Power business dual routing planning method and device

Abstract

The present invention provides a method and device for dual-route planning of electric power services, the method comprising: obtaining network topology information and information of services to be planned, determining the routing path between the source node and the destination node of the services to be planned; determining the risk value, delay information and the intersection degree of the primary and backup routes of the services to be planned according to the network topology information, the information of services to be planned and the routing path; constructing a joint optimization model of primary and backup routes according to the risk value, the delay information and the intersection degree of the primary and backup routes; solving the joint optimization model of primary and backup routes based on an improved ant colony algorithm to obtain the primary and backup routing paths. The present invention introduces the intersection degree of primary and backup routes to characterize the overlap between primary and backup routes, reduce the possibility of high similarity between primary and backup routes, enable the backup route to complete the route switching more stably when the primary route fails, and reduce the risk that the backup route after the route switching cannot bear the service transmission.

Description

Technical Field

[0001] The present invention relates to the field of power communication technology, and in particular to a method and device for dual-route planning of power services. Background Art

[0002] Key power services such as system protection and control in the power communication network need to design effective protection solutions, which can quickly switch services in the event of network failures to achieve continuous and stable service transmission. Therefore, dual routing configuration should be performed for key power production services. Usually, the dual routing algorithm is to establish two node or link non-intersecting or nearly non-intersecting routing paths between the service source and destination node pairs, one of which is the working route and the other is the backup route. After a failure occurs, the route switching is used to ensure continuous service transmission. Compared with the single routing method, the dual routing configuration method is of great significance to improving service transmission reliability and reducing network congestion.

[0003] However, the current dual routing algorithm may cause the primary and backup routing paths to be highly similar, and there is a risk that the primary routing fails and the backup routing cannot bear the risk of business transmission. Summary of the invention

[0004] The present invention provides a method and device for dual-route planning of electric power services, which are used to solve the defect in the prior art that the dual-route algorithm may cause the primary and backup routing paths to be highly similar, and there is a risk that the primary routing fails and the backup routing cannot bear the risk of service transmission.

[0005] The present invention provides a method for dual-route planning of electric power services, comprising:

[0006] Obtain network topology information and information about the service to be planned, and determine the routing path between the source node and the destination node of the service to be planned;

[0007] Determine, according to the network topology information, the service information to be planned and the routing path, the risk value, delay information and the intersection degree of the primary and backup routes of the service to be planned, wherein the intersection degree of the primary and backup routes is used to characterize the overlap between the primary and backup routes;

[0008] Constructing a primary and backup route joint optimization model according to the risk value, the delay information and the primary and backup route intersection degree;

[0009] The primary and backup routing joint optimization model is solved based on an improved ant colony algorithm to obtain primary and backup routing paths, wherein an inspiration factor of the improved ant colony algorithm is determined based on the risk value and the delay information.

[0010] According to a dual routing planning method for electric power business provided by the present invention, the risk value is determined based on the node risk value and the link risk value, wherein the node risk value is determined based on the sum of the node failure probability, the node importance and the node's business importance, and the link risk value is determined based on the sum of the link failure probability, the link importance and the link's business importance.

[0011] According to a dual-route planning method for electric power services provided by the present invention, the intersection degree of the primary and backup routes is determined based on the number of public links, the total number of links, the number of public nodes and the total number of nodes in the primary and backup routes of the services to be planned.

[0012] According to a dual-route planning method for electric power services provided by the present invention, a primary-backup route joint optimization model is constructed according to the risk value, the delay information and the primary-backup route intersection degree, including:

[0013] Acquire the deterministic delay of the service to be planned, and obtain a main routing objective function according to the deterministic delay, the risk value and the delay information;

[0014] Obtaining a backup route objective function according to the deterministic delay, the risk value, the delay information and the intersection degree of the primary and backup routes;

[0015] According to the primary route objective function and the backup route objective function, a primary and backup route joint optimization model is obtained, wherein the constraint conditions of the primary and backup route joint optimization model include bandwidth constraint and delay constraint.

[0016] According to a dual-route planning method for electric power business provided by the present invention, the pheromone update formula of the improved ant colony algorithm is determined based on the total time used by ants in the current traversal.

[0017] According to a dual-route planning method for electric power services provided by the present invention, the method of solving the primary and backup route joint optimization model based on an improved ant colony algorithm to obtain the primary and backup route paths includes:

[0018] The primary and backup routing joint optimization model is solved based on the improved ant colony algorithm to obtain the optimal and suboptimal primary and backup routing paths.

[0019] The present invention also provides a dual-route planning device for electric power services, comprising:

[0020] A routing path determination module is used to obtain network topology information and information of the service to be planned, and determine the routing path between the source node and the destination node of the service to be planned;

[0021] A model building module, used to determine the risk value, delay information and primary and backup route intersection of the service to be planned according to the network topology information, the service information to be planned and the routing path, and to build a primary and backup route joint optimization model according to the risk value, the delay information and the primary and backup route intersection; wherein the primary and backup route intersection is used to characterize the overlap between the primary and backup routes;

[0022] The model solving module is used to solve the primary and backup routing joint optimization model based on the improved ant colony algorithm to obtain the primary and backup routing paths, wherein the heuristic factor of the improved ant colony algorithm is determined based on the risk value and the delay information.

[0023] The present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the dual routing planning method for electric power services as described in any one of the above is implemented.

[0024] The present invention also 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 dual-route planning method for electric power services as described in any one of the above is implemented.

[0025] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the dual routing planning method for electric power services as described in any one of the above is implemented.

[0026] The electric power business dual-route planning method and device provided by the present invention introduce the intersection degree of the primary and backup routes to characterize the overlap between the primary and backup routes, thereby reducing the possibility of high similarity between the primary and backup routes, so that the backup route can complete route switching more stably when the primary route fails, thereby reducing the risk that the backup route after route switching cannot bear business transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 It is a flow chart of the dual-route planning method for electric power business provided by the present invention;

[0029] Figure 2 It is a flow chart of constructing a primary-backup routing joint optimization model provided by the present invention;

[0030] Figure 3It is a block diagram of the dual-route planning device for electric power business provided by the present invention;

[0031] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] In the description of the embodiments of the present application, it should be noted that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, which are only for the convenience of describing the embodiments of the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the embodiments of the present application. In addition, the terms "first", "second", and "third" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0034] In the description of the embodiments of the present application, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the embodiments of the present application can be understood according to specific circumstances.

[0035] In the embodiments of the present application, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0036] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiments of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0037] Figure 1 is a flow chart of the dual routing planning method for power business provided by the present invention, referring to Figure 1 The present invention provides a dual-route planning method for electric power services, comprising:

[0038] S110, acquiring network topology information and information of the service to be planned, and determining a routing path between a source node and a destination node of the service to be planned;

[0039] S120, determining a risk value, latency information, and a primary / backup route intersection degree of the service to be planned according to the network topology information, the service information to be planned, and the routing path, wherein the primary / backup route intersection degree is used to characterize an overlap degree between the primary / backup routes;

[0040] S130, constructing a primary and backup route joint optimization model according to the risk value, the delay information and the primary and backup route intersection degree;

[0041] S140, solving the primary and backup routing joint optimization model based on an improved ant colony algorithm to obtain primary and backup routing paths, wherein a heuristic factor of the improved ant colony algorithm is determined based on the risk value and the delay information.

[0042] In step S110 , the network topology information is an abstraction of the physical structure of the network, which can be represented in the form of an undirected graph, including a set of nodes in the network and a set of edges in the network.

[0043] In one embodiment, the network topology information can be expressed as G = (V, E), where the set of nodes in the network can be expressed as V = {v1, v2, ..., v n}, n is the total number of nodes; the set of edges in the network can be expressed as E = {e1, e2, …, e m}, m is the total number of edges.

[0044] The information of the services to be planned includes a set of services to be planned, a set of service importances corresponding to the services to be planned, and a deterministic delay corresponding to the services to be planned. The deterministic delay is a time interval determined by a minimum delay and a maximum delay.

[0045] In one embodiment, the service set to be planned can be expressed as S = {s1, s2, ..., s l}, l is the total number of services to be planned; the service importance set corresponding to the services to be planned can be expressed as W = {w1,w2,…,w l}.

[0046] s k represents the kth service to be planned, 1≤k≤l, and the service importance is w k , the deterministic latency of the service is The business can be represented as a two-tuple and Respectively represent business k The source node and destination node of

[0047] Business k The routing path between the source node and the destination node can be expressed as p k , the main routing path is The alternate routing path is

[0048] In step S120, the risk value of the service to be planned is related to the service node risk and the service link risk, and a lower value indicates a lower current service risk value.

[0049] In one embodiment, the risk value is at least related to the failure rate of nodes and links corresponding to the routing path.

[0050] In one embodiment, the delay information represents the delay of the service to be planned, which is determined based on the propagation delay of the link and the delay on the node.

[0051] The intersection degree of primary and backup routes is used to characterize the overlap between primary and backup routes. When allocating routes for each service, it is necessary to consider reasonable backup routes at the same time. When a node or link on the primary route path fails, the backup route should complete the route switching in time. Therefore, in order to reduce the risk after route switching, the node and link overlap between the backup route and the primary route should be as low as possible.

[0052] In one embodiment, the primary-backup route intersection degree is determined by at least one of the coincidence degree of nodes and the coincidence degree of links in the routing path.

[0053] In step S130, the primary and backup route joint optimization model is a dual-objective joint optimization mathematical model, and at least two factors are selected from the risk value, the delay information and the primary and backup route intersection to construct an objective function, and the optimization goal is to minimize the objective functions at the same time.

[0054] In step S140, the embodiment of the present application improves the heuristic factor of the original ant colony algorithm, and the improved ant colony algorithm can meet the solution requirements of the above model.

[0055] It can be understood that the embodiment of the present application introduces the intersection degree of the primary and backup routes to characterize the overlap between the primary and backup routes, reduce the possibility of high similarity between the primary and backup routes, and enable the backup route to complete the route switching more stably when the primary route fails, thereby reducing the risk that the backup route after the route switching cannot bear the business transmission; in addition, by improving the heuristic factor of the original ant colony algorithm, the solution requirements of the model are met and the accuracy of the solution results is improved.

[0056] Based on the above embodiments, as an optional embodiment, the risk value is determined based on the node risk value and the link risk value, wherein the node risk value is determined based on the sum of the node failure probability, the node importance and the node's business importance, and the link risk value is determined based on the sum of the link failure probability, the link importance and the link's business importance.

[0057] Optionally, set business s k The risk value is expressed as SR k , the node risk value is expressed as The link risk value is expressed as The lower the value, the lower the risk of the current node and link.

[0058] In one embodiment, the risk value is calculated as follows:

[0059]

[0060] Among them, v i Represents the routing path p k The i-th node in e i,j represents the link from node i to node j.

[0061] In one embodiment, the node risk value is determined based on the sum of the node failure probability, the node importance and the node business importance, and the calculation formula is as follows:

[0062]

[0063] in, For node v i The failure probability of node v in one year iThe ratio of failure time to the total time in a year.

[0064] For node v i The importance of a node can be reflected by the voltage level of the node in the power network.

[0065] is the current node v i The sum of the importance of existing services on the node indicates that the higher the sum of the importance of services carried on the current node, the higher the risk value of the current node.

[0066] Optional, The calculation formula is:

[0067]

[0068] in, are the maximum and minimum voltages in the nodes, respectively. For node v i Voltage value.

[0069] In one embodiment, the link risk value is determined based on the sum of the link failure probability, the importance of the link, and the business importance of the link, and the calculation formula is as follows:

[0070]

[0071] in, Link e i,j The failure probability of link e in one year is i,j The ratio of failure time to the whole year time.

[0072] Link e i,j The importance of power grid can be reflected by the voltage level of the link in the power grid.

[0073] For the current link e i,j The sum of the importance of existing services on the link is obtained. It can be seen that the higher the sum of the importance of services carried on the current link, the higher the risk value of the current link.

[0074] Optional, The calculation formula is:

[0075]

[0076] in are the maximum and minimum voltage in the link respectively. is the voltage value of the current link.

[0077] It can be understood that the embodiment of the present application determines the node risk value and the link risk value, and constructs a risk value model by combining the business importance, node and link failure rate and importance, to solve the primary and backup paths that minimize the business risk and meet the deterministic delay requirements, so as to improve the reliability of business operations.

[0078] Based on the above embodiment, as an optional embodiment, the intersection degree of the primary and backup routes is determined based on the number of public links, the total number of links, the number of public nodes and the total number of nodes in the primary and backup routes of the service to be planned.

[0079] The calculation formula for the intersection degree of the primary and backup routes is:

[0080]

[0081] in and Business k The number of common links and the total number of links in the primary and backup routes. and Business k The number of common nodes and total number of nodes in the primary and backup routers.

[0082] It can be understood that the embodiment of the present application introduces a primary-backup correlation model to minimize the link and node overlap between the primary and backup routes, so that the backup route can complete route switching more stably when the primary route fails, thereby reducing the risk after route switching.

[0083] Based on the above embodiment, as an optional embodiment, Figure 2 As shown, the primary and backup routes joint optimization model is constructed according to the risk value, the delay information and the primary and backup routes intersection degree, including:

[0084] S210, obtaining the deterministic delay of the service to be planned, and obtaining a main routing objective function according to the deterministic delay, the risk value and the delay information;

[0085] S220, obtaining a backup route objective function according to the deterministic delay, the risk value, the delay information and the intersection degree of the primary and backup routes;

[0086] S230, obtaining a primary and backup routing joint optimization model according to the primary routing objective function and the backup routing objective function, wherein the constraint conditions of the primary and backup routing joint optimization model include bandwidth constraint and delay constraint.

[0087] In one embodiment, the delay information is service s k The delay is calculated as follows:

[0088]

[0089] in, represents the propagation delay on the link, N represents the number of nodes on the link, represents the sending delay on the node, represents the processing delay on the node, represents the queuing delay on the node, The calculation formula is:

[0090]

[0091] Len k For path p k The total length of the link is , and c is the speed of light.

[0092] In step S210, the main routing objective function can be expressed as:

[0093]

[0094] In step S220, the backup route objective function can be expressed as:

[0095]

[0096] In step S230, the optimization goal of the primary-backup route joint optimization model is to minimize the primary route objective function and the backup route objective function at the same time.

[0097] In one embodiment, the bandwidth constraint:

[0098]

[0099] b k Indicates business k The occupied bandwidth, F ij Represents the remaining bandwidth capacity of edge (i, j).

[0100] In one embodiment, the latency constraint:

[0101]

[0102] T k For business k The delay, For the preset business k The minimum delay allowed, For the preset business k The maximum delay allowed.

[0103] It can be understood that the embodiment of the present application builds a joint optimization model based on the business routing risk value and the business deterministic delay requirement, introduces the correlation between the primary and backup routes, and proposes a risk-aware dual routing planning model, which can reduce the risk of the primary route failing and the backup route being unable to bear the risk of business transmission.

[0104] Based on the above embodiment, as an optional embodiment, the pheromone update formula of the improved ant colony algorithm is determined based on the total time used by the ants in the current traversal.

[0105] It can be understood that the embodiment of the present application improves the pheromone update formula in the original ant colony algorithm, and the improved ant colony algorithm can meet the solution requirements of the model proposed in this application and improve the accuracy of the solution.

[0106] Based on the above embodiment, as an optional embodiment, solving the primary and backup routing joint optimization model based on the improved ant colony algorithm to obtain the primary and backup routing paths includes:

[0107] The primary and backup routing joint optimization model is solved based on the improved ant colony algorithm to obtain the optimal and suboptimal primary and backup routing paths.

[0108] It can be understood that the embodiment of the present application takes into account the situation where none of the input routing paths meet the preset requirements, and obtains the optimal and suboptimal primary and backup routing solutions at the same time, ensuring the continuous and reliable transmission of the business and improving the utilization rate of network resources.

[0109] The following is a specific description of the solution process of the improved ant algorithm using an embodiment, which is not limited in the present application.

[0110] For business k , the specific solution process of the improved ant colony algorithm is as follows:

[0111] Step 1: Parameter initialization. Set the initial parameters: total number of ants M, pheromone intensity τ on edge (i, j) i,j , information heuristic factor α, expectation heuristic factor β, maximum number of loops N cmax , pheromone intensity Q, pheromone volatility coefficient ρ.

[0112] Step 2: Randomly place M ants at different nodes in the network.

[0113] Step 3: The probability of ant k is calculated as follows: Select the next node to move forward:

[0114]

[0115]

[0116]

[0117] Where a k is the set of nodes that ant k can choose in the next step, η i,j is the heuristic factor for node i to transfer to node j, and is the risk value of node i and edge (i, j), T i,j is the time it takes for node i to transfer to node j, l i,j is the distance between node i and node j, and is the sending delay, processing delay and queuing delay of node i.

[0118] Step 4: Repeat step 3 until all M ants generate a path.

[0119] Step 5: Update the pheromone on each edge in the network. The pheromone on edge (i, j) is updated as follows:

[0120]

[0121]

[0122] In the formula is the pheromone increment of ant k on edge (i, j) in this cycle, T k is the total time used by ant k in this traversal.

[0123] Step 6: Loop through steps 2 to 5 until the number of iterations reaches the specified number N. cmax Or no better solution appears after several consecutive iterations.

[0124] Step 7: Based on the pheromone concentration on each edge of the network and the business s k The source node and destination node Select the main routing path that optimizes the main routing objective function.

[0125] Step 8: Based on the main routing path selected in step 7, the pheromone concentration on each edge of the network and the business s k The source node and destination node Select an alternate routing path that optimizes the alternate routing objective function.

[0126] It can be understood that the heuristic factor in the original ant colony algorithm is defined as the inverse of the distance between node i and node j. This heuristic factor can be used to find the shortest path. However, the model proposed in this application comprehensively considers node risk, link risk and deterministic delay. The original heuristic factor definition cannot meet the solution requirements of the model proposed in this application. Therefore, the definition of the heuristic factor in the original ant colony algorithm is improved, and the heuristic factor definition is improved to the inverse of the product of three elements: node risk, link risk and delay. At the same time, the pheromone update formula in the original ant colony algorithm is improved. The improved ant colony algorithm can meet the solution requirements of the model proposed in this application and improve the accuracy of the solution.

[0127] The power service dual-route planning device provided by the present invention is described below. The power service dual-route planning device described below and the power service dual-route planning method described above can be referenced to each other.

[0128] Figure 3 is a block diagram of the dual-route planning device for electric power business provided by the present invention, referring to Figure 3 The present invention also provides a dual-route planning device for electric power services, comprising:

[0129] The routing path determination module 310 is used to obtain network topology information and information of the service to be planned, and determine the routing path between the source node and the destination node of the service to be planned;

[0130] The model building module 320 is used to determine the risk value, delay information and the intersection degree of the primary and backup routes of the service to be planned according to the network topology information, the service information to be planned and the routing path, and to build a primary and backup route joint optimization model according to the risk value, the delay information and the intersection degree of the primary and backup routes; wherein the primary and backup route intersection degree is used to characterize the overlap between the primary and backup routes;

[0131] The model solving module 330 is used to solve the primary and backup routing joint optimization model based on the improved ant colony algorithm to obtain the primary and backup routing paths, wherein the heuristic factor of the improved ant colony algorithm is determined based on the risk value and the delay information.

[0132] In one embodiment, the risk value is determined based on a node risk value and a link risk value, wherein the node risk value is determined based on the sum of the node failure probability, the node importance and the node's business importance, and the link risk value is determined based on the sum of the link failure probability, the link importance and the link's business importance.

[0133] In one embodiment, the intersection degree of the primary and backup routes is determined based on the number of common links, the total number of links, the number of common nodes and the total number of nodes in the primary and backup routes of the service to be planned.

[0134] In one embodiment, the model building module 320 is further configured to:

[0135] Acquire the deterministic delay of the service to be planned, and obtain a main routing objective function according to the deterministic delay, the risk value and the delay information;

[0136] Obtaining a backup route objective function according to the deterministic delay, the risk value, the delay information and the intersection degree of the primary and backup routes;

[0137] According to the primary route objective function and the backup route objective function, a primary and backup route joint optimization model is obtained, wherein the constraint conditions of the primary and backup route joint optimization model include bandwidth constraint and delay constraint.

[0138] In one embodiment, the pheromone update formula of the improved ant colony algorithm is determined based on the total time used by the ants in the current traversal.

[0139] In one embodiment, solving the primary and backup routing joint optimization model based on the improved ant colony algorithm to obtain the primary and backup routing paths includes:

[0140] The primary and backup routing joint optimization model is solved based on the improved ant colony algorithm to obtain the optimal and suboptimal primary and backup routing paths.

[0141] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communication interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the power service dual routing planning method, including:

[0142] Obtain network topology information and information about the service to be planned, and determine the routing path between the source node and the destination node of the service to be planned;

[0143] Determine, according to the network topology information, the service information to be planned and the routing path, the risk value, delay information and the intersection degree of the primary and backup routes of the service to be planned, wherein the intersection degree of the primary and backup routes is used to characterize the overlap between the primary and backup routes;

[0144] Constructing a primary and backup route joint optimization model according to the risk value, the delay information and the primary and backup route intersection degree;

[0145] The primary and backup routing joint optimization model is solved based on an improved ant colony algorithm to obtain primary and backup routing paths, wherein an inspiration factor of the improved ant colony algorithm is determined based on the risk value and the delay information.

[0146] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0147] On the other hand, the present invention further provides a computer program product, the computer program product comprising a computer program, the computer program can be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer can execute the power service dual routing planning method provided by the above methods, including:

[0148] Obtain network topology information and information about the service to be planned, and determine the routing path between the source node and the destination node of the service to be planned;

[0149] Determine, according to the network topology information, the service information to be planned and the routing path, the risk value, delay information and the intersection degree of the primary and backup routes of the service to be planned, wherein the intersection degree of the primary and backup routes is used to characterize the overlap between the primary and backup routes;

[0150] Constructing a primary and backup route joint optimization model according to the risk value, the delay information and the primary and backup route intersection degree;

[0151] The primary and backup routing joint optimization model is solved based on an improved ant colony algorithm to obtain primary and backup routing paths, wherein an inspiration factor of the improved ant colony algorithm is determined based on the risk value and the delay information.

[0152] In another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which is implemented when the computer program is executed by a processor to execute the power service dual routing planning method provided by the above methods, including:

[0153] Obtain network topology information and information about the service to be planned, and determine the routing path between the source node and the destination node of the service to be planned;

[0154] Determine, according to the network topology information, the service information to be planned and the routing path, the risk value, delay information and the intersection degree of the primary and backup routes of the service to be planned, wherein the intersection degree of the primary and backup routes is used to characterize the overlap between the primary and backup routes;

[0155] Constructing a primary and backup route joint optimization model according to the risk value, the delay information and the primary and backup route intersection degree;

[0156] The primary and backup routing joint optimization model is solved based on an improved ant colony algorithm to obtain primary and backup routing paths, wherein an inspiration factor of the improved ant colony algorithm is determined based on the risk value and the delay information.

[0157] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0158] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method 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 this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for 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.

[0159] 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 it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A dual-route planning method for electric power services, characterized in that: include: Obtain network topology information and information about the service to be planned, and determine the routing path between the source node and the destination node of the service to be planned; Determine the risk value, delay information and primary and backup route intersection of the service to be planned according to the network topology information, the service information to be planned and the routing path, wherein the primary and backup route intersection is used to characterize the overlap between the primary and backup routes; the risk value is determined based on the node risk value and the link risk value; Constructing a primary and backup route joint optimization model according to the risk value, the delay information and the primary and backup route intersection degree; Solving the primary and backup routing joint optimization model based on an improved ant colony algorithm to obtain primary and backup routing paths, wherein an inspiration factor of the improved ant colony algorithm is determined based on the risk value and the delay information, and the inspiration factor is defined as the inverse of the product of three elements: node risk, link risk, and delay; The constructing a primary and backup route joint optimization model according to the risk value, the delay information and the primary and backup route intersection degree includes: Acquire the deterministic delay of the service to be planned, and obtain a main routing objective function according to the deterministic delay, the risk value and the delay information; The main routing objective function is expressed as: in, is the main routing objective function, SR k For business k The risk value, T k For business k The delay, For business k The maximum delay of For business k Minimum delay Obtaining a backup route objective function according to the deterministic delay, the risk value, the delay information and the intersection degree of the primary and backup routes; The backup routing objective function is expressed as: in, is the backup routing objective function, For business k The intersection degree of the primary and backup routes; According to the primary route objective function and the backup route objective function, a primary and backup route joint optimization model is obtained, wherein the constraint conditions of the primary and backup route joint optimization model include bandwidth constraint and delay constraint; The risk value is determined based on the node risk value and the link risk value, wherein the node risk value is determined based on the sum of the node failure probability, the node importance and the node business importance, and the link risk value is determined based on the sum of the link failure probability, the link importance and the link business importance; The calculation formula of node risk value is as follows: in, For node v i The failure probability of node v in one year i The ratio of failure time to the whole year time; For node v i The importance of the node, which is reflected by the voltage level of the node in the power network; is the current node v i The sum of the importance of existing services on the node. The higher the sum of the importance of services carried on the current node, the higher the risk value of the current node. The calculation formula of link risk value is as follows: in, Link e i,j The failure probability of link e in one year is i,j The ratio of failure time to the whole year time; Link e i,j The importance of the link, which is reflected by the voltage level of the link in the power network; For the current link e i,j The higher the sum of the importance of the services carried on the current link, the higher the risk value of the current link.

2. The dual-route planning method for electric power services according to claim 1, characterized in that: The intersection degree of the primary and backup routes is determined based on the number of public links, the total number of links, the number of public nodes and the total number of nodes in the primary and backup routes of the service to be planned.

3. The dual-route planning method for electric power services according to claim 1, characterized in that: The pheromone update formula of the improved ant colony algorithm is determined based on the total time used by the ants in the current traversal.

4. The dual-route planning method for electric power services according to claim 1, characterized in that: The method of solving the primary and backup routing joint optimization model based on the improved ant colony algorithm to obtain the primary and backup routing paths includes: The primary and backup routing joint optimization model is solved based on the improved ant colony algorithm to obtain the optimal and suboptimal primary and backup routing paths.

5. A dual-route planning device for electric power business, characterized in that: include: A routing path determination module is used to obtain network topology information and information of the service to be planned, and determine the routing path between the source node and the destination node of the service to be planned; A model building module is used to determine the risk value, delay information and the intersection degree of the primary and backup routes of the service to be planned according to the network topology information, the service information to be planned and the routing path, and to build a primary and backup route joint optimization model according to the risk value, the delay information and the intersection degree of the primary and backup routes; wherein the primary and backup route intersection degree is used to characterize the overlap between the primary and backup routes; and the risk value is determined based on the node risk value and the link risk value; A model solving module, used for solving the primary-backup routing joint optimization model based on an improved ant colony algorithm to obtain a primary-backup routing path, wherein an inspiration factor of the improved ant colony algorithm is determined based on the risk value and the delay information, and the inspiration factor is defined as the reciprocal of the product of three elements: node risk, link risk and delay; The constructing a primary and backup route joint optimization model according to the risk value, the delay information and the primary and backup route intersection degree includes: Acquire the deterministic delay of the service to be planned, and obtain a main routing objective function according to the deterministic delay, the risk value and the delay information; The main routing objective function is expressed as: in, is the main routing objective function, SR k For business k The risk value, T k For business k The delay, For business k The maximum delay of For business k Minimum delay Obtaining a backup route objective function according to the deterministic delay, the risk value, the delay information and the intersection degree of the primary and backup routes; The backup routing objective function is expressed as: in, is the backup routing objective function, For business k The intersection degree of the primary and backup routes; According to the primary route objective function and the backup route objective function, a primary and backup route joint optimization model is obtained, wherein the constraint conditions of the primary and backup route joint optimization model include bandwidth constraint and delay constraint; The risk value is determined based on the node risk value and the link risk value, wherein the node risk value is determined based on the sum of the node failure probability, the node importance and the node business importance, and the link risk value is determined based on the sum of the link failure probability, the link importance and the link business importance; The calculation formula of node risk value is as follows: in, For node v i The failure probability of node v in one year i The ratio of failure time to the whole year time; For node v i The importance of the node, which is reflected by the voltage level of the node in the power network; is the current node v i The sum of the importance of existing services on the node. The higher the sum of the importance of services carried on the current node, the higher the risk value of the current node. The calculation formula of link risk value is as follows: in, Link e i,j The failure probability of link e in one year is i,j The ratio of failure time to the whole year time; Link e i,j The importance of the link, which is reflected by the voltage level of the link in the power network; For the current link e i,j The higher the sum of the importance of the services carried on the current link, the higher the risk value of the current link.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the dual routing planning method for electric power services as described in any one of claims 1 to 4 is implemented.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the dual routing planning method for electric power services as described in any one of claims 1 to 4 is implemented.

8. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the dual routing planning method for electric power services as described in any one of claims 1 to 4 is implemented.

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