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Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data

  • The transition towards climate neutrality will result in an increase in electrical vehicles, as well as other electric loads, leading to higher loads on electrical distribution grids. This paper presents an optimisation algorithm that enables the integration of more loads into distribution grid infrastructure using information from smart meters and/or smart meter gateways. To achieve this, a mathematical programming formulation was developed and implemented. The algorithm determines the optimal charging schedule for all electric vehicles connected to the distribution grid, taking into account various criteria to avoid violating physical grid limitations and ensuring non-discriminatory charging of all electric vehicles on the grid while also optimising grid operation. Additionally, the expandability of the infrastructure and fail-safe operation are considered through the decentralisation of all components. Various scenarios are modelled and evaluated in a simulation environment. The results demonstrate that the developed optimisation algorithm allows for higher transformer loads compared to a P(U) control approach, without causing grid overload as observed in scenarios without optimisation or P(U) control.
Metadaten
Author:André Ulrich, Sergej Baum, Ingo Stadler, Christian Hotz, Eberhard Waffenschmidt
URN:urn:nbn:de:hbz:832-epub4-21517
DOI:https://doi.org/10.3390/en16093790
ISSN:1996-1073
Parent Title (English):Energies
Publisher:MDPI
Editor:Francesco Calise
Document Type:Article
Language:English
Date of first Publication:2023/04/28
Date of Publication (online):2023/05/09
GND-Keyword:Brennstoffzellenfahrzeug; Hybridfahrzeug; Optimierung
Tag:Electric Vehicle; Grid Load; Linear Programming; Optimisation; Smart Meter Gateway
Volume:16
Issue:9
Page Number:20
Institutes:Informations-, Medien- und Elektrotechnik (F07) / Fakultät 07 / Institut für Elektrische Energietechnik
Dewey Decimal Classification:600 Technik, Medizin, angewandte Wissenschaften / 620 Ingenieurwissenschaften und Maschinenbau
Open Access:Open Access
DeepGreen:DeepGreen
OA-Publicationfonds TH Köln:OA-Publicationfonds TH Köln
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International