A layout method of electric vehicle charging piles based on improved tlbo algorithm

A layout method and technology of charging piles, applied in computing, data processing applications, forecasting, etc., can solve problems such as poor global search ability, easy loss of individual diversity, and difficulty in obtaining the global optimal value of the objective function to achieve a guaranteed balance performance, high precision and good convergence, and the effect of achieving the global optimal solution

Active Publication Date: 2021-03-23
ZHEJIANG UNIV OF TECH
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Problems solved by technology

However, the diversity of individuals is easy to lose, and it is easy to fall into local optimum when solving multi-peak complex problems, the global search ability is poor, and it is difficult to obtain the global optimum value of the objective function

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  • A layout method of electric vehicle charging piles based on improved tlbo algorithm
  • A layout method of electric vehicle charging piles based on improved tlbo algorithm
  • A layout method of electric vehicle charging piles based on improved tlbo algorithm

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Embodiment Construction

[0029] The present invention will be described in detail below according to the accompanying drawings and preferred embodiments, and the purpose and effect of the present invention will become clearer. The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0030] A layout method of electric vehicle charging piles based on the improved TLBO algorithm, such as figure 1 As shown, the method includes the following steps:

[0031] S1: Calculate the K distance dist(i, j) from the i-th user demand to the j-th charging pile, where i∈D, D is the user demand data set;

[0032] S2: Put the dist(i, j) obtained in S1 into the following formula to get the K distance field point N of i k-dist (i)

[0033] N k-dist (i)={i∈D|Dp(i,j)=dist(i,j), dist(i,j)≤k-dist(i)}

...

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Abstract

The invention discloses an electric vehicle charging pile layout method based on an improved TLBO algorithm. The method comprises the following steps of calculating a K distance from a user demand to a charging pile, storing the neighborhood points of the K distance in a set Nk-dist (), solving an average value of the K distance and a mean value of the average value of the K distance according to the known K distance and the neighborhood points of the K distance, and obtaining a K distance factor; comparing the average value of the K distance with the mean value of the average value of the K distance, and storing the obtained result in a set f (x) to determine the position of the charging pile; and calculating the number of the charging piles required by the user according to the K distance factor. According to the method, the relationship between the users and the positions and quantity supply and demand of the electric vehicle charging piles is balanced, and the man-machine interaction ordered charging is better achieved.

Description

technical field [0001] The invention belongs to the field of algorithm planning and specifically designs a method for the layout of electric vehicle charging piles based on an improved TLBO algorithm. Background technique [0002] With the increasing number of electric vehicles in my country, the randomness and mobility of electric vehicles are increasing, and the corresponding charging equipment is also increasing; at the same time, there are many obstacles in the charging of electric vehicles. Charging with electricity has potential safety hazards. At present, the supply of electric vehicle charging equipment in my country is in short supply. The fluidity and randomness of the body make it difficult to determine the location of the installation of charging piles, and it is impossible to solve the balance between the demand and the amount of charging piles. [0003] For the existing swarm intelligence optimization algorithms, such as particle swarm optimization algorithm, D...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q10/06G06Q50/06
CPCG06Q10/043G06Q10/06315G06Q50/06
Inventor 王宪保周红王辛刚
Owner ZHEJIANG UNIV OF TECH
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