CN117656913B

CN117656913B - Aggregation regulation and control system for supporting safe access and quick control of mass charging piles

Info

Publication number: CN117656913B
Application number: CN202410130303.9A
Authority: CN
Inventors: 林振福; 马溪原; 李鹏; 杨铎铜; 张子昊; 聂智杰; 葛俊; 俞靖一; 徐全; 王鹏宇; 曾博儒
Original assignee: Southern Power Grid Digital Grid Research Institute Co Ltd
Current assignee: Southern Power Grid Digital Grid Research Institute Co Ltd
Priority date: 2024-01-31
Filing date: 2024-01-31
Publication date: 2024-05-03
Anticipated expiration: 2044-01-31
Also published as: CN117656913A

Abstract

The application relates to an aggregation regulation system, an aggregation regulation method, an aggregation regulation device, computer equipment, a storage medium and a computer program product for supporting safe access and quick control of a mass charging pile, which can be used in the technical field of new energy. The method comprises the following steps: receiving operation data of the charging pile uploaded by an edge computing terminal system; identifying the operation data through a pre-trained regulation and control information identification model to obtain regulation and control information of the charging pile; generating a regulation and control instruction of the charging pile according to the regulation and control information; issuing a regulation and control instruction to an edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction. By adopting the method, the efficiency of controlling the charging pile can be improved.

Description

Aggregation regulation and control system for supporting safe access and quick control of mass charging piles

Technical Field

The application relates to the technical field of new energy, in particular to an aggregation regulation and control system, an aggregation regulation and control method, an aggregation regulation and control device, computer equipment, a storage medium and a computer program product for supporting safe access and quick control of a mass charging pile.

Background

With the development of new energy fields, electric automobile charging facilities are applied to various fields such as urban traffic and environmental protection. Through the analysis of the existing charging infrastructure, the situation that the access quantity of the charging piles and the charging requirement are rapidly increased can be known. Therefore, how to efficiently control the charging pile has become an important research direction.

The traditional technology is to control the charging pile by manual monitoring and manual adjustment; but this way, the control of the charging pile requires more manual processing time, resulting in lower efficiency of the control of the charging pile.

Disclosure of Invention

In view of the foregoing, it is desirable to provide an aggregation control system, an aggregation control method, an aggregation control device, a computer apparatus, a computer-readable storage medium, and a computer program product for supporting secure access and fast control of a mass charging pile, which can improve the efficiency of controlling the charging pile.

In a first aspect, the application provides an aggregation regulation system for supporting safe access and rapid control of a mass charging pile. The system comprises: charging pile aggregation regulation and control system cloud platform and edge computing terminal system;

The edge computing terminal system is used for acquiring operation data of the charging pile and uploading the operation data to the cloud platform of the charging pile aggregation regulation system;

the charging pile aggregation regulation and control system cloud platform is used for identifying the operation data through a pre-trained regulation and control information identification model to obtain the regulation and control information of the charging pile, generating a regulation and control instruction of the charging pile according to the regulation and control information, and transmitting the regulation and control instruction to the edge computing terminal system;

and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction.

In one embodiment, the polymerization regulation system further comprises: a charging pile on-site control unit;

the charging pile on-site control unit is used for collecting operation data of the charging pile and uploading the operation data to the edge computing terminal system;

The edge computing terminal system is used for sending the regulation and control instruction to the charging pile on-site control unit;

and the charging pile on-site control unit is used for controlling the charging pile according to the regulation and control instruction.

In one embodiment, the charging pile on-site control unit is further configured to upload the operation data to the charging pile aggregation regulation system cloud platform;

the edge computing terminal system is used for carrying out feature recognition on the operation data through a pre-trained operation data feature recognition model to obtain feature data of the operation data, and uploading the feature data to the charging pile aggregation regulation and control system cloud platform;

And the charging pile aggregation regulation and control system cloud platform is used for identifying the operation data and the characteristic data through the pre-trained regulation and control information identification model to obtain the regulation and control information.

In one embodiment, the cloud platform of the charging pile aggregation regulation and control system is further configured to obtain sample operation data of a sample charging pile, real feature data of the sample operation data, and real regulation and control information of the sample charging pile, input the sample operation data and the real feature data to a regulation and control information identification model to be trained to obtain predicted regulation and control information of the sample charging pile, train the regulation and control information identification model to be trained according to a difference between the predicted regulation and control information and the real regulation and control information to obtain a pre-trained regulation and control information identification model, input the sample operation data to a running data feature identification model to be trained to obtain predicted feature data of the sample operation data, train the running data feature identification model to be trained according to a difference between the predicted feature data and the real feature data to obtain the pre-trained running data feature identification model, and send the pre-trained running data feature identification model to the edge computing terminal system.

In one embodiment, the cloud platform of the charging pile aggregation regulation and control system is configured to identify, through the pre-trained regulation and control information identification model, the operation data and the feature data according to the power grid load status information, the capacity information of the charging pile and the charging demand information of the electric automobile, so as to obtain the regulation and control information.

In one embodiment, the charging pile aggregation regulation system cloud platform comprises a demand information sub-platform, an aggregation regulation sub-platform and an energy management sub-platform;

The demand information sub-platform is used for predicting the charging demand of a user, obtaining the charging demand information of the electric automobile and sending the charging demand information of the electric automobile to the aggregation control sub-platform;

The aggregation regulation sub-platform is used for identifying the operation data and the characteristic data according to the power grid load condition information, the capacity information of the charging pile and the charging demand information of the electric automobile through the pre-trained regulation information identification model to obtain the regulation information;

The energy management sub-platform is used for detecting the charging pile according to the operation data and the characteristic data to obtain a detection result of the charging pile; the detection result comprises attribute information of the charging pile, distribution configuration information of the charging pile and real-time running state information of the charging pile; the attribute information comprises rated power, rated voltage, operational years, historical charging power and maintenance records of the charging pile.

In a second aspect, the present application also provides a polymerization regulation method applied to the polymerization regulation system of any one of the first aspects, the method comprising:

receiving operation data of the charging pile uploaded by an edge computing terminal system;

Identifying the operation data through a pre-trained regulation and control information identification model to obtain the regulation and control information of the charging pile;

generating a regulation and control instruction of the charging pile according to the regulation and control information;

Issuing the regulation and control instruction to the edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction.

In a third aspect, the present application also provides an aggregation regulating device applied to the aggregation regulating system according to any one of the first aspects, the device comprising:

The data receiving module is used for receiving the operation data of the charging pile uploaded by the edge computing terminal system;

The data identification module is used for identifying the operation data through a pre-trained regulation and control information identification model to obtain the regulation and control information of the charging pile;

The instruction generation module is used for generating a regulation and control instruction of the charging pile according to the regulation and control information;

the instruction issuing module is used for issuing the regulation and control instruction to the edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction.

In a fourth aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:

In a fifth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

In a sixth aspect, the application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of:

The aggregation regulation and control system, the aggregation regulation and control method, the aggregation regulation and control device, the computer equipment, the storage medium and the computer program product for supporting the safe access and the rapid control of the mass charging piles receive the operation data of the charging piles uploaded by the edge computing terminal system; identifying the operation data through a pre-trained regulation and control information identification model to obtain regulation and control information of the charging pile; generating a regulation and control instruction of the charging pile according to the regulation and control information; issuing a regulation and control instruction to an edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction. The aggregation regulation system comprises a charging pile aggregation regulation system cloud platform and an edge computing terminal system; the edge computing terminal system is used for acquiring the operation data of the charging piles and uploading the operation data to the cloud platform of the charging pile aggregation regulation system; the charging pile aggregation regulation and control system cloud platform is used for identifying operation data through a pre-trained regulation and control information identification model to obtain regulation and control information of the charging pile, generating a regulation and control instruction of the charging pile according to the regulation and control information, and sending the regulation and control instruction to the edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction, and realizing automatic control of the charging pile according to the regulation and control instruction, thereby being beneficial to improving the efficiency and accuracy of controlling the charging pile.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for those skilled in the art.

FIG. 1 is an application environment diagram of an aggregation regulation system supporting secure access and rapid control of mass charging piles in one embodiment;

FIG. 2 is a schematic flow diagram of a method of aggregate conditioning in one embodiment;

FIG. 3 is a schematic diagram of an architecture of an aggregate regulation system supporting secure access and fast control of mass charging piles in one embodiment;

Fig. 4 is a schematic diagram of a logic architecture of a cloud platform of a charging pile aggregation control system in an embodiment;

FIG. 5 is a block diagram of an aggregate control device in one embodiment;

fig. 6 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are both information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data are required to meet the related regulations.

The aggregation regulation and control system for supporting the safe access and the rapid control of the mass charging piles can be applied to an application environment shown in figure 1. The application scenario may include: the charging pile aggregation regulation system cloud platform 110 and the edge computing terminal system 120 can be in communication connection with each other. Specifically, the edge computing terminal system 120 is configured to obtain operation data of the charging pile, and upload the operation data to the charging pile aggregation regulation system cloud platform 110; the charging pile aggregation regulation and control system cloud platform 110 is configured to identify operation data through a pre-trained regulation and control information identification model, obtain regulation and control information of a charging pile, generate a regulation and control instruction of the charging pile according to the regulation and control information, and send the regulation and control instruction to the edge computing terminal system 120; the edge computing terminal system 120 is configured to control the charging pile according to the regulation command. The charging pile aggregation regulation system cloud platform 110 may be, but is not limited to, a terminal, a server or a system including a terminal and a server, for example, the charging pile aggregation regulation system cloud platform 110 may be a variety of personal computers, notebook computers, smart phones and tablet computers, or may be implemented by a stand-alone server or a server cluster formed by a plurality of servers; the edge computing terminal system 120 may be, but is not limited to, a terminal, a server, or a system including a terminal and a server, for example, the edge computing terminal system 120 may be various personal computers, notebook computers, smart phones, and tablet computers, or may be implemented by a stand-alone server or a server cluster composed of a plurality of servers.

In an exemplary embodiment, referring to fig. 1, there is provided an aggregation regulation system supporting secure access and fast control of a mass charging pile, the system comprising: charging pile aggregation regulation and control system cloud platform and edge computing terminal system;

the edge computing terminal system is used for acquiring the operation data of the charging piles and uploading the operation data to the cloud platform of the charging pile aggregation regulation system;

The charging pile aggregation regulation and control system cloud platform is used for identifying operation data through a pre-trained regulation and control information identification model to obtain regulation and control information of the charging pile, generating a regulation and control instruction of the charging pile according to the regulation and control information, and sending the regulation and control instruction to the edge computing terminal system;

The edge computing terminal system can be a distributed computing system deployed at the charging pile end.

The operation data may be real-time operation state data, such as charging power, voltage, etc., obtained by the edge computing terminal system from the charging pile.

The cloud platform of the charging pile aggregation regulation system can be a central control system deployed at a cloud end and used for generating a regulation instruction and sending the regulation instruction to an edge system (an edge computing terminal system).

The regulation information identification model can be a model obtained through training of a machine learning algorithm and is used for identifying regulation information.

The regulation and control information can be regulation and control requirement information of the charging pile obtained after the operation data is analyzed through a regulation and control information identification model.

The regulation and control instruction can be an instruction command which is generated according to the regulation and control information and is used for controlling the operation of the charging pile.

The control may be actual operation control such as adjustment of charging power.

Optionally, the edge computing terminal system acquires operation data of the charging pile, such as real-time data of charging power, voltage and the like; uploading the acquired operation data of the charging piles to a cloud platform of a charging pile aggregation regulation system; the cloud platform of the charging pile aggregation regulation and control system carries out identification analysis on the operation data through a pre-trained regulation and control information identification model, and identifies the current regulation and control requirement information of the charging pile as the regulation and control information of the charging pile; generating a corresponding regulation and control instruction according to the obtained regulation and control information, wherein the instruction comprises a command for controlling the charging pile; issuing the generated regulation and control instruction to an edge computing terminal system; the edge computing terminal system performs actual control operation on the charging pile according to the received regulation and control instruction, such as adjusting charging power; the edge computing terminal system continuously acquires new operation data of the charging pile and uploads the new operation data to the cloud platform of the charging pile aggregation regulation system to realize closed-loop control; and the cloud platform of the charging pile aggregation regulation and control system continuously generates and issues new regulation and control instructions according to the new data, so that the real-time control of the charging pile is realized.

In the aggregation regulation system for supporting the safe access and the rapid control of the mass charging piles, the operation data of the charging piles uploaded by the edge computing terminal system are received; identifying the operation data through a pre-trained regulation and control information identification model to obtain regulation and control information of the charging pile; generating a regulation and control instruction of the charging pile according to the regulation and control information; issuing a regulation and control instruction to an edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction. The aggregation regulation system comprises a charging pile aggregation regulation system cloud platform and an edge computing terminal system; the edge computing terminal system is used for acquiring the operation data of the charging piles and uploading the operation data to the cloud platform of the charging pile aggregation regulation system; the charging pile aggregation regulation and control system cloud platform is used for identifying operation data through a pre-trained regulation and control information identification model to obtain regulation and control information of the charging pile, generating a regulation and control instruction of the charging pile according to the regulation and control information, and sending the regulation and control instruction to the edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction, and realizing automatic control of the charging pile according to the regulation and control instruction, thereby being beneficial to improving the efficiency and accuracy of controlling the charging pile.

In one exemplary embodiment, the aggregate conditioning system further comprises: a charging pile on-site control unit;

The local control unit of the charging pile can be local control equipment arranged on each charging pile and used for collecting operation data of the charging pile, and the local control unit of the charging pile can be in communication connection with the edge computing terminal system.

Optionally, the charging pile on-site control unit collects operation data of the charging pile (the operation data comprises real-time parameters of the charging pile, such as voltage, current, charging power and the like), and uploads the collected operation data to the edge computing terminal system; the edge computing terminal system acquires the operation data of the charging pile, and uploads the operation data to the cloud platform of the charging pile aggregation regulation system; the cloud platform of the charging pile aggregation regulation and control system recognizes the operation data through a pre-trained regulation and control information recognition model to obtain the regulation and control information of the charging pile, generates a regulation and control instruction of the charging pile according to the regulation and control information, and sends the regulation and control instruction to the edge computing terminal system; the edge computing terminal system issues a regulating instruction to the charging pile on-site control unit; the charging pile on-site control unit controls the charging pile according to the received regulation and control instruction (the control may include actual operations such as adjusting charging power, switching charging modes, etc.).

According to the technical scheme provided by the embodiment, the charging pile local control unit is added on the basis of the original aggregation regulation system, so that the local collection of the operation data and the local execution of the control instruction are realized, the complete framework of edge calculation is formed, the efficiency and the accuracy of the operation data collection and the regulation instruction execution are improved, and the efficiency and the accuracy of the control of the charging pile are improved.

In an exemplary embodiment, the charging pile in-situ control unit is further configured to upload the operation data to a charging pile aggregation regulation system cloud platform;

And the charging pile aggregation regulation and control system cloud platform is used for identifying the operation data and the characteristic data through a pre-trained regulation and control information identification model to obtain regulation and control information.

The operation data feature recognition model may be a model trained in advance by the edge computing terminal system, and is used for extracting features of operation data.

The feature data may be a feature extraction result obtained by processing the operation data through an operation data feature recognition model, such as a power waveform feature.

Optionally, the charging pile on-site control unit collects and uploads operation data of the charging pile to the edge computing terminal system; the edge computing terminal system performs feature extraction on the uploaded operation data through a pre-trained operation data feature recognition model to obtain feature data of the operation data; uploading the extracted characteristic data to a cloud platform of a charging pile aggregation regulation system; and the cloud platform of the charging pile aggregation regulation and control system carries out comprehensive identification analysis on the received operation data and the characteristic data through a pre-trained regulation and control information identification model, and identifies the regulation and control information.

According to the technical scheme, through the cooperative work of the edge and the cloud, the multistage feature extraction of the operation data is realized, so that richer information is obtained for regulation and control, and the accuracy of controlling the charging pile is improved.

In an exemplary embodiment, the cloud platform of the charging pile aggregation regulation and control system is further configured to obtain sample operation data of the sample charging pile, real feature data of the sample operation data, and real regulation and control information of the sample charging pile, input the sample operation data and the real feature data to a regulation and control information identification model to be trained to obtain prediction regulation and control information of the sample charging pile, train the regulation and control information identification model to be trained according to differences between the prediction regulation and control information and the real regulation and control information to obtain a pre-trained regulation and control information identification model, input the sample operation data to the operation data feature identification model to be trained to obtain prediction feature data of the sample operation data, train the operation data feature identification model to be trained according to differences between the prediction feature data and the real feature data to obtain the pre-trained operation data feature identification model, and send the pre-trained operation data feature identification model to the edge computing terminal system.

The sample charging piles can be selected ones as sample charging piles for model training.

The sample operation data may be real operation data collected for the sample charging pile.

The real feature data may be a feature tag obtained by manually labeling the sample operation data.

The real regulation information can be a real control instruction determined according to sample operation data and environmental conditions.

The predicted regulation information may be a control instruction predicted by a regulation information recognition model to be trained according to sample operation data.

The predicted feature data may be feature labels predicted by the feature recognition model of the operation data to be trained according to the sample operation data.

The regulatory information recognition model to be trained may be an initialized but untrained machine learning model for predicting control commands from input data.

The operational data feature recognition model to be trained may be an initialized but untrained machine learning model for predicting feature labels from input data.

The training may be a process of continuously optimizing parameters of the model according to differences between the prediction result and the real result, so that the prediction capability of the model is continuously improved.

Optionally, the cloud platform of the charging pile aggregation regulation and control system acquires sample operation data of a certain number of sample charging piles, and acquires real characteristic data and real regulation and control information corresponding to the sample operation data; inputting sample operation data and real characteristic data into a regulation and control information identification model to be trained to obtain predicted regulation and control information of a sample charging pile output by the regulation and control information identification model to be trained, and training the regulation and control information identification model to be trained according to the difference between the predicted regulation and control information and the real regulation and control information to obtain a pre-trained regulation and control information identification model; the cloud platform of the charging pile aggregation regulation and control system inputs sample operation data into an operation data feature recognition model to be trained to obtain prediction feature data of the sample operation data output by the operation data feature recognition model to be trained, trains the operation data feature recognition model to be trained according to the difference between the prediction feature data and the real feature data to obtain a pre-trained operation data feature recognition model, and transmits the pre-trained operation data feature recognition model and/or model parameters of the pre-trained operation data feature recognition model to an edge computing terminal system.

According to the technical scheme provided by the embodiment, the sample data is utilized to train the operation data feature recognition model and the regulation information recognition model so as to be used for feature extraction and regulation information acquisition in an actual system, so that the efficiency and the accuracy of controlling the charging pile are improved.

In an exemplary embodiment, the cloud platform of the charging pile aggregation regulation and control system is used for identifying operation data and characteristic data according to power grid load condition information, capacity information of charging piles and charging requirement information of an electric vehicle through a pre-trained regulation and control information identification model to obtain regulation and control information.

The power grid load condition information may be load conditions of the power grid at different time points, such as load peak periods, load valley periods and the like.

The capacity information of the charging piles may be a maximum charging capacity of each charging pile, such as a maximum charge amount that can be provided per unit time.

The charging demand information of the electric automobile may be a demand of the electric automobile connected to the charging pile network for charging energy at different time points.

Optionally, the charging pile aggregation regulation system cloud platform acquires power grid load condition information, capacity information of a charging pile and charging demand information of the electric automobile; and inputting the power grid load condition information, the capacity information of the charging pile, the charging demand information, the operation data and the characteristic data of the electric vehicle into a pre-trained regulation and control information identification model, and identifying the operation data and the characteristic data according to the power grid load condition information, the capacity information of the charging pile and the charging demand information of the electric vehicle through the pre-trained regulation and control information identification model to obtain the regulation and control information.

According to the technical scheme provided by the embodiment, the intelligent regulation and control is realized by utilizing the pre-trained regulation and control information identification model and identifying the regulation and control decision corresponding to the operation data according to the conditions of power grid load condition information, capacity information of the charging pile, charging demand information of the electric automobile and the like, so that the accuracy rate of controlling the charging pile is improved.

In one exemplary embodiment, the charging pile aggregation regulation system cloud platform comprises a demand information sub-platform, an aggregation regulation sub-platform and an energy management sub-platform;

the demand information sub-platform is used for predicting the charging demand of a user, obtaining charging demand information of the electric automobile and sending the charging demand information of the electric automobile to the aggregation control sub-platform;

the aggregation regulation sub-platform is used for identifying the operation data and the characteristic data according to the power grid load condition information, the capacity information of the charging pile and the charging demand information of the electric automobile through a pre-trained regulation information identification model to obtain regulation information;

The energy management sub-platform is used for detecting the charging pile according to the operation data and the characteristic data to obtain a detection result of the charging pile; the detection result comprises attribute information of the charging pile, distribution configuration information of the charging pile and real-time running state information of the charging pile; the attribute information includes rated power, rated voltage, operational years, historical charging power, and service records of the charging pile.

The requirement information sub-platform can be used for predicting the charging requirement of a user and obtaining charging requirement information of the electric vehicle.

Wherein, the aggregate regulatory sub-platform may be a sub-platform for identifying regulatory information.

The energy management sub-platform can be used for detecting according to the operation data of the charging pile to obtain a detection result of the charging pile.

The demand information sub-platform, the aggregation regulation sub-platform and the energy management sub-platform are three sub-platforms forming a charging pile aggregation regulation system cloud platform.

The attribute information of the charging pile can be technical parameters such as rated power, rated voltage, operational life and the like of the charging pile.

The distribution configuration information of the charging piles may be distribution layout information of the charging piles in an area, for example, refer to a specific position distribution condition of the charging piles in a certain area.

The real-time operation state information of the charging pile may be current operation state information of the charging pile, for example, refer to operation parameters of the charging pile at the current moment, such as charging current, voltage, and the like.

The historical charging power may be the total charging energy of the charging pile in the past period of time.

The maintenance record can be a history record of maintenance of the charging pile.

Optionally, the demand information sub-platform predicts the demand of users for charging at different time points according to information such as historical data, so as to obtain charging demand information of the electric automobile, and sends the charging demand information of the electric automobile to the aggregation regulation sub-platform; the aggregation regulation sub-platform is used for identifying operation data and characteristic data of the charging pile acquired in real time by combining power grid load condition information, capacity information of the charging pile and charging demand information of the electric automobile through a pre-trained regulation information identification model, so as to obtain regulation information; the energy management sub-platform detects the charging piles according to the operation data and the characteristic data of the charging piles to obtain detection results, wherein the detection results comprise attribute information, distribution configuration information and real-time operation state information of each charging pile, and the detection results are sent to the aggregation control sub-platform; the aggregation regulation sub-platform performs scheduling control of the charging piles according to the regulation information and the detection result of the charging piles, for example, decides which charging piles are charged at a certain time point; and generating a regulation and control instruction of the charging pile according to the regulation and control information and the detection result of the charging pile, and sending the regulation and control instruction to an edge computing terminal system to realize the dispatching control of the charging pile.

According to the technical scheme, the three sub-platforms work cooperatively, so that the processes of charging demand prediction, charging pile detection, regulation and control decision are realized, and the aggregation regulation and control of the charging pile are completed, so that the efficiency and the accuracy of controlling the charging pile are improved.

In an exemplary embodiment, as shown in fig. 2, there is provided an aggregation regulation method (an aggregation regulation method for supporting a massive charging pile based on an aggregation regulation system for supporting the massive charging pile to safely access and quickly control), where the method may be applied to the aggregation regulation system for supporting the massive charging pile to safely access and quickly control, and the embodiment is applied to a cloud platform of the aggregation regulation system for charging pile to illustrate the method, where the method includes the following steps:

step S201, operation data of the charging pile uploaded by the edge computing terminal system is received.

Step S202, identifying the operation data through a pre-trained regulation and control information identification model to obtain the regulation and control information of the charging pile.

And step S203, generating a regulation and control instruction of the charging pile according to the regulation and control information.

Step S204, issuing a regulation instruction to an edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction.

Optionally, the charging pile aggregation regulation system cloud platform receives the operation data of the charging pile uploaded by the edge computing terminal system; identifying the operation data through a pre-trained regulation and control information identification model to obtain regulation and control information of the charging pile; generating a regulation and control instruction of the charging pile according to the regulation and control information; issuing a regulation and control instruction to an edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction.

In the aggregation regulation method, the operation data of the charging pile uploaded by the edge computing terminal system is received; identifying the operation data through a pre-trained regulation and control information identification model to obtain regulation and control information of the charging pile; generating a regulation and control instruction of the charging pile according to the regulation and control information; issuing a regulation and control instruction to an edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction. The aggregation regulation system comprises a charging pile aggregation regulation system cloud platform and an edge computing terminal system; the edge computing terminal system is used for acquiring the operation data of the charging piles and uploading the operation data to the cloud platform of the charging pile aggregation regulation system; the charging pile aggregation regulation and control system cloud platform is used for identifying operation data through a pre-trained regulation and control information identification model to obtain regulation and control information of the charging pile, generating a regulation and control instruction of the charging pile according to the regulation and control information, and sending the regulation and control instruction to the edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction, and realizing automatic control of the charging pile according to the regulation and control instruction, thereby being beneficial to improving the efficiency and accuracy of controlling the charging pile.

The following illustrates an application example of the aggregation regulation system for supporting safe access and rapid control of a mass charging pile provided by the application, and referring to fig. 3, the aggregation regulation system comprises: charging pile aggregation regulation and control system cloud platform, edge computing terminal system and charging pile on-site control unit.

The aggregation regulation and control system ensures that the charging piles run in an orderly mode in the whole network through centralized management and cooperative scheduling, and resource conflict and confusion are avoided. In addition, the charging demand may change over time, and thus a system capable of dynamically adapting to different demands is required. The aggregation regulation and control system can flexibly adjust the state and power of the charging pile according to the real-time data and the user demand change so as to meet the demands under different scenes. Grid-built charging piles present challenges to the power network, which may lead to grid load imbalances if not effectively scheduled. The aggregation regulation system can monitor the load condition of the power network in real time and adjust the running state of the charging pile so as to realize load balancing and improve the stability of the power system. The aggregation regulation control system can intelligently schedule the nearest available charging piles by monitoring the charging demands and the position information of the users in real time. The method is beneficial to improving user service experience, reducing waiting time of users and enhancing use confidence of the users on the electric vehicle. The aggregation regulation system can collect and analyze a large amount of real-time data, and provides powerful support for decision making. Through data analysis, the system can make intelligent decisions, optimize the operation strategy of the charging pile, and promote the intelligence and the adaptivity of the system.

Aiming at the safety access problem of the charging pile management system, a safety access module is designed in the application example, wherein a two-factor identity authentication mechanism is introduced into the safety access module, and the charging pile is required to provide an effective digital certificate and a hardware token before accessing the system so as to ensure the legitimacy of the identity. And the application example implements a white list mechanism aiming at the communication of the charging pile, only the pre-registered charging pile can be accessed into the system, the unique identifier such as a hardware address is used for access control, meanwhile, an intrusion detection system and an intrusion prevention system are introduced, a security mechanism based on behavior analysis is deployed, and potential threats are timely dealt with by detecting abnormal behaviors. And a detailed log recording mechanism is realized, related events of charging pile access and identity verification are recorded to support audit and monitoring, and audit logs are used for carrying out system performance assessment and analysis of potential threats. The problem of safe access of the mass distributed charging piles can be solved through the safe access module.

The cloud edge cooperative system architecture is to sink part of computing capacity of aggregation regulation of the charging piles to the edge. Under the architecture, the edge end is responsible for completing preprocessing and pre-analysis of acquired data, partial calculation requirements are solved at the edge end, network overhead of data transmission is effectively reduced, calculation burden of a cloud is shared, and lower time delay and quicker response are brought. In general, the cloud edge cooperative system architecture fully exerts the advantages of edge computing resources by distributing computing tasks from a centralized cloud to an edge, reduces network overhead and delay, and improves the response speed of the system. The architecture is more flexible and efficient, meets the requirements of adjustable potential calculation on real-time performance and computation density, and provides powerful support for intelligent and agile management of the charging pile.

The system is based on a unified universal core control board, carries diversified software definition algorithms and applications, adopts an architecture based on the combination of an edge control terminal and an aggregation regulation system, adopts an edge computing terminal to realize safe access and on-site rapid control of the charging pile, and carries out planning and management through the aggregation regulation system of a cloud, so that flexible control of the charging pile of the electric automobile with wide points and multiple faces in a regional range is realized, safe and stable operation of a power system is supported, and the novel power system is assisted.

Architecture of the system referring to fig. 3, the system is designed in terms of an end, side and cloud architecture. The cloud platform of the charging pile aggregation regulation system represents a cloud end and is used for cloud end decision making, including market information acquisition, aggregation regulation, energy management, load aggregation, regulation decision making, system monitoring and other functions; the edge computing terminal system represents an edge and is used for edge decision, including functions of data aggregation, secure access, edge computing and the like; the charging pile on-site control unit represents an execution end and is used for executing feedback, including functions such as data acquisition and on-site control.

The cloud platform of the charging pile aggregation regulation and control system is deployed at the cloud end and is responsible for load aggregation regulation and control management, ordered charging control regulation and control decision and charging pile system monitoring, and the cloud platform mainly comprises three sub-platforms, namely a market information sub-platform, an aggregation regulation and control sub-platform and an energy management sub-platform.

The main functions of the market information sub-platform are as follows: (1) The market information sub-platform is responsible for formulating a pricing strategy of the charging service, and factors such as power cost, time period difference, user demand and the like are considered. By calculating resources (e.g., fees) in real time, the system can provide reasonable charging resources and adjust according to market demands. (2) Through the market information sub-platform, operators can push out charging offers and promotional campaigns, such as discounts for specific time periods, member-specific offers, and the like. The utility model is helpful for attracting users to select charging at different time periods, balancing the load of the power grid and improving the utilization rate of the charging pile. (3) By analyzing the market information, the market information sub-platform can predict the charging needs of the user. Based on these predictions, the system can recommend optimal charging periods and charging sites to the user, improving user experience, and optimizing resource allocation of the charging pile network. (4) The market information sub-platform monitors market demands and charging pile supply conditions in real time, and the power assisting achieves market supply and demand balance. The system can flexibly adjust charging pricing, preferential measures and the like according to market conditions, and ensures the stable operation of the charging pile.

The aggregation regulation sub-platform is a key component in the charging pile system and is mainly responsible for the flexible load aggregation regulation management of the agent user. Specific responsibilities comprise tasks such as station-line-to-user relation management, load characteristic analysis, adjustment performance evaluation, load baseline prediction, load modeling, adjustment benefit analysis, adjustment attribute management and the like. In short, the platform aims to integrate and manage various works related to flexible loads so as to ensure that the scheduling and operation of the system reach an optimal state. In the control process of the cloud ordered charging optimization scheduling, a local data acquisition function is realized by integrating charging piles deployed on the edge side with a control terminal. This includes acquiring real-time load information, power information, voltage information, etc. within the bay. Meanwhile, the real-time communication connection is established with the charging pile, so that the real-time running state, capacity, power and other related data of the charging pile are obtained. Based on the collected real-time operation data, the calculation is performed by using a cloud ordered charging optimization scheduling algorithm. This algorithm takes into account a number of factors including grid load conditions, charging pile capacity, charging requirements of the electric vehicle, etc. And (3) formulating and updating an ordered charge and discharge control strategy of the electric automobile through cloud computing. And finally, the scheduling instructions are issued to the charging pile fusion control terminal equipment for execution. The intelligent scheduling and optimization of the cloud end are realized, and the operation of the charging pile system is coordinated with the charging requirement of the electric automobile, so that the system efficiency is improved to the greatest extent, the power grid load is balanced, and the reliability of the charging service is ensured. In this way, the whole charging pile system can more intelligently and efficiently cope with dynamic power requirements and system running conditions.

The energy management sub-platform mainly develops the monitoring function of the related information data of the charging pile, and carries out real-time detection on the running state of the charging pile including the charging pile standing account, the charging pile map distribution configuration and the charging pile based on the collected charging pile information. And combining with a GIS (geographic information system) map, carrying out visual display on the charging pile of the monitoring area, wherein the visual display comprises grid-structured quick charging, grid-structured slow charging and conventional charging piles. The distribution condition of the direct current quick charging piles in the monitoring range is displayed in a position graphic mode, and key information such as grid-connected voltage level, rated power of the charging piles, historical charging quantity and the like can be displayed by clicking the charging piles. And establishing all charging pile accounts within the monitoring range, wherein the charging pile accounts comprise grid-structured quick charging, grid-structured slow charging and conventional charging piles, and the account accounts comprise rated power, rated voltage, operational years, historical charging power, maintenance records and the like of the charging piles.

The edge computing terminal system is a comprehensive system deployed at an edge position, is a distributed synchronous control system, and allows a plurality of nodes in the charging pile aggregation system to synchronously perform state synchronization so as to accelerate the control speed of the whole system. The core functions of the method comprise the tasks of data acquisition, data aggregation, adjustable potential analysis, control decomposition, control execution and the like. The system is of particular importance in terms of charging pile management, as it is not only responsible for handling the data of a large number of charging piles, but also needs to ensure that this huge charging pile network can be safely accessed and achieve fast control. Firstly, the system can rapidly and accurately acquire real-time data from a large number of charging piles through a powerful data acquisition function, wherein the real-time data comprise the running state, the power requirement, the connection condition and the like of the charging piles. This provides a sufficient information basis for subsequent scheduling and control. And secondly, the edge computing terminal system effectively integrates information of a large number of charging piles through data aggregation and adjustable potential analysis, performs potential analysis, identifies schedulable resources in the system and makes corresponding control decisions. This process requires efficient data processing and analysis capabilities to ensure a fast response to a large scale charging pile network. In terms of control, the system has the ability to control the decomposition and execution. Even if the system faces to a large number of charging piles, the system can disassemble the whole control task into small blocks, and the fine control of each charging pile is realized through an intelligent control algorithm. This ensures the efficiency and accuracy of the control process. Most importantly, the edge computing terminal system pays attention to safe access when handling mass charging piles. The method adopts an advanced security protocol and an identity authentication mechanism to ensure the security of the charging pile when the charging pile is accessed into a system. This includes measures such as authentication of the charging stake, encryption of the data transmission, etc., to prevent potential security risks. The edge computing terminal system can sample the input alternating voltage, current and frequency of each channel through the alternating current board card, and the sampling period is 0.15625 ms, namely 128 points are sampled in one power frequency period. The alternating voltage and the alternating current adopt a filtering discrete fast Fourier transform algorithm, and the frequency value adopts a phase-locked loop algorithm, so that the sampling processing of the data in the time range of a subtle level can be realized, and the primary frequency modulation and the inertia control of the charging pile system can be realized.

Referring to fig. 4, the logic architecture of the charging pile aggregation regulation and control system cloud platform is a central control decision mechanism for charging pile regulation and control, and includes a resource layer (which may include functions of data acquisition, security management, control delivery, model delivery, edge monitoring, etc.), a data layer (which is used for data cleaning and storage, providing training data), a decision layer, and an application layer.

In the aggregate regulation cloud platform, key components of the decision layer comprise a machine learning engine, a model parameter library and a decision analysis engine. The three components work cooperatively, so that the high-efficiency treatment of the aggregation regulation and control requirement in the complex environment is realized.

Machine learning engine: training is performed by using historical load data and business parameters to adapt to multi-objective guidance and multi-constraint conditions. Specific model algorithms (algorithm model libraries) are trained, including adjustable potential analysis models, load aggregation, load anti-aggregation, regulatory decisions, and the like. And forming a model parameter library, wherein the model parameter library comprises a cloud model and parameters and a side model and parameters.

Model parameter library: the cloud model and the parameters are used for executing analysis decisions at the cloud. The edge model and parameters are transmitted to an edge computing terminal (model transmission and control transmission) through an Internet of things management platform and are used for analyzing at the edge. Rich information is provided, and a foundation is provided for the work of a decision layer.

Decision analysis engine: based on cloud model and parameters, load data acquired in real time and business targets, results of aggregation, inverse aggregation, control decision (regulation decision) and the like are generated in real time. And supporting the service application upwards by the generated decision result so as to meet the regulation and control requirements under the multi-objective and multi-constraint conditions. Meanwhile, the result is issued to the edge computing terminal through the Internet of things management platform, so that effective management (aggregation management) of edge computing is realized.

Comprehensively, the decision layer flexibly meets diversified regulation and control requirements through training of a machine learning engine and real-time generation of a decision analysis engine. The dual structure of the model parameter library ensures sufficient support for the cloud end and the edge end, so that the whole aggregation regulation system can operate efficiently in different scenes.

The cloud platform of the charging pile aggregation regulation and control system is deployed at the cloud end and is responsible for load aggregation regulation and control management, ordered charging control regulation and control decision and charging pile system monitoring, and the cloud platform mainly comprises three sub-platforms, namely a market information sub-platform, an aggregation regulation and control sub-platform and an energy management sub-platform. The application layer plays an important role in service guidance and collaboration in the aggregate regulation cloud platform. The following is a detailed description of the application layer:

service guiding and cooperating mechanism: the application layer is a mechanism responsible for guiding and coordinating the whole aggregation regulation cloud platform. The platform is ensured to operate effectively according to the business targets by defining business rules, business constraints and business processes. The service guiding involves setting the service direction of the whole system, and ensuring that the operation of the platform accords with the service strategy and the target.

Business rules and constraints define: the application layer is responsible for defining and managing business rules and constraints in the aggregate regulatory system. This includes rule formulation and constraint setting for energy use, load scheduling, equipment management, etc. The definition of business rules and constraints is based on business requirements and rules to ensure that the operation of the system meets the rules and business objectives.

Business process definition: the application layer is responsible for designing and defining the business processes in the aggregate regulation system. The method comprises the flow of the whole energy life cycle, including links such as data acquisition, analysis, decision generation and execution. The design of the business process aims at optimizing the system operation and ensuring that the business target can be efficiently realized under different conditions.

Integrated interaction with peripheral business systems: and the application layer performs integrated interaction with peripheral service systems such as scheduling and the like, so that cooperative work of the aggregate control cloud platform and other related systems is ensured. Interaction with the dispatch system is critical because the dispatch system may involve a wider business in terms of power system management, etc.

Business target driving decision and cloud edge cooperative work: the application layer drives the decision of the whole system and cloud edge cooperative work by setting a business target. Business objectives may relate to several aspects of energy efficiency improvement, cost reduction, environmental friendliness, and the like.

And the decision layer generates corresponding load scheduling and energy management strategies through the machine learning engine and the decision analysis engine according to the business targets set by the application layer so as to realize optimization of the business targets. Comprehensively, the application layer bears key tasks such as business direction setting, rule making, flow design and the like in the aggregation control cloud platform, so that the whole system can be ensured to take a business target as a guide, and efficient load aggregation and energy scheduling are realized. Integration with the ambient business system makes the platform more synergistic and monolithic.

Charging pile aggregation regulation and control system safety access module: the security access module mainly comprises four security protection mechanisms, namely a double-factor identity authentication mechanism, a white list mechanism, a unique identifier protection mechanism, an intrusion detection system, an intrusion prevention system and a detailed log recording mechanism.

(1) Two-factor authentication mechanism:

The secure access module introduces a two-factor authentication mechanism requiring that the charging stake must provide a valid digital certificate and hardware token before accessing the system. By simultaneously verifying two different identity elements, the mechanism improves the verification degree of identity validity and strengthens the definite confirmation of the system on the charging pile body. The specific implementation steps are as follows:

1) Issuance of digital certificates:

in the system initialization phase, a digital certificate is generated for each legal charging stake. Digital certificates typically include a public key of the charging stake, associated metadata, and a digital signature, issued by a certification authority or system manager.

2) Distribution of hardware tokens:

A hardware token is distributed for each charging peg, which token may be part of a hardware security module or a physical device such as a USB (universal serial bus) key. The hardware token typically contains a unique identifier and is used to generate a temporary one-time password or for digital signature.

3) And (3) a charging pile body verification request:

when the charging pile attempts to access the system, an authentication request is first sent. This may be by sending an encrypted authentication request containing the identity information and digital signature of the charging stake through a communication channel with the system.

4) Digital certificate verification:

upon receiving the authentication request, the system uses a pre-stored digital certificate to verify the public key and signature of the charging stake. This ensures that the digital certificate of the charging stake is valid and not tampered with.

5) Hardware token verification:

at the same time, the system requires that the charging stake provide a one-time password or digital signature generated by the hardware token to prove compliance. This is achieved by verifying that the data generated by the hardware token matches the expected value.

6) And (5) comprehensively verifying the result:

And combining the digital certificate verification and the hardware token verification results, and comprehensively evaluating the identity compliance of the charging pile by the system. Only if both are verified is the charging stake allowed access to the system.

7) Periodic update and re-authentication:

the digital certificate and hardware token of the charging stake are updated periodically to enhance the security of the system. Re-authentication ensures that identity legitimacy remains after a period of time.

Through the implementation steps, the two-factor identity authentication mechanism effectively improves the authentication degree of the charging pile body. The combined use of the digital certificate and the hardware token increases the difficulty of an attacker in stealing the identity information, and provides stronger security guarantee.

(2) White list mechanism and unique identifier:

for the communication of the charging pile, a white list mechanism is implemented, and only the charging pile registered in advance can be accessed to the system. Access control is performed using a unique identifier, such as a hardware address, to ensure that only compliant, registered charging posts can communicate with the system, thereby effectively preventing unauthorized access.

(3) Intrusion detection system and intrusion prevention system:

An intrusion detection system and an intrusion prevention system are introduced, and potential security threats are timely discovered and dealt with by monitoring network flow and behaviors in the system in real time. The security mechanism based on behavior analysis enhances the sensitivity to abnormal behaviors and improves the security capability of the system to threats. The following are implementation schemes based on behavioral analysis to enhance the sensitivity of the system to abnormal behavior and to improve the protection against threats:

1) Network traffic analysis:

Deep packet inspection: deep packet inspection techniques are used to analyze the contents of network packets in order to discover potential malicious activity. This may include examining the protocol, source address, destination address, port, etc. information of the packet.

Flow anomaly detection: based on the model of normal traffic behavior, network traffic is monitored in real-time and any abnormal traffic that does not conform to the expected behavior is detected. This may cover anomalies in bandwidth usage, connection frequency, amount of data transfer, etc.

2) Behavioral analysis:

Baseline modeling: a baseline model of normal network and system behavior is established to identify any behavior that does not coincide with the baseline in time. This helps detect new threats and changing network environments.

Behavioral analysis: normal behavior patterns, such as login time, access patterns, etc., are monitored to detect potential account abuse or unauthorized activity.

3) Real-time response mechanism:

Automatic blocking: for detected malicious behavior, an automatic response mechanism is implemented that automatically blocks related traffic or system access to reduce potential damage.

And (3) an alarm system: an integrated alarm system that can notify security administrators or teams on the fly so that they can quickly take action to deal with potential threats.

4) Vulnerability management and patching:

real-time vulnerability scanning: and periodically scanning the system and network vulnerabilities and timely repairing the known vulnerabilities to reduce the chance of an attacker to exploit the vulnerabilities.

Updating a vulnerability database: the vulnerability database is updated periodically to ensure that the intrusion detection system can identify the latest threats and vulnerabilities.

5) Security information and event management:

centralized log management: a SIEM (Security information and event management) tool is integrated to centrally manage logs generated by the system and network to analyze large amounts of data to identify potential threats.

Log association analysis: and detecting modes related to different events by using a log correlation analysis technology so as to improve the accuracy of detecting the threat.

(4) Detailed logging mechanism:

The security access module implements a detailed log recording mechanism to record the related events of the access and the identity verification of the charging pile. This includes key information such as identification information of the charging stake, verification results, access time, etc. These logs are used to support auditing and monitoring, while also providing a powerful basis for system performance assessment and potential threat analysis.

Through the safety measures, the safety access module effectively solves the safety access problem of mass distributed charging piles. The system integrates multi-level identity authentication, access control and security monitoring mechanisms, ensures the security and stability of the system, and provides flexible and strong security guarantee for coping with potential threats.

The core idea of the architecture of the system is to sink part of the computing power of the load aggregation regulation to the edge. Preprocessing and pre-analysis of the acquired data are completed at the edge end, and meanwhile, partial calculation requirements are met. This brings multiple advantages: network overhead is reduced: the edge end completes partial data processing work, reduces the data transmission amount from the end to the cloud end, and effectively reduces the pressure on the network bandwidth; and the cloud load is lightened: the edge end processes part of calculation tasks, so that the load of the cloud is reduced, and the cloud can be more focused on high-level decision and overall analysis; and (3) improving response speed: the edge end can respond to real-time calculation requirements more rapidly, network delay existing in the traditional model is reduced, and the response speed of the system is improved greatly; by making the cloud end and the edge end cooperate with each other, the architecture aims to realize a more efficient and low-delay load aggregation regulation system. The method not only can fully exert the advantages of the cloud, but also can more flexibly process part of calculation tasks at the edge end so as to adapt to the requirements of different scenes.

The cloud-edge collaborative system architecture is constructed by the application example, so that real-time computing requirements can be responded more quickly at the edge, network delay existing in a traditional model is reduced, the response speed of the system is improved greatly, and quick control of the charging pile is realized. Meanwhile, the advantages of the cloud can be fully exerted, and training and decision-making of the charging pile related ordered charging strategy are realized by utilizing the resource integration capability and the super-large calculation power of the cloud; the safe access module of the application example can effectively solve the problems of the traditional safe access system of the charging pile system, can effectively support the safe access of mass charging piles, and solves the problems of the safe access system of side equipment. The technical scheme provided by the application example also realizes improvement of the efficiency and accuracy of controlling the charging pile.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides an aggregation regulating device for realizing the above-mentioned aggregation regulating method (an aggregation regulating system for supporting safe access and rapid control of mass charging piles). The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of one or more aggregation control devices provided below may be referred to the limitation of the aggregation control method (aggregation control system for supporting secure access and rapid control of a mass charging pile) hereinabove, and will not be described herein.

In one exemplary embodiment, as shown in FIG. 5, an aggregation regulating device 500 is provided, which may include:

the data receiving module 501 is configured to receive operation data of the charging pile uploaded by the edge computing terminal system;

The data identification module 502 is configured to identify, through a pre-trained regulation information identification model, operation data, and obtain regulation information of the charging pile;

The instruction generating module 503 is configured to generate a regulation instruction of the charging pile according to the regulation information;

The instruction issuing module 504 is configured to issue a regulation instruction to the edge computing terminal system; and the edge computing terminal system is used for controlling the charging pile according to the regulation and control instruction.

The above-mentioned individual modules in the aggregation regulating device may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In an exemplary embodiment, a computer device, which may be a terminal, is provided, and an internal structure diagram thereof may be as shown in fig. 6. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement an aggregate conditioning method. The display unit of the computer device is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.

It will be appreciated by those skilled in the art that the structure shown in FIG. 6 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

In an exemplary embodiment, a computer device is also provided, comprising a memory and a processor, the memory having stored therein a computer program, the processor implementing the steps of the method embodiments described above when the computer program is executed.

In one exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method embodiments described above.

In an exemplary embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magneto-resistive random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (PHASE CHANGE Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as Static Random access memory (Static Random access memory AccessMemory, SRAM) or dynamic Random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.

Claims

1. An aggregation regulation and control system for supporting safe access and rapid control of mass charging piles, which is characterized by comprising: the charging pile aggregation regulation and control system comprises a cloud platform, an edge computing terminal system and a charging pile on-site control unit;

The charging pile aggregation regulation and control system cloud platform is used for acquiring sample operation data of a sample charging pile, real characteristic data of the sample operation data and real regulation and control information of the sample charging pile, inputting the sample operation data and the real characteristic data into a regulation and control information identification model to be trained to obtain prediction regulation and control information of the sample charging pile, training the regulation and control information identification model to be trained according to the difference between the prediction regulation and control information and the real regulation and control information to obtain a pre-trained regulation and control information identification model, inputting the sample operation data into the operation data characteristic identification model to be trained to obtain prediction characteristic data of the sample operation data, training the operation data characteristic identification model to be trained according to the difference between the prediction characteristic data and the real characteristic data to obtain a pre-trained operation data characteristic identification model, and issuing the pre-trained operation data characteristic identification model to the edge computing terminal system;

The charging pile on-site control unit is further used for uploading the operation data to the charging pile aggregation regulation system cloud platform;

The edge computing terminal system is used for acquiring the operation data and uploading the operation data to the charging pile aggregation regulation and control system cloud platform;

the edge computing terminal system is used for carrying out feature recognition on the operation data through the pre-trained operation data feature recognition model to obtain feature data of the operation data, and uploading the feature data to the charging pile aggregation regulation and control system cloud platform;

The charging pile aggregation regulation and control system cloud platform is used for identifying the operation data and the characteristic data according to the power grid load condition information, the capacity information of the charging piles and the charging demand information of the electric automobile through the pre-trained regulation and control information identification model to obtain regulation and control information of the charging piles, generating regulation and control instructions of the charging piles according to the regulation and control information, and sending the regulation and control instructions to the edge computing terminal system;

the charging pile on-site control unit is used for controlling the charging pile according to the regulation and control instruction;

the charging pile aggregation regulation and control system cloud platform comprises a demand information sub-platform, an aggregation regulation and control sub-platform and an energy management sub-platform;

2. The aggregate conditioning system of claim 1, wherein the edge computing terminal system is a distributed computing system deployed at the charging stub.

3. The aggregate conditioning system of claim 1, wherein the operational data is real-time operational status data.

4. The aggregate conditioning system of claim 3, wherein the real-time operating state data comprises charging power and voltage.

5. The aggregate conditioning system of claim 1, wherein the conditioning information is charging pile conditioning demand information.

6. The aggregate conditioning system of claim 1, wherein the characteristic data is a power waveform characteristic.

7. A method of polymerization regulation, characterized in that it is applied to the polymerization regulation system of any one of claims 1 to 6, the method comprising:

receiving operation data of the charging pile and characteristic data of the operation data, which are uploaded by an edge computing terminal system;

identifying the operation data and the characteristic data according to power grid load condition information, capacity information of the charging pile and charging demand information of the electric automobile through a pre-trained regulation and control information identification model to obtain regulation and control information of the charging pile;

Issuing the regulation and control instruction to the edge computing terminal system; the edge computing terminal system is used for sending the regulation and control instruction to the charging pile on-site control unit; and the charging pile on-site control unit is used for controlling the charging pile according to the regulation and control instruction.

8. An aggregation regulating device for use in the aggregation regulating system according to any one of claims 1 to 6, the device comprising:

The data receiving module is used for receiving the operation data of the charging pile and the characteristic data of the operation data, which are uploaded by the edge computing terminal system;

The data identification module is used for identifying the operation data and the characteristic data according to the power grid load condition information, the capacity information of the charging pile and the charging demand information of the electric automobile through a pre-trained regulation and control information identification model to obtain the regulation and control information of the charging pile;

The instruction issuing module is used for issuing the regulation and control instruction to the edge computing terminal system; the edge computing terminal system is used for sending the regulation and control instruction to the charging pile on-site control unit; and the charging pile on-site control unit is used for controlling the charging pile according to the regulation and control instruction.

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of claim 7 when executing the computer program.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of claim 7.