Heterogeneous networking service flow scheduling method, system, device and medium

Abstract

The application discloses a heterogeneous networking service flow scheduling method, system, device and medium, and belongs to the technical field of power grid operation scheduling. The method comprises the following steps: receiving a service flow of a virtual power plant participating in power grid demand response; constructing a service flow model based on the delay characteristics of multiple interaction functions, and then obtaining a service flow queue; calculating the preference value of each service flow queue selecting a channel, and constructing a preference list according to the order of the channel preference value of each service flow queue; the service flow queue of an unmatched channel sends a matching request to the channel corresponding to the ranking in the preference list; each channel detects whether there is a channel request conflict, if there is a conflict, the service flow with the highest priority is allowed to access and other services are rejected; the rejected service flow deletes the channel rejecting itself from the preference list and returns to send a channel matching request again; if there is no conflict, each service flow performs data transmission according to the matched channel; and the heterogeneous networking service flow is scheduled, and the application guarantees the differentiated delay requirements of the service flow.

Description

Technical Field

[0001] This invention belongs to the field of power grid operation and dispatching technology, specifically relating to a heterogeneous network service flow dispatching method, system, equipment, and medium. Background Technology

[0002] A Virtual Power Plant (VPP) is a power supply coordination and management system that uses advanced information and communication technologies and software systems to aggregate and coordinate distributed resources such as generator sets, energy storage systems, controllable loads, and electric vehicles, allowing it to participate in the electricity market and grid operation as a special type of power plant. The participation of VPPs in grid demand response (DR) is a crucial means of improving the power system's balance and regulation capabilities. The real-time nature of DR information exchange is critical for stable grid operation. DR includes interactive functions with differentiated latency characteristics, such as peak shaving, frequency regulation, normal DR, and emergency DR. It involves various service flows with different latency requirements, data flow characteristics, and message sizes. Therefore, it is necessary to optimize the service flow scheduling strategy of the DR aggregation gateway in the VPP DR system to avoid DR communication network congestion and ensure the real-time transmission of various types of service data traffic.

[0003] Existing technologies provide a demand response service scheduling strategy based on fuzzy logic-based improved weighted fair queues. This strategy constructs a fuzzy logic system combining supply and Mamdani's method, dynamically determining the weight of each DR service data queue based on DR service queue length and burstiness information.

[0004] However, the implementation of heterogeneous network service flow scheduling that takes into account the latency characteristics of multiple interactive functions still faces the following technical challenges: On the one hand, to achieve optimal performance in terms of service flow transmission latency, virtual power plant service flow scheduling optimization needs to consider not only the current data backlog of the service flow but also the future arrival status of the service flow data. On the other hand, due to the limited number of communication channels, each service flow tends to choose the channel with the best communication performance, resulting in a conflict in the compatibility between each service flow and the communication channel. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention provides a heterogeneous network service flow scheduling method, system, device, and medium. This invention achieves optimal service flow transmission latency performance when the future arrival status of data is unknown, ensuring differentiated latency requirements for service flows.

[0006] To achieve the above objectives, the present invention employs the following technical solution:

[0007] A heterogeneous network service flow scheduling method includes:

[0008] Receive the business flow of virtual power plant participating in grid demand response, construct a business flow model based on the latency characteristics of multiple interactive functions, and then obtain the business flow queue;

[0009] Calculate the channel preference value for each service flow queue, and construct a preference list for each service flow queue according to the channel preference value order;

[0010] The traffic flow queue of the unmatched channel sends a matching request to the channel ranked in the preference list;

[0011] Each channel checks for channel request conflicts. If a conflict is found, the highest priority service flow is allowed to access while other services are rejected. The rejected service flow will remove the channel that rejected it from its preference list and resend the channel matching request. If no conflict is found, each service flow transmits data according to the matched channel.

[0012] Heterogeneous network service flow scheduling is performed based on the data transmission results of each service flow according to the matched channel.

[0013] As a further improvement of the present invention, receiving the business flow data of virtual power plants participating in grid demand response refers to:

[0014] The power grid demand response aggregation gateway connects to the power grid demand response terminal via HPLC and 5G, and transmits business flow data to the power grid demand response terminal in real time by executing the proposed business flow scheduling method. The power grid demand response terminal is connected to photovoltaic panels, charging piles, and energy storage equipment, and regulates distributed resources within its control range according to the received business flow.

[0015] As a further improvement of the present invention, the service flow selects an appropriate channel for data transmission in each time slot according to the real-time channel status; each service flow queue selects only one channel to transmit data.

[0016] The process of constructing a business flow model based on the latency characteristics of multiple interactive functions, and then obtaining a business flow queue, specifically includes:

[0017] The business flow queue set is The number of 5G channels is The number of HPLC channels is , The set of service flow channels is represented as follows: ;

[0018] A quasi-static time-slot model is adopted. There are several equal-length time slots, with a time slot length of [missing information]. The set is represented as Service flow queue scheduling channel selection variables ,in Indicates the first Each time slot service flow Select Channel Data transmission must be performed, otherwise ;

[0019] Business Flow queue backlog Represented as

[0020]

[0021] In the formula, For the first Time-slot service flow The amount of data received; For business flow In the Data volume sent per time slot; service flow Select Channel The throughput for data transmission is:

[0022]

[0023] Then business flow In the Data volume sent per time slot Represented as:

[0024]

[0025] in, and These are the bandwidths of the 5G channel and the HPLC channel, respectively. and These represent the business flow respectively. The power of selecting 5G channel and HPLC channel for data transmission; and These represent the business flow respectively. Channel gain of the selected 5G channel and HPLC channel; This represents noise power.

[0026] As a further improvement of the present invention, the service flow includes periodic data flow and random data flow;

[0027] Periodic business flow model for:

[0028]

[0029] In the formula: The polling cycle is... For business flow queue Queuing delay, For business flow queue Maximum transmission delay limit requirements;

[0030] Random traffic flows are approximated using a Poisson process; within a time interval Within, the average arrival rate of business flows is Then for any Then, the randomness of the business flow is represented as:

[0031]

[0032] In the formula: Represents probability. Represents a random process. This represents the average arrival rate of the business flow.

[0033] As a further improvement of the present invention, the latency model of the service flow is as follows:

[0034]

[0035] In the formula: For the first Service flow queue within each time slot Queuing delay, ,express Service flow queue within time slot Average time to arrive data volume;

[0036] Queuing delay needs to meet the following constraints:

[0037]

[0038] in, For the first Service flow queue within each time slot Queuing delay; For business flow queue Maximum transmission delay limit requirements.

[0039] As a further improvement of the present invention, the service flow scheduling priority satisfies the following function:

[0040]

[0041] In the formula, As weight, , For business flow queue Maximum transmission delay limit requirements; For business flow queue The degree of suddenness; For business flow queue The queue is backlogged.

[0042] As a further improvement of the present invention, the calculation of the channel preference value for each service flow queue includes:

[0043] In the current time slot where the virtual power plant participates in grid demand response, calculate the business flow queue. Select Channel Preference value Define it as the front Service flow queue within each time slot Select Channel The average queue latency for data transmission is calculated as follows:

[0044]

[0045] In the formula, Select variables for scheduling channels in the service flow queue. t For a moment, For business flow queue Select Channel The queue delay for data transmission.

[0046] A heterogeneous network service flow scheduling system includes:

[0047] The business flow receiving module is used to receive business flows from virtual power plants participating in grid demand response, construct a business flow model based on the latency characteristics of multiple interactive functions, and then obtain the business flow queue.

[0048] The preference value calculation module is used to calculate the preference value of each service flow queue for selecting a channel, and to construct a preference list for each service flow queue according to the channel preference value order.

[0049] The matching request module is used to send matching requests from the service flow queue of unmatched channels to the channel with the corresponding ranking in the preference list.

[0050] The data transmission module is used to detect whether there is a channel request conflict for each channel. If there is a conflict, the highest priority service flow is allowed to access and other services are rejected. The rejected service flow will remove the channel that rejected it from its preference list and return to resend the channel matching request. If there is no conflict, each service flow will transmit data according to the matched channel.

[0051] The service flow scheduling module is used to schedule heterogeneous network service flows based on the data transmission results of each service flow according to the matched channel.

[0052] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the heterogeneous network service flow scheduling method.

[0053] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the heterogeneous network service flow scheduling method.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] The scheduling method of this invention comprehensively considers the differentiated characteristics of multi-interactive function service flows, such as latency, data traffic burstiness, and queue backlog, to construct service flow priorities. This achieves optimal service flow transmission latency performance when the future arrival status of data is unknown. Furthermore, a channel selection conflict mitigation mechanism for service flows is established. By assigning higher priorities and allocating channels with better performance to service flows with strict latency requirements, stronger data traffic burstiness, and larger queue backlogs, the differentiated latency requirements of service flows are guaranteed. Attached Figure Description

[0056] Figure 1 This is a flowchart of a heterogeneous network service flow scheduling method according to the present invention;

[0057] Figure 2 This invention provides a heterogeneous network service flow scheduling system.

[0058] Figure 3 This is a flowchart of a heterogeneous network service flow scheduling method according to an embodiment of the present invention;

[0059] Figure 4 This is a comparison chart of data transmission latency for service flows provided by the present invention;

[0060] Figure 5 This is a schematic diagram of the heterogeneous network service flow scheduling system provided by the present invention;

[0061] Figure 6 This is a schematic diagram of an electronic device provided by the present invention. Detailed Implementation

[0062] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0063] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0064] According to the "Specification for Electricity Demand Response Information Exchange (DL / T 1867—2018)," the Virtual Power Plant (VR) DR service includes six types of information exchange services: emergency event services, general event services, selection services, registration services, reporting services, and polling services. Based on the characteristics of the service flow, these six types can be further divided into four levels of VR DR services: Emergency event services are highly sensitive to latency, requiring a latency of less than 50ms, and have extremely high burst characteristics with a large net load; therefore, they are classified as Level I services. General event demand response services include three categories: general events, selection, and registration services. They have high real-time requirements, requiring a latency of 50-400ms, and have a large net load fluctuation; therefore, these services are classified as Level II services. Reporting services belong to the data monitoring and reporting category, used to report VR DR response status, VR DR resource change information, etc. They have a latency requirement of 500-1100ms, are less sensitive to latency, but have a certain degree of burstiness; therefore, these demand response services are defined as Level III services. Polling services, as auxiliary support services, have low real-time requirements, latency can be above 1100ms, and the business data flow has periodic characteristics, resulting in a small net load. Therefore, they are defined as Level IV services.

[0065] Due to the diverse participants in Virtual Power Plant (VPG) Data Redirection (DR), the communication network between the DR aggregation gateway and the VPG DR terminal typically employs a heterogeneous network architecture with multiple communication methods, such as 5G, HPLC, and dedicated power communication networks. These different communication methods exhibit varying transmission rates and latency characteristics. Given the high burstiness, high concurrency, and varying latency of DR data streams, it is necessary to consider the differentiated transmission performance of various media within the heterogeneous network during the VPG business flow scheduling process. This requires precise adaptation of network communication resources to the data transmission needs of different types of business flows to ensure the timely delivery of multi-business flow data in the VPG DR system.

[0066] Existing technologies allocate transmission rates based on the weights of DR service data queues, neglecting the differentiated transmission performance of multi-media channels between the DR aggregation gateway and the power DR terminal. Secondly, this method does not consider the conflicts in channel selection for different service flows, failing to fully utilize multi-media communication resources. How to optimize service flow scheduling to achieve optimal service flow transmission time extension performance when the future arrival status of data is unknown is an urgent problem to be solved. How to achieve a reasonable adaptation between multiple heterogeneous communication channels and the data transmission requirements of multiple service flows is a crucial prerequisite for ensuring the smooth operation of multi-interaction functions between the virtual power plant and the power grid.

[0067] like Figure 1 As shown, this invention provides a heterogeneous network service flow scheduling method, including:

[0068] Receive the business flow of virtual power plant participating in grid demand response, construct a business flow model based on the latency characteristics of multiple interactive functions, and then obtain the business flow queue;

[0069] Calculate the channel preference value for each service flow queue, and construct a preference list for each service flow queue according to the channel preference value order;

[0070] The traffic flow queue of the unmatched channel sends a matching request to the channel ranked in the preference list;

[0071] Each channel checks for channel request conflicts. If a conflict is found, the highest priority service flow is allowed to access while other services are rejected. The rejected service flow will remove the channel that rejected it from its preference list and resend the channel matching request. If no conflict is found, each service flow transmits data according to the matched channel.

[0072] Heterogeneous network service flow scheduling is performed based on the data transmission results of each service flow according to the matched channel.

[0073] In the above embodiments, the preference values ​​can be arranged in descending order. The ranking of the preference list can be, for example, the first-ranked preference.

[0074] The heterogeneous network service flow scheduling system proposed in this invention covers various virtual power plant interaction functions, as shown in the system diagram below. Figure 2 As shown, the DR aggregation gateway connects to the power DR terminal via HPLC and 5G, and transmits service flow data to the power DR terminal in real time by executing the proposed service flow scheduling method. The power DR terminal connects to photovoltaic panels, charging piles, and energy storage devices via RS485 and other means, and regulates distributed resources within its control range based on the received service flow data.

[0075] Based on the above system, this embodiment of the invention provides a business flow model constructed based on the latency characteristics of multiple interactive functions, thereby obtaining a business flow queue, as explained below:

[0076] (1) Business flow model

[0077] Interactive functions such as peak shaving, frequency regulation, and demand response can be described using six types of information exchange services: S1 Emergency Event Service, S2 General Event Service, S3 Selection Service, S4 Registration Service, S5 Reporting Service, and S6 Polling Service.

[0078] Based on latency, payload, and data flow characteristics, the six service categories can be divided into four levels of services. The service flow queue set corresponding to each of the four levels is defined as follows: Assume the number of selectable 5G channels is... The number of selectable HPLC channels is , Therefore, the set of selectable channels for a service flow is represented as follows: ,when When, it is represented as a 5G channel, when When, it is represented as the HPLC channel.

[0079] This invention employs a quasi-static time-slot model, which has... There are several equal-length time slots, with a time slot length of [missing information]. The set is represented as Channel state information remains constant within a single time slot but varies across different time slots. Within each time slot, traffic flows can select the appropriate channel for data transmission based on the real-time channel state.

[0080] This invention assumes that each traffic queue can only select one channel to transmit data. A channel selection variable for traffic queue scheduling is defined. ,in Indicates the first Each time slot service flow Select Channel Data transmission must be performed, otherwise .

[0081] Business Flow queue backlog It can be represented as

[0082] (1)

[0083] In the formula, For the first Time-slot service flow The amount of data received; For business flow In the Data volume sent per time slot; service flow Select Channel The throughput for data transmission is:

[0084] (2)

[0085] Therefore, business flow In the Data volume sent per time slot It can be represented as:

[0086] (3)

[0087] in, and These are the bandwidths of the 5G channel and the HPLC channel, respectively. and These represent the business flow respectively. The power of selecting 5G channel and HPLC channel for data transmission; and These represent the business flow respectively. Channel gain of the selected 5G channel and HPLC channel; This represents noise power.

[0088] For the first Time-slot service flow The amount of data arriving is related to the characteristics of the business flow data. Specifically, business flows can be divided into periodic data flows and random data flows. Periodic data flows are mostly generated when large-scale user-side devices and loads access the source network interaction system and perform periodic polling services, and their traffic is significantly time-driven. Random data flows, on the other hand, are mostly for general event-related services and emergency events.

[0089] The following explains the DR service flow model:

[0090] 1. Periodic DR service flow model

[0091] Periodic DR service flow model It can be defined as:

[0092] (4)

[0093] In the formula: The polling cycle is... For business flow queue Queuing delay, For business flow queue Maximum transmission delay limit requirements.

[0094] 2. Stochastic DR Service Flow Model

[0095] Random traffic flows can be approximated using a Poisson process. Let the time interval be... Within, the average arrival rate of DR service flow is Then for any ,have

[0096] (5)

[0097] In the formula: Represents probability. Represents a random process. This represents the average arrival rate of the business flow.

[0098] To further measure the burstiness of data arrival in the business flow queue and the volatility of queue backlog, the burstiness function is defined as follows:

[0099] (6)

[0100] In the formula: For the queue to be at the front Maximum length within a time slot; For the front Average queue length within each time slot This is an estimate of the arrival status of business flow queue data at the next time step.

[0101] 3. Delay Model

[0102] This invention defines For the first Service flow queue within each time slot The queuing delay is represented as:

[0103] (7)

[0104] In the formula: ,express Service flow queue within time slot The average amount of data arriving over time.

[0105] Queuing delay needs to meet the following constraints:

[0106] (8)

[0107] in, For the first Service flow queue within each time slot Queuing delay; For business flow queue Maximum transmission delay limit requirements.

[0108] (2) Service flow scheduling priority considering differentiated latency characteristics

[0109] Since conflicts may occur when different service flow queues select channels, it is necessary to construct a service flow scheduling priority that takes into account the differentiated latency characteristics. By allocating channels with better transmission performance to high-priority service flows, the data transmission requirements of service flows and channel resources can be fully matched, thereby ensuring that the latency characteristics of different service flows can be met.

[0110] To achieve real-time and orderly transmission of multi-service flow data, this invention constructs a service flow scheduling priority function, as shown in equation (9).

[0111] (9)

[0112] In the formula, As weight, . For business flow queue Maximum transmission delay limit requirements; For business flow queue The degree of suddenness; For business flow queue Queue backlog. Business flows with strict latency requirements, stronger data traffic bursts, and larger queue backlogs have higher priority.

[0113] (3) Service flow scheduling method for heterogeneous networking considering the latency characteristics of multiple interactive functions

[0114] The process of the heterogeneous network service flow scheduling method that takes into account the latency characteristics of multiple interactive functions proposed in this invention is as follows: Figure 3 As shown.

[0115] Step 1: Calculate the service flow queue for the current time slot. Select Channel Preference value Define it as the front Service flow queue within each time slot Select Channel The average queue delay for data transmission is shown in formula (10).

[0116] (10)

[0117] In the formula, Select variables for scheduling channels in the service flow queue. t For a moment, For business flow queue Select Channel The queue delay for data transmission.

[0118] Next, each service flow queue constructs a preference list according to the channel preference value.

[0119] Step 2: The traffic flow queue of the unmatched channel sends a matching request to the channel ranked in the preference list.

[0120] Step 3: Each channel checks for channel request conflicts. If a conflict is found, the channel allows the highest-priority service flow to access and rejects other services. The rejected service flow will then remove the channel it rejected from its preference list and return to Step 2 to resend a channel matching request. If no conflict is found, each service flow transmits data according to the matched channel.

[0121] Step 4: Move to the next time slot and repeat the above process until the optimization process is complete.

[0122] (4) Simulation analysis

[0123] This invention compares the proposed heterogeneous network traffic flow scheduling method that considers the latency characteristics of multiple interactive functions with the Delay-Aware Traffic Scheduling Algorithm (DATS), such as... Figure 4 As shown, DATS allocates higher-performance channels to traffic flows with strict latency requirements.

[0124] The proposed algorithm sets queue latency requirements of 50ms for Type I traffic and 400ms for Type II traffic. Simulation results show that the proposed algorithm can meet the queue latency requirements of both Type I and Type II traffic, while the DATS algorithm cannot guarantee a queue latency of less than 400ms for Type II traffic in the 4th and 7th time slots. This is because the proposed algorithm considers the differentiated latency requirements of various services and establishes a traffic scheduling priority list based on characteristics such as traffic latency, data burstiness, and queue backlog. This allows for priority evaluation of the multi-traffic scheduling function, thereby ensuring the timely delivery of multi-traffic data.

[0125] like Figure 5 As shown, the present invention provides a heterogeneous network service flow scheduling system, comprising:

[0126] The business flow receiving module is used to receive business flows from virtual power plants participating in grid demand response, construct a business flow model based on the latency characteristics of multiple interactive functions, and then obtain the business flow queue.

[0127] The preference value calculation module is used to calculate the preference value of each service flow queue for selecting a channel, and to construct a preference list for each service flow queue according to the channel preference value order.

[0128] The matching request module is used to send matching requests from the service flow queue of unmatched channels to the channel with the corresponding ranking in the preference list.

[0129] The data transmission module is used to detect whether there is a channel request conflict for each channel. If there is a conflict, the highest priority service flow is allowed to access and other services are rejected. The rejected service flow will remove the channel that rejected it from its preference list and return to resend the channel matching request. If there is no conflict, each service flow will transmit data according to the matched channel.

[0130] The service flow scheduling module is used to schedule heterogeneous network service flows based on the data transmission results of each service flow according to the matched channel.

[0131] like Figure 6 As shown, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the heterogeneous network service flow scheduling method that takes into account the latency characteristics of multiple interactive functions.

[0132] The present invention also provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the steps of the heterogeneous networking service flow scheduling method taking into account the latency characteristics of multiple interactive functions.

[0133] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0134] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0135] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0136] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0137] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A heterogeneous network service flow scheduling method, characterized in that, include: Receive the business flow of virtual power plant participating in grid demand response, construct a business flow model based on the latency characteristics of multiple interactive functions, and then obtain the business flow queue; Calculate the channel preference value for each service flow queue, and construct a preference list for each service flow queue according to the channel preference value order; The traffic flow queue of the unmatched channel sends a matching request to the channel ranked in the preference list; Each channel detects whether there is a channel request conflict. If a conflict is found, the highest priority service flow is allowed to access while other services are rejected. The rejected service flow will remove the channel that rejected it from its preference list and resend the channel matching request; if there is no conflict, each service flow will transmit data according to the matched channel. Heterogeneous network service flow scheduling is performed based on the data transmission results of each service flow according to the matched channel. The process of constructing a business flow model based on the latency characteristics of multiple interactive functions, and then obtaining a business flow queue, specifically includes: The business flow queue set is The number of 5G channels is The number of HPLC channels is , The set of service flow channels is represented as follows: ; A quasi-static time-slot model is adopted. There are several equal-length time slots, with a time slot length of [missing information]. The set is represented as Service flow queue scheduling channel selection variables ,in Indicates the first Each time slot service flow Select Channel Data transmission must be performed, otherwise ; Business Flow queue backlog Represented as In the formula, For the first Time-slot service flow The amount of data received; For business flow In the Data volume sent per time slot; service flow Select Channel The throughput for data transmission is: Then business flow In the Data volume sent per time slot Represented as: in, and These are the bandwidths of the 5G channel and the HPLC channel, respectively. and These represent the business flow respectively. The power of selecting 5G channel and HPLC channel for data transmission; and These represent the business flow respectively. Channel gain of the selected 5G channel and HPLC channel; This represents noise power.

2. The heterogeneous network service flow scheduling method according to claim 1, characterized in that, The business flow includes periodic data flow and random data flow; Periodic business flow model for: In the formula: The polling cycle is... For business flow queue Queuing delay, For business flow queue Maximum transmission delay limit requirements; Random traffic flows are approximated using a Poisson process; within a time interval Within, the average arrival rate of business flows is Then for any Then, the randomness of the business flow is represented as: In the formula: Represents probability. Represents a random process. This represents the average arrival rate of the business flow.

3. The heterogeneous network service flow scheduling method according to claim 1, characterized in that, The latency model for the service flow is as follows: In the formula: For the first Service flow queue within each time slot Queuing delay, ,express Service flow queue within time slot Average time to arrive data volume; Queuing delay needs to meet the following constraints: in, For the first Service flow queue within each time slot Queuing delay; For business flow queue Maximum transmission delay limit requirements.

4. The heterogeneous network service flow scheduling method according to claim 1, characterized in that, The aforementioned receiving of business flow data related to virtual power plant participation in grid demand response refers to: The power grid demand response aggregation gateway connects to the power grid demand response terminal via HPLC and 5G, and transmits business flow data to the power grid demand response terminal in real time by executing the proposed business flow scheduling method. The power grid demand response terminal is connected to photovoltaic panels, charging piles, and energy storage equipment, and regulates distributed resources within its control range according to the received business flow.

5. The heterogeneous network service flow scheduling method according to claim 1, characterized in that, In each time slot, the service flow selects an appropriate channel for data transmission based on the real-time channel status; each service flow queue selects only one channel to transmit data.

6. The heterogeneous network service flow scheduling method according to claim 1, characterized in that, The service flow scheduling priority satisfies the following function: In the formula, As weight, , For business flow queue Maximum transmission delay limit requirements; For business flow queue The degree of suddenness; For business flow queue Queue backlog.

7. The heterogeneous network service flow scheduling method according to claim 1, characterized in that, The calculation of the channel preference value for each service flow queue includes: In the current time slot where the virtual power plant participates in grid demand response, calculate the business flow queue. Select Channel Preference value Define it as the front Service flow queue within each time slot Select Channel The average queue latency for data transmission is calculated as follows: In the formula, Select variables for scheduling channels in the service flow queue. t For a moment, For business flow queue Select Channel The queue delay for data transmission.

8. A heterogeneous network service flow scheduling system, implementing the heterogeneous network service flow scheduling method according to any one of claims 1-7, characterized in that, include: The business flow receiving module is used to receive business flows from virtual power plants participating in grid demand response, construct a business flow model based on the latency characteristics of multiple interactive functions, and then obtain the business flow queue. The preference value calculation module is used to calculate the preference value of each service flow queue for selecting a channel, and to construct a preference list for each service flow queue according to the channel preference value order. The matching request module is used to send matching requests from the service flow queue of unmatched channels to the channel with the corresponding ranking in the preference list. The data transmission module is used to detect whether there is a channel request conflict on each channel. If a conflict is found, the highest priority service flow is allowed to access while other services are rejected. The rejected service flow will remove the channel that rejected it from its preference list and resend the channel matching request; if there is no conflict, each service flow will transmit data according to the matched channel. The service flow scheduling module is used to schedule heterogeneous network service flows based on the data transmission results of each service flow according to the matched channel.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the heterogeneous networking service flow scheduling method according to any one of claims 1-7.

10. A computer-readable storage medium storing a computer program that, when executed by a processor, implements the heterogeneous networking service flow scheduling method according to any one of claims 1-7.

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