Charging station charging load prediction method and system

Abstract

The invention discloses a charging station charging load prediction method and a system, and the method comprises the steps: obtaining a historical charging record of a target charging station, screening and preprocessing a charging sample data set, and obtaining the charging duration and charging electric quantity of each charging record, and the number of charging vehicles of the charging station in each unit time period; obtaining a charging load characteristic data set according to the charging duration and the charging electric quantity of each charging record; obtaining a charging vehicle quantity characteristic data set according to the charging vehicle quantity of the charging station in each unit time period in the charging sample data set; constructing and training a charging load prediction model of each unit time period of the charging station according to the time-of-use electricity price, the charging load characteristic data set and the charging vehicle number characteristic data set; and predicting the charging load of each unit time period by utilizing the charging load prediction model of each unit time period of the charging station. The charging load predictionis carried out on a single-region charging station based on a data rule method, so that the accuracy and applicability of charging load prediction can be improved.

Description

technical field [0001] The invention belongs to the technical field of load forecasting, and relates to a charging load forecasting method and system for a charging station. Background technique [0002] At this stage, with the gradual popularization of charging cars, charging at charging stations has become one of the main charging methods for residents to travel by car. As a power load, the charging load of the charging pile can balance the peak-valley difference through effective power dispatching, and increase the power supply utilization rate of the grid dispatching. [0003] The traditional research method of charging pile charging load is mainly based on probability model. Typical probability models include: probability average model, Monte Carlo sampling probability model, probability model based on travel statistics, etc. The probability average model uses the idea of ​​probability average to calculate the charging load of discrete points, and considers the probab...

AI Technical Summary

Problems solved by technology

[0004] The above-mentioned traditional charging load forecasting depends on the probability model, and the accuracy of the charging load forecasting depends on the accuracy of the probability statistics, and the charging laws in different regions are not the same, and the traditional model depends on the user habits, battery charging characteristics and other probability models, It has a large randomness, so the traditional probability model is not applicable to the charging load in different regions

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