Routing Planning Method and Device for Hierarchical Requirements of Power Grid Power Services

Abstract

An embodiment of the present invention provides a routing planning method and device for grading requirements of power services in a smart grid. The method includes: obtaining power services in the smart grid, and assigning hierarchical importance values to the reliability requirements and real-time requirements of the power services; obtaining node failure and link failure data, and determining a calculation formula for the reliability impact quantization value; obtaining node delay and link delay data, and determining a calculation formula for the real-time impact quantization value; when a service request is detected, performing reliability and real-time weight allocation for the request, substituting the weight allocation result into the calculation formula to obtain an objective function; determining the shortest K paths between the source node and the target node according to the service request, obtaining the parameters corresponding to the service request and the K paths, and substituting them into the objective function, and selecting the path with the smallest calculation result as the final preferred path. Using this method can make the selection of the final preferred path more reliable; and it also improves the accuracy and flexibility of service routing planning.

Description

Technical Field

[0001] The present invention relates to the technical field of smart grid planning, and particularly to a routing planning method and device for grading requirements of electric power services in a smart grid. Background Art

[0002] With the rapid development of computer networks and communication technologies, the number of services carried by power communication networks has increased significantly, including a large number of new services. Facing such a huge volume of services, the service requirements of power services are also diverse. Against the background of the continuous growth of the number of users and the diversification of user groups, for the existing traditional services in the network, such as relay protection services and security and stability control services, there are higher requirements for the real-time performance of the transmission network than before. For the new services pouring into the network, such as 4K / 8K high-definition video services, video conferencing services, 5G services, etc., there are not only higher requirements for bandwidth, but also higher requirements for the reliability and real-time performance of the transmission network. Therefore, the transmission network technology of smart grids must be continuously upgraded and optimized in the direction of large bandwidth, low latency, and high reliability. When selecting transmission network technologies, OTN (Optical Transport Network) technology stands out with its advantages such as larger transmission bandwidth and more flexible scheduling, and has become the first choice for modern transmission network technologies. Based on the large-capacity ultra-high-speed long-distance transmission of WDM (Wavelength Division Multiplexing), OTN inherits the highly flexible scheduling system and powerful operation management and maintenance mechanism of SDH (Synchronous Digital Hierarchy). Currently, the optimization and upgrade of power service routing selection in smart grids are carried out under the background of OTN technology.

[0003] At present, when domestic and foreign scholars study the OTN network service planning strategy, the mainstream idea is to find the optimizable factors in the network, consider the correlations and constraints between different factors, establish a mathematical model for them, determine the final optimization objective function, and then select the target path in combination with relevant algorithms. In the research of relevant algorithms, domestic and foreign scholars focus on path selection and resource planning problems. The path selection algorithms include the general shortest path (SP) algorithm and the K-shortest path (K-SP) algorithm extended on the basis of this algorithm. Both of these algorithms select the shortest path according to the shortest physical link length or the minimum number of hops. The difference is that the K-shortest path algorithm can obtain the first K (K>1) shortest paths. Compared with the shortest path algorithm that can only obtain one shortest path, it can more conveniently find the optimal path that meets the constraints when there are other constraints. The resource planning problem is usually considered as the wavelength resource allocation problem in service routing planning. The number of wavelengths in each optical fiber is limited. To avoid wavelength blocking, it is necessary to reasonably allocate wavelength resources.

[0004] However, the existing routing planning algorithms generally establish objective functions from aspects such as node failure, link failure, and load balancing, and consider less the specific requirements of existing services, and the aspects considered are also relatively single. For example, only real-time requirements or only reliability requirements are considered, and specific planning adjustments cannot be flexibly made according to service requirements. Summary of the Invention

[0005] In view of the problems existing in the prior art, an embodiment of the present invention provides a routing planning method and device for the hierarchical requirements of power services in a smart grid.

[0006] An embodiment of the present invention provides a routing planning method for the hierarchical requirements of power services in a smart grid, including:

[0007] Obtain the power services of the smart grid, and assign hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment includes the quantization value of service reliability importance and the quantization value of service real-time importance;

[0008] Obtain the node failure and link failure data in the power services, and determine the calculation formula of the reliability impact quantization value through the node failure and link failure data in combination with the quantization value of service reliability importance;

[0009] Obtain the node delay and link delay data in the power services, and determine the calculation formula of the real-time impact quantization value through the node delay and link delay data in combination with the quantization value of service real-time importance;

[0010] When a service request is detected, according to the type of the service request, weight allocation for the reliability and real-time performance of the service request is performed, and the weight allocation result is substituted into the calculation formulas for the reliability impact quantization value and the real-time performance impact quantization value for addition calculation to obtain the objective function of the service request;

[0011] Determine the corresponding source node and target node according to the service request, obtain the K paths with the shortest physical link length from the source node to the destination node, obtain the parameters corresponding to the service request and the K paths, substitute the parameters into the objective function, and select the path with the smallest calculation result of the objective function as the final preferred path of the service request.

[0012] In one embodiment, the method further includes:

[0013] Establish a hierarchical structure model through the analytic hierarchy process, compare the data at each level in the hierarchical structure model, and generate a corresponding reliability requirement judgment matrix and real-time performance requirement judgment matrix according to the comparison result. The hierarchical structure model includes the power service demand degree data at the upper target layer, the reliability and real-time performance data at the index layer, and the power service data at the lower target layer;

[0014] Perform normalization processing on the reliability requirement judgment matrix and the real-time performance requirement judgment matrix respectively to obtain a new matrix after normalization processing, and perform normalization processing on the new matrix to obtain the service reliability importance quantization value and the service real-time performance importance quantization value of the power service.

[0015] In one embodiment, the method further includes:

[0016] Perform column-wise normalization processing on the reliability requirement judgment matrix and the real-time performance requirement judgment matrix respectively. The column-wise normalization processing means dividing each data in the matrix by the sum of the data corresponding to the column.

[0017] In one embodiment, the calculation formula for the reliability impact quantization value includes:

[0018]

[0019] Wherein, R(i) is the service reliability importance quantization value, is the product of the availabilities of all links on the path through which service i passes, is the product of the availabilities of all nodes on the path through which the service passes;

[0020] The calculation method is:

[0021]

[0022] Among them, is the availability of service i on path j;

[0023] The calculation method is:

[0024]

[0025] Among them, is the failure probability of service i on node k.

[0026] In one embodiment, the calculation formula of the real-time impact quantization value includes:

[0027]

[0028] Among them, is the quantization value of the importance of service real-time performance, is the sum of the total delay of service i on network nodes and the total delay of the service on network links.

[0029] An embodiment of the present invention provides a routing planning device for the hierarchical requirements of power services in a smart grid, including:

[0030] A first acquisition module, configured to acquire power services of the smart grid, and assign hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment includes a quantization value of service reliability importance and a quantization value of service real-time importance;

[0031] A second acquisition module, configured to acquire node failure and link failure data in the power services, and determine a calculation formula for the reliability impact quantization value by combining the node failure and link failure data with the quantization value of service reliability importance;

[0032] A third acquisition module, configured to acquire node delay and link delay data in the power services, and determine a calculation formula for the real-time impact quantization value by combining the node delay and link delay data with the quantization value of service real-time importance;

[0033] A detection module, configured to, when detecting a service request, perform weight allocation for the reliability and real-time performance of the service request according to the type of the service request, substitute the weight allocation result into the calculation formula for the reliability impact quantization value and the calculation formula for the real-time impact quantization value for addition calculation, and obtain an objective function of the service request;

[0034] A selection module, configured to determine corresponding source nodes and target nodes according to the service request, obtain K paths with the shortest physical link lengths from the source nodes to the target nodes, obtain the parameters corresponding to the service request and the K paths, substitute the parameters into the objective function, and select the path with the smallest calculation result of the objective function as the final preferred path of the service request.

[0035] In one embodiment, the device further includes:

[0036] A model establishment module, configured to establish a hierarchical structure model through the analytic hierarchy process, compare the data of each layer in the hierarchical structure model, and generate a corresponding reliability requirement judgment matrix and real-time requirement judgment matrix according to the comparison results. The hierarchical structure model includes power service requirement degree data in the upper target layer, reliability and real-time data in the index layer, and power service data in the lower target layer.

[0037] A normalization module, configured to perform normalization processing on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively to obtain new matrices after the normalization processing, and perform normalization processing on the new matrices to obtain the quantitative values of the service reliability importance and the service real-time importance of the power service.

[0038] In one embodiment, the device further includes:

[0039] A column-wise normalization module, configured to perform column-wise normalization processing on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively. The column-wise normalization processing means dividing each data in the matrix by the sum of the data corresponding to the column.

[0040] An embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the above routing planning method for the hierarchical requirements of power services in the smart grid are implemented.

[0041] An embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above routing planning method for the hierarchical requirements of power services in the smart grid are implemented.

[0042] A routing planning method and device for hierarchical requirements of power services in a smart grid provided by an embodiment of the present invention obtain power services of the smart grid, and assign hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment includes a business reliability importance quantization value and a business real-time importance quantization value; obtain node failure and link failure data in the power service, and determine a calculation formula for the reliability impact quantization value through the node failure and link failure data in combination with the business reliability importance quantization value; obtain node delay and link delay data in the power service, and determine a calculation formula for the real-time impact quantization value through the node delay and link delay data in combination with the business real-time importance quantization value; when a service request is detected, perform weight allocation for the reliability and real-time of the service request according to the type of the service request, substitute the weight allocation result into the calculation formula for the reliability impact quantization value and the calculation formula for the real-time impact quantization value for addition calculation to obtain an objective function of the service request; determine a corresponding source node and target node according to the service request, obtain K paths with the shortest physical link length from the source node to the destination node, obtain parameters corresponding to the service request and the K paths, substitute the parameters into the objective function, and select the path with the smallest calculation result of the objective function as the final optimal path for the service request. In this way, the service requirements can be considered from multiple perspectives of real-time and reliability, and the analytic hierarchy process is used to quantify the hierarchical requirements of the service, making the selection of the final optimal path more reliable; and it can perform weight allocation for the reliability and real-time of each service with an access request, and the weight value can be adjusted according to actual requirements, improving the accuracy and flexibility of service routing planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0044] Figure 1 It is a flowchart of a routing planning method for hierarchical requirements of power services in a smart grid according to an embodiment of the present invention;

[0045] Figure 2 It is a structural diagram of a routing planning device for hierarchical requirements of power services in a smart grid according to an embodiment of the present invention;

[0046] Figure 3 It is a schematic structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0048] Figure 1 As shown in the flowchart of a routing planning method for hierarchical requirements of power grid power services provided by an embodiment of the present invention, Figure 1 As shown, an embodiment of the present invention provides a routing planning method for hierarchical requirements of power grid power services, including:

[0049] Step S201: Obtain the power services of the smart grid, and assign hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment includes a service reliability importance quantification value and a service real-time importance quantification value.

[0050] Specifically, obtain the relevant data of the power services in the database of the smart grid, and assign hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment may include a service reliability importance quantification value and a service real-time importance quantification value. Among them, the specific hierarchical importance assignment steps may include:

[0051] Step 1: Establish a hierarchical structure model through the analytic hierarchy process. The hierarchical structure model is divided into three layers. The top layer is the upper target layer, the middle layer is the index layer, and the bottom layer is the lower target layer. In this embodiment, specifically, set the upper target layer as the importance of power service requirements, set the index layer as reliability and real-time, and set the lower target layer as nine classic power services including line protection, protection management system, dispatching telephone, dispatching automation, video conference, conference television, administrative telephone, distribution automation, and SG-EPR service, and number these services in sequence as (=1, 2, 3,..., 9);

[0052] Step 2: Compare the data of each layer in the hierarchical structure model, and generate corresponding reliability requirement judgment matrices and real-time requirement judgment matrices according to the comparison results. The comparison results usually use numerical values from 1 to 9 to represent the importance degree of one service to another service, and numerical values from 1 / 9 to 1 / 3 to represent the unimportance degree of one service to another service. The judgment matrix should satisfy; ;, where, and respectively represent the numbers of two different power services, and. is the importance comparison result. The specific judgment matrix can be as Figure 2 shown;

[0053] Step 3: Perform normalization processing on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively to obtain new matrices after normalization processing, and then perform normalization processing on the new matrices to obtain the quantization values of the business reliability importance and the quantization values of the business real-time importance of the power service. Among them, the normalization processing performed on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively is column-wise normalization processing, and the column-wise normalization processing means dividing each data in the matrix by the sum of the data corresponding to the column.

[0054] Step S202: Obtain the node failure and link failure data in the power service, and determine the calculation formula of the reliability impact quantization value by combining the node failure and link failure data with the quantization value of the business reliability importance.

[0055] Specifically, obtain the data on node failure and link failure in the power service, and determine the calculation formula of the reliability impact quantization value by combining the data with the quantization value of the business reliability importance. The specific calculation formula of the reliability impact quantization value is:

[0056]

[0057] Among them, R(i) is the quantization value of the business reliability importance, is the product of the availabilities of all links on the path through which service i passes, is the product of the availabilities of all nodes on the path through which the service passes;

[0058] The calculation method is:

[0059]

[0060] Among them, is the availability of service i on path j;

[0061] The calculation method is:

[0062]

[0063] Among them, is the failure probability of service i on node k.

[0064] Step S203: Obtain the node delay and link delay data in the power service, and determine the calculation formula of the real-time impact quantization value by combining the node delay and link delay data with the quantization value of the business real-time importance.

[0065] Specifically, obtain data on node delay and link delay in the power business, and combine with the quantization value of service real-time importance to determine the calculation formula for the quantization value of real-time impact. The specific calculation formula for the quantization value of real-time impact is:

[0066]

[0067] Among them, is the quantization value of service real-time importance, is the sum of the total delay of service i on the network node and the total delay of the service on the network link.

[0068] Step S204, when a service request is detected, according to the type of the service request, perform weight allocation for the reliability and real-time of the service request, substitute the weight allocation result into the calculation formula for the quantization value of reliability impact and the calculation formula for the quantization value of real-time impact for addition calculation, and obtain the objective function of the service request.

[0069] Specifically, when a service request is detected, perform weight allocation for the indicators of the services with access requests. For a single service, the sum of the weight x of its reliability requirement and the weight y of its real-time requirement is 1. The specific weight allocation can be performed according to the specific content of the service request. Multiply the corresponding index weights x and y by the calculation formula for the quantization value of reliability impact and the calculation formula for the quantization value of real-time impact respectively, and add the two newly obtained calculation formulas to obtain the objective function. The specific objective function is:

[0070]

[0071] After obtaining the objective function, the objective function can also be normalized. In this embodiment, the maximum-minimum normalization method can be used for normalization, and and are respectively substituted into the following normalization formula for normalization:

[0072]

[0073] The expression of the normalized objective function is:

[0074]

[0075] Step S205, determine the corresponding source node and target node according to the service request, obtain the K paths with the shortest physical link length from the source node to the destination node, obtain the parameters corresponding to the service request and the K paths, substitute the parameters into the objective function, and select the path with the smallest calculation result of the objective function as the final preferred path of the service request.

[0076] Specifically, according to the service request, the source node and the target node corresponding to the service can be determined, and the K paths with the shortest physical link length from the source node to the destination node are obtained. Then, the parameters corresponding to the service request and the K paths are determined, and the parameters are substituted into the objective function for calculation. The path with the smallest result is selected from the calculation results as the final preferred path for the service request.

[0077] A routing planning method for hierarchical requirements of power services in a smart grid provided by an embodiment of the present invention includes: obtaining the power services of the smart grid, and assigning hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment includes the service reliability importance quantization value and the service real-time importance quantization value; obtaining the node failure and link failure data in the power services, and determining the calculation formula of the reliability impact quantization value through the node failure and link failure data in combination with the service reliability importance quantization value. Obtaining the node delay and link delay data in the power services, and determining the calculation formula of the real-time impact quantization value through the node delay and link delay data in combination with the service real-time importance quantization value; when a service request is detected, according to the type of the service request, perform weight allocation for the reliability and real-time of the service request, and substitute the weight allocation result into the calculation formula of the reliability impact quantization value and the calculation formula of the real-time impact quantization value for addition calculation to obtain the objective function of the service request; determine the corresponding source node and target node according to the service request, and obtain the K paths with the shortest physical link length from the source node to the destination node, obtain the parameters corresponding to the service request and the K paths, substitute the parameters into the objective function, and select the path with the smallest calculation result of the objective function as the final preferred path for the service request. In this way, the service requirements can be considered from multiple perspectives of real-time and reliability, and the hierarchical requirements of the service are quantified by the analytic hierarchy process, making the selection of the final preferred path more reliable; and it can perform weight allocation for the reliability and real-time of each service with an access request, and the weight value can be adjusted according to actual needs, improving the accuracy and flexibility of service routing planning.

[0078] Figure 2 A routing planning device for hierarchical requirements of power services in a smart grid provided by an embodiment of the present invention includes: a first acquisition module 101, a second acquisition module 102, a third acquisition module 103, a detection module 104, and a selection module 105, where:

[0079] The first acquisition module 101 is configured to obtain the power services of the smart grid, and assign hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment includes the service reliability importance quantization value and the service real-time importance quantization value.

[0080] The second acquisition module 102 is configured to acquire node failure and link failure data in the power service, and determine a calculation formula for the reliability impact quantization value by combining the node failure and link failure data with the service reliability importance quantization value.

[0081] The third acquisition module 103 is configured to acquire node delay and link delay data in the power service, and determine a calculation formula for the real-time impact quantization value by combining the node delay and link delay data with the service real-time importance quantization value.

[0082] The detection module 104 is configured to, when a service request is detected, perform weight allocation for the reliability and real-time performance of the service request according to the type of the service request, substitute the weight allocation result into the calculation formula for the reliability impact quantization value and the calculation formula for the real-time impact quantization value for addition calculation, and obtain the objective function of the service request.

[0083] The selection module 105 is configured to determine a corresponding source node and target node according to the service request, obtain K paths with the shortest physical link lengths from the source node to the destination node, obtain the parameters corresponding to the service request and the K paths, substitute the parameters into the objective function, and select the path with the smallest calculation result of the objective function as the final preferred path of the service request.

[0084] In one embodiment, the apparatus may further include:

[0085] The model establishment module is configured to establish a hierarchical structure model through the analytic hierarchy process, compare the data of each layer in the hierarchical structure model, and generate a corresponding reliability requirement judgment matrix and real-time requirement judgment matrix according to the comparison result. The hierarchical structure model includes power service requirement degree data in the upper target layer, reliability and real-time data in the index layer, and power service data in the lower target layer;

[0086] The normalization module is configured to perform normalization processing on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively to obtain a new matrix after normalization processing, and perform normalization processing on the new matrix to obtain the service reliability importance quantization value and the service real-time importance quantization value of the power service.

[0087] In one embodiment, the apparatus may further include:

[0088] The column-wise normalization module is configured to perform column-wise normalization processing on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively. The column-wise normalization processing means dividing each data in the matrix by the column-wise sum corresponding to the data.

[0089] For the specific limitations of the routing planning device for the hierarchical requirements of power grid power services, reference can be made to the limitations of the routing planning method for the hierarchical requirements of power grid power services in the above text, which will not be elaborated here. Each module in the above routing planning device for the hierarchical requirements of power grid power services can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0090] Figure 3 An entity structure diagram of an electronic device is exemplified, as Figure 3 shown. The electronic device may include: a processor 301, a memory 302, a communication interface 303, and a communication bus 304. Among them, the processor 301, the memory 302, and the communication interface 303 complete mutual communication through the communication bus 304. The processor 301 can call the logical instructions in the memory 302 to execute the following method: obtain the power services of the smart grid, and assign hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment includes the quantified value of service reliability importance and the quantified value of service real-time importance; obtain the node failure and link failure data in the power services, and determine the calculation formula of the reliability impact quantified value through the node failure and link failure data in combination with the quantified value of service reliability importance; obtain the node delay and link delay data in the power services, and determine the calculation formula of the real-time impact quantified value through the node delay and link delay data in combination with the quantified value of service real-time importance; when a service request is detected, perform the weight allocation of the reliability and real-time of the service request according to the type of the service request, substitute the weight allocation result into the calculation formula of the reliability impact quantified value and the calculation formula of the real-time impact quantified value for addition calculation to obtain the objective function of the service request; determine the corresponding source node and target node according to the service request, obtain the K paths with the shortest physical link length from the source node to the destination node, obtain the parameters corresponding to the service request and the K paths, substitute the parameters into the objective function, and select the path with the smallest calculation result of the objective function as the final preferred path of the service request.

[0091] In addition, when the logical instructions in the above-mentioned memory 302 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0092] On the other hand, an embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it is configured to execute the transmission method provided in the above-mentioned various embodiments. For example, it includes: obtaining the power services of the smart grid, and assigning hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment includes the quantization value of service reliability importance and the quantization value of service real-time importance; obtaining the node failure and link failure data in the power service, and determining the calculation formula of the reliability impact quantization value by combining the node failure and link failure data with the quantization value of service reliability importance; obtaining the node delay and link delay data in the power service, and determining the calculation formula of the real-time impact quantization value by combining the node delay and link delay data with the quantization value of service real-time importance; when a service request is detected, performing weight allocation for the reliability and real-time of the service request according to the type of the service request, substituting the weight allocation result into the calculation formula of the reliability impact quantization value and the calculation formula of the real-time impact quantization value for addition calculation to obtain the objective function of the service request; determining the corresponding source node and target node according to the service request, obtaining the K paths with the shortest physical link lengths from the source node to the destination node, obtaining the parameters corresponding to the service request and the K paths, substituting the parameters into the objective function, and selecting the path with the smallest calculation result of the objective function as the final preferred path of the service request.

[0093] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative work.

[0094] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A routing planning method for hierarchical requirements of power grid power services, characterized in that, Including: Obtain the power services of the smart grid, and assign hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment includes the quantified value of service reliability importance and the quantified value of service real-time importance; Obtain the node failure and link failure data in the power service. Through the node failure and link failure data, combined with the quantified value of service reliability importance, determine the calculation formula for the quantified value of reliability impact; Obtain the node delay and link delay data in the power service. Through the node delay and link delay data, combined with the quantified value of service real-time importance, determine the calculation formula for the quantified value of real-time impact; When a service request is detected, according to the type of the service request, perform weight allocation for the reliability and real-time of the service request, and substitute the weight allocation result into the calculation formula for the quantified value of reliability impact and the calculation formula for the quantified value of real-time impact for addition calculation to obtain the objective function of the service request; Determine the corresponding source node and target node according to the service request, and obtain the K paths with the shortest physical link length from the source node to the target node. Obtain the parameters corresponding to the service request and the K paths, substitute the parameters into the objective function, and select the path with the smallest calculation result of the objective function as the final preferred path of the service request; The process of assigning hierarchical importance values to the reliability requirements and real-time requirements of the power service through the analytic hierarchy process includes: Establish a hierarchical structure model through the analytic hierarchy process, compare the data of each layer in the hierarchical structure model, and generate a corresponding reliability requirement judgment matrix and real-time requirement judgment matrix according to the comparison result. The hierarchical structure model includes the power service requirement degree data in the upper target layer, the reliability and real-time data in the index layer, and the power service data in the lower target layer; Perform normalization processing on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively to obtain a new matrix after normalization processing, and perform normalization processing on the new matrix to obtain the quantified value of service reliability importance and the quantified value of service real-time importance of the power service; The process of performing normalization processing on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively includes: Perform column normalization processing on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively. The column normalization processing means dividing each data in the matrix by the sum of the corresponding columns; The calculation formula for the quantified value of reliability impact includes: where R(i) is the quantified value of the business reliability importance degree, which is the product of the availabilities of all the links on the path through which Service i passes, and which is the product of the availabilities of all the nodes on the path through which the service passes; The calculation method is as follows: Among them, is the availability of service i on path j; The said The calculation method is as follows: Among them, is the failure probability of service i on node k.

2. The routing planning method for the hierarchical requirements of power grid power services according to claim 1, wherein The calculation formula for the quantified value of real-time impact includes: Among them, is the quantization value of the importance of business real-time performance, is the sum of the total delay of service i on the network node and the total delay of the service on the network link.

3. A routing planning device for the hierarchical requirements of power grid power services, characterized in that, The device includes: The first acquisition module is used to obtain the power services of the smart grid, and assign hierarchical importance values to the reliability requirements and real-time requirements of the power services through the analytic hierarchy process. The hierarchical importance assignment includes the quantified value of service reliability importance and the quantified value of service real-time importance; A second acquisition module, configured to acquire node failure and link failure data in the power service, and determine a calculation formula for a reliability impact quantification value based on the node failure and link failure data in combination with the service reliability importance quantification value; A third acquisition module, configured to acquire node delay and link delay data in the power service, and determine a calculation formula for a real-time impact quantification value based on the node delay and link delay data in combination with the service real-time importance quantification value; A detection module, configured to, when detecting a service request, perform weight allocation for the reliability and real-time performance of the service request according to the type of the service request, substitute the weight allocation result into the calculation formula for the reliability impact quantification value and the calculation formula for the real-time impact quantification value for addition calculation, and obtain an objective function of the service request; A selection module, configured to determine a corresponding source node and target node according to the service request, acquire K paths with the shortest physical link length from the source node to the destination node, acquire parameters corresponding to the service request and the K paths, substitute the parameters into the objective function, and select the path with the smallest calculation result of the objective function as the final preferred path of the service request; A model establishment module, configured to establish a hierarchical structure model through the analytic hierarchy process, compare data at each level in the hierarchical structure model, and generate a corresponding reliability requirement judgment matrix and real-time requirement judgment matrix according to the comparison result, where the hierarchical structure model includes power service requirement degree data at the upper target layer, reliability and real-time data at the index layer, and power service data at the lower target layer; A normalization module, configured to perform normalization processing on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively to obtain a new matrix after the normalization processing, and perform normalization processing on the new matrix to obtain the service reliability importance quantification value and the service real-time importance quantification value of the power service; A column-wise normalization module, configured to perform column-wise normalization processing on the reliability requirement judgment matrix and the real-time requirement judgment matrix respectively, where the column-wise normalization processing means dividing each data in the matrix by the sum of the data corresponding to the column; The calculation formula for the reliability impact quantification value includes: where R(i) is the quantified value of the business reliability importance degree, which is the product of the availabilities of all links on the path through which Service i passes, and which is the product of the availabilities of all nodes on the path through which the service passes; The calculation method is as follows: Among them, is the availability of service i on path j; The said calculation method is as follows: Among them, is the failure probability of service i on node k.

4. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, the steps of the routing planning method for hierarchical requirements of power services for the smart grid according to any one of claims 1 to 2 are implemented.

5. A non-transitory computer-readable storage medium storing a computer program thereon, characterized in that, When the computer program is executed by the processor, the steps of the routing planning method for hierarchical requirements of power services for the smart grid according to any one of claims 1 to 2 are implemented.

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