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 infr...

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Bibliographic Details
Published in:Energies (Basel) 2023-04, Vol.16 (9), p.3790
Main Authors: Ulrich, André, Baum, Sergej, Stadler, Ingo, Hotz, Christian, Waffenschmidt, Eberhard
Format: Article
Language:English
Subjects:
Algorithms
Automobiles, Electric
Carbon dioxide
Charging
Climate policy
Control algorithms
Decentralization
Electric power
electric vehicle
Electric vehicles
Electrical loads
Electricity distribution
Electricity generation
Emission standards
Emissions
Environmental policy
grid load
Households
Infrastructure (Economics)
Linear programming
Load
Mathematical optimization
Mathematical programming
optimisation
Power supply
smart meter gateway
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Summary: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.
ISSN:1996-1073
1996-1073
DOI:10.3390/en16093790