A multi-dimensional collaborative method and device for ensuring the reliability of a distribution network

Abstract

The present application discloses a multi-dimensional collaborative method and device for ensuring the reliability of a distribution network, which relates to the technical field of smart grids. The main technical solution of the present application is as follows: It provides a more reliable "failure rate and repair time" affected by the interaction of information, physical, and social multi-source information, realizes from the perspective of multi-dimensional collaboration of information, physical, and society, thereby providing better and more reliable distribution network monitoring data for constructing better reliability indicators required for the distribution network, and is applicable to the distribution network project of large-scale events, so as to solve the problem of providing a better reliability guarantee scheme for the distribution network.

Description

Technical Field

[0001] This application relates to the technical field of smart grids, and in particular, to a method and device for ensuring the reliability of a distribution network through multi-dimensional collaboration. Background Art

[0002] In practical applications, in order to host large-scale events (such as international competitions), considering specific competition venues, living areas and training areas for international athletes, etc., it is necessary to provide a complete distribution network project for such large-scale events and require high-reliability power supply.

[0003] Currently, for the distribution network project of hosting large-scale events, it will face multiple backgrounds such as 100% renewable energy access, extreme weather impacts, and the complexity of major social activities. How to ensure the reliability of the distribution network has always been a difficult problem under research. Summary of the Invention

[0004] This application provides a method and device for ensuring the reliability of a distribution network through multi-dimensional collaboration. The main purpose is to provide a more reliable "failure rate and repair time" affected by the interaction of information, physical, and social multi-source information, and to achieve a better and more reliable distribution network monitoring data from the perspective of multi-dimensional collaboration of information, physical, and social, so as to construct better reliability indicators required for the distribution network, and to deal with the distribution network project of large-scale events, so as to provide a better reliability guarantee scheme for the distribution network.

[0005] To achieve the above objective, this application mainly provides the following technical solutions:

[0006] In the first aspect of this application, a method for ensuring the reliability of a distribution network through multi-dimensional collaboration is provided. The method includes:

[0007] Processing target data information by using a physical system model corresponding to the distribution network, and outputting the failure rate and repair time of physical components. The target data information at least includes: the distribution network topology of the physical system, and the historical failure rate information, historical repair time information, and historical operating condition information of physical components;

[0008] Updating the failure rate of the physical components by using the first processing ability and the second processing ability provided by an information system model corresponding to the distribution network. The information system model has two parts of processing functions, including: a first processing function composed of primary equipment status monitoring, fault diagnosis, and environmental warning, and a second processing function composed of secondary equipment data perception and panoramic imaging;

[0009] Using the third processing capability and the fourth processing capability provided by the social system model corresponding to the distribution network, update the failure rate and the repair time corresponding to the physical components, where the social system model has two parts of processing functions, including: a third processing function for implementing a power protection plan by coping with the shift arrangement of inspection personnel, and a fourth processing function for coping with an emergency repair plan;

[0010] Based on the failure rate corresponding to the physical components updated by using the information system model, and based on the failure rate and the repair time corresponding to the physical components updated by using the social system model, construct the reliability index corresponding to the distribution network and apply it to provide reliability guarantee for the distribution network.

[0011] The second aspect of the present application provides a multi-dimensional collaborative distribution network reliability guarantee device, and the device includes:

[0012] A first processing unit, configured to process target data information by using a physical system model corresponding to a distribution network, and output a failure rate and a repair time corresponding to a physical component, where the target data information at least includes: a distribution network topology of the physical system, and historical failure rate information, historical repair time information, and historical operating condition information of the physical component;

[0013] A second processing unit, configured to update the failure rate corresponding to the physical component by using the first processing capability and the second processing capability provided by the information system model corresponding to the distribution network, where the information system model has two parts of processing functions, including: a first processing function composed of primary equipment status monitoring, fault diagnosis, and environmental early warning, and a second processing function composed of secondary equipment data perception and panoramic imaging;

[0014] A third processing unit, configured to update the failure rate and the repair time corresponding to the physical component by using the third processing capability and the fourth processing capability provided by the social system model corresponding to the distribution network, where the social system model has two parts of processing functions, including: a third processing function for implementing a power protection plan by coping with the shift arrangement of inspection personnel, and a fourth processing function for coping with an emergency repair plan;

[0015] A construction unit, configured to construct a reliability index corresponding to the distribution network based on the failure rate corresponding to the physical component updated by using the information system model, and based on the failure rate and the repair time corresponding to the physical component updated by using the social system model, and apply it to provide reliability guarantee for the distribution network.

[0016] The third aspect of the present application provides a storage medium, and the storage medium includes a stored program, where when the program runs, it controls the device where the storage medium is located to execute the multi-dimensional collaborative distribution network reliability guarantee method as described above.

[0017] A fourth aspect of the present application provides an electronic device, which includes at least one processor, at least one memory connected to the processor, and a bus;

[0018] Wherein, the processor and the memory communicate with each other through the bus;

[0019] The processor is used to call program instructions in the memory to execute the multi-dimensional collaborative power distribution reliability guarantee method as described above.

[0020] By means of the above technical solutions, the technical solutions provided by the present application have at least the following advantages:

[0021] The present application provides a multi-dimensional collaborative power distribution reliability guarantee method and device. The present application pre-establishes a physical system model, an information system model, and a social system model for the power distribution project of large-scale events, so that the power distribution project becomes a complex system affected by the interaction of multiple information such as information, physics, and society. Then, in such a complex system, the present application first uses the physical system model to comprehensively process the power distribution topology of the physical system, as well as the historical failure rate information, historical repair time information, and historical operating condition information of physical components, so as to output the failure rate and repair time corresponding to physical components. Then, the processing capabilities of the information system model for primary equipment and secondary equipment are used to update the obtained failure rate. And then, the processing capabilities of the social system model for power protection plans and emergency repair plans are used to update the failure rate and repair time corresponding to physical components. The above realizes the coupling of information and physics, integrates social factors to obtain the updated failure rate and repair time respectively, and finally is used to construct more reliable reliability indicators required for power distribution, providing reliability guarantee for power distribution. The present application provides better "failure rate and repair time" affected by the interaction of multiple information such as information, physics, and society, realizes from the perspective of multi-dimensional collaboration of information, physics, and society, thereby providing better and more reliable power distribution monitoring data, used to construct better reliability indicators required for power distribution, and coping with the power distribution project of large-scale events, so as to solve the problem of providing a better reliability guarantee plan for power distribution.

[0022] The above description is only an overview of the technical solutions of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features, and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically listed below. Description of the Drawings

[0023] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present application. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0024] Figure 1 It is a flowchart of a multi-dimensional collaborative distribution network reliability guarantee method provided by an embodiment of the present application;

[0025] Figure 2 It is a reliability evaluation process provided by an embodiment of the present application in terms of integrating social factors;

[0026] Figure 3 It is a block diagram of the composition of a multi-dimensional collaborative distribution network reliability guarantee device provided by an embodiment of the present application. Specific embodiments

[0027] The exemplary embodiments of the present application will be described in more detail below with reference to the drawings. Although the exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present application can be more thoroughly understood and the scope of the present application can be fully conveyed to those skilled in the art.

[0028] An embodiment of the present application provides a multi-dimensional collaborative distribution network reliability guarantee method, as Figure 1 shown, and the following specific steps are provided for this embodiment of the present invention:

[0029] 101. Process the target data information using the physical system model corresponding to the distribution network, and output the failure rate and repair time corresponding to the physical components. The target data information includes at least: the distribution network topology of the physical system and the historical failure rate information, historical repair time information, and historical operating condition information of the physical components.

[0030] The physical components are physical devices in the distribution network. In the distribution network, the physical system model mainly focuses on the physical layer of the distribution network, including: the operation of primary electrical equipment and the transmission of electrical quantities, which describes the physical layer of the distribution network and the transmission process of electrical quantities. Among them, the primary electrical equipment includes, for example, transformers, circuit breakers, transmission lines, etc.

[0031] This step 101 can be refined to include: inputting the target data information into the physical system model, constructing the corresponding relationship between the physical components and the outage rate under different operating conditions; and calculating the failure rate and repair time corresponding to the physical components according to this corresponding relationship.

[0032] Example 1. Taking a cable line as an example, data processing is carried out in the physical system model, and the relationship between the fault outage rate and the line power flow is obtained as expressed by the following formula (1).

[0033]

[0034] Formula (1);

[0035] Among them, L represents the operating state of the device.

[0036] In the physical system model, consider the influence of the operating conditions of each physical component on its own outage probability, and combine the operating state of the physical system. Consider the changes in real-time operating conditions such as line power flow, bus voltage, and physical system frequency on the outage probability of physical components, and establish a time-varying reliability evaluation model of physical components based on real-time operating conditions. Update the failure rate of physical components with the outage probability of physical components calculated.

[0037] In the embodiment of the present application, at the physical level of the distribution network, a large amount of data information is integrated (such as the distribution network topology of the physical system and the historical failure rate information, historical repair time information, and historical operating condition information of physical components), and the physical system model is used to process and output the failure rate and repair time of physical components, which are actually used as the initial failure rate and initial repair time (that is, as initial data), so as to update the initial data in combination with the information dimension and social factor dimension subsequently, so as to obtain more reliable failure rate and repair time adapted to the distribution network from multiple dimensions.

[0038] 102. Use the first processing ability and the second processing ability provided by the information system model corresponding to the distribution network to update the failure rate corresponding to the physical component. Among them, the information system model has two parts of processing functions, including: the first processing function composed of primary equipment status monitoring, fault diagnosis, and environmental warning, and the second processing function composed of secondary equipment data perception and panoramic imaging.

[0039] In the distribution network, the information system model is a model that reflects the internal structure mode of the distribution network and the connection mode between each part, for example, an abstract representation used to describe how an information system is organized and operates. In the embodiment of the present application, it is mainly to use the information system model to achieve: primary equipment status monitoring, fault diagnosis, and environmental warning; secondary equipment data perception and panoramic imaging. And based on different processing objects, that is, primary equipment and secondary equipment, the embodiment of the present application divides the information system model into two aspects of processing ability. And it should be noted that, in order to facilitate the distinction of different aspects of processing ability, the embodiment of the present application uses the words "first" and "second" for identification and only serves as an identification.

[0040] In the embodiments of the present application, considering the impact of the availability of the information system required for the distribution network on the availability of physical components in the interface layer, the availability of physical components in the interface layer is updated. Among them, the above-mentioned impacts mainly include three categories: the distribution automation system, the health status of the equipment itself and external environmental factors, and information network transmission failures. Therefore, the embodiments of the present application can respectively construct mathematical models for these three types of impacts in the information system model to quantify the three types of impacts. The ultimate purpose of using such quantification is to update the failure rate of physical components output based on the physical system model in 101, so as to obtain a more reliable failure rate in the cyber-physical coupling.

[0041] 103. Utilize the third processing capability and the fourth processing capability provided by the social system model corresponding to the distribution network to update the failure rate and repair time corresponding to the physical components. The social system model has two processing functions, including: the third processing function of implementing a power protection plan by coping with the patrol personnel scheduling, and the fourth processing function of coping with the emergency repair plan.

[0042] The embodiments of the present application consider the impact of the power protection plan and the emergency repair plan in the social system required for the distribution network on the reliability of physical components. For example, in the power protection plan (that is, the plan customized to ensure the distribution network without emergency repair), the impact of the patrol cycle on the failure rate of physical components is considered. In the emergency repair plan, the impact of the travel time (that is, the time on the way to the fault point) and the repair time on the repair time is considered.

[0043] The embodiments of the present application pre-construct a social system model corresponding to the distribution network, and mainly use such a social system model to achieve: in the power protection plan (that is, the plan to ensure the distribution network without emergency repair), the impact of the patrol cycle on the failure rate of physical components; in the emergency repair plan, the impact of the travel time and the repair time on the repair time. And based on coping with different plans, the embodiments of the present application design that the social system model has corresponding two aspects of processing capabilities. It should be noted that, for the convenience of distinguishing different aspects of processing capabilities, the embodiments of the present application use the words "third" and "fourth" for identification and only play a role of identification.

[0044] Thus, by using the above two aspects of processing capabilities of the social system model, the integration of social factors is realized to update the failure rate and repair time output by the physical system model in 101, so as to obtain a more reliable failure rate and repair time integrating social factors.

[0045] 104. Based on the failure rate of physical components updated corresponding to the information system model and the failure rate and repair time of physical components updated corresponding to the social system model, construct the reliability index corresponding to the distribution network and apply it to provide reliability guarantee for the distribution network.

[0046] In the embodiments of the present application, "cyber-physical coupling" is implemented based on the information system model to obtain a more reliable failure rate, and "incorporating social factors" is implemented based on the social system model to obtain a more reliable failure rate and repair time, which are used to construct the corresponding reliability indicators for the distribution network. Some reliability indicators are exemplified as follows:

[0047] (1) Load point outage rate (λ): It represents the probability that a certain load point in the distribution network is out of service within a unit time, and it is usually related to the failure rate of the equipment supplying power to this load point.

[0048] (2) Average outage duration per failure of the load point (γ): It represents how long it takes on average to restore power supply when the load point is out of service.

[0049] As above, the embodiments of the present application provide a multi-dimensional collaborative method for ensuring the reliability of the distribution network. The embodiments of the present application have pre-built a physical system model, an information system model, and a social system model for the distribution network project of a large-scale event, so that the distribution network project becomes a complex system affected by the interaction of multiple information such as information, physics, and society; then in such a complex system, the present application first uses the physical system model to comprehensively process the distribution network topology of the physical system and the historical failure rate information, historical repair time information, and historical operating condition information of physical components, so as to output the failure rate and repair time corresponding to physical components, and then uses the processing capabilities of the information system model for primary equipment and secondary equipment to update the obtained failure rate; and then uses the processing capabilities of the social system model for the power protection plan and the emergency repair plan to update the failure rate and repair time corresponding to physical components; the above realizes cyber-physical coupling and incorporates social factors to obtain the updated failure rate and repair time respectively, which are finally used to construct better reliability indicators required for the distribution network to provide reliability guarantee for the distribution network.

[0050] The embodiments of the present application provide "failure rate and repair time" affected by the interaction of multiple information such as information, physics, and society, and realize the perspective of multi-dimensional collaboration from information, physics, and society, so as to provide better and more reliable distribution network monitoring data, which are used to construct better reliability indicators required for the distribution network, and respond to the distribution network project of a large-scale event, so as to solve the problem of providing a better reliability guarantee scheme for the distribution network.

[0051] In some specific embodiments, for "using the first processing ability and the second processing ability provided by the information system model corresponding to the distribution network to update the failure rate corresponding to physical components", it can be refined to include: the following (A1-A2) and (B1-B2) are parallel execution steps:

[0052] (A1) Using the first processing ability of the information system model, obtain equipment operation status information, fault diagnosis cycle and effect data, early warning data, and algorithm accuracy data;

[0053] (A2)Process the device operation status information, fault diagnosis cycle and effect data, early warning data, and algorithm accuracy data based on the first processing capability, and output the real-time outage rate, developing fault rate, and destructive fault rate.

[0054] Among them, the developing fault rate in the power grid usually refers to the phenomenon that during the operation of the power grid, due to factors such as equipment aging, wear, and environmental changes, the fault rate gradually increases. This change in the fault rate is usually not sudden but accumulates gradually with the increase in the operation time of the equipment.

[0055] The developing fault rate in the power grid is a dynamically changing process and is affected by various factors. To reduce the fault rate, a series of measures need to be taken, including improving equipment quality, optimizing operating conditions, strengthening equipment maintenance and servicing, etc. At the same time, it is also necessary to pay attention to the impact of external factors on the power grid and take corresponding preventive measures. Through comprehensive measures, the developing fault rate in the power grid can be effectively reduced, and the safety and reliability of the power grid can be improved.

[0056] Among them, the destructive fault rate in the power grid refers to the fault rate of sudden failure of equipment or systems caused by external factors. This fault rate is usually related to the physical protection of equipment or systems, the operating environment, and human factors, etc.

[0057] The destructive fault rate in the power grid is closely related to external factors such as natural disasters, external force damage, and malicious attacks. To reduce the destructive fault rate, a series of measures need to be taken, including strengthening the physical protection of power grid equipment, improving the disaster resistance ability of equipment, optimizing the power grid layout to reduce the impact of natural disasters, strengthening the safety management around power grid facilities to prevent external force damage, etc. At the same time, it is also necessary to establish a sound emergency response mechanism to deal with possible malicious attack incidents. Through the implementation of these measures, the destructive fault rate in the power grid can be effectively reduced, and the safety and reliability of the power grid can be improved.

[0058] (B1)Utilize the second processing capability of the information system model to obtain the information transmission punctuality rate, information transmission accuracy rate, and secondary equipment fault rate.

[0059] (B2)Process the information transmission punctuality rate, information transmission accuracy rate, and secondary equipment fault rate based on the second processing capability, and output the channel information transmission punctuality rate, channel information transmission accuracy rate, and channel topology effectiveness data.

[0060] (AB)Update the fault rate corresponding to the physical components based on the real-time outage rate, developing fault rate, and destructive fault rate, as well as based on the channel information transmission punctuality rate, channel information transmission accuracy rate, and channel topology effectiveness data.

[0061] For the data processing implemented for primary equipment in the distribution network, primary equipment refers to the equipment that directly participates in the production, transmission, distribution, and use of electric energy in the power system. They are responsible for key functions such as voltage transformation, power transmission, switching, and isolation of power sources. Examples of primary equipment in the power grid distribution network include: transformers, transmission / distribution lines, circuit breakers, disconnectors, lightning arresters, current transformers (CTs), and voltage transformers (PTs).

[0062] In the embodiments of the present application, by applying technologies such as online data acquisition and equipment status perception, the operating data of physical components such as line power flow, node voltage, and system frequency are obtained, and the equipment operating outage rates of physical equipment such as distribution transformers, power cable lines, and switch components are calculated. Based on the collected data, a relevant index system is established, and these indexes can well reflect the operating characteristics and operating status of this type of power equipment. Through the state evaluation of electrical equipment, more accurate information about the operating reliability data of the equipment can be obtained, providing a reliable reference basis for formulating the daily maintenance plan of physical equipment, reducing the failure rate of physical components, and thus improving the power supply reliability of the system.

[0063] In the above process, the data sampling frequency of physical equipment status perception, the accuracy of equipment status diagnosis algorithms, the accuracy of the early warning mechanism, as well as the delay and error codes of the information transmission channel, etc., will all affect the calculation of the real-time operating outage rate of physical equipment. All of the above will affect the actual failure rate of physical components in practical applications, thereby affecting the dispatcher's judgment of the current power supply reliability of the system.

[0064] Therefore, for primary equipment, in the embodiments of the present application, by collecting equipment operating status data, obtaining fault diagnosis cycle and effect data, collecting early warning data, and obtaining algorithm difficulty data used, the real-time outage rate, development-type failure rate, and destructive failure rate of physical components are further calculated to achieve the status monitoring, fault diagnosis, and environmental early warning of primary equipment, and these are used as consideration factors for the failure rate of physical components output by the physical system model in the subsequent update step 101.

[0065] For the data processing implemented for secondary equipment in the distribution network, secondary equipment refers to: mainly used for monitoring, controlling, measuring, regulating, and protecting the operating conditions of the power system and primary equipment. These devices do not directly connect to the main power circuit, but they are important auxiliary devices to ensure the safe and efficient operation of the power system. Examples of primary equipment in the power grid distribution network include: measuring instruments, insulation monitoring devices, control and signal devices, relay protection and automatic devices, DC power supply equipment, high-frequency wave traps, backup power supply automatic switching devices, communication equipment, and so on.

[0066] In the embodiments of the present application, three-dimensional panoramic visualization and rapid imaging technologies are used to collect operation data such as the ambient temperature and humidity of secondary equipment, establish a health model for each intelligent device in the substation, and comprehensively judge the health status of each intelligent device based on the received real-time information. Further reduce the failure rates of relay protection and safety automatic devices, channel communication devices, secondary circuits and related devices, and intelligent substation auxiliary devices in the secondary system, improve the monitoring and protection effects of secondary equipment on primary equipment, and enhance the system reliability.

[0067] For the information system in the distribution network, when the communication network that supports the normal operation of the distribution automation system has: topological failures of information components or communication links, transmission delays, and transmission errors, the monitoring, control, and control feedback information cannot be transmitted normally, which will affect the working state of the distribution automation system, thereby reducing the availability of physical components and increasing the failure rate. Considering the above three failure situations of the information system, an information system effectiveness model is established. The channel topology availability calculation model is obtained by analogy with the reliability series model of the physical system; the channel information transmission accuracy calculation model is obtained by analogy with the reliability series model of the physical system; the availability model of the information system is obtained from the three aspects of the topology availability, delay characteristics, and error code characteristics of the information system, and the availability of each interface layer component of the physical system is updated, thereby reflecting the impact of the transmission effect of the secondary system communication network on the reliability of the distribution network.

[0068] In the treatment of secondary equipment, on the one hand, the embodiments of the present application comprehensively consider the impact of the above transmission effect on the reliability of the distribution network. This impact is often negative, so the system reliability level will be slightly reduced compared with that before considering the transmission effect; on the other hand, the embodiments of the present application adopt the panoramic imaging technology of the secondary system to further reduce the failure rate of secondary equipment and improve the transmission effect of the secondary system communication network, so as to enhance the reliability of the distribution system.

[0069] Exemplarily, the present application uses the failure rate of physical equipment updated by cyber-physical coupling to provide a reliability assessment process. For example: state monitoring, fault diagnosis, and environmental warning are implemented on primary equipment (such as A1 - A2), data perception and panoramic imaging are implemented on secondary equipment (such as B1 - B2). In two parallel execution steps, such as obtaining the real-time outage rate, development model failure rate, and destructive failure rate on primary equipment, and obtaining the channel information transmission punctuality rate, channel information transmission accuracy rate, and channel topology effectiveness on secondary equipment, so as to update the failure rate of physical components output by the physical system model in 101 based on the data information obtained from the two parallel steps, so as to obtain a more reliable failure rate in cyber-physical coupling.

[0070] Moreover, based on the updated failure rate of physical components, the embodiments of the present application further perform the following steps: based on the distribution network topology, find the equipment and lines on the minimal paths and non-minimal paths of the load points (i = 1, traversing one by one but less than N), use series-parallel equivalence to convert the failure rate of non-minimal facilities to the minimal paths, enumerate the failure cases of the minimal paths of the load points (i), form the failure rate and power outage time list of the load points (i) and solve the reliability index of the load points (i). The above steps are iteratively executed (i = i + 1, i < N) until the end. Based on the above steps, the embodiments of the present application provide "obtaining updated failure rates in the cyber-physical coupling" to construct the reliability index of the distribution network.

[0071] In some specific embodiments, for the power protection plan, for 103, "updating the failure rate and repair time corresponding to physical components by using the third processing ability and the fourth processing ability provided by the social system model corresponding to the distribution network" can be refined to include:

[0072] (C1) Using the third processing ability of the social system model, obtain historical inspection data and historical fault data;

[0073] (C2) Based on the third processing ability, adopt the maximum likelihood estimation method to estimate the defect occurrence probability and time delay parameters;

[0074] (C3) Based on the third processing ability, use the defect occurrence probability and time delay parameters to update the failure rate corresponding to the physical components.

[0075] If (C1-C3) is to update the failure rate of physical equipment for the power protection plan, considering the influence between the inspection personnel scheduling (i.e., inspection cycle) and the failure rate of the inspected equipment in social factors, a mathematical model can be constructed based on the time delay theory. In the mathematical model, the failure development process of power components is divided into "defect occurrence" and "time delay process of defect developing into a failure" (i.e., two parts), and the probability of power equipment having defects per unit time is regarded as satisfying the Poisson distribution , and the time delay process of defect developing into a failure is regarded as satisfying the exponential distribution. Through the historical fault data and historical inspection data T, the defect occurrence rate and time delay parameters are obtained by maximum likelihood estimation. Considering that the failure incidence rate after inspection satisfies the non-homogeneous Poisson distribution, the failure rate of physical equipment after considering the social system inspection plan is obtained by further integration, and thus the initial failure rate of equipment in the physical domain (i.e., the failure rate of physical components output by the physical system model in 101) is updated.

[0076] Furthermore, considering the travel time and repair time, for the emergency repair plan, for 103, it can be refined to include:

[0077] (D1)Based on the fourth processing ability of the social system model, obtain historical emergency repair data, where the historical emergency repair data includes at least: repair personnel data, material data, vehicle data, the repair time of each repair personnel for a fault, and the geographical distance data between the fault and the repair personnel;

[0078] (D2)Based on the fourth processing ability and the historical emergency repair data, construct an emergency repair fault repair time model;

[0079] (D3)Use the emergency repair fault repair time model to update the repair time corresponding to the physical component.

[0080] As (D1 - D3) is to update the repair time of the physical device for the emergency repair plan. Compared with the power protection plan, the difference between the two lies in "emergency". The emergency repair plan mainly considers the travel time and repair time. On the basis of the power protection plan, the historical emergency repair data obtained in the emergency repair plan includes at least: repair personnel , materials m, vehicles , the repair time Tre of each repair personnel for each fault, and the geographical distance L between the fault and the repair personnel. The travel time is determined by the deployment speed of personnel and materials and the path length selected by the emergency repair plan. Further, the travel time can be solved through the emergency repair fault repair time model of "person - vehicle - material" coordination. The repair time at the fault point is mainly determined by the quantity of repair personnel and repair materials and the ability of the repair personnel.

[0081] In summary, on the basis of power protection, emergency repair is also considered, so that the physical device fault repair time in the emergency repair plan is the sum of the travel time and the repair time. Accordingly, the embodiment of the present application updates the repair time output by the physical system model in 101 considering comprehensive social factors, and obtains a more reliable repair time considering comprehensive social factors.

[0082] Exemplarily, the present application uses the failure rate and repair time of the physical device updated by integrating social factors to provide a reliability assessment process, as Figure 2 shown: Update the failure rate of the physical component in 101 in the power protection plan, and update the repair time of the physical component in 101 in the emergency repair plan.

[0083] It should be noted that the "power protection plan" and "emergency repair plan" referred to in the embodiments of the present application are almost similar in essence in terms of implementation means. However, the "emergency repair plan" realizes "emergency" on the basis of the "power protection plan", that is, it also takes into account the repair journey time and repair time, so it is an optimization on the basis of the "power protection plan". Therefore, the embodiments of the present application actually update the failure rate of the physical components in Update 101 based on both of these two plans. However, especially for the "emergency repair plan", the repair time of the physical components in 101 is also updated. In Figure 2 in order to avoid repetition, the content of updating the failure rate of physical components for the "emergency repair plan" will not be reflected.

[0084] Such as Figure 2 shown, based on the updated failure rate and repair time, the embodiments of the present application also execute the following: based on the distribution network topology structure, find the equipment and lines on the minimum path and non-minimum path of the load point (i = 1, traversing one by one but less than N), use series-parallel equivalence to convert the failure rate of non-minimum facilities to the minimum path, enumerate the failure conditions of the minimum path of the load point (i), form a list of the failure rate and power outage time of the load point (i) and solve the reliability index of the load point (i), and perform the above iteration (i = i + 1, i < N) until the end. Based on the above steps, the embodiments of the present application provide "obtaining the updated failure rate in the cyber-physical coupling" to construct the reliability index of the distribution network.

[0085] Furthermore, as an implementation of the method shown above Figure 1 shown, the embodiments of the present application provide a multi-dimensional collaborative distribution network reliability guarantee device. The device embodiments correspond to the foregoing method embodiments. For the convenience of reading, the device embodiments will not repeat the detailed content in the foregoing method embodiments one by one. However, it should be clear that the device in this embodiment can correspondingly implement all the content in the foregoing method embodiments. This device is applied to the distribution network project for large-scale events to solve the problem of providing a better reliability guarantee scheme for the distribution network, specifically as Figure 3 shown, this device includes:

[0086] A first processing unit 21, configured to process target data information by using a physical system model corresponding to the distribution network, and output the failure rate and repair time of physical components, where the target data information at least includes: the distribution network topology of the physical system, and the historical failure rate information, historical repair time information, and historical operating condition information of physical components;

[0087] The second processing unit 22 is used to update the failure rate corresponding to the physical element by using the first processing capability and the second processing capability provided by the information system model corresponding to the distribution network, wherein the information system model has two processing functions, including: a first processing function consisting of primary equipment status monitoring, fault diagnosis and environmental early warning, and a second processing function consisting of secondary equipment data perception and panoramic imaging;

[0088] The third processing unit 23 is used to update the failure rate and the repair time corresponding to the physical element by using the third processing capacity and the fourth processing capacity provided by the social system model corresponding to the distribution network, wherein the social system model has two processing functions, including: a third processing function for implementing a power protection plan by responding to the inspection personnel scheduling, and a fourth processing function for responding to the emergency repair plan;

[0089] The construction unit 24 is used to construct a reliability index corresponding to the distribution network based on the failure rate corresponding to the physical component updated corresponding to the information system model, and the failure rate and repair time corresponding to the physical component updated corresponding to the social system model, so as to provide reliability assurance for the distribution network.

[0090] In some modified embodiments, the first processing unit 21 is specifically configured to:

[0091] Inputting the target data information into the physical system model to construct a corresponding relationship between the physical element and the outage rate under different operating conditions;

[0092] According to the corresponding relationship, the failure rate and repair time corresponding to the physical element are calculated.

[0093] In some modified embodiments, the second processing unit 22 is specifically configured to:

[0094] Using the first processing capability of the information system model, obtaining equipment operation status information, fault diagnosis cycle and effect data, early warning data and algorithm accuracy data;

[0095] Processing the equipment operation status information, the fault diagnosis cycle and effect data, the warning data and the algorithm accuracy data based on the first processing capability, and outputting a real-time outage rate, a developmental failure rate and a destructive failure rate;

[0096] Using the second processing capability of the information system model, obtaining information transmission punctuality rate, information transmission accuracy rate, and secondary equipment failure rate;

[0097] Process the information transmission punctuality rate, the information transmission accuracy rate, and the secondary equipment failure rate based on the second processing capability, and output channel information transmission punctuality rate, channel information transmission accuracy rate, and channel topology effectiveness data;

[0098] Based on the real-time outage rate, the developmental failure rate and the destructive failure rate, as well as the channel information transmission punctuality rate, the channel information transmission accuracy rate and the channel topology validity data, the failure rate corresponding to the physical element is updated.

[0099] In some modified embodiments, in response to the power conservation solution, the third processing unit 23 is specifically used to:

[0100] Using the third processing capability of the social system model to obtain historical inspection data and historical fault data;

[0101] Based on the third processing capability, using a maximum likelihood estimation method to estimate the probability of defect occurrence and the time delay parameter;

[0102] Based on the third processing capability, the failure rate corresponding to the physical element is updated using the defect occurrence probability and the time delay parameter.

[0103] In some modified embodiments, in response to the emergency repair plan, the third processing unit 23 is further specifically used for:

[0104] Based on the fourth processing capability of the social system model, historical emergency repair data is obtained, wherein the historical emergency repair data at least includes: repair personnel data, material data, vehicle data, repair time of each repair personnel for the fault, and geographical distance data between the fault and the repair personnel;

[0105] Based on the fourth processing capability and the historical emergency repair data, construct an emergency repair fault repair time model;

[0106] The emergency repair fault restoration time model is used to update the restoration time corresponding to the physical element.

[0107] The multi-dimensional collaborative distribution network reliability assurance device provided in the embodiment of the present application includes a processor and a memory. The above-mentioned first processing unit, second processing unit, third processing unit and construction unit are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

[0108] The processor contains a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and by adjusting the kernel parameters, the "failure rate and repair time" affected by the interaction of information, physics, and social multi-information is provided, realizing the multi-dimensional coordination from the perspective of information, physics, and society, thereby providing better and more reliable distribution network monitoring data for building distribution network reliability indicators, and responding to the distribution network engineering of large-scale events, so as to provide a better reliability guarantee solution for the distribution network.

[0109] An embodiment of the present application provides a storage medium on which a program is stored. When the program is executed by a processor, the multi-dimensional collaborative distribution network reliability assurance method is implemented.

[0110] An embodiment of the present application provides a processor, which is used to run a program, wherein the multi-dimensional coordinated distribution network reliability assurance method is executed when the program is running.

[0111] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program for initializing the steps of a distribution network reliability assurance method with multi-dimensional collaboration.

[0112] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0113] In a typical configuration, the device includes one or more processors (CPU), memory and bus. The device may also include input / output interface, network interface and the like.

[0114] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip. The memory is an example of a computer-readable medium.

[0115] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0116] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0117] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0118] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A multi-dimensional coordinated distribution network reliability assurance method, characterized in that: The method comprises: Processing the target data information using the physical system model corresponding to the distribution network, and outputting the failure rate and repair time corresponding to the physical element, wherein the target data information at least includes: the physical system distribution network topology and the historical failure rate information, historical repair time information and historical operating condition information of the physical element; The method of processing the target data information by using the physical system model corresponding to the distribution network and outputting the failure rate and repair time corresponding to the physical component includes: inputting the target data information into the physical system model, constructing the corresponding relationship between the physical component and the outage rate under different operating conditions; and calculating the failure rate and repair time corresponding to the physical component according to the corresponding relationship; The failure rate corresponding to the physical element is updated by using the first processing capability and the second processing capability provided by the information system model corresponding to the distribution network, wherein the information system model has two processing functions, including: a first processing function consisting of primary equipment status monitoring, fault diagnosis and environmental early warning, and a second processing function consisting of secondary equipment data perception and panoramic imaging; Wherein, using the first processing capability and the second processing capability provided by the information system model corresponding to the distribution network to update the failure rate corresponding to the physical component includes: Using the first processing capability of the information system model, obtaining equipment operation status information, fault diagnosis cycle and effect data, early warning data and algorithm accuracy data; Processing the equipment operation status information, the fault diagnosis cycle and effect data, the warning data and the algorithm accuracy data based on the first processing capability, and outputting a real-time outage rate, a developmental failure rate and a destructive failure rate; Using the second processing capability of the information system model, obtaining information transmission punctuality rate, information transmission accuracy rate, and secondary equipment failure rate; Process the information transmission punctuality rate, the information transmission accuracy rate, and the secondary equipment failure rate based on the second processing capability, and output channel information transmission punctuality rate, channel information transmission accuracy rate, and channel topology effectiveness data; Based on the real-time outage rate, the developmental failure rate, and the destructive failure rate, as well as the channel information transmission punctuality rate, the channel information transmission accuracy rate, and the channel topology validity data, updating the failure rate corresponding to the physical element; The failure rate and the repair time corresponding to the physical element are updated by using the third processing capability and the fourth processing capability provided by the social system model corresponding to the distribution network, wherein the social system model has two processing functions, including: a third processing function for implementing a power protection plan by responding to the scheduling of patrol personnel, and a fourth processing function for responding to an emergency repair plan; Wherein, the third processing capability and the fourth processing capability provided by the social system model corresponding to the distribution network are used to update the failure rate and the repair time corresponding to the physical element, and applied to the power supply protection solution, including: Using the third processing capability of the social system model to obtain historical inspection data and historical fault data; Based on the third processing capability, using a maximum likelihood estimation method to estimate the probability of defect occurrence and the time delay parameter; Based on the third processing capability, using the defect occurrence probability and the time delay parameter, updating the failure rate corresponding to the physical element; Based on the failure rate corresponding to the physical components updated according to the information system model, and based on the failure rate and repair time corresponding to the physical components updated according to the social system model, a reliability index corresponding to the distribution network is constructed, which is used to provide reliability assurance for the distribution network.

2. The method according to claim 1, characterized in that The utilizing the third processing capability and the fourth processing capability provided by the social system model, based on the data processing capability provided by the social system model, to update the failure rate and the repair time corresponding to the physical component, in response to an emergency repair plan, includes: Based on the fourth processing capability of the social system model, historical emergency repair data is obtained, wherein the historical emergency repair data at least includes: repair personnel data, material data, vehicle data, repair time of each repair personnel for the fault, and geographical distance data between the fault and the repair personnel; Based on the fourth processing capability and the historical emergency repair data, construct an emergency repair fault repair time model; The emergency repair fault restoration time model is used to update the restoration time corresponding to the physical element.

3. A multi-dimensional coordinated distribution network reliability assurance device, characterized in that: The device comprises: A first processing unit is used to process target data information using a physical system model corresponding to the distribution network, and output a failure rate and a repair time corresponding to the physical element, wherein the target data information at least includes: a physical system distribution network topology and historical failure rate information, historical repair time information, and historical operating condition information of the physical element; A second processing unit is used to update the failure rate corresponding to the physical element by using a first processing capability and a second processing capability provided by an information system model corresponding to the distribution network, wherein the information system model has two processing functions, including: a first processing function consisting of primary equipment status monitoring, fault diagnosis and environmental early warning, and a second processing function consisting of secondary equipment data perception and panoramic imaging; The third processing unit is used to update the failure rate and the repair time corresponding to the physical element by using the third processing capacity and the fourth processing capacity provided by the social system model corresponding to the distribution network, wherein the social system model has two processing functions, including: a third processing function for implementing a power protection plan by responding to the scheduling of patrol personnel, and a fourth processing function for responding to an emergency repair plan; A construction unit, configured to construct a reliability index corresponding to the distribution network based on the failure rate corresponding to the physical component updated using the information system model, and the failure rate and repair time corresponding to the physical component updated using the social system model, so as to provide reliability assurance for the distribution network; Wherein, the first processing unit is specifically used for: Inputting the target data information into the physical system model to construct a corresponding relationship between the physical element and the outage rate under different operating conditions; According to the corresponding relationship, calculating the failure rate and repair time corresponding to the physical element; Wherein, the second processing unit is specifically used for: Using the first processing capability of the information system model, obtaining equipment operation status information, fault diagnosis cycle and effect data, early warning data and algorithm accuracy data; Processing the equipment operation status information, the fault diagnosis cycle and effect data, the warning data and the algorithm accuracy data based on the first processing capability, and outputting a real-time outage rate, a developmental failure rate and a destructive failure rate; Using the second processing capability of the information system model, obtaining information transmission punctuality rate, information transmission accuracy rate, and secondary equipment failure rate; Process the information transmission punctuality rate, the information transmission accuracy rate, and the secondary equipment failure rate based on the second processing capability, and output channel information transmission punctuality rate, channel information transmission accuracy rate, and channel topology effectiveness data; Based on the real-time outage rate, the developmental failure rate, and the destructive failure rate, as well as the channel information transmission punctuality rate, the channel information transmission accuracy rate, and the channel topology validity data, updating the failure rate corresponding to the physical element; Wherein, the third processing unit is specifically used for: Utilize the third processing capability of the social system model to obtain historical inspection data and historical fault data; based on the third processing capability, use the maximum likelihood estimation method to estimate the probability of defect occurrence and time delay parameters; based on the third processing capability, use the defect probability and the time delay parameters to update the failure rate corresponding to the physical component.

4. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the multi-dimensional collaborative distribution network reliability assurance method as claimed in claim 1 or 2 is implemented.

5. An electronic device, characterized in that: The device includes at least one processor, and at least one memory and a bus connected to the processor; Wherein, the processor and the memory communicate with each other through the bus; The processor is used to call the program instructions in the memory to execute the multi-dimensional collaborative distribution network reliability assurance method as described in claim 1 or 2.

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