| Title: | Method for planning, optimizing, and regulating EV charging Infrastructure |
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| Authors: | ID Chowdhury, Amor (Author)
ID Klampfer, Saša (Author)
ID Sredenšek, Klemen (Author)
ID Seme, Sebastijan (Author)
ID Hadžiselimović, Miralem (Author)
ID Štumberger, Bojan (Author) |
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| Files: |  Method_for_Planning,_Optimizing-Chowdhury-2022.pdf (5,63 MB)
MD5: 1A8E31847CAAC47A83AA322839380145
 https://www.mdpi.com/1996-1073/15/13/4756
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| Language: | English |
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| Work type: | Scientific work |
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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 paper presents and solves the problems of modeling and designing the required EV charging service capacity for systems with a slow dynamic component. This includes possible bursts within a peak hour interval. A simulation tool with a newly implemented capacity planning method has been developed and implemented for these needs. The method can be used for different system simulations and simultaneously for systems with high, medium, and low service dynamics. The proposed method is based on a normal distribution, a primary mechanism that describes events within a daily interval (24 h) or a peak hour interval (rush hour). The goal of the presented approach, including the proposed method, is to increase the level and quality of the EV charging service system. The near-optimal solution with the presented method can be found manually by changing the service capacity parameter concerning the criterion function. Manual settings limit the number of rejected events, the time spent in the queue, and other service system performance parameters. In addition to manual search for near-optimal solutions, the method also provides automatic search by using the automation procedure of simulation runs and increasing/decreasing the service capacity parameter by a specifically calculated amount. |
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| Keywords: | service system, capacity planning, bursts, rush-hour, normal distribution, stochastic process |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Publication date: | 01.01.2022 |
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| Year of publishing: | 2022 |
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| Number of pages: | str. 1-33 |
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| Numbering: | Letn. 15, št. 13, št. članka 4756 |
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| PID: | 20.500.12556/DKUM-85291  |
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| UDC: | 621.317:502.21:523.9 |
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| ISSN on article: | 1996-1073 |
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| COBISS.SI-ID: | 113319427 |
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| DOI: | 10.3390/en15134756 |
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| Publication date in DKUM: | 24.08.2023 |
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| Views: | 735 |
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| Downloads: | 60 |
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| Metadata: |    |
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| Categories: | Misc.
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