Electric vehicle charging load spatio-temporal distribution prediction method

An electric vehicle, charging load technology, applied in electric vehicle charging technology, climate sustainability, design optimization/simulation, etc., to achieve the effect of widely expanding analysis capabilities, reducing dependencies, and avoiding simplified assumptions

Pending Publication Date: 2022-08-05
TIANJIN UNIV
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  • Description
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  • Electric vehicle charging load spatio-temporal distribution prediction method
  • Electric vehicle charging load spatio-temporal distribution prediction method
  • Electric vehicle charging load spatio-temporal distribution prediction method

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Embodiment Construction

[0118] The present invention is described in detail below in conjunction with the accompanying drawings:

[0119] like figure 1 shown, step (1) traffic simulation and information initialization

[0120] According to the regional information, establish the dynamic topology structure of the regional road network including the road segment weight matrix and the node turning weight matrix; and calculate the road segment travel time in each time period based on the historical road network road segment flow data; based on the established road network topology and history Data such as road flow, road length, capacity, etc., are simulated by the micro-simulation software Synchro to obtain various information such as the signal period and effective red light duration of the signal lights at each intersection, and then the intersection delay time of different turns at each intersection is calculated according to the Synchro software. ;Initialize simulation information such as vehicle p...

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Abstract

The invention discloses an electric vehicle charging load space-time distribution prediction method, which is a charging load space-time distribution prediction model considering the influence of time delay caused by intersection signal lamps and the like on an electric vehicle travel route. The prediction model adopts the following steps: step (1) using Synchro software to assist in establishing a traffic simulation module and initializing information; step (2), obtaining user travel parameters in a prediction area; (3) establishing a spatio-temporal information prediction unit by predicting the traveling and charging behaviors of the electric vehicles in the region; (4) calculating nodes in the power distribution network according to a spatio-temporal information prediction result to generate a charging power matrix; on one hand, optimization design of traffic signals can be carried out based on a road network structure and historical traffic flow data according to a traffic system related signal optimization theory; on the other hand, the problem that actual traffic signal control parameters of road network intersections are difficult to obtain is solved, and the average vehicle delay time obtained through calculation can consider traffic flow fluctuation and different delays of different turning intersections under signal control.

Description

Technical field: [0001] The invention belongs to the field of electric vehicle charging, in particular to a method for predicting the spatiotemporal distribution of electric vehicle charging loads. Background technique: [0002] Market penetration of electric vehicles is growing rapidly as a clean alternative to gasoline vehicles, and their electricity demand is also rising sharply. Under the traditional uncontrolled charging strategy, the access of a large number of electric vehicles will affect the operation and planning of the distribution network, put pressure on the distribution network infrastructure, cause the voltage drop of the distribution network nodes, transformer overload and shortened life, and line overload. , higher power distribution loss, power supply and demand mismatch, phase imbalance and other issues. In order to estimate the impact of electric vehicles on the power distribution system and support the normal operation and planning of the system, the ch...

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Application Information

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IPC IPC(8): G06F30/20
CPCG06F30/20Y04S30/12
Inventor 刘艳丽刘珂
Owner TIANJIN UNIV
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