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Electric vehicle charging load prediction method considering space-time distribution

A technology for electric vehicles and charging loads, applied in the field of power grids, can solve problems such as intermittency, randomness in time and space, and little consideration of spatial distribution laws

Inactive Publication Date: 2018-02-16
NARI TECH CO LTD +4
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AI Technical Summary

Problems solved by technology

At the same time, the charging load of electric vehicles has uncertain characteristics such as randomness, intermittency, and volatility in time and space, which brings new problems to power grid planning, safe operation, and optimal scheduling.
[0003] Existing load forecasting technology usually only focuses on the time-varying characteristics of electric vehicle charging load when analyzing its impact on distribution network load
However, its spatial distribution is rarely considered, and most forecasting methods do not fully consider the influencing factor of traffic flow.

Method used

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  • Electric vehicle charging load prediction method considering space-time distribution

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Embodiment Construction

[0031] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.

[0032] A method for predicting electric vehicle charging load considering time-space distribution of the present invention fully considers electric vehicle battery characteristics, charging mode, initial state of charge (SOC), traffic volume distribution and other factors.

[0033] First, according to the current travel distribution data of each traffic area, the growth coefficient method is used to calculate the predicted value of future traffic occurrence and attraction volume, and then predict the future traffic distribution among various regions; and then use the shortest path method to predict all traffic The traffic volume between the districts (i.e. OD matrix), combined with the existing road network structure information, covers all road se...

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Abstract

The invention discloses an electric vehicle charging load prediction method considering space-time distribution. The electric vehicle charging load prediction method considering space-time distribution includes the following steps: 1) according to the trip occurrence quantity and the trip attraction of an existing traffic zone, utilizing a growth factor method to calculate the trip occurrence quantity and the trip attraction of a future traffic zone; 2) utilizing a traffic distribution prediction model to calculate traffic volume distribution among each traffic zone in the future; 3) through ashortest path method, covering all the roads, of the road network, with the OD data among all the traffic zones, and calculating the traffic flow on all the trip paths in the road network, and the traffic flow values of all the roads; and 4) inputting the original data of an electric vehicle, based on the traffic flow of each road, performing analog simulation on the trip path of the electric vehicle, and calculating the charging load of the electric vehicle during the charging period to generate a charging load curve of each charging station in the set time quantum in the future so as to provide data support for planning and operating of the charging stations so as to provide basis for space load prediction of the power distribution network.

Description

technical field [0001] The invention relates to a method for predicting electric vehicle charging loads considering time and space distribution, and belongs to the technical field of power grids. Background technique [0002] As a low-carbon and clean means of transportation, electric vehicles have received more and more attention. At present, the industrial development of electric vehicles is mainly restricted by factors such as price, cruising range, and construction of charging facilities. At the same time, the charging load of electric vehicles has uncertain characteristics such as randomness, intermittency, and volatility in time and space, which brings new problems to power grid planning, safe operation, and optimal scheduling. [0003] The existing load forecasting technology usually only focuses on the time-varying characteristics of electric vehicle charging load when analyzing its impact on distribution network load. However, its spatial distribution is rarely co...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 姜晓慧韩韬戚艳张磐宋云翔吴雪琼亢洁徐玮黄素娟张晓青宋伟谢琳
Owner NARI TECH CO LTD
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