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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/16/9/3790 |
| _version_ | 1797602687684968448 |
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| author | André Ulrich Sergej Baum Ingo Stadler Christian Hotz Eberhard Waffenschmidt |
| author_facet | André Ulrich Sergej Baum Ingo Stadler Christian Hotz Eberhard Waffenschmidt |
| author_sort | André Ulrich |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-11T04:20:07Z |
| format | Article |
| id | doaj.art-6c28b3842f514030b3d6b7926dbd041e |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-11T04:20:07Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-6c28b3842f514030b3d6b7926dbd041e2023-11-17T22:51:51ZengMDPI AGEnergies1996-10732023-04-01169379010.3390/en16093790Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway DataAndré Ulrich0Sergej Baum1Ingo Stadler2Christian Hotz3Eberhard Waffenschmidt4Cologne Institute for Renewable Energies (CIRE), TH Köln, 51519 Cologne, GermanyCologne Institute for Renewable Energies (CIRE), TH Köln, 51519 Cologne, GermanyCologne Institute for Renewable Energies (CIRE), TH Köln, 51519 Cologne, GermanyCologne Institute for Renewable Energies (CIRE), TH Köln, 51519 Cologne, GermanyCologne Institute for Renewable Energies (CIRE), TH Köln, 51519 Cologne, GermanyThe 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.https://www.mdpi.com/1996-1073/16/9/3790electric vehicleoptimisationlinear programmingsmart meter gatewaygrid load |
| spellingShingle | André Ulrich Sergej Baum Ingo Stadler Christian Hotz Eberhard Waffenschmidt Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data Energies electric vehicle optimisation linear programming smart meter gateway grid load |
| title | Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data |
| title_full | Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data |
| title_fullStr | Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data |
| title_full_unstemmed | Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data |
| title_short | Maximising Distribution Grid Utilisation by Optimising E-Car Charging Using Smart Meter Gateway Data |
| title_sort | maximising distribution grid utilisation by optimising e car charging using smart meter gateway data |
| topic | electric vehicle optimisation linear programming smart meter gateway grid load |
| url | https://www.mdpi.com/1996-1073/16/9/3790 |
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