Development of the Module of Charging Stations Placement for Electric Transport Based on Genetic Algorithm

The implementation of energy transformation strategies has led to tangible changes in the approaches to the organization of modern energy systems through the involvement of new generation sources and new types of consumers that require better planning and organization of distributed systems. One example of such innovations is the ubiquity of electric transportation in large cities, which is becoming widespread. This process is driven by various factors, the most important of which is the environmental safety factor of modern society. Despite the fact that the development of technology makes such transport more and more capable and competitive with traditional types, there are some limitations, primarily due to the low autonomy of such vehicles, which leads to the need to organize specialized charging points. The problem of charging station location involves determining the most optimal locations for station placement, depending on the selected parameters of the target function, for which various approaches are used: linear programming, multi-criteria and meta-heuristic optimization, genetic and evolutionary algorithms. This paper considers the process of implementation of the software module for determining the optimal locations of electric vehicle charging stations based on the use of genetic algorithm, the main criterion of which is the maximum utilization rate of the operated stations.