CN-121980671-A - Electric automobile space-time load characteristic modeling method considering differentiated travel mode and electronic equipment

Abstract

The invention relates to an electric vehicle space-time load characteristic modeling method considering a differential travel mode and electronic equipment, wherein the method comprises the steps of establishing a traffic network-power distribution network coupling model; the method comprises the steps of constructing an OD matrix considering a differentiated travel mode, searching to obtain the shortest path of the passing time of each electric automobile, establishing a dynamically updated running parameter model and an electric quantity parameter model, wherein seasonal factors are considered in the construction of the electric quantity parameter model, and when the charging requirements of each electric automobile are triggered, carrying out corresponding slow charging or quick charging, and superposing charging loads to achieve the description of the space-time load characteristics of the electric automobile. Compared with the prior art, the method and the device for modeling the space-time load characteristics of the electric automobile based on the traffic network-power distribution network coupling model have the advantages that the influence of seasonal factors is considered when the power consumption of the electric automobile is modeled, the space-time load characteristics of the electric automobile can be described more accurately, the actual situation is fitted, and a more reliable basis is provided for subsequent load analysis.

Inventors

• LIN ZHIHUANG
• ZHENG JIANYI
• YANG MOYUAN
• LIN YUFENG
• YANG SIXIANG
• YANG YIZHOU
• WU TONG
• LIU WENLIANG
• ZHANG SHENXI
• ZHANG RUNXIAN
• CHEN MING
• CHENG HAOZHONG
• CHEN RONGFENG
• MOU HONGJIAN
• MEI CHAO

Assignees

• 国网福建省电力有限公司厦门供电公司
• 上海交通大学

Dates

Publication Date

20260505

Application Date

20251218

Claims (10)

1. 1. The electric automobile space-time load characteristic modeling method considering the differentiated travel mode is characterized by comprising the following steps of: establishing a traffic network-power distribution network coupling model introduced with multiple types of electric vehicles; Randomly generating running parameters and electric quantity parameters of each electric automobile, and constructing an OD matrix considering the differentiated travel mode; Searching to obtain the shortest path of the passing time of each electric automobile based on the traffic network-power distribution network coupling model and the constructed OD matrix, and establishing a dynamically updated driving parameter model and an electric quantity parameter model, wherein the construction of the electric quantity parameter model considers the load influence of a vehicle-mounted air conditioner; And judging the charging requirements of each electric automobile based on the dynamic updating results of the driving parameters and the electric quantity parameters, and when the charging requirements are triggered, carrying out corresponding slow charging or fast charging, and superposing each charging load in the traffic nodes of the traffic network-power distribution network coupling model to realize the description of the space-time load characteristics of the electric automobiles.
2. 2. The method for modeling space-time load characteristics of an electric vehicle considering differentiated travel modes according to claim 1, wherein the traffic network-power distribution network coupling model is expressed as: wherein: The system is a connecting edge set formed by a power distribution network and a traffic network; The network layer is a respective network layer of a power distribution network and a traffic network; The coupling number is 1, if the coupling number is 1, the coupling is not related to the coupling; 、 For the layer index to be used, 、 Indexing nodes.
3. 3. The method for modeling the space-time load characteristics of the electric vehicle taking the differentiated travel mode into consideration according to claim 1, wherein the travel parameters comprise an origin-destination, travel time and return time; the charge parameters include battery capacity, initial state of charge, and consumed charge.
4. 4. The method for modeling space-time load characteristics of electric vehicles taking into account differentiated travel patterns according to claim 1, wherein the multi-type electric vehicles include electric private vehicles, electric taxis and electric buses.
5. 5. The modeling method for space-time load characteristics of electric vehicles considering differentiated travel modes according to claim 4, wherein when determining the charging requirements of each electric vehicle, for electric private vehicles, the determination criterion is the current remaining power The triggering charging requirement of the next trip can not be met I.e. Wherein: Indicating the current position of an electric automobile Distance destination Is a distance of (2); Representing the power consumption of unit mileage; Representing total mileage power consumption; the power of the vehicle-mounted air conditioner of the electric automobile; representing the average traffic speed of the road segment.
6. 6. The method for modeling space-time load characteristics of an electric vehicle in consideration of differentiated travel patterns according to claim 5, wherein the electric vehicle-mounted air conditioner power is determined based on vehicle factors including vehicle type and manufacturer.
7. 7. The modeling method for space-time load characteristics of electric vehicles considering differentiated travel modes according to claim 4, wherein the shortest path of the passing time of each electric vehicle is searched, an OD matrix is used for modeling the whole-day travel process from start to stop of the electric vehicles, and different types of electric vehicles are modeled as follows: For electric private car Wherein, the PEV is an electric private car; A 24 hour OD matrix for an electric private car; Value range of electric private car number, m is traffic node number, element Representing the number of electric private cars traveling from node i to node j of the daily commute between times t and t+1; Probability of traveling from node i to node j of daily commute between times t and t+1 for an electric private car; For electric taxis Wherein ET is an electric taxi; a 24-hour OD matrix for an electric taxi; value range of electric taxi number, m is traffic node number, element Representing the number of electric taxis driven to node j by each node i that may be carrying passengers between times t and t+1; probability that each node i possibly carrying passengers runs to a node j for the electric taxi between time t and t+1; For electric buses Wherein EB is an electric bus; a 24-hour OD matrix for an electric bus; the value range of the number of the electric buses, m is the number of traffic nodes, and the element Representing the number of electric buses running from a node i to a node j in a bus planned running route between time t and t+1; and planning the probability of the node i running to the node j in the running route for the electric bus between the time t and the time t+1.
8. 8. The modeling method for the space-time load characteristics of the electric vehicles considering the differentiated travel mode according to claim 1, wherein the shortest path of the passing time of each electric vehicle is obtained by searching by adopting a dynamic Dijkstra algorithm.
9. 9. A computer-readable storage medium comprising one or more programs for execution by one or more processors of an electronic device, the one or more programs including instructions for performing the method of modeling temporal and spatial load characteristics of an electric vehicle that accounts for differentiated travel modes according to any one of claims 1-8.
10. 10. An electronic device comprising one or more processors, memory, and one or more programs stored in the memory, the one or more programs comprising instructions for performing the method of modeling temporal-spatial load characteristics of an electric vehicle taking into account differentiated travel patterns according to any one of claims 1-8.

Description

Electric automobile space-time load characteristic modeling method considering differentiated travel mode and electronic equipment Technical Field The invention belongs to the technical field of power distribution network load characteristic modeling, relates to an electric vehicle charging load characteristic modeling method, and particularly relates to an electric vehicle space-time load characteristic modeling method considering a differentiated travel mode and electronic equipment. Background Along with the increasingly urgent global energy structure transformation and environmental protection requirements, the electric automobile becomes an important development direction of the traffic field by virtue of the characteristics of cleanness and high efficiency, and has great advantages in the aspects of energy conservation and emission reduction as a new generation of traffic tool. In order to relieve the energy crisis and improve the ecological environment, the development of the electric automobile industry is actively promoted all over the world. On the one hand, the electric automobile has mobility and flexible charge and discharge capability, and can be converted into high-quality resources for power grid operation adjustment through guidance by reasonable means. On the other hand, the strong randomness of the electric vehicle load and the high power charging requirement under large-scale access also provide serious challenges for power distribution network planning and operation. The time-space distribution characteristics of the charging load of the electric automobile are comprehensively influenced by multiple factors such as different travel modes, charging access modes, traffic network dynamic characteristics and the like, and how to model the time-space load characteristics is a key problem for subsequently evaluating the influence of the electric automobile on a power distribution network and realizing the cooperative optimization of the vehicle network. However, the existing research is often only carried out for modeling a single electric vehicle travel mode and a charging access mode when the space-time load characteristic of the electric vehicle is modeled, and the differentiated travel modes of different electric vehicles such as private vehicles, taxis and buses are not comprehensively considered, so that the method is difficult to accurately analyze the influence of large-scale access of the electric vehicles on power flow and node voltage of a power distribution network. How to model the space-time load characteristics of the electric automobile more accurately and finely under the condition of increasing scale access of the electric automobile is a technical problem to be solved in the field. Disclosure of Invention The invention aims to overcome the defects of the prior art and provide an electric vehicle space-time load characteristic modeling method and electronic equipment which can more accurately describe the space-time load characteristic of the electric vehicle and consider a differentiated travel mode. The aim of the invention can be achieved by the following technical scheme: the electric automobile space-time load characteristic modeling method considering the differentiated travel mode is characterized by comprising the following steps of: establishing a traffic network-power distribution network coupling model introduced with multiple types of electric vehicles; Randomly generating running parameters and electric quantity parameters of each electric automobile, and constructing an OD matrix considering the differentiated travel mode; Searching to obtain the shortest path of the passing time of each electric automobile based on the traffic network-power distribution network coupling model and the constructed OD matrix, and establishing a dynamically updated driving parameter model and an electric quantity parameter model, wherein the construction of the electric quantity parameter model considers the load influence of a vehicle-mounted air conditioner; And judging the charging requirements of each electric automobile based on the dynamic updating results of the driving parameters and the electric quantity parameters, and when the charging requirements are triggered, carrying out corresponding slow charging or fast charging, and superposing each charging load in the traffic nodes of the traffic network-power distribution network coupling model to realize the description of the space-time load characteristics of the electric automobiles. Further, the traffic network-distribution network coupling model is expressed as: wherein: The system is a connecting edge set formed by a power distribution network and a traffic network; The network layer is a respective network layer of a power distribution network and a traffic network; The coupling number is 1, if the coupling number is 1, the coupling is not related to the coupling; 、 For the layer index to be used, 、Indexing nodes.