Communication routing optimization method, system and device applicable to power distribution network

Abstract

The present invention relates to the field of wireless communication network technology, and specifically to a communication route optimization method, system, and device suitable for a power distribution network. The method comprises: determining abnormal nodes in the power distribution network nodes by utilizing the disconnection duration of the power distribution network nodes and the degree of data deviation therein; determining the degree of impact of the routing failure on the abnormal node by utilizing the sequence of unresponsive communications in the node path of the abnormal node; determining the routing priority of the abnormal node and obtaining the preferred order of the power distribution network nodes by utilizing the degree of impact of the routing failure; and determining the target routing connection in the power distribution network by utilizing the preferred order of the power distribution network nodes. Based on the above-mentioned main technical means in the present invention, the present invention can more accurately and efficiently select the routing connection of the better distribution network nodes, thereby realizing efficient communication of the power distribution network.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication networks, and in particular to a communication route optimization method, system and device applicable to a power distribution network. Background Art

[0002] With the development of smart grids and the improvement of power system automation, distribution network communication routing optimization is crucial for ensuring power system security and stability, improving maintenance efficiency, reducing maintenance costs, and enhancing power safety. In smart distribution networks, real-time and reliable information acquisition is a key factor in the stable transmission of power. Wireless sensor networks, with their unique low power consumption, rapid self-organization, and superior interoperability, are considered to have broad application prospects in remote monitoring, fault diagnosis, and wireless remote meter reading of power equipment in smart distribution networks.

[0003] Since the routing selection of existing distribution networks is usually based on network link node fault detection, and according to changes in network topology, the communication status of the network is predicted, and the routing path is dynamically decided, the wireless sensor network in the distribution network is different from other common wireless networks. It has its own characteristics, especially the self-organizing characteristic: the distribution and deployment of the network do not depend on any fixed network equipment. The nodes coordinate their respective monitoring and control behaviors through communication protocols and node algorithms. The nodes can quickly self-organize into a complete wireless network. The autonomous movement and dynamic networking characteristics of the nodes in the self-organizing network can easily lead to frequent changes in the network topology, which may mask some node failure phenomena (such as intermittent disconnection and normal movement are difficult to distinguish), increase the difficulty of real-time fault detection, and especially have a greater impact on the routing capability of a single node, making it difficult to judge the fault condition, thereby affecting the accuracy and efficiency of communication routing selection. Summary of the Invention

[0004] In order to solve the technical problem that the routing selection of existing distribution networks cannot distinguish between node failures and normal movement, resulting in low communication routing accuracy and efficiency, the purpose of the present invention is to provide a communication routing optimization method, system and device suitable for distribution networks. The technical solutions adopted are as follows:

[0005] The present invention provides a communication route optimization method applicable to a power distribution network, the method comprising:

[0006] Using the disconnection duration of the distribution network nodes and the degree of data deviation, abnormal nodes in the distribution network are identified;

[0007] Using the unresponsive communication sequence in the node path of the abnormal node, the impact of the routing failure on the abnormal node is determined;

[0008] By using the impact degree of routing failure, the routing priority of abnormal nodes is determined and the preferred order of distribution network nodes is obtained;

[0009] Determine target routing connections in the distribution network using the preferred order of distribution network nodes;

[0010] The unresponsive communication sequence represents the communication data timing when the abnormal node does not respond to the access request in the node path where it is located; the routing failure impact degree represents the impact degree of the abnormal node on the communication in the node path where it is located.

[0011] Furthermore, the method of determining abnormal nodes in the distribution network nodes by using the disconnection duration of the distribution network nodes and the degree of data deviation therein includes:

[0012] The data anomaly degree of the distribution network node is calculated by using the disconnection duration of the distribution network node and the degree of data deviation;

[0013] The data anomaly degree is compared with the preset anomaly threshold, and the distribution network nodes whose data anomaly degree is greater than or equal to the preset anomaly threshold are regarded as abnormal nodes.

[0014] Furthermore, the method of calculating the degree of data anomaly of the distribution network node by using the disconnection duration of the distribution network node and the degree of data deviation therein includes:

[0015] Determine the data mean of the target data and the normal value range corresponding to the target data within a preset sampling period;

[0016] Using the data mean and normal value range, the degree of data deviation in the distribution network nodes is calculated;

[0017] The data anomaly degree of the distribution network node is calculated by using the disconnection duration of the distribution network node and the degree of data deviation.

[0018] Furthermore, the determining the impact of the routing failure on the abnormal node by utilizing the unresponsive communication sequence in the node path of the abnormal node includes:

[0019] Determine a node path that has communication and data transmission with the abnormal node, and obtain an unresponsive communication sequence based on the communication data during the abnormal node's unresponsive process on the node path;

[0020] The impact of routing failure on abnormal nodes is determined by using the unresponsive communication sequence and path information in the node path.

[0021] Furthermore, the determining the impact of the routing failure on the abnormal node by utilizing the unresponsive communication sequence and path information in the node path includes:

[0022] Using the unresponded communication sequence in the node path, a straight line is fitted to obtain the corresponding sequence slope;

[0023] The impact of routing failures on abnormal nodes is determined by using sequence slope and path information.

[0024] Furthermore, the use of the sequence slope and path information to determine the impact of the routing failure on the abnormal node includes:

[0025] Determine the number of node paths and the length of node paths in the path information;

[0026] The impact of routing failures on abnormal nodes is calculated using the sequence slope, the number of node paths, and the node path length.

[0027] Furthermore, the determining of the routing priority on the abnormal node by utilizing the impact degree of the routing failure includes:

[0028] The routing priority on the abnormal node is determined by using the impact of the routing failure of the abnormal node and its adjacent network.

[0029] Furthermore, the determining of the routing priority on the abnormal node by using the respective routing failure impact levels of the abnormal node and its adjacent network includes:

[0030] Determine the average impact degree of the first route failure and the average impact degree of the second route failure of the adjacent network before and after the abnormal node failure;

[0031] The routing priority on the abnormal node is calculated using the routing fault impact degree of the abnormal node, the average of the first routing fault impact degree, and the average of the second routing fault impact degree.

[0032] The present invention provides a communication route optimization system applicable to a power distribution network, for implementing the communication route optimization method applicable to a power distribution network as described in any one of the above items; the system comprises:

[0033] A node detection module is used to identify abnormal nodes in the distribution network by using the disconnection duration of the distribution network nodes and the degree of data deviation;

[0034] a fault analysis module for determining the impact of a routing fault on an abnormal node by utilizing a sequence of unresponsive communications in a node path of the abnormal node;

[0035] The optimization analysis module is used to determine the routing priority of abnormal nodes and obtain the optimization order of distribution network nodes based on the impact of routing failures;

[0036] a connection module for determining a target routing connection in the distribution network using a preferred order of the distribution network nodes;

[0037] The unresponsive communication sequence represents the communication data timing when the abnormal node does not respond to the access request in the node path where it is located; the routing failure impact degree represents the impact degree of the abnormal node on the communication in the node path where it is located.

[0038] The present invention also provides a communication route optimization device suitable for a power distribution network, the device comprising a processor, a memory, and a communication route optimization program suitable for a power distribution network stored on the memory and executable by the processor, wherein when the communication route optimization program suitable for a power distribution network is executed by the processor, the steps of the communication route optimization method suitable for a power distribution network as described in any one of the above items are implemented.

[0039] The present invention has the following beneficial effects:

[0040] The present invention first analyzes the multiple dimensions of the disconnection duration and data deviation degree of the distribution network nodes, and more accurately identifies the abnormal nodes therein. Then, based on the communication connection influence relationship between the abnormal nodes and the neighboring nodes, and considering the overall communication situation of the neighborhood network, the invention accurately judges the impact of the routing failure of the abnormal nodes on the communication path. Finally, based on the impact degree of the routing failure, the routing priority of each abnormal node is determined, and the overall preferred order of the distribution network nodes is obtained according to different routing selection priorities, so that the routing connection of the better distribution network nodes can be selected more accurately and efficiently, thereby realizing efficient communication of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 A flowchart of a communication route optimization method applicable to a power distribution network provided by one embodiment of the present invention;

[0043] Figure 2 A detailed flow chart of step S1 in a communication route optimization method applicable to a power distribution network provided by one embodiment of the present invention;

[0044] Figure 3 A detailed flow chart of step S11 in a communication route optimization method applicable to a power distribution network provided by one embodiment of the present invention;

[0045] Figure 4A detailed flow chart of step S2 in a communication route optimization method applicable to a power distribution network provided by one embodiment of the present invention;

[0046] Figure 5 This is a schematic diagram of the structure of the hardware operating environment of a communication route optimization device applicable to a power distribution network according to an embodiment of the present invention;

[0047] Figure 6 This is a schematic diagram of the framework structure of a communication route optimization system applicable to a power distribution network according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] To further illustrate the technical means and effectiveness of the present invention in achieving its intended objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a communication routing optimization method for power distribution networks, including its specific implementation, structure, features, and effectiveness. In the following description, references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0049] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0050] A specific solution of a communication route optimization method applicable to a power distribution network provided by the present invention will be described in detail below with reference to the accompanying drawings.

[0051] Example 1:

[0052] For the communication routing optimization method applicable to power distribution network provided by the present invention, please refer to Figure 1 , which shows a flowchart of the steps of a communication route optimization method applicable to a power distribution network provided by an embodiment of the present invention.

[0053] The method comprises:

[0054] Step S1, using the disconnection duration of the distribution network nodes and the degree of data deviation therein, to determine abnormal nodes in the distribution network nodes;

[0055] In smart distribution grids, the following sensors and their installation methods are usually configured to monitor key parameters of the power system:

[0056] The distribution network nodes (referred to as nodes) have built-in environmental sensors such as temperature, humidity, and air pressure, and obtain raw data through periodic sampling (e.g., once per second);

[0057] Real-time measurement of power parameters (such as voltage fluctuation and harmonic content) is achieved through high-precision voltage / current transformers. The sampling rate is set according to business needs (distribution automation requires at least 10ms sampling).

[0058] Nodes dynamically select communication protocols based on network load: low-bandwidth data (such as environmental data) is transmitted via HPLC (High Performance Line Communication) power line carriers; high-real-time data (such as electrical fault signals) is switched to 5G URLLC (Ultra-Reliable Low-Latency Communication) slices;

[0059] The path with the minimum number of hops or the lowest latency is selected based on dynamic topology information (such as the neighbor node status table). Routing decisions are calculated in real time by the edge computing gateway.

[0060] After the sensing elements (sensors) in the smart distribution network transmission nodes are placed, the data of the working process of the electrical equipment of the smart distribution network transmission nodes can be collected and sensed in real time.

[0061] When selecting routes for distribution network nodes, the stability of the nodes must be ensured. This is especially true for faulty nodes (abnormal nodes). The selection of alternative communication nodes should be based on optimal routing, ensuring stable communication routes. Furthermore, wireless sensor networks are distributed across the monitoring area, with nodes operating in a similar manner, creating a relatively balanced, peer-to-peer network. Each node interacts and links only with its neighboring nodes. Wireless sensor networks leverage data communication between neighboring nodes, making them highly adaptable. Therefore, node status perception requires analysis based on multiple dimensions, including electrical and environmental data, as well as changes in the distribution network topology between nodes.

[0062] For details, please refer to Figure 2 , the step S1 comprises:

[0063] Step S11, using the disconnection duration of the distribution network node and the degree of data deviation therein, calculate the degree of data anomaly of the distribution network node;

[0064] Please refer to Figure 3 , the step S11 specifically includes:

[0065] Step S111, determining the data mean of the target data and the normal value range corresponding to the target data within a preset sampling period;

[0066] Step S112: Calculate the data deviation degree in the distribution network node using the data mean and normal value range;

[0067] Step S113 , using the disconnection duration of the distribution network node and the degree of data deviation therein, calculate the degree of data anomaly of the distribution network node.

[0068] Wireless distribution networks employ a self-organizing network architecture. Nodes such as smart meters and distributed power controllers must dynamically adjust communication paths based on network status, leading to frequent topology reconstruction. This includes the movement of mobile energy storage devices or changes in network load, such as the entry / exit of distributed photovoltaics. These trigger routing requests and path updates from the routing protocol AODV (Ad-hoc On-Demand Distance Vector), which exhibit similar behavior at the protocol layer as disconnections caused by node failures. Disconnections caused by actual node hardware failures, however, are more often associated with abnormalities in different dimensions. For example, during actual operation, the flow of current and voltage within the numerous electrical devices within the nodes of a distribution network may generate some heat. Abnormal changes in temperature and humidity can also correlate with corresponding changes in the same period. Therefore, when environmental conditions are stable, a disconnection is more consistent with the distribution network topology.

[0069] The data extracted by multiple types of sensors installed in the distribution network are used to analyze multi-dimensional target data, including temperature, humidity, current, voltage and other data factors. The degree to which the data mean value within the preset sampling period deviates from the normal value range indicates the abnormal condition of this type of target data, that is, the degree of data deviation of the target data in the distribution network node:

[0070] ;

[0071] Indicates the degree of data deviation. Indicates the data mean of the target data within the preset sampling period. Indicates the upper and lower limits of the normal value range corresponding to the target data, which is Compared with the nearest range limit value, it is easier to understand that if the data mean is greater than the upper limit value, then Represents the upper limit value. If the data mean is less than the lower limit value, then Indicates the lower limit value. Represents normalized calculation.

[0072] The on-off performance of the node path is represented by the disconnection duration of the node path within the preset sampling period. ,The node path is the communication path connected to the node.

[0073] The The first sampling period within the preset The degree of data anomaly of distribution network nodes for:

[0074]

[0075] in, Indicates the The first sampling period within the preset The degree of data anomaly of the distribution network nodes, Indicates the degree of data deviation. Indicates the disconnection duration, using () function pair The value of is normalized in direct proportion. If the ratio is larger, it means the The more obvious the abnormal performance of this type of target data in a sampling period is.

[0076] Step S12: comparing the data anomaly degree with a preset anomaly threshold, and treating the distribution network nodes whose data anomaly degree is greater than or equal to the preset anomaly threshold as abnormal nodes.

[0077] Similarly, the degree of data anomaly of all types of data in each sampling period is obtained, and the nodes with different degrees of data anomaly are screened using a preset anomaly threshold (for example, 0.53, which can be adjusted according to actual conditions). Nodes with a value greater than or equal to the preset anomaly threshold are considered abnormal nodes, otherwise they can be considered normal nodes.

[0078] Step S2, using the unresponsive communication sequence in the node path of the abnormal node to determine the impact of the routing failure on the abnormal node;

[0079] In this embodiment, the unresponsive communication sequence represents the communication data timing when the abnormal node does not respond to the access request in the node path where it is located; the routing fault impact degree represents the impact degree of the abnormal node on the communication in the node path where it is located.

[0080] Due to the autonomous mobility and dynamic networking characteristics of nodes in self-organizing networks, the network topology changes frequently, which will mask some node failure phenomena. That is, node failures occur in the gaps between network changes, causing the node failure to be considered a normal network structure relink process.

[0081] Therefore, for a single node on the distribution network, for all other nodes that have data transmission with it during the monitoring time (sampling period), there are changes in the transmission status within multiple sampling periods on all paths. That is, the probability of disconnection will show an increasing trend, and the routing fault condition of the corresponding node will be more obvious.

[0082] For details, please refer to Figure 4 , the step S2 comprises:

[0083] Step S21, determining a node path that has communication data transmission with the abnormal node, and obtaining an unresponsive communication sequence based on the communication data of the abnormal node on the node path during the unresponsive process;

[0084] Get the The node paths with which the node has communication and data transmission in all sampling periods of the node are extracted, and the timestamps of all access requests on the node paths but the node does not respond are extracted, and arranged into a communication sequence in chronological order, which is expressed as the first The node Unresponsive communication sequence for node paths ;

[0085] Step S22: using the unresponsive communication sequence and path information in the node path, determine the impact degree of the routing failure on the abnormal node.

[0086] The step S22 specifically includes:

[0087] Using the unresponded communication sequence in the node path, a straight line is fitted to obtain the corresponding sequence slope;

[0088] The impact of routing failures on abnormal nodes is determined by using sequence slope and path information.

[0089] The path information includes the number of node paths and the length of node paths. The impact of routing failures on abnormal nodes is calculated using the sequence slope, the number of node paths, and the length of node paths.

[0090] Unresponsive communication sequence on different node communication paths The length of the communication sequence should be the same as the fault manifestation. Different, perform linear fitting on their respective communication sequences to obtain the sequence slope , and then obtain the first Impact of routing failure on each node:

[0091]

[0092] in, Indicates that the smart distribution network The impact of routing failures on each node; Indicates the The node Unresponsive communication sequence for each node communication path Slope of the series fitted by the straight line , Indicates the The number of node paths with which the node has communication and data transmission in all sampling periods, Indicates the The average length of the node paths with which the node has communication data transmission in all sampling periods; Indicates minimum and maximum value normalization.

[0093] Step S3, using the impact degree of the routing failure, determine the routing priority of the abnormal node and obtain the preferred order of the distribution network nodes;

[0094] Step S4: Determine the target routing connection in the power distribution network using the preferred order of the power distribution network nodes.

[0095] Based on the impact of routing failures, since the network's distribution and deployment do not rely on any fixed network devices, nodes coordinate their monitoring and control behaviors through communication protocols and node algorithms. Nodes can quickly self-organize into a complete wireless network. Correspondingly, considering the wireless communication structure of the distribution network, the self-organizing characteristics automatically allocate communication nodes to mitigate the impact of a single node failure on network communication. Therefore, routing selection should prioritize holistic and stable communication paths.

[0096] Specifically, step S3 includes:

[0097] The routing priority on the abnormal node is determined by using the impact of the routing failure of the abnormal node and its adjacent network.

[0098] More specifically:

[0099] Determine the average impact degree of the first route failure and the average impact degree of the second route failure of the adjacent network before and after the abnormal node failure;

[0100] The routing priority on the abnormal node is calculated using the routing fault impact degree of the abnormal node, the average of the first routing fault impact degree, and the average of the second routing fault impact degree.

[0101] The routing fault impact performance (routing fault impact degree) of all distribution network routing nodes is regarded as the degree of structural impact analyzed from the node. Correspondingly, the more consistent the routing fault impact performance of the node is with the structural changes under the self-organizing characteristics analyzed from the overall perspective, the stronger the necessity of the node as a stable node on the communication path.

[0102] In a single distribution network subnet, for any single distribution network node, including abnormal nodes, the routing fault impact performance of the nodes directly associated with it is obtained.

[0103] When a node fails, its nearby nodes will spontaneously connect according to the operating mechanism. The overall difference in the impact of the routing failure on the adjacent network of the abnormal node before and after the failure is expressed as the routing priority of the node. :

[0104]

[0105] in, Indicates that the smart distribution network The routing priority of each node, Indicates that the smart distribution network On the node The first type of data The impact of routing failures at each monitoring time point (preset sampling period), Indicates that the smart distribution network The average impact degree of routing failure of the adjacent network of the node before the node fails (the average impact degree of the first routing failure), Indicates that the smart distribution network The average impact degree of routing failure of the adjacent network of the node after the node fails (the average impact degree of the second routing failure), Measures the overall difference in the impact of the routing failure on the node's adjacent network before and after the failure. The smaller the difference, the more stable the node's path performance.

[0106] Therefore, based on the obtained routing priorities of all nodes (including abnormal nodes and normal nodes, where the priority value of normal nodes is 1 and the priority value of abnormal nodes calculated by the above formula is less than 1), the node priority is used to update the order of the node's adjacent nodes. That is, the node updates the local neighbor table and routing table, and regularly sends small-scale link maintenance messages (Keep-Alive packets) to confirm that the neighbor node is still active. If the node does not receive the Keep-Alive packet from the neighbor node for several consecutive cycles (for example, 3 times), it is determined that the neighbor is faulty or offline, and the faulty node is removed from it. The routing node is selected according to the arrangement order, thereby realizing the communication route optimization selection of the distribution network.

[0107] The present invention first analyzes the multiple dimensions of the disconnection duration and data deviation degree of the distribution network nodes, and more accurately identifies the abnormal nodes therein. Then, based on the communication connection influence relationship between the abnormal nodes and the neighboring nodes, and considering the overall communication situation of the neighborhood network, the invention accurately judges the impact of the routing failure of the abnormal nodes on the communication path. Finally, based on the impact degree of the routing failure, the routing priority of each abnormal node is determined, and the overall preferred order of the distribution network nodes is obtained according to different routing selection priorities, so that the routing connection of the better distribution network nodes can be selected more accurately and efficiently, thereby realizing efficient communication of the distribution network.

[0108] Example 2:

[0109] The embodiment of the present invention further provides a communication route optimization device applicable to a power distribution network. The communication route optimization device applicable to a power distribution network can be a data computing and processing device such as a computer, a server, or a combination of multiple devices.

[0110] like Figure 5 As shown, Figure 5 It is a structural diagram of the hardware operating environment of the communication route optimization device applicable to the power distribution network involved in the embodiment of the present invention.

[0111] like Figure 5 As shown, the communication route optimization device for a power distribution network may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Communication bus 1002 is used to enable communication between these components. User interface 1003 may include a display and an input unit, such as a control panel. Optionally, user interface 1003 may also include a standard wired interface or a wireless interface. Network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). Memory 1005 may be high-speed RAM or non-volatile memory, such as a disk drive. Memory 1005 may also be a storage device independent of processor 1001. Memory 1005, a computer storage medium, may include a communication route optimization program for a power distribution network.

[0112] Those skilled in the art will understand that Figure 5 The hardware structure shown in the figure does not constitute a limitation of the device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0113] Continue to refer to Figure 5 , Figure 5The memory 1005 as a computer-readable storage medium may include an operating system, a user interface module, a network communication module, and a communication route optimization program applicable to a power distribution network.

[0114] exist Figure 5 In the embodiment, the network communication module is mainly used to connect to the server and can communicate data with the server; and the processor 1001 can call the communication route optimization program suitable for the power distribution network stored in the memory 1005 and execute the steps in the above embodiments.

[0115] Based on the hardware structure of the communication route optimization device applicable to the power distribution network, various embodiments of the communication route optimization method applicable to the power distribution network of the present invention are implemented.

[0116] In addition, the present invention also provides a communication routing optimization system applicable to power distribution network, please refer to Figure 6 , the communication routing optimization system applicable to the power distribution network includes:

[0117] The node detection module A10 is used to determine abnormal nodes in the distribution network by using the disconnection duration of the distribution network nodes and the degree of data deviation therein;

[0118] The fault analysis module A20 is used to determine the impact of the routing fault on the abnormal node by using the unresponsive communication sequence in the node path of the abnormal node;

[0119] The optimization analysis module A30 is used to determine the routing priority of abnormal nodes and obtain the optimization order of distribution network nodes based on the impact degree of routing failure;

[0120] a connection module A40 for determining a target routing connection in the power distribution network using a preferred order of the distribution network nodes;

[0121] The unresponsive communication sequence represents the communication data timing when the abnormal node does not respond to the access request in the node path where it is located; the routing failure impact degree represents the impact degree of the abnormal node on the communication in the node path where it is located.

[0122] The specific implementation of the communication route optimization system applicable to the power distribution network of the present invention is basically the same as the embodiments of the communication route optimization method applicable to the power distribution network described above, and will not be repeated here.

[0123] The present invention also provides a computer-readable storage medium having stored thereon a communication route optimization program applicable to a power distribution network, wherein when the communication route optimization program applicable to a power distribution network is executed by a processor, the steps of the communication route optimization method applicable to a power distribution network are implemented as described above.

[0124] The method implemented when the communication route optimization program applicable to the power distribution network is executed can refer to the various embodiments of the communication route optimization method applicable to the power distribution network of the present invention, and will not be described in detail here.

[0125] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0126] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from the reference embodiment.

[0127] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0128] The above description is only a preferred embodiment of the present invention and does not limit the scope of protection of the present invention. All equivalent structural / method transformations made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or direct / indirect application in reference to related technical fields are included in the scope of protection of the present invention.

Claims

1. A communication routing optimization method applicable to a power distribution network, characterized in that: The method comprises: Using the disconnection duration of the distribution network nodes and the degree of data deviation, abnormal nodes in the distribution network are identified; Using the unresponsive communication sequence in the node path of the abnormal node, the impact of the routing failure on the abnormal node is determined; By using the impact degree of routing failure, the routing priority of abnormal nodes is determined and the preferred order of distribution network nodes is obtained; Determine target routing connections in the distribution network using the preferred order of distribution network nodes; The unresponsive communication sequence represents the communication data timing when the abnormal node does not respond to the access request in the node path where it is located; the routing failure impact degree represents the impact degree of the abnormal node on the communication in the node path where it is located.

2. The communication route optimization method applicable to a power distribution network according to claim 1, characterized in that: The method of determining abnormal nodes in the distribution network nodes by utilizing the disconnection duration of the distribution network nodes and the degree of data deviation therein includes: The data anomaly degree of the distribution network node is calculated by using the disconnection duration of the distribution network node and the degree of data deviation; The data anomaly degree is compared with the preset anomaly threshold, and the distribution network nodes whose data anomaly degree is greater than or equal to the preset anomaly threshold are regarded as abnormal nodes.

3. The communication route optimization method applicable to the power distribution network according to claim 2, characterized in that: The method of calculating the data anomaly degree of the distribution network node by using the disconnection duration of the distribution network node and the degree of data deviation therein includes: Determine the data mean of the target data and the normal value range corresponding to the target data within a preset sampling period; Using the data mean and normal value range, the degree of data deviation in the distribution network nodes is calculated; The data anomaly degree of the distribution network node is calculated by using the disconnection duration of the distribution network node and the degree of data deviation.

4. The communication route optimization method applicable to a power distribution network according to claim 1, characterized in that: The determining the impact of the routing failure on the abnormal node by utilizing the unresponsive communication sequence in the node path of the abnormal node includes: Determine a node path that has communication and data transmission with the abnormal node, and obtain an unresponsive communication sequence based on the communication data during the abnormal node's unresponsive process on the node path; The impact of routing failure on abnormal nodes is determined by using the unresponsive communication sequence and path information in the node path.

5. The communication route optimization method applicable to a power distribution network according to claim 4, characterized in that: The determining the impact of the routing failure on the abnormal node by utilizing the unresponsive communication sequence and path information in the node path includes: Using the unresponded communication sequence in the node path, a straight line is fitted to obtain the corresponding sequence slope; The impact of routing failures on abnormal nodes is determined by using sequence slope and path information.

6. The communication route optimization method applicable to a power distribution network according to claim 5, characterized in that: Determining the impact of the routing failure on the abnormal node by using the sequence slope and path information includes: Determine the number of node paths and the length of node paths in the path information; The impact of routing failures on abnormal nodes is calculated using the sequence slope, the number of node paths, and the node path length.

7. The communication route optimization method applicable to a power distribution network according to claim 1, characterized in that: Determining the routing priority on the abnormal node by utilizing the impact degree of the routing failure includes: The routing priority on the abnormal node is determined by using the impact of the routing failure of the abnormal node and its adjacent network.

8. The communication route optimization method applicable to a power distribution network according to claim 7, characterized in that: The determining of the routing priority of the abnormal node by utilizing the respective routing failure impact levels of the abnormal node and its adjacent network includes: Determine the average impact degree of the first route failure and the average impact degree of the second route failure of the adjacent network before and after the abnormal node failure; The routing priority on the abnormal node is calculated using the routing fault impact degree of the abnormal node, the average of the first routing fault impact degree, and the average of the second routing fault impact degree.

9. A communication routing optimization system for a power distribution network, characterized in that: The system is used to implement the communication route optimization method applicable to a power distribution network according to any one of claims 1 to 8; the system comprises: A node detection module is used to identify abnormal nodes in the distribution network by using the disconnection duration of the distribution network nodes and the degree of data deviation; a fault analysis module for determining the impact of a routing fault on an abnormal node by utilizing a sequence of unresponsive communications in a node path of the abnormal node; The optimization analysis module is used to determine the routing priority of abnormal nodes and obtain the optimization order of distribution network nodes based on the impact of routing failures; a connection module for determining a target routing connection in the distribution network using a preferred order of the distribution network nodes; The unresponsive communication sequence represents the communication data timing when the abnormal node does not respond to the access request in the node path where it is located; the routing failure impact degree represents the impact degree of the abnormal node on the communication in the node path where it is located.

10. A communication route optimization device suitable for a power distribution network, characterized in that: The device includes a processor, a memory, and a communication route optimization program applicable to a power distribution network stored in the memory and executable by the processor, wherein when the communication route optimization program applicable to a power distribution network is executed by the processor, the steps of the communication route optimization method applicable to a power distribution network as described in any one of claims 1 to 8 are implemented.

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