POI information-based electric vehicle charging station load characteristic clustering modeling method
A technology of electric vehicles and modeling methods, applied in character and pattern recognition, instruments, data processing applications, etc., can solve problems that affect the safe and reliable operation of distribution networks, hidden safety hazards, etc., to achieve safe and reliable operation, accurate and effective, reduce aggregation The effect of class error
Active Publication Date: 2021-09-07
SOUTHEAST UNIV
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However, due to the randomness and volatility of the charging load of electric vehicles currently connected to the power grid, the connection of large-scale electric vehicles to the distribution network will inevitably affect the safe and reliable operation of the distribution network and bring certain security risks.
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[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.
[0045] Such as figure 1 As shown, a clustering modeling method for load characteristics of electric vehicle charging stations based on POI information includes the following steps:
[0046] S1. Traversing the POI data, counting all the subcategories of the POI data, and then according to the correlation between the subcategories, classify the POI data twice to obtain at least one major category of POI data, which includes at least one subclass type;
[0047] In t...
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The invention discloses a POI information-based electric vehicle charging station load characteristic clustering modeling method, and the method comprises the following steps: traversing POI data, carrying out the statistics of all types of the POI data, and carrying out the secondary classification of the POI data; in consideration of the occupied area of the entity building corresponding to the POI information points and the problem of mixing and overlapping of multiple types of POI information points existing in a single entity building, preprocessing the original data; clustering a plurality of electric vehicle charging stations by considering the charging pile power difference of different electric vehicle charging stations and the distribution difference of POI information points within a certain range around the electric vehicle charging stations; for different typical day types in workdays, holidays and festivals, in combination with historical data such as arrival time, charging power, stay duration and charging electric quantity of the electric vehicle, fitting load characteristic models such as a daily load curve, an arrival time distribution curve, an electric quantity difference distribution curve and a V2G participation potential distribution curve of each type of electric vehicle charging station after clustering is completed.
Description
technical field [0001] The invention belongs to the field of steady-state analysis of electric power systems, and in particular relates to a clustering modeling method for load characteristics of electric vehicle charging stations based on POI information. Background technique [0002] In recent years, with the energy crisis and the rapid development of low-carbon economy, electric vehicles, as an important part of the new energy strategy and smart grid, have become the focus of the development of the automobile industry and the energy industry. As an important part of the electric vehicle industry, the number and scale of electric vehicle charging stations have naturally increased and expanded rapidly. However, due to the randomness and volatility of the charging load of electric vehicles currently connected to the power grid, the connection of large-scale electric vehicles to the distribution network will inevitably affect the safe and reliable operation of the distributio...
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IPC IPC(8): G06K9/62G06Q50/06
CPCG06Q50/06G06F18/2321Y02T10/70
Inventor 罗李子王杰顾伟周苏洋吴志
Owner SOUTHEAST UNIV