Time and space prediction method for electric vehicle charging load under constraint of urban traffic road network and user travel chain

An electric vehicle, charging load technology, applied in forecasting, data processing applications, instruments, etc., can solve the problem that the traffic road network model does not consider the road level and so on

Active Publication Date: 2018-10-19
SOUTH CHINA UNIV OF TECH +1
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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 consi

Method used

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  • Time and space prediction method for electric vehicle charging load under constraint of urban traffic road network and user travel chain
  • Time and space prediction method for electric vehicle charging load under constraint of urban traffic road network and user travel chain
  • Time and space prediction method for electric vehicle charging load under constraint of urban traffic road network and user travel chain

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Embodiment

[0066] Such as figure 1 , a spatio-temporal prediction method for electric vehicle charging load under the constraints of urban traffic network and user travel chain, including the following steps:

[0067] Step S1, obtaining road network topology information, regional traffic information and travel information;

[0068] Step S1-1, obtain figure 2 The shown regional road network topology information includes the number of road nodes, coordinates, connections, etc., and represents the road topology map with G=(V, E), wherein V represents the collection of nodes in the figure, that is, the starting and ending points or intersections of the road, Numbered in the form of 1,2,3...|V|, E represents the relationship between vertices, that is, the road in the regional traffic system, assuming that all traffic roads in this area are two-way roads; the weighted graph is represented by an adjacency matrix, Graph G=(V,E) corresponds to a matrix D of |V|×|V|; ω represents the weight fun...

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Abstract

The invention discloses a time and space prediction method for an electric vehicle charging load under the constraint of an urban traffic road network and a user travel chain. The method comprises a step of establishing a traffic road model which considers a traffic road network topology and road-impedance function relationship of a Logit-based traffic delay function, a step of dividing an area according to function characteristics and constructing simple and complex travel chains of an electrical vehicle, selecting a travel path with smallest time consumption by using an improved Dijkstra algorithm, and constructing a vehicle travel time and space model, and a step of simulating the spatial and temporal distribution characteristics of the electric vehicle charging load within one day under the constraint of the urban traffic road network and the travel chain.

Description

technical field [0001] The invention relates to the technical field of electric vehicle charging load forecasting, in particular to a spatiotemporal prediction method for electric vehicle charging load under the constraints of urban traffic road network and user travel chain. Background technique [0002] As a green transportation mode that can effectively reduce carbon dioxide emissions, electric vehicles have received extensive attention and support in recent years. Affected by user behavior uncertainty, electric vehicle battery capacity, charging facilities and other factors, electric vehicle charging load shows randomness and volatility in time and space. In the future electric vehicle charging load forecast, it is necessary to fully consider the distribution of electricity consumption behavior under the constraints of traffic road network and travel purpose, and take electric vehicles as a flexible resource to evaluate their adjustable capacity and time period, so as to...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06Q50/30
CPCG06Q10/04G06Q50/06G06Q50/30
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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