Method and system for predicting short-time power of electric vehicle charging stations

Abstract

The invention provides a method and system for predicting short-time power of electric vehicle charging stations. The method comprises the following steps of: obtaining charging models of types of electric vehicles, and constructing an electric vehicle load prediction model of an electric vehicle charging station according to the charging models; simulating the electric vehicle load prediction model by adoption of a Monte Carlo simulation method so as to obtain a charging power prediction value of the electric vehicle charging station in a preset time range; judging a residual error of the charging power prediction value satisfies a verification condition or not; and if the judging result is negative, correcting the electric car load prediction model by adoption of a Markov chain model, and re-simulating the corrected electric vehicle load prediction model to obtain a new charging power prediction value until a residual error of the new charging power prediction value satisfies the verification condition. Compared with the prior art, the method and system for predicting short-time power of electric vehicle charging stations can improve the accuracy of predicting the short-time power of the electric vehicle charging stations.

Description

A short-term power prediction method and system for an electric vehicle charging station technical field The invention relates to the technical field of power system power prediction, in particular to a short-term power prediction method and system for an electric vehicle charging station. Background technique The electric vehicle charging station can be regarded as the load of the active power distribution network. There are many obstacles to power modeling of . At present, the method of parameter fitting is mainly used to obtain the probability density function of the mileage of electric vehicles, and convolution calculation is performed to obtain the charging power expectation of a single vehicle sequence, and then the charging model of electric vehicles in the power distribution network is obtained. This electric vehicle charging model is based on the electric vehicle charging power distribution of the electric vehicle group based on the central limit theorem, so it c...

AI Technical Summary

Problems solved by technology

This electric vehicle charging model is based on the electric vehicle charging power distribution of the electric vehicle group based on the central limit theorem, so it can obtain the charging load of the whole system with time series characteristics, but it cannot accurately obtain the spatial distribution characteristics of the electric vehicle charging power, thus affecting Prediction Results of Electric Vehicle Charging Load in Distribution Network

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