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Spatio-temporal prediction method of electric vehicle charging load under the constraints of urban traffic network and user travel chain

A technology for electric vehicles and charging loads, which is applied in forecasting, data processing applications, instruments, etc., and can solve the problem that the traffic road network model does not consider road grades, etc.

Active Publication Date: 2021-12-21
SOUTH CHINA UNIV OF TECH +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The research on electric vehicle charging load has involved the traffic road network, but the establishment of the traffic road network model is relatively simple without considering the comprehensive impact of various factors such as road grades, traffic lights at intersections, and user travel chains on the charging demand of electric vehicle users.

Method used

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  • Spatio-temporal prediction method of electric vehicle charging load under the constraints of urban traffic network and user travel chain
  • Spatio-temporal prediction method of electric vehicle charging load under the constraints of urban traffic network and user travel chain
  • Spatio-temporal prediction method of electric vehicle charging load under the constraints of urban traffic network and user travel chain

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Embodiment

[0066] like figure 1 , Electric vehicle charging load temporal prediction method in an urban road network and user constraints trip chain, comprising the steps of:

[0067] Step S1, the road network acquiring topology information, travel information and traffic information region;

[0068] Step S1-1, get figure 2 Shown regional road network topology information, including road node number, coordinates, etc. is connected to G = (V, E) represents the road topology, where V represents a set of nodes in the graph, i.e., start and end points of a road or intersection, to 1,2,3 ...... | V | form of numbers, E represents the relationship between the vertices, i.e., the region represents a road traffic system, assuming all the roads in the region are bidirectional path; weighted adjacency matrix representation in FIG. FIG G = (V, E) corresponding to a | V | × | V | matrix D; ω is the weight function of the road network, i.e. impedance function. D adjacency matrix elements d ij Assignment ...

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Abstract

The invention discloses a spatio-temporal forecasting method for electric vehicle charging load under the constraints of urban traffic road network and user travel chain, the method includes the following steps: firstly establish road-impedance considering traffic road network topology and flow delay function based on Logit The traffic road model of functional relationship; secondly, divide the area according to the functional characteristics, construct the simple and complex travel chains of household electric vehicles, use the improved Dijkstra algorithm to select the shortest time-consuming driving path, and build the vehicle travel space-time model; then simulate the regional traffic network and Spatio-temporal distribution characteristics of electric vehicle charging load in one day under the double constraints of travel chain.

Description

Technical field [0001] The present invention relates to the field of electric vehicle charging load prediction techniques, and more particularly to an urban traffic network and an electric vehicle charging load time and space prediction method under the constraint of users. Background technique [0002] Electric vehicles are used as an effective way to reduce carbon dioxide emissions, and have received extensive attention and support in recent years. Affected by uncertainty of user behavior and electric vehicle battery capacity, charging facilities, electric vehicle charging load exhibits randomness and volatility of time and space. In the future, electric vehicle charging load predictions need to be fully considered to use electricity behavior distribution under traffic road network and travel purposes, and use electric vehicles as a flexible resource, evaluate its adjustable capacity and time, and reduce large-scale electricity for the development of regulatory strategies. The ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06Q50/06G06Q50/30
CPCG06Q10/04G06Q50/06G06Q50/40
Inventor 杜兆斌李含玉陈丽丹周保荣洪潮赵文猛
Owner SOUTH CHINA UNIV OF TECH
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