Region electric vehicle charge load time and space distribution prediction method

An electric vehicle, charging load technology, applied in electric vehicle charging technology, forecasting, data processing applications, etc., can solve problems such as insufficient consideration

Active Publication Date: 2018-09-07
GUANGZHOU COLLEGE OF SOUTH CHINA UNIV OF TECH
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Problems solved by technology

[0003] At present, many literatures have carried out research on the forecasting of electric vehicle charging load, and achieved fruitful results, some of which are based on the time distribution characteristics of electric vehicle charging load, and there are many related research results on the analysis of the impact analysis of electric vehicle access to the grid. , but the current method does not take into a

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  • Region electric vehicle charge load time and space distribution prediction method
  • Region electric vehicle charge load time and space distribution prediction method
  • Region electric vehicle charge load time and space distribution prediction method

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Embodiment

[0086] Such as figure 1 As shown, the electric vehicle charging load spatio-temporal prediction model framework constructed by the present invention includes three parts: multi-source information / data layer, model layer and algorithm layer. , using the residents’ travel survey database to form a travel model, constructing a power consumption model per kilometer based on weather temperature data and traffic flow data, and establishing a single electric vehicle charging model based on vehicle information and charging facility information. Based on this, the Monte Carlo method is used to generate uncertainty parameters such as the travel chain type, first travel time, and residence time of each electric vehicle when predicting the charging load of electric vehicles; Electricity consumption per kilometer of the road section; according to the destination of the travel chain, the shortest path is used as the constraint condition, combined with the road traffic model, the shortest pa...

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Abstract

The invention discloses a region electric vehicle charge load time and space distribution prediction method, comprising the following steps S1, establishing a road network model based on road networkinformation, establishing a power grid model according to power grid information, and establishing a road network-power grid coupling relationship; S2, through combination of a resident travel database and through introduction of travel chains, fitting first-time travel time and residence time at travel destinations of vehicles according to a probability function; S3, planning vehicle travel pathsto obtain travel distance through adoption of a Dijkstra algorithm, and calculating travel driving time and states of charge; and S4, through combination of battery electric quantity levels, judgingcharge demands, determining electric vehicle charge periods and positions, and carrying out repeated sampling through utilization of a Monte Carlo method, thereby obtaining an electric vehicle chargeload time and space distribution prediction result. According to the method, the charge demands of any time, any place and any vehicle can be obtained, and through combination of a road network and power grid geographical coupling property, influences on aspects such as power grid load, network loss and a voltage after electric vehicles are connected are estimated from a time dimension and a spacedimension.

Description

technical field [0001] The invention belongs to the technical field of electric vehicles and relates to a method for predicting the temporal and spatial distribution of charging loads of regional electric vehicles. Background technique [0002] Due to its energy-saving, emission-reducing, and green environmental protection features, electric vehicles are considered to be one of the beneficial ways to solve today's energy shortage and environmental problems, and thus are strongly supported and promoted by governments and enterprises of various countries. At present, a certain number of electric vehicles have been used in urban areas in my country. With the gradual construction of charging facilities and the increase in the use of electric vehicles, their charging demand will also have a new round of growth. Effective forecasting and evaluation of electric vehicle charging load The impact of electric vehicles connected to the grid is the basis for the interaction between the gr...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y02T90/167Y04S30/12
Inventor 陈丽丹
Owner GUANGZHOU COLLEGE OF SOUTH CHINA UNIV OF TECH
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