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A Load Forecasting Method for Charging Stations Based on Multiple Choices by Users
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A technology of load forecasting and charging stations, applied in forecasting, data processing applications, instruments, etc., can solve the problem of no combination of multiple influencing factors, and achieve high accuracy
Active Publication Date: 2022-06-24
GUANGDONG UNIV OF TECH
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[0004] In order to solve the problem that multiple influencing factors are not combined in the process of existing charging station load forecasting, the present invention provides a charging station load forecasting method based on multiple choices of users
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Embodiment 1
[0053] A charging station load prediction method based on user multiple selection, applied to such as figure 2 In the scenario shown, the method includes as figure 1 The following steps are shown:
[0054] S1. Determine the location range for prediction, and obtain relevant parameters of charging stations and electric vehicles to be charged within the location range, and the relevant parameters include the number of charging stations within the location range, the number of charging stations in each charging station The number of charging piles, the number of electric vehicles;
[0055] S2. Within the range of the location, obtain the influence of different factors on the selection of charging stations by the corresponding users of electric vehicles, and calculate the attractiveness of each charging station to the corresponding users of electric vehicles a i,n ;
[0056] S3. According to the attraction a i,n Calculate the number of electric vehicles in the charging station ...
Embodiment 2
[0059] A charging station load prediction method based on user multiple selection, applied to such as figure 2 In the scenario shown, the method includes the following steps:
[0060] S1. Determine the location range for prediction, and obtain relevant parameters of charging stations and electric vehicles to be charged within the location range, and the relevant parameters include the number of charging stations within the location range, the number of charging stations in each charging station The number of charging piles, the number of electric vehicles;
[0061] S2. Within the range of the location, obtain the influence of different factors on the selection of charging stations by the corresponding users of electric vehicles, and calculate the attractiveness of each charging station to the corresponding users of electric vehicles a i,n ;
[0062] The specific steps include:
[0063] S21. Within the range of the location, obtain the distance between the electric vehicle ...
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Abstract
The invention discloses a charging station load forecasting method based on multiple user choices, comprising: S1. determining the location range for prediction, and acquiring relevant parameters of the charging station and electric vehicles to be charged within the location range; S2. Within the scope of the location, obtain the impact of different factors on the selection of charging stations for corresponding users of electric vehicles, and calculate the attractiveness of each charging station to corresponding users of electric vehicles; S3. The number of cars, and the probability that the electric cars currently in the charging station will leave; S4. Calculate the charging load of the charging station through the Monte Carlo method. The present invention takes the distance of the charging station and the surrounding shops, schools and other factors into the calculation when predicting the load of the charging station, and performs load prediction for multiple charging stations at the same time, which solves the problem that many charging stations are not included in the existing charging load prediction process. A question of combining influencing factors.
Description
technical field [0001] The invention relates to the technical field of electric vehicle charging load prediction, in particular to a charging station load prediction method based on multiple user selections. Background technique [0002] As an important support system for the development of electric vehicles, the reasonable planning and construction of charging infrastructure is of great significance to the development of the electric vehicle industry. At this stage, the research on charging infrastructure planning needs to be carried out on the basis of electric vehicle charging load prediction. Usually, a load forecasting model is established by considering factors such as the scale, charging mode, operation law, battery characteristics and electricity price system of electric vehicles. [0003] In general, the load of the charging pile is mainly affected by two factors, one is the charging power of the electric vehicle, and the other is the charging time of the electric ...
Claims
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