publishing, Singapore
Status:Accepted
Keywords:worst-case scenarios, random loads, asymmetric loads, risk assessment, low voltage electricity grid
Event Title:30th ESREL 2020
Event Location:Venedig, Italien and online
Event Type:international Conference
Event Dates:1.-5. Nov 2020
HGF - Research field:Energy
HGF - Program:Technology, Innovation and Society
HGF - Program Themes:Renewable Energy and Material Resources for Sustainable Futures - Integrating at Different Scales
DLR - Research area:Energy
DLR - Program:E SY - Energy Systems Analysis
DLR - Research theme (Project):E - Energy Systems Technology (old)
Location: Oldenburg
Institutes and Institutions:Institute of Networked Energy Systems
Deposited By: Derendorf, Karen
Deposited On:09 Dec 2020 18:35
Last Modified:09 Dec 2020 18:35

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