DETERMINATION OF OPTIMAL NUMBER AND PLACES OF LOCATION OF CHARGING STATION FOR ELECTRIC VEHICLES INSIDE THE CITY
Journal Title: Комп’ютерне моделювання: аналіз, управління, оптимізація - Year 2019, Vol 1, Issue 1
Abstract
The article deals with the problem of optimal placement of charging stations for electric vehicles in Dnipro under the assumption that the existing sites for parking should be primarily equipped with such stations. Based on the results of electric vehicles market analysis, generally in Ukraine, as well as inside Dnipro city, of the number of electric car owners, technical parameters of electric vehicles and charging stations and also operation conditions of charging stations that already exist in the territory of the city, the issue about rational quantity of charging stations which need to be placed for satisfying current demand should be settled above all. After that, taking into consideration transport infrastructure of the city, the search of the estimated number of car parking lots among operational ones is carried out in order to find the ones where chargers are mostly rational to be installed (according to territorial criterion). Thus, the purpose of optimization is to minimize the distance from the most remote car parking lot to the nearest charging station. Determination of the optimal number of charging stations in Dnipro, which ensures minimal total losses from posts downtime and service denial, is carried out using models and methods of Queuing theory. The analysis of such parameters of the Queuing system as the flow of applications and the possible efficiency of channels was carried out. The implementation of the Queuing system is effected using C++ programming language with the following source data. The calculation of the optimal number of charging pistols in the city is based on the assumption that in terms of value, income from one charging pistol operation and expenses for its maintenance under forced downtime are almost the same and the coefficient of net income of charging station for electric vehicles is proportional to the difference between the average number of electric vehicles serviced by the system and the number of pistols forced to stand idle. To solve the combinatorial optimization issue, the approximate algorithm of the artificial immune system is used.
Authors and Affiliations
Л. С. Коряшкіна, О. Р. Бєляєв
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