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Optimal design of electric vehicle charging stations for commercial premises

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submitted on 2024-04-23, 10:15 and posted on 2024-04-23, 10:17 authored by Islam Safak Bayram, Michael Devetsikiotis, Raka Jovanovic

Influx of plug-in electric vehicles (PEVs) creates a pressing need for carefulcharging infrastructure planning. In this paper, the primary goal is to devise aclosed-form expression for the PEV charging station capacity problem. Twotypes of commercial charging stations are considered. The first problem isrelated to the calculation of the optimal service capacity for charging lotslocated at workplaces where PEV parking statistics are given as a priori. Thesecond problem, on the other hand, is related to the optimisation of arrivalrates for a given station capacity. In the second part, the mathematical modelsare expanded for the case where multiple charger technologies serve customerdemand. This time the goal is to calculate the optimal customer load for eachcharger type according to its rate. Calculations are carried out for both socialand individual optimality cases. Markovian queues are used to model thecharging station system to capture the complex interactions between customerload, service waiting times, and electricity cost. The related optimisation prob-lems are solved using convex optimisation methods. Closed-form expressionsof station capacity and optimal arrival rates are explicitly derived. Both analyti-cal calculations and discrete-event simulations are carried out and the resultsshow that 60% of the waiting times and 42% of the queue length can bereduced by optimal capacity planning.

Other Information

Published in: International Journal of Energy Research
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1002/er.6523

History

Language

  • English

Publisher

Wiley

Publication Year

  • 2021

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • Qatar Environment and Energy Research Institute - HBKU

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