Electric taxi charging station planning method based on adaptive quantum genetic algorithm

Abstract

The present invention relates to an electric taxi charging station planning method based on an adaptive quantum genetic algorithm. The method comprises the steps of (1) initializing basic data needed by planning, and estimating the value range of a charging station number, (2) randomly generating a chromosome corresponding formula, and forming a population, (3) carrying out solution space transformation and mapping a randomly generated angular space to a charging station address coordinate space, (4) using a Voronoi diagram to divide the service range of a charging station corresponding to chromosome, (5) calculating the average waiting time in queue of each charging station based on the charging requirement in the service range, (6) planning the expression of total society whole year total cost target function minimization according to electric taxi charging stations, (7) carrying out a quantum rotation gate updating operation and a quantum bit variation operation, (8) returning to the step (3) to carry out loop calculation until a convergence condition is satisfied. The method has the advantages that the optimized layout of charging station site is realized, the influence on the planning by taxi distribution, passenger demand distribution, and a road network structure can be reflected, and the method is effective and practical.

Description

technical field [0001] The invention relates to electric taxi charging station planning, in particular to an electric taxi charging station planning method based on an adaptive quantum genetic algorithm. Background technique [0002] The promotion of new energy vehicles is conducive to reducing vehicle exhaust emissions and reducing the dependence of transportation operations on fossil fuels, which has become an important measure to solve my country's environmental problems. In recent years, my country has vigorously promoted electric taxis. More than 800 electric taxis have been put into use in Shenzhen, and 400 electric taxis are in operation in Nanjing. However, due to the short mileage and long charging time of electric taxis, serious charging queues appear in charging stations, which is not conducive to the promotion of electric taxis; Consumed time is a precious resource that cannot be ignored. [0003] Electric taxis have a wide range of operations, and the behavior...

AI Technical Summary

Problems solved by technology

However, due to the short mileage and long charging time of electric taxis, serious charging queues appear in charging stations, which is not conducive to the promotion of electric taxis; Consumed time is a precious resource that cannot be ignored

[0003] Electric taxis have a wide range of operations, and the behavior patterns of empty driving, passenger search, and passenger loading are very random, which brings difficulties to the planning of charging stations for electric taxis that do not exist in the planning of charging stations for ordinary electric vehicles

At present, many scholars have done a lot of research on the planning of electric vehicle charging stations, but there are few studies on the planning of electric taxi charging stations based on the charging behavior characteristics of electric taxis.

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