| Title: | Energy consumption and grid interaction analysis of electric vehicles based on particle swarm optimisation method |
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| Authors: | ID Deželak, Klemen (Author)
ID Sredenšek, Klemen (Author)
ID Seme, Sebastijan (Author) |
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| Files: |  Energy_consumption_and_grid_interaction_analysis_Dezelak_2023.pdf (2,22 MB)
MD5: DA2D60E336E8548F8D3C6A5804F746E7
 https://www.mdpi.com/1996-1073/16/14/5393
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FE - Faculty of Energy Technology
FERI - Faculty of Electrical Engineering and Computer Science
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| Abstract: | The widespread adoption of electric vehicles poses certain challenges to the distribution grid, which refers to the network of power lines, transformers, and other infrastructure that delivers electricity from power plants to consumers. This higher demand can strain the distribution grid, particularly in areas with a high concentration of electric vehicles. Grid operators need to ensure that the grid infrastructure can handle this additional load and prevent overloading and consequences in terms of additional losses. As part of the task, a methodology was developed for the assessment of the electricity consumption of battery electric vehicles in Slovenia. The approach used for the calculation includes the number of electric cars, average consumption, distance travelled and efficiency of the system. Additionally, the results of the modelling approach for an integrated distribution grid model in terms of steady-state simulations are presented. The regular situation of the power losses within the distribution grid is managed together with an optimal result. In this sense, an application of the particle swarm optimisation-based strategy is suggested to minimise reliance on grid systems. |
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| Keywords: | electric vehicles, distribution grid, optimisation, power losses |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 21.06.2023 |
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| Article acceptance date: | 13.07.2023 |
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| Publication date: | 14.07.2023 |
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| Place of publishing: | Basel |
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| Publisher: | Molecular Diversity Preservation International (MDPI) |
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| Year of publishing: | 2023 |
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| Number of pages: | 15 str. |
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| Numbering: | Letn. 16, Št. 14, 5393 |
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| PID: | 20.500.12556/DKUM-86121  |
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| UDC: | 629.331:621.8.037 |
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| ISSN on article: | 1996-1073 |
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| COBISS.SI-ID: | 158941699 |
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| DOI: | 10.3390/en16145393 |
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| Publication date in DKUM: | 10.10.2023 |
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| Views: | 403 |
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| Downloads: | 33 |
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| Metadata: |    |
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| Categories: | Misc.
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