Novel power system-oriented service-model-data combined drive satellite-ground fusion network resource intelligent collaborative scheduling method and system

Abstract

The invention provides a service-model-data combined drive satellite-ground fusion network resource intelligent collaborative scheduling method and system oriented to a novel power system, and relates to the technical field of power resource scheduling. In consideration of communication requirements of different power services in the satellite-ground convergence network, a communication requirement feature model of the dynamic satellite-ground convergence network and the services is established, and the services are divided into a transmission sensitive type and a calculation sensitive type. In order to reasonably utilize limited satellite-ground convergence network resources, a priority processing strategy of service data is formulated, transmission and calculation resources can be distributed and scheduled according to service requirements, and different types of service data can be unloaded and processed in the same time period. Under the condition that different power business communication requirements are met, a joint optimization problem considering system time delay and energy consumption is provided, and the total cost of the system is minimized. And intelligent collaborative scheduling of resources is realized, and the power business is served in real time according to needs, so that multi-type power business requirements under the satellite-ground fusion network are met.

Description

Technical Field

[0001] The present application relates to the technical field of electric power resource dispatching, and in particular to a method and system for intelligent collaborative dispatching of satellite-ground fusion network resources driven by a business-model-data joint approach for a new type of electric power system. Background Art

[0002] With the construction and development of new power systems, the ubiquitous access of widely distributed power equipment has generated massive business data, which has brought huge challenges to the ground communication network with limited coverage and transmission capacity. Different power services have different communication service quality requirements. For example, control services such as distribution automation and distributed energy control have a small amount of data and low requirements for communication bandwidth, but have high requirements for communication delay and bit error rate; while information collection services such as transmission line monitoring and power quality monitoring have a large amount of data and high requirements for communication bandwidth, but low requirements for delay and bit error rate. However, services with different characteristics and requirements are often generated at the same time, and the network service capacity is limited within a certain period of time. Therefore, how to model and characterize the communication requirements of different types of power services and realize clustering and parallel processing is one of the important issues facing current research.

[0003] In response to the problems of insufficient coverage and limited communication capacity of ground communication networks, the satellite-ground fusion network has become an important construction direction for the next generation of communication networks by integrating satellite network services to expand the service scope and capacity of ground communication networks. Due to the different characteristics of satellite networks and ground networks, the satellite-ground fusion network has heterogeneous and dynamic characteristics, which makes it face problems such as extended transmission time, complex link conditions, and dynamic changes in network topology. At the same time, the mobility of network nodes and the complexity of the communication environment under the fusion operation of the two networks bring new problems to task offloading and resource management that cannot be solved by existing methods. In summary, unreasonable scheduling strategies will not only cause waste of resources, but also increase the operating costs of the system.

[0004] Therefore, how to achieve intelligent coordinated scheduling of resources and provide real-time services for power business on demand to meet the needs of multiple types of power business under the satellite-ground fusion network has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] In order to realize intelligent coordinated scheduling of resources, provide real-time services for power business on demand, and meet the needs of various types of power business in the satellite-ground fusion network, the present application provides a method and system for intelligent coordinated scheduling of satellite-ground fusion network resources driven by business-model-data joint for new power systems.

[0006] In the first aspect, the present application provides a business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for a new power system, which adopts the following technical solutions: A business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative dispatching method for a new power system, comprising: A satellite-ground fusion network model is constructed to describe the satellite-ground fusion network consisting of a satellite layer and a ground layer. The satellite layer includes low-orbit satellites, and the ground layer includes gateways, data processing centers, and control centers. Satellites and ground nodes are represented by a bidirectional time-varying graph, and the connectivity, transmission rate, buffer size, and CPU cycle frequency of nodes and links change dynamically. Construct the channel model in the satellite-ground fusion network, establish the inter-satellite communication model and the satellite-ground communication model, consider the impact of channel fading, loss and interference on the transmission rate, calculate the inter-satellite communication rate based on the Shannon formula, and establish the Rice fading channel model of satellite-ground communication; Establish a new power system business model, divide power business into transmission-sensitive and computation-sensitive types, describe the data volume, CPU cycle requirements, processing ratio coefficient and QoS requirements of each type of business, and schedule according to business type and demand; Build a service data priority queuing model to determine the priority of service data based on the service's maximum latency tolerance and generation time, give priority to service data with low latency tolerance, and manage the backlog and processing of service data through offload queues and computing queues; Establish a system cost model, comprehensively consider transmission delay, computing delay, queuing delay and energy consumption cost, and define the total system cost as the weighted sum of delay cost and energy consumption cost; Establish a joint optimization problem to minimize the total system cost and optimize business offloading, business processing, transmission resource allocation, and computing resource allocation decisions while meeting the communication needs of various power services; Solve the joint optimization problem and obtain the results of intelligent coordinated scheduling of satellite-ground integrated network resources, so as to realize efficient processing of power business and optimal allocation of resources.

[0007] Optionally, the steps of constructing the satellite-ground fusion network model include: Building a satellite layer, which consists of low-orbit satellites to provide wide-area communication coverage, and satellite nodes are equipped with edge servers to provide computing services; Constructing a ground layer, wherein the ground layer is composed of a gateway station, a data processing center and a control center, and the gateway station is connected to the satellite layer; Constructing a bidirectional time-varying graph, wherein the bidirectional time-varying graph represents the dynamic changes of connectivity, transmission rate, buffer size, and CPU cycle frequency of nodes and links, wherein the nodes include satellite nodes and ground nodes, and the links represent communication connections between the nodes; A satellite-ground fusion network model is constructed according to the satellite layer, the ground layer and the bidirectional time-varying graph.

[0008] Optionally, the step of constructing a channel model in the satellite-ground fusion network includes: Establish an intersatellite communication model and calculate the transmission rate between satellite nodes based on Shannon's formula, taking into account free space path loss, additional link loss and signal interference; A satellite-to-ground communication model is established to calculate the transmission rate between the satellite and the ground node based on the Rice fading channel model, taking into account the additional signal loss caused by small-scale fading coefficients and rain attenuation; A channel model in a satellite-to-ground fusion network is constructed according to the inter-satellite communication model and the satellite-to-ground communication model.

[0009] Optionally, the step of establishing a new power system business model includes: Constructing transmission-sensitive services to describe information collection services; Constructing computationally sensitive services to describe control services; Construct service tuples to describe the data volume, CPU cycle requirements, processing ratio coefficient and QoS requirements of each type of service. QoS requirements include target node, maximum delay requirement and minimum bandwidth requirement. A new power system business model is established according to the transmission-sensitive business, the calculation-sensitive business and the business tuple.

[0010] Optionally, the step of constructing a business data priority queuing model includes: Construct a priority function to determine the priority of service data according to the maximum delay tolerance and generation time of the service, and give priority to processing service data with low delay tolerance; Build an offload queue to store business data and calculation results waiting to be offloaded, and offload them in order of priority; Build a computing queue to store computing-sensitive business data waiting to be processed and process them in order of priority; A service data priority queuing model is constructed according to the priority function, the offloading queue and the computing queue.

[0011] Optionally, the step of establishing the system cost model includes: Construct the delay cost to calculate the sum of transmission delay, calculation delay and queuing delay, and calculate the queuing delay based on Little's law; Constructing energy consumption cost to calculate the sum of transmission energy consumption, computing energy consumption and satellite operation energy consumption, where transmission energy consumption is calculated based on transmission delay, and computing energy consumption is calculated based on computing delay; Construct the total system cost, which is used to represent the weighted sum of delay cost and energy consumption cost as the optimization objective function; A system cost model is established based on the delay cost, energy consumption cost and total system cost.

[0012] Optionally, the step of establishing the joint optimization problem includes: Establish a service offloading decision variable to indicate whether the service is offloaded from the source node to the target node; Establish business processing decision variables to indicate the processing ratio of business on the node; Establish a transmission resource allocation decision variable to represent the bandwidth allocated to the service by the link; Establish a computing resource allocation decision variable to represent the CPU cycle frequency allocated by the node to the business; Establish constraints to ensure the rationality and feasibility of service offloading, service processing, transmission resource allocation, and computing resource allocation, including bandwidth requirements, computing resource limitations, and node storage capacity constraints; A joint optimization problem is established according to the service offloading decision variables, the service processing decision variables, the transmission resource allocation decision variables, the computing resource allocation decision variables and the constraint conditions.

[0013] In a second aspect, the present application provides a business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative dispatching system for a new power system. The business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative dispatching system for a new power system includes: The fusion network module is used to build a satellite-ground fusion network model, describing the satellite-ground fusion network composed of a satellite layer and a ground layer. The satellite layer includes low-orbit satellites, and the ground layer includes gateways, data processing centers, and control centers. Satellites and ground nodes are represented by a bidirectional time-varying graph, and the connectivity, transmission rate, buffer size, and CPU cycle frequency of nodes and links change dynamically. The channel module is used to construct the channel model in the satellite-ground fusion network, establish the inter-satellite communication model and the satellite-ground communication model, consider the impact of channel fading, loss and interference on the transmission rate, calculate the inter-satellite communication rate based on the Shannon formula, and establish the Rice fading channel model of satellite-ground communication; The business module is used to establish a new power system business model, which divides power business into two categories: transmission-sensitive and computation-sensitive. It describes the data volume, CPU cycle requirements, processing ratio coefficient, and QoS requirements of each type of business, and performs scheduling based on business type and requirements. Priority module, used to build a business data priority queuing model, determine the priority of business data according to the maximum delay tolerance and generation time of the business, give priority to business data with low delay tolerance, and manage the backlog and processing of business data through unloading queues and computing queues; The cost module is used to establish a system cost model, comprehensively considering transmission delay, computing delay, queuing delay and energy consumption cost, and defining the total system cost as the weighted sum of delay cost and energy consumption cost; Joint optimization module, which is used to establish joint optimization problems, minimize the total system cost, and optimize business offloading, business processing, transmission resource allocation, and computing resource allocation decisions while meeting the communication needs of various power services; The solving module is used to solve the joint optimization problem and obtain the results of intelligent coordinated scheduling of satellite-ground integrated network resources, so as to realize efficient processing of power business and optimal allocation of resources.

[0014] In a third aspect, the present application provides a computer device, comprising: a memory and a processor, wherein the processor executes the method described above when running computer instructions stored in the memory.

[0015] In a fourth aspect, the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a computer, enable the computer to execute the method described above.

[0016] In summary, the present application includes the following beneficial technical effects: This application considers the communication needs of different power services in the satellite-ground fusion network, establishes a communication demand characteristic model for dynamic satellite-ground fusion networks and services, and divides services into two categories: transmission-sensitive and computing-sensitive. In order to rationally utilize limited satellite-ground fusion network resources, a priority processing strategy for business data has been formulated, which can allocate and schedule transmission and computing resources according to business needs, and unload and process different types of business data in the same period. While meeting the communication needs of different power services, a joint optimization problem considering system latency and energy consumption is proposed to minimize the total system cost. Intelligent collaborative scheduling of resources is realized, and real-time services for power services are provided on demand to meet the needs of multiple types of power services under the satellite-ground fusion network. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the computer device structure of the hardware operating environment involved in the embodiment of the present application.

[0018] Figure 2 It is a flow chart of an embodiment of the business-model-data jointly driven satellite-ground fusion network resource intelligent collaborative scheduling method for the new power system of the present application.

[0019] Figure 3 This is a schematic diagram of the satellite-ground fusion network power application scenario of this application; Figure 4 This is the data processing flow chart of the power business of this application; Figure 5 It is a structural block diagram of an embodiment of the business-model-data jointly driven satellite-ground integrated network resource intelligent collaborative dispatching system for the new power system of the present application. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below through the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0021] Reference Figure 1 , Figure 1 A schematic diagram of the computer device structure of the hardware operating environment involved in the embodiment of the present application.

[0022] like Figure 1 As shown, the computer device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0023] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the computer device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0024] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling program for the new power system.

[0025] exist Figure 1In the computer device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the present application can be set in the computer device, and the computer device calls the business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling program for the new power system stored in the memory 1005 through the processor 1001, and executes the business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for the new power system provided in the embodiment of the present application.

[0026] The present application embodiment provides a business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for a new power system, referring to Figure 2 , Figure 2 This is a flow chart of an embodiment of a method for intelligent collaborative scheduling of satellite-ground fusion network resources driven by business-model-data joint for a new power system in this application.

[0027] In this embodiment, the business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for the new power system includes the following steps: Step S10: Construct a satellite-ground fusion network model to describe a satellite-ground fusion network consisting of a satellite layer and a ground layer, wherein the satellite layer includes low-orbit satellites, and the ground layer includes a gateway station, a data processing center, and a control center. Satellites and ground nodes are represented by a bidirectional time-varying graph, and the connectivity, transmission rate, buffer size, and CPU cycle frequency of nodes and links change dynamically.

[0028] It is understood that the commonly used technical terms in this field in this embodiment are explained as follows: Satellite-ground fusion network: The satellite-ground fusion network is a space-based network infrastructure composed of multiple satellites, ground gateway stations, and measurement and control stations located in different orbits, and a ground-based network infrastructure composed of ground mobile base stations, WiFi hotspots, and optical fiber networks. Through the integrated and integrated design, the multi-dimensional three-dimensional information network can provide global ubiquitous communication, navigation, and remote sensing services for users in different application scenarios in the sky, air, ground, and sea. The satellite-ground fusion network runs through the remote frontiers of the ocean, the high frontiers of space, and the new frontiers of the network. Due to its important position, the world's major aerospace powers have formulated development strategies and invested heavily to lay out the construction of satellite communication networks focusing on high-orbit high-throughput satellite communication constellations and low-orbit satellite Internet constellations, seeking leading advantages in new technologies, new industries, and space frequency orbital resources. The "full coverage, all-day, all-weather" communication services provided by the satellite-ground fusion network can effectively make up for the systemic shortcomings of the informationization capabilities of the new power system, such as "incomplete coverage, uneven performance, insufficient resilience, and shallow integration", and help realize the "comprehensive observability, precise measurability, and high controllability" of the new power system, which has broad application prospects in the power field.

[0029] QoS: Abbreviation for Quality of Service Shannon's formula Boltzmann's constant Little's law.

[0030] It should be noted that the steps of constructing a satellite-ground fusion network model include: constructing a satellite layer, which is composed of low-orbit satellites to provide wide-area communication coverage, and satellite nodes are equipped with edge servers to provide computing services; constructing a ground layer, which is composed of a gateway, a data processing center, and a control center, and the gateway is connected to the satellite layer; constructing a bidirectional time-varying graph, which represents the connectivity of nodes and links, the transmission rate, the buffer size, and the dynamic changes of the CPU cycle frequency, the nodes include satellite nodes and ground nodes, and the links represent the communication connections between the nodes; constructing a satellite-ground fusion network model according to the satellite layer, the ground layer, and the bidirectional time-varying graph.

[0031] In the specific implementation, a satellite-ground fusion network model is constructed. Figure 3As shown, this embodiment considers that the satellite-ground fusion network can support distributed energy control, transmission line monitoring and other power services. The satellite-ground fusion network consists of two layers: the satellite layer and the ground layer. In the satellite layer, low-orbit satellites provide wide-area communication coverage; in the ground layer, the gateway is connected to the data processing center with high-speed data processing capabilities and the control center with communication needs. It is assumed that the satellites are equipped with edge servers that can provide effective computing services. Establish a bidirectional time-varying graph consisting of nodes and links .in, Satellite Node and ground nodes The node set is composed of ; is the set of communication links, Represents a slave node To Node communication links; Indicates that The time period of time slots, the time between time slots is ; represents the edge time set, Indicates the communication link The connectivity, when When the communication link is connected, On the contrary, nodes are connected when they are within each other's communication range; is the rate time series, Indicates the communication link In time slot The transmission rate; is a collection of node functions, and Represents nodes The buffer size and CPU cycle frequency. In this bidirectional time-varying graph, and They represent the QoS characteristics of links and nodes in terms of communication, computing, and storage, respectively. Due to differences in transmission capabilities, the transmission rates of different links are different. It is assumed that the network topology and resources remain stable in each time slot, but the topology and resources of different time slots change dynamically.

[0032] Step S20: Construct a channel model in the satellite-ground fusion network, establish an inter-satellite communication model and a satellite-ground communication model, consider the impact of channel fading, loss and interference on the transmission rate, calculate the inter-satellite communication rate based on the Shannon formula, and establish a Ricean fading channel model for satellite-ground communication.

[0033] It can be understood that the steps of constructing a channel model in a satellite-ground fusion network include: establishing an inter-satellite communication model, calculating the transmission rate between satellite nodes based on the Shannon formula, taking into account free space path loss, additional link loss and signal interference; establishing a satellite-ground communication model, calculating the transmission rate between the satellite and the ground node based on the Rice fading channel model, taking into account the additional signal loss caused by small-scale fading coefficients and rain attenuation; and constructing a channel model in a satellite-ground fusion network based on the inter-satellite communication model and the satellite-ground communication model.

[0034] In the specific implementation, a channel model in the satellite-ground fusion network is constructed. Taking into account the influence of fading, loss and interference on the channel, the inter-satellite communication model and the satellite-ground communication model are established.

[0035] 1) Intersatellite communication model. According to Shannon's formula, at the satellite node and In the time slot The transmission rate can be expressed as In the formula, Intersatellite Link bandwidth; Indicates satellite The transmission power of Represents the total signal gain of the transmitting antenna and the receiving antenna; represents the free space path loss associated with signal transmission; represents the additional link loss for intersatellite communications; Represents signal interference; represents the Boltzmann constant; Represents the total system noise temperature.

[0036] Among them, the free space path loss associated with signal transmission Expressed as In the formula, represents the speed of light; represents the distance between nodes in time slots; represents the center frequency; Signal interference Expressed as In the formula, Indicates link The set of interference links; represents the link's offload state variable, Indicates that the link actively offloads tasks and can cause interference in the time slot, The opposite is true.

[0037] 2) Satellite-to-ground communication model. The satellite-to-ground communication channel is established as a Rician fading channel. When performing satellite-to-ground communication, the data transmission rate of the link in the time slot is expressed as In the formula, represents the small-scale fading coefficient; Represents the additional signal loss caused by rain attenuation.

[0038] The small-scale fading coefficient is expressed as in, The corresponding Rice fading coefficient; is the influence state coefficient within the line of sight. ; represents the random effect within non-line-of-sight; the corresponding interference Expressed as Step S30: Establish a new power system business model, divide the power business into two categories: transmission-sensitive and computation-sensitive, describe the data volume, CPU cycle requirements, processing ratio coefficient and QoS requirements of each type of business, and schedule according to business type and demand.

[0039] In the specific implementation, the steps of establishing a new power system business model include: constructing transmission-sensitive businesses to describe information collection businesses; constructing computing-sensitive businesses to describe control businesses; constructing business tuples to describe the data volume, CPU cycle requirements, processing ratio coefficients and QoS requirements of each type of business, QoS requirements include target nodes, maximum delay requirements and minimum bandwidth requirements; establishing a new power system business model based on transmission-sensitive businesses, computing-sensitive businesses and business tuples.

[0040] It is understandable that a new power system service model is established in the satellite-ground fusion network. In different power scenarios, source nodes will generate different types of power services. This embodiment divides the services into transmission-sensitive (information collection) and calculation-sensitive (control) services. Considering different characteristics and requirements Electricity business, establish the electricity business set as According to the main characteristics of the power business, the business is described as a tuple ,in, Indicates power business The amount of data; Indicates the CPU cycles required to process each bit of data; represents the processing scale factor; Indicates the source node of the business. For computing-sensitive businesses, the amount of data required to be calculated is ; For transmission-sensitive services without data processing requirements, the CPU cycles required to process each bit of data , processing scale factor In addition, define the tuple express QoS requirements for type services, including: Indicates the target node of the business; Indicates the maximum delay requirement; represents the minimum bandwidth requirement. Assume that the source node is in time slot Randomly generate a number in the range Various types of business within the time slot Produced Number of business types These services are scheduled according to their needs, scheduling decisions, and allocated resources. During the service processing, the node can offload the arriving transmission-sensitive services or calculation results, or perform local calculations or offload the arriving calculation-sensitive services. If the transmission-sensitive services and calculation results arrive at the target node within the maximum delay requirement, the service processing is completed; otherwise, the processing process is terminated and the service processing fails.

[0041] Step S40: Construct a service data priority queuing model, determine the priority of service data according to the maximum delay tolerance and generation time of the service, give priority to service data with low delay tolerance, and manage the backlog and processing of service data through unloading queues and computing queues.

[0042] It should be noted that the steps of building a business data priority queuing model include: A priority function is constructed to determine the priority of business data according to the maximum delay tolerance and generation time of the business, and business data with low delay tolerance is processed first; an unloading queue is constructed to store business data and calculation results waiting to be unloaded, and unload them in order of priority; a calculation queue is constructed to store calculation-sensitive business data waiting to be processed, and process them in order of priority; a business data priority queuing model is constructed based on the priority function, unloading queue and calculation queue.

[0043] In the specific implementation, Figure 4As shown in the flowchart of power business data processing, a business data priority queuing model is established in this embodiment. Considering the limited transmission and computing resources of the satellite-ground fusion network, some businesses cannot be processed immediately after arriving at the node. It is assumed that each node has two buffer queues, an unloading queue and a storage queue, to store tasks. The unloading queue stores the business and calculation results waiting to be unloaded, and the settlement queue stores the calculation-sensitive tasks waiting to be processed. When the business incoming to the node exceeds the storage capacity of the node, the business will be discarded.

[0044] First, formulate a business data priority processing strategy. Considering the different times when business data is generated and the changing latency requirements, prioritize unloading and processing business data with low latency tolerance. The priority function is expressed as the remaining time to complete the business within the maximum tolerable delay. Specifically, the time slot is defined Middle indivual The priority function of business data processing is as follows: In the formula, Representative indivual The time when the business data is generated. Business type, Is a collection Business data generation order, yes The total number of services generated by this type of service in the previous time slot.

[0045] Since the service data will not be processed once the remaining time exceeds the maximum delay tolerance, the priority function Based on the business data priority processing strategy, the business data in the unloading queue and computing queue are arranged in order of priority. In the priority queue, the smaller the function value, the higher the priority, and the earlier the data will be unloaded or processed.

[0046] Secondly, we conduct queue analysis. and Indicates that the unloading and computing queues are on the node The amount of business data backlog at the location. Considering the differences in business characteristics and needs, the queues are analyzed according to business types. Based on this, we define and They are Type of business at the node The number of business backlogs at , expressed as: - + - + In the formula, and Respectively represent the time slot Uninstalled and processed Type of business data volume; and Respectively represent the time slot Arrival Node The amount of new offload and computing business data.

[0047] In summary, and They can be expressed as: definition is the unloading decision variable of the power business. Business slave node Offloading to Node hour, , otherwise the opposite. To effectively utilize limited network transmission resources, different types of services are unloaded in parallel by allocating bandwidth to the services that need to be unloaded. Definition For link uninstall The bandwidth allocated to the service when the service is unloaded. The calculation method of the number of business types is as follows: In the formula, Indicates time slot By bandwidth The data transmission rate of the transmission. Unload to other nodes The total number of business types is expressed as follows: At the same time, in order to make full use of computing resources, the computing resources of the nodes are allocated to various computing-sensitive businesses to process the businesses in parallel. For the time slot node Assigned to The CPU cycle frequency of the business type, The processing volume of the type of business is expressed as follows: Afterwards, the generated calculation results are distributed to the calculation queue, waiting to be offloaded to the target node.

[0048] Among the newly arrived services at each node, some computing-sensitive services are waiting to be processed in the computing queue, and the rest are scheduled to the offloading queue. For business processing decision variables, determine the node Newly arrived Based on this, the processing ratio of type business is scheduled to the computing queue. The number of business types is calculated as follows: For transmission-sensitive services and calculation results, . Compute and schedule to nodes Unload the queue The number of business types is: Considering the number of unloaded tasks, the number of generated tasks, and the calculation results, the node of The total number of business types is expressed as follows: Through the above analysis, we can get all the queue information affected by the scheduling decision, based on which we can deduce the link The uninstall decision variables are: In the formula, Indicates that the service can be unloaded only when the allocated bandwidth is greater than the minimum bandwidth required by the service. , .

[0049] Step S50: Establish a system cost model, comprehensively consider transmission delay, computation delay, queuing delay and energy consumption cost, and define the total system cost as the weighted sum of delay cost and energy consumption cost.

[0050] It should be noted that the steps of establishing a system cost model include: constructing a delay cost for calculating the sum of transmission delay, computing delay and queuing delay, and calculating the queuing delay based on Little's law; constructing an energy consumption cost for calculating the sum of transmission energy consumption, computing energy consumption and satellite operation energy consumption, wherein the transmission energy consumption is calculated based on the transmission delay, and the computing energy consumption is calculated based on the computing delay; constructing a total system cost to represent the weighted sum of the delay cost and the energy consumption cost as the optimization objective function; and establishing a system cost model based on the delay cost, the energy consumption cost and the total system cost.

[0051] In the specific implementation, the system cost model comprehensively considers factors such as data transmission, data calculation and service queuing delay in the satellite-ground fusion network resource scheduling process, analyzes the energy consumption generated by transmission, calculation and system operation, and defines the system cost including delay cost and energy consumption cost, as follows: In the formula, and They represent delay cost and energy consumption cost respectively.

[0052] 1) Latency cost: Considering parallel offloading, the link In time slot uninstall The maximum time spent on this type of business is expressed as: Similarly, consider the computational latency of parallel processing of computationally sensitive services, expressed as: Based on Little's law, we get the node In time slot The queuing delay is: In summary, in the time slot The total queuing delay is expressed as: 2) Energy consumption cost: based on link In time slot uninstall Maximum time spent on business , the link is in time slot The corresponding transmission energy consumption is expressed as: Similarly, based on the computational delay The calculated energy consumption is: In the formula, To calculate the energy consumption parameters.

[0053] In addition, the operating energy consumption of satellite nodes is considered. In time slot The operating power is , then the satellite operation energy consumption is expressed as: In summary, in the time slot The total system energy consumption is expressed as: .

[0054] Step S60: Establish a joint optimization problem to minimize the total system cost and optimize business offloading, business processing, transmission resource allocation and computing resource allocation decisions while meeting the communication needs of various power services.

[0055] In a specific implementation, the steps of establishing a joint optimization problem include: establishing a service offloading decision variable, indicating whether the service is offloaded from a source node to a target node; establishing a service processing decision variable, indicating the processing ratio of the service on the node; establishing a transmission resource allocation decision variable, indicating the bandwidth allocated to the service by the link; establishing a computing resource allocation decision variable, indicating the CPU cycle frequency allocated by the node to the service; establishing constraints to ensure the rationality and feasibility of service offloading, service processing, transmission resource allocation and computing resource allocation, including bandwidth requirements, computing resource limitations and node storage capacity constraints; and establishing a joint optimization problem based on the service offloading decision variable, the service processing decision variable, the transmission resource allocation decision variable, the computing resource allocation decision variable and the constraints.

[0056] In the specific implementation, in order to meet the business communication requirements of various new power systems under the satellite-ground fusion network and minimize the system cost, the objective function is defined as Considering the requirements of service offloading, service processing, transmission resource allocation and computing resource allocation, a joint optimization problem is established. The service offloading variable set is defined as , the business processing decision variable set is ; The decision variable for link bandwidth resource allocation is , the node computing resource allocation decision variable is .

[0057] In summary, the joint optimization problem is established as follows: (28) (29) (30) (31) (32) (33) (34) (35) (36) (37) Among them, formula (29) represents the binary service offloading decision variable; formula (30) represents the service processing decision continuous variable; formula (31) represents the service only in the link Only when connected can the node Offloading to Node ; Formula (32) indicates that the service offloading decision is affected by the bandwidth demand. The allocated bandwidth should be greater than the minimum bandwidth demand of the service, and no bandwidth is allocated to services that do not need to be offloaded; Formula (33) indicates the continuous variable for allocating computing resources; Formula (34) indicates that the bandwidth allocated to the link cannot be greater than the total bandwidth of each link; Formula (35) indicates that the CPU cycle frequency allocated to the node is limited by the available computing resources of the node; Formula (36) indicates that the number of services in the node queue cannot exceed the storage capacity of the node; Formula (37) indicates that the priority function cannot be negative, that is, when the delay exceeds the maximum delay tolerance of the unprocessed service, the service will not be processed.

[0058] Step S70: Solve the joint optimization problem to obtain the intelligent coordinated dispatch result of satellite-ground integrated network resources, so as to realize efficient processing of power business and optimal allocation of resources.

[0059] This embodiment establishes a satellite-ground fusion network resource intelligent collaborative dispatching strategy that takes into account the communication needs of different types of new power system services, allocates and dispatches network resources according to the needs of different services, and unloads and processes tasks in order of priority. Taking the minimization of the total system cost as the optimization goal, the joint optimization problem of communication delay and system energy consumption is proposed.

[0060] Through the method of this embodiment, the characteristics of multiple services and the quality of communication services are characterized, and the service requirements are classified accordingly. It is possible to meet the communication requirements of various new power system services under the satellite-ground fusion network while minimizing the system cost, ensuring the quality of communication service requirements of new power system services, and improving system efficiency.

[0061] This embodiment takes into account the communication requirements of different power services in the satellite-ground fusion network, establishes a communication requirement characteristic model for dynamic satellite-ground fusion networks and services, and divides services into two categories: transmission-sensitive and computing-sensitive. In order to rationally utilize limited satellite-ground fusion network resources, a priority processing strategy for business data is formulated, which can allocate and schedule transmission and computing resources according to business needs, and unload and process different types of business data in the same period. While meeting the communication requirements of different power services, a joint optimization problem considering system latency and energy consumption is proposed to minimize the total system cost. Intelligent collaborative scheduling of resources is realized, and real-time services for power services are provided on demand to meet the needs of multiple types of power services under the satellite-ground fusion network.

[0062] In addition, an embodiment of the present application also proposes a computer-readable storage medium, on which is stored a program for business-model-data joint-driven intelligent collaborative scheduling of satellite-ground fusion network resources for a new type of power system. When the program for business-model-data joint-driven intelligent collaborative scheduling of satellite-ground fusion network resources for a new type of power system is executed by a processor, the steps of the method for business-model-data joint-driven intelligent collaborative scheduling of satellite-ground fusion network resources for a new type of power system as described above are implemented.

[0063] Reference Figure 5 , Figure 5 This is a structural block diagram of an embodiment of the business-model-data jointly driven satellite-ground integrated network resource intelligent collaborative dispatching system for the new power system of this application.

[0064] like Figure 5 As shown, the business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative dispatching system for the new power system proposed in the embodiment of the present application includes: The fusion network module 10 is used to construct a satellite-ground fusion network model, describing a satellite-ground fusion network consisting of a satellite layer and a ground layer, wherein the satellite layer includes a low-orbit satellite, and the ground layer includes a gateway station, a data processing center, and a control center. The satellite and ground nodes are represented by a bidirectional time-varying graph, and the connectivity, transmission rate, buffer size, and CPU cycle frequency of the nodes and links change dynamically; The channel module 20 is used to construct a channel model in the satellite-ground fusion network, establish an inter-satellite communication model and a satellite-ground communication model, consider the impact of channel fading, loss and interference on the transmission rate, calculate the inter-satellite communication rate based on the Shannon formula, and establish a Rice fading channel model for satellite-ground communication; The service module 30 is used to establish a new power system service model, classify power services into two categories: transmission-sensitive and computation-sensitive, describe the data volume, CPU cycle requirements, processing ratio coefficient and QoS requirements of each type of service, and schedule according to service type and requirements; The priority module 40 is used to build a service data priority queuing model, determine the priority of service data according to the maximum delay tolerance and generation time of the service, give priority to the service data with low delay tolerance, and manage the backlog and processing of service data through the unloading queue and the computing queue; The cost module 50 is used to establish a system cost model, comprehensively consider the transmission delay, computing delay, queuing delay and energy consumption cost, and define the total system cost as the weighted sum of the delay cost and the energy consumption cost; The joint optimization module 60 is used to establish a joint optimization problem, minimize the total system cost, and optimize the business offloading, business processing, transmission resource allocation and computing resource allocation decisions under the premise of meeting the communication requirements of various power business; The solving module 70 is used to solve the joint optimization problem, obtain the intelligent coordinated scheduling result of the satellite-ground integrated network resources, and realize the efficient processing of power business and the optimal allocation of resources.

[0065] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present application. In specific applications, technicians in this field can make settings as needed, and the present application does not impose any limitation on this.

[0066] This embodiment takes into account the communication requirements of different power services in the satellite-ground fusion network, establishes a communication requirement characteristic model for dynamic satellite-ground fusion networks and services, and divides services into two categories: transmission-sensitive and computing-sensitive. In order to rationally utilize limited satellite-ground fusion network resources, a priority processing strategy for business data is formulated, which can allocate and schedule transmission and computing resources according to business needs, and unload and process different types of business data in the same period. While meeting the communication requirements of different power services, a joint optimization problem considering system latency and energy consumption is proposed to minimize the total system cost. Intelligent collaborative scheduling of resources is realized, and real-time services for power services are provided on demand to meet the needs of multiple types of power services under the satellite-ground fusion network.

[0067] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present application. In practical applications, technicians in this field can select part or all of it according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0068] In addition, for technical details not described in detail in this embodiment, please refer to the method for business-model-data joint-driven intelligent collaborative scheduling of satellite-ground fusion network resources for new power systems provided in any embodiment of the present application, which will not be repeated here.

[0069] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0070] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0071] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods of each embodiment of the present application.

[0072] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for new power systems, characterized in that: include: A satellite-ground fusion network model is constructed to describe the satellite-ground fusion network consisting of a satellite layer and a ground layer. The satellite layer includes low-orbit satellites, and the ground layer includes gateways, data processing centers, and control centers. Satellites and ground nodes are represented by a bidirectional time-varying graph, and the connectivity, transmission rate, buffer size, and CPU cycle frequency of nodes and links change dynamically. Construct the channel model in the satellite-ground fusion network, establish the inter-satellite communication model and the satellite-ground communication model, consider the impact of channel fading, loss and interference on the transmission rate, calculate the inter-satellite communication rate based on the Shannon formula, and establish the Rice fading channel model of satellite-ground communication; Establish a new power system business model, divide power business into transmission-sensitive and computation-sensitive types, describe the data volume, CPU cycle requirements, processing ratio coefficient and QoS requirements of each type of business, and schedule according to business type and demand; Build a service data priority queuing model to determine the priority of service data based on the service's maximum latency tolerance and generation time, give priority to service data with low latency tolerance, and manage the backlog and processing of service data through offload queues and computing queues; Establish a system cost model, comprehensively consider transmission delay, computing delay, queuing delay and energy consumption cost, and define the total system cost as the weighted sum of delay cost and energy consumption cost; Establish a joint optimization problem to minimize the total system cost and optimize business offloading, business processing, transmission resource allocation, and computing resource allocation decisions while meeting the communication needs of various power services; Solve the joint optimization problem and obtain the results of intelligent coordinated scheduling of satellite-ground integrated network resources, so as to realize efficient processing of power business and optimal allocation of resources.

2. The business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for new power systems according to claim 1 is characterized in that: The step of constructing the satellite-ground fusion network model includes: Building a satellite layer, which consists of low-orbit satellites to provide wide-area communication coverage, and satellite nodes are equipped with edge servers to provide computing services; Constructing a ground layer, wherein the ground layer is composed of a gateway station, a data processing center and a control center, and the gateway station is connected to the satellite layer; Constructing a bidirectional time-varying graph, wherein the bidirectional time-varying graph represents the dynamic changes of connectivity, transmission rate, buffer size, and CPU cycle frequency of nodes and links, wherein the nodes include satellite nodes and ground nodes, and the links represent communication connections between the nodes; A satellite-ground fusion network model is constructed according to the satellite layer, the ground layer and the bidirectional time-varying graph.

3. The business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for new power systems according to claim 1 is characterized in that: The step of constructing a channel model in a satellite-ground fusion network includes: Establish an intersatellite communication model and calculate the transmission rate between satellite nodes based on Shannon's formula, taking into account free space path loss, additional link loss and signal interference; A satellite-to-ground communication model is established to calculate the transmission rate between the satellite and the ground node based on the Rice fading channel model, taking into account the additional signal loss caused by small-scale fading coefficients and rain attenuation; A channel model in a satellite-to-ground fusion network is constructed according to the inter-satellite communication model and the satellite-to-ground communication model.

4. The business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for a new power system according to claim 1 is characterized in that: The steps of establishing a new power system business model include: Constructing transmission-sensitive services to describe information collection services; Constructing computationally sensitive services to describe control services; Construct service tuples to describe the data volume, CPU cycle requirements, processing ratio coefficient and QoS requirements of each type of service. QoS requirements include target node, maximum delay requirement and minimum bandwidth requirement. A new power system business model is established according to the transmission-sensitive business, the calculation-sensitive business and the business tuple.

5. The business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for new power systems according to claim 1 is characterized in that: The step of constructing the service data priority queuing model includes: Construct a priority function to determine the priority of service data according to the maximum delay tolerance and generation time of the service, and give priority to processing service data with low delay tolerance; Build an offload queue to store business data and calculation results waiting to be offloaded, and offload them in order of priority; Build a computing queue to store computing-sensitive business data waiting to be processed and process them in order of priority; A service data priority queuing model is constructed according to the priority function, the offloading queue and the computing queue.

6. The business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for new power systems according to claim 1 is characterized in that: The steps of establishing the system cost model include: Construct the delay cost to calculate the sum of transmission delay, calculation delay and queuing delay, and calculate the queuing delay based on Little's law; Constructing energy consumption cost to calculate the sum of transmission energy consumption, computing energy consumption and satellite operation energy consumption, where transmission energy consumption is calculated based on transmission delay, and computing energy consumption is calculated based on computing delay; Construct the total system cost, which is used to represent the weighted sum of delay cost and energy consumption cost as the optimization objective function; A system cost model is established based on the delay cost, energy consumption cost and total system cost.

7. The business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative scheduling method for new power systems according to claim 1 is characterized in that: The step of establishing the joint optimization problem comprises: Establish a service offloading decision variable to indicate whether the service is offloaded from the source node to the target node; Establish business processing decision variables to indicate the processing ratio of business on the node; Establish a transmission resource allocation decision variable to represent the bandwidth allocated to the service by the link; Establish a computing resource allocation decision variable to represent the CPU cycle frequency allocated by the node to the business; Establish constraints to ensure the rationality and feasibility of service offloading, service processing, transmission resource allocation, and computing resource allocation, including bandwidth requirements, computing resource limitations, and node storage capacity constraints; A joint optimization problem is established according to the service offloading decision variables, the service processing decision variables, the transmission resource allocation decision variables, the computing resource allocation decision variables and the constraint conditions.

8. A business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative dispatching system for new power systems, characterized by: The business-model-data joint-driven satellite-ground fusion network resource intelligent collaborative dispatching system for the new power system includes: The fusion network module is used to build a satellite-ground fusion network model, describing the satellite-ground fusion network composed of a satellite layer and a ground layer. The satellite layer includes low-orbit satellites, and the ground layer includes gateways, data processing centers, and control centers. Satellites and ground nodes are represented by a bidirectional time-varying graph, and the connectivity, transmission rate, buffer size, and CPU cycle frequency of nodes and links change dynamically. The channel module is used to construct the channel model in the satellite-ground fusion network, establish the inter-satellite communication model and the satellite-ground communication model, consider the impact of channel fading, loss and interference on the transmission rate, calculate the inter-satellite communication rate based on the Shannon formula, and establish the Rice fading channel model of satellite-ground communication; The business module is used to establish a new power system business model, which divides power business into two categories: transmission-sensitive and computation-sensitive. It describes the data volume, CPU cycle requirements, processing ratio coefficient, and QoS requirements of each type of business, and performs scheduling based on business type and requirements. Priority module, used to build a business data priority queuing model, determine the priority of business data according to the maximum delay tolerance and generation time of the business, give priority to business data with low delay tolerance, and manage the backlog and processing of business data through unloading queues and computing queues; The cost module is used to establish a system cost model, comprehensively considering transmission delay, computing delay, queuing delay and energy consumption cost, and defining the total system cost as the weighted sum of delay cost and energy consumption cost; Joint optimization module, which is used to establish joint optimization problems, minimize the total system cost, and optimize business offloading, business processing, transmission resource allocation, and computing resource allocation decisions while meeting the communication needs of various power services; The solving module is used to solve the joint optimization problem and obtain the results of intelligent coordinated scheduling of satellite-ground integrated network resources, so as to realize efficient processing of power business and optimal allocation of resources.

9. A computer device, characterized in that: The device comprises: a memory and a processor, and when the processor runs the computer instructions stored in the memory, the processor executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The method comprises instructions, which, when executed on a computer, cause the computer to execute the method according to any one of claims 1 to 7.

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