Electric vehicle peak regulation capacity calculation method based on multi-factor influence conditions

Abstract

The invention relates to the technical field of intelligent power grids, and provides an electric vehicle peak regulation capacity calculation method based on multi-factor influence conditions, whichcomprises the following steps of obtaining the electric vehicle state information and the charging station state information of an electric vehicle, and then preprocessing the electric vehicle state information and the charging station state information; calculating the total income, the weather influence degree value and the SOC threshold value of the electric vehicle participating in the peak regulation according to the preprocessed electric vehicle state information and charging station state information in combination with a distance influence factor, a weather influence factor and an SOCthreshold value influence factor; and according to the calculated total income, the weather influence degree and the SOC threshold value of the electric vehicle participating in the peak regulation and the number of the current charging piles, calculating the peak regulation capacity of the electric vehicle, and obtaining the peak regulation capacity of the electric vehicle based on the multi-factor influence conditions. According to the present invention, the electric vehicle peak regulation capacity obtained through calculation considers the influence of various factors at the same time, sothat the accuracy of the peak regulation capacity can be effectively improved.

Description

technical field [0001] The present invention relates to the technical field of smart grids, and more specifically, to a method for calculating peak-shaving capacity of electric vehicles under the influence of multiple factors. Background technique [0002] Due to the characteristics of large charging and discharging power and fast response to peak regulation, electric vehicle load can be used as an important means of coordinated peak regulation between source and load. [0003] At present, for the V2H mode (vehicle-to-house) of electric vehicles, the research on the impact of electric vehicles on the grid, the research on the participation of electric vehicle loads in peak regulation, and the research on V2H demand management schemes only consider electric vehicles. The impact of single factors such as scale uncertainty, battery capacity uncertainty, power size uncertainty, or demand management on the peaking capacity of electric vehicles does not take into account the numbe...

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Problems solved by technology

[0003]Currently, for the V2H mode (vehicle-to-house) of electric vehicles, the research on the influence of electric vehicles on the grid voltage and the load participation of electric vehicles The peak shaving research and the V2H demand management scheme research only consider the influence of a single conditional factor such as the uncertainty of the scale of electric vehicles, the uncertainty of battery capacity, the uncertainty of power size, or demand management on the peak shaving capacity of electric vehicles , does not take into account the number of electric vehicle charging piles, distance, weather conditions and other factors that affect the peaking capacity of electric vehicles participating in peaking, so there are certain limitations

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