Weak link determination method, device, and nonvolatile storage medium

Abstract

The application discloses a weak link determination method and device and a nonvolatile storage medium. The method comprises the following steps: acquiring position information of nodes in a power distribution network and wind information of a region where the power distribution network is located; constructing a failure rate model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network, wherein the failure rate model is a model for predicting a failure probability of the power distribution network caused by wind factors; constructing a power supply model corresponding to the nodes in the power distribution network; determining a weak degree corresponding to the nodes in the power distribution network based on the power supply model and the failure rate model corresponding to the nodes in the power distribution network; and determining a weak link of the power distribution network based on the weak degree corresponding to the nodes in the power distribution network. The application solves the technical problem that the wind factors have an impact on the operation of the power distribution network without considering the weak link of the power distribution network.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power electronics, and in particular to a weak link determination method and device and a nonvolatile storage medium. BACKGROUND

[0002] When typhoons or heavy rain occur, different situations of different nodes in the power distribution network are not considered, which leads to the influence of typhoons on the operation of the power distribution network. The broken line and pole accidents caused by typhoons can directly affect the power transmission of the power grid and endanger the safe and stable operation of the power distribution network and the development of social production.

[0003] At present, no effective solution has been proposed for the above problems. SUMMARY

[0004] The embodiments of the present application provide a weak link determination method, device and nonvolatile storage medium to at least solve the technical problem that the wind factor affects the operation of the power distribution network due to the failure to consider the weak link of the power distribution network.

[0005] According to an aspect of an embodiment of the present application, a weak link determination method is provided, including: obtaining position information of nodes in a power distribution network and wind information of a region where the power distribution network is located; constructing a failure rate model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network, wherein the failure rate model is a model for predicting the probability of a power distribution network failure caused by a wind factor; constructing a power supply model corresponding to the nodes in the power distribution network; determining a weak degree corresponding to the nodes in the power distribution network based on the power supply model and the failure rate model corresponding to the nodes in the power distribution network; and determining a weak link of the power distribution network based on the weak degree corresponding to the nodes in the power distribution network.

[0006] Optionally, the constructing of the failure rate model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network includes: constructing a wind change model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network; obtaining a maximum bearable wind corresponding to the nodes in the power distribution network; and constructing the failure rate model corresponding to the nodes in the power distribution network based on the wind change model corresponding to the nodes in the power distribution network and the maximum bearable wind corresponding to the nodes in the power distribution network.

[0007] Optionally, the power supply model corresponding to the nodes in the power distribution network includes at least one of the following: a wind turbine power supply model, an electric vehicle reverse power supply model, an energy storage device power supply model, and a gas turbine power supply model.

[0008] Optionally, in the case that the power supply model corresponding to the node in the power distribution network comprises a wind turbine power supply model, the method further comprises: constructing a wind power change model corresponding to the node in the power distribution network according to the wind power information and the position information of the node in the power distribution network; and determining the wind turbine power supply model corresponding to the node in the power distribution network according to the wind power change model corresponding to the node in the power distribution network and the operation information of the wind turbine corresponding to the node in the power distribution network.

[0009] Optionally, determining the weakness degree corresponding to the node in the power distribution network based on the power supply model corresponding to the node in the power distribution network and the failure rate model comprises: obtaining a weight corresponding to each of a plurality of load types; determining a total load corresponding to the node in the power distribution network based on the weight corresponding to each of the plurality of load types and the load type corresponding to the node in the power distribution network; determining a load loss corresponding to the node in the power distribution network according to the total load corresponding to the node in the power distribution network and the power supply model corresponding to the node in the power distribution network; and determining the weakness degree corresponding to the node in the power distribution network according to the load loss corresponding to the node in the power distribution network and the failure rate model corresponding to the node in the power distribution network.

[0010] Optionally, the wind power information of the region where the power distribution network is located comprises wind power information of the region where the power distribution network is located at a plurality of historical time points, and the wind power information comprises at least one of the following: wind speed, wind port position, and size of a wind power influence region.

[0011] Optionally, determining the weak link of the power distribution network based on the weakness degree corresponding to the node in the power distribution network comprises: sorting the nodes in the power distribution network based on the weakness degree corresponding to the node in the power distribution network to obtain a node sequence; and determining the weak link of the power distribution network according to the node sequence.

[0012] According to another aspect of the embodiments of the present application, a weak link determination apparatus is further provided, comprising: an acquisition module configured to acquire position information of a node in a power distribution network and wind power information of a region where the power distribution network is located; a first construction module configured to construct a failure rate model corresponding to the node in the power distribution network according to the wind power information and the position information of the node in the power distribution network, wherein the failure rate model is a model for predicting a probability of a wind power factor causing a failure of the power distribution network; a second construction module configured to construct a power supply model corresponding to the node in the power distribution network; a first determination module configured to determine a weakness degree corresponding to the node in the power distribution network based on the power supply model corresponding to the node in the power distribution network and the failure rate model; and a second determination module configured to determine a weak link of the power distribution network based on the weakness degree corresponding to the node in the power distribution network.

[0013] According to still another aspect of the embodiments of the present application, a non-volatile storage medium is further provided, which comprises a stored program, wherein when the program is run, the non-volatile storage medium controls a device where the non-volatile storage medium is located to execute any one of the weak link determination methods described above.

[0014] According to still another aspect of the embodiments of the present application, a computer device is provided, which comprises a processor configured to execute a program, wherein the program, when executed, implements any of the above-mentioned weak link determination methods.

[0015] According to still another aspect of the embodiments of the present application, a computer program product is provided, which comprises a computer program configured to implement any of the above-mentioned weak link determination methods when executed by a processor.

[0016] In the embodiments of the present application, the weak link determination method is adopted, the position information of the nodes in the power distribution network and the wind information of the region where the power distribution network is located are acquired, the fault rate model corresponding to the nodes in the power distribution network is constructed according to the wind information and the position information of the nodes in the power distribution network, wherein the fault rate model is a model for predicting the probability of the wind factor causing the fault of the power distribution network, the power supply model corresponding to the nodes in the power distribution network is constructed, the weak degree corresponding to the nodes in the power distribution network is determined based on the power supply model and the fault rate model corresponding to the nodes in the power distribution network, and the weak link of the power distribution network is determined based on the weak degree corresponding to the nodes in the power distribution network, so as to achieve the purpose of determining the position in the power distribution network which is easily affected by the wind, thereby realizing the technical effect of effectively improving the resilience of the power distribution network and reducing the loss, and further solving the technical problem that the influence of the wind factor on the operation of the power distribution network is caused due to the failure to consider the weak link of the power distribution network. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are included to provide a further understanding of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and serve to explain the present application. In the drawings:

[0018] Figure 1 Fig. 1 shows a hardware structure block diagram of a computer terminal for implementing the weak link determination method;

[0019] Figure 2 Fig. 2 is a flow schematic diagram of the weak link determination method according to the embodiments of the present application;

[0020] Figure 3 Fig. 3 is a structure block diagram of the weak link determination device according to the embodiments of the present application. DETAILED DESCRIPTION

[0021] In order to enable persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by persons skilled in the art without creative labor should fall within the scope of protection of the present application.

[0022] It should be noted that the terms "first", "second", and the like in the description and in the claims of the present application and in the above-described drawings are intended to distinguish similar objects and not necessarily to describe a particular sequential or chronological order. It is to be understood that the use of such terms herein is merely for distinguishing between objects in order to more clearly describe the embodiments of the application described herein and the terms so used are not necessarily used in their normal order so that explicit reference to one term preceding or following another is not understood. Moreover, the terms "comprise", "have", and any variations thereof are intended to cover a non-exclusive inclusion, for example, a process, method, article, or apparatus that comprises a list of steps or units can not necessarily be limited to those steps or units, but can include additional steps or units not expressly listed or inherent to such process, method, article, or apparatus.

[0023] According to an embodiment of the present application, a method embodiment of a weak link determination method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown.

[0024] The method embodiment provided by the embodiment of the present application can be executed in a mobile terminal, a computer terminal, or a similar computing device. Figure 1 A hardware structure block diagram of a computer terminal for implementing a weak link determination method is shown. As shown in Figure 1 , the computer terminal 10 can include one or more (shown in the figure as 102a, 102b, …, 102n) processors (the processor can include but not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data. In addition, it can also include a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which can be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. Those skilled in the art can understand that Figure 1 The structure shown is only schematic, which does not limit the structure of the above-mentioned electronic device. For example, the computer terminal 10 can include more or fewer components than those shown in Figure 1 , or have a different configuration than that shown in Figure 1 .

[0025] It should be noted that the one or more processors and / or other data processing circuitry described above can be referred to herein generally as "data processing circuitry". The data processing circuitry can be embodied in whole or in part as software, hardware, firmware, or any combination thereof. In addition, the data processing circuitry can be a single standalone processing module, or incorporated in whole or in part within any one of the other elements of the computer terminal 10. As referred to in embodiments of the present application, the data processing circuitry functions as a processor to control, for example, the selection of the variable resistance terminal path in connection with the interface.

[0026] The memory 104 can be used to store software programs of application software and modules, such as program instructions / data storage means corresponding to the weak link determination method in embodiments of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, implements the weak link determination method of the application program described above. The memory 104 can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 can further include a memory disposed remotely with respect to the processor, which can be connected to the computer terminal 10 through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0027] The display can be, for example, a touch screen type liquid crystal display (LCD) that can enable a user to interact with the user interface of the computer terminal 10.

[0028] Figure 2 is a flowchart of the weak link determination method provided according to embodiments of the present application, as shown in Figure 2 The method comprises the following steps:

[0029] In step S202, the position information of the nodes in the power distribution network and the wind information of the area where the power distribution network is located are obtained.

[0030] In this step, the position information of the nodes in the power distribution network is obtained. The power distribution network can include multiple lines, and each line can have multiple nodes. The total number of nodes and the positions of the nodes can be obtained. Because the positions of the nodes are different, the influence of the wind and the devices that can be powered can be different. Because the influence of the wind on the power distribution network needs to be considered, the wind information of the area where the power distribution network is located needs to be obtained. The wind information can be obtained from historical wind data, such as historical wind speed, wind direction, etc.

[0031] In step S204, a failure rate model corresponding to the nodes in the power distribution network is constructed according to the wind power information and the position information of the nodes in the power distribution network, wherein the failure rate model is a model for predicting the probability of failure of the power distribution network caused by wind power factors.

[0032] In this step, a failure rate model corresponding to the nodes in the power distribution network can be constructed according to the wind power information and the position information of the nodes in the power distribution network. The failure rate model is a model for predicting the probability of failure of the power distribution network caused by wind power factors. Specifically, a wind speed change model corresponding to different nodes can be determined according to the wind power information and the position information of the nodes in the power distribution network. According to the wind speed change model and the maximum wind speed that can be tolerated by different nodes in the power distribution network, a failure rate model corresponding to different nodes can be determined. Different nodes have different positions and lines, and have different tolerances to wind disasters. By selecting weak links in the power distribution network, protective measures can be taken in advance to avoid failure of the power distribution network and normal operation during a typhoon or other wind disasters.

[0033] In step S206, a power supply model corresponding to the nodes in the power distribution network is constructed.

[0034] In this step, a power supply model corresponding to different nodes in the power distribution network can be constructed. The power supply model can be a model that can provide power to the power distribution network under the influence of wind power. For example, wind turbines, energy storage systems, and the like can provide power to the power distribution network under the influence of wind power. Considering the characteristics of multiple types of resources in the power distribution network, the weak links in the power distribution network can be better determined. Under the influence of wind power, multiple resources that can supply power to the power distribution network are analyzed to determine the load that can be tolerated, and then the load shortage can be determined, which can better determine the weak links of the line. The greater the load shortage of a node, the greater the influence of wind power factors on the node, and therefore the node can be a weak link in the power distribution network.

[0035] In step S208, the weak degree corresponding to the nodes in the power distribution network is determined based on the power supply model and the failure rate model corresponding to the nodes in the power distribution network.

[0036] In this step, the weak degree corresponding to the nodes in the power distribution network can be determined based on the power supply model and the failure rate model corresponding to the nodes in the power distribution network. The weak degree can consider not only the load shortage, i.e., the load that cannot be met under the influence of wind power, but also the consumption cost under the influence of wind power factors, such as the reverse power supply fee for electric vehicle users when the electric vehicle is used for reverse power supply in the power supply model. Therefore, the weak degree corresponding to different nodes in the power distribution network can be determined by considering multiple factors, which can more comprehensively evaluate the flexibility of the power distribution network.

[0037] Step S210: Based on the degree of weakness of the nodes in the distribution network, determine the weak links of the distribution network.

[0038] In this step, based on the vulnerability levels of nodes in the distribution network, weak links can be identified. Specifically, nodes with vulnerability levels below a preset threshold can be selected as weak links. Alternatively, the vulnerability levels of multiple nodes can be sorted in descending order, and a fixed number of nodes can be selected as weak links. Identifying weak links in the distribution network can reduce the probability of network failures under wind-related disasters such as typhoons, improve the resilience of the distribution network, and reduce losses.

[0039] Through the above steps, the purpose of identifying locations in the distribution network that are susceptible to wind impact is achieved, thereby effectively improving the resilience of the distribution network and reducing losses. This also solves the technical problem of the impact of wind factors on the operation of the distribution network due to the failure to consider weak links in the distribution network.

[0040] As an optional embodiment, a failure rate model corresponding to a node in the distribution network is constructed based on wind information and the location information of nodes in the distribution network, including: constructing a wind change model corresponding to a node in the distribution network based on wind information and the location information of nodes in the distribution network; obtaining the maximum wind load capacity corresponding to a node in the distribution network; and constructing a failure rate model corresponding to a node in the distribution network based on the wind change model corresponding to a node in the distribution network and the maximum wind load capacity corresponding to a node in the distribution network.

[0041] Optionally, the failure rate model can be constructed by first building a wind force variation model for different nodes based on wind information and the location information of nodes in the distribution network. The wind force variation model can be a wind speed variation model. Then, the maximum wind load capacity corresponding to the node in the distribution network is obtained. Based on the maximum wind load capacity and the wind speed variation model, the failure rate model corresponding to the node can be determined.

[0042] Specifically, the current location of the typhoon center can be determined based on historical typhoon data. Maximum wind speed radius Wind speed at the radius of maximum wind speed Total number of distribution network nodes Location of each node in the power distribution network and the center location of each line in the power distribution network Then, a model of historical wind speed variation at various locations in the distribution network is constructed. For each node in the distribution network, the historical wind speed variation is... , ,in, These are parameters for determining the location of nodes in the distribution network; they are 0-1 variables used to determine the location of nodes. Compared to the location of the radius of maximum wind speed, for to distance, The intensity attenuation coefficient, For nodes of Real-time historical wind speed. For distribution network lines, since the length of the distribution network lines is relatively small compared to the scale of the typhoon's wind speed impact range, it can be assumed that the historical wind speed is consistent at all points on a single line. The average wind speed location is taken as the center of the line, and an effective historical wind speed variation model is established: , ,in, This is a parameter for determining the center location of power distribution network lines; it is a 0-1 variable used to determine the line's position. The center point relative to the radius of the point with the maximum wind speed. for to distance, The angle between the line and the wind direction. For the line exist Effective historical wind speed at any given time. The ratio of historical wind speed to actual wind speed along the line is... , The relationship between the line's design wind speed (i.e., the maximum wind force it can withstand) and the line's historical failure rate and historical wind speed ratio is as follows: ,in, For the line's historical failure rate, and These are the disaster experience parameters for the power distribution network, which can be determined based on the historical experience of relevant personnel. Assuming the typhoon begins to affect the distribution network from time 0, then when... At this point, it can be assumed that there is no impact, so All are taken as 0.

[0043] As an optional embodiment, the power supply model corresponding to the node in the distribution network includes at least one of the following: wind turbine power supply model, electric vehicle reverse power supply model, energy storage device power supply model, and gas turbine power supply model.

[0044] As an optional embodiment, when the power supply model corresponding to the node in the distribution network includes a wind turbine power supply model, the method further includes: constructing a wind force change model corresponding to the node in the distribution network based on wind force information and the location information of the node in the distribution network; and determining the wind turbine power supply model corresponding to the node in the distribution network based on the wind force change model corresponding to the node in the distribution network and the operation information of the wind turbine corresponding to the node in the distribution network.

[0045] Optionally, the power supply model corresponding to the node can include a wind turbine power supply model, which refers to the process of converting wind energy into electrical energy by a wind turbine, which usually includes components such as wind turbines, converters, generators, etc., and realizes power supply to the power grid through a control system. The electric vehicle reverse power supply model refers to the electric vehicle as an energy storage device, which can provide power to the power grid when needed. This mode is called "vehicle-to-grid" or "V2G (Vehicle-to-Grid)". The energy storage device power supply model refers to various types of energy storage devices (such as lithium batteries, super capacitors, etc.) storing electrical energy and supplying power to the power grid or providing backup power support when needed. The gas turbine power supply model refers to using a gas turbine to generate electricity by burning gas to drive a generator to generate electricity, and then supplying power to the power grid.

[0046] Specifically, the wind turbine is usually installed near the distribution network node, and the wind speed it experiences is the wind speed at the distribution network node. The wind speed can be determined according to the wind speed change model. Aggregating multiple wind turbines at a single node into a single wind turbine for processing can construct its disaster output model: The cut-in wind speed, rated wind speed and cut-out wind speed of the wind turbine, respectively, the cut-in wind speed refers to the minimum wind speed required for the wind turbine to start rotating and generating electricity. The rated wind speed refers to the wind speed at which the wind turbine can output electricity at rated power. The cut-out wind speed refers to the wind speed at which the wind turbine stops running to avoid damage to the wind turbine when the wind speed reaches a certain height. The wind speed interval coefficient of the wind turbine, all of which are 0-1 variables, represents the wind speed interval of the wind turbine, The active power output of the wind turbine under the current disaster wind speed, The maximum active power output of the wind turbine. The electric vehicle disaster reverse power supply model, that is, the electric vehicle reverse power supply model can be determined according to The node The electric vehicle disaster reverse power supply power, The maximum electric vehicle disaster reverse power supply power, The electric vehicle disaster excitation rate of the node The remaining electric energy holding capacity of the electric vehicle, The electric vehicle disaster reverse power supply power, The electric vehicle disaster reverse power supply power, to​​​​​​​​​​​​ time length of the time period, and respectively represent the node maximum and minimum electric energy reserves of the electric vehicle, represent the electric vehicle reverse power supply unit electric quantity incentive cost, the incentive cost provides the reverse power supply fee to the electric vehicle user when the electric vehicle reverse power supply, represent incentive cost rate at the moment. Establishing the energy storage device power supply model is that when the line fault is caused by typhoon disaster, the energy storage device works in the discharge state to supply power to the power grid, and the model can be , , wherein, represent the energy storage discharge power, represent the maximum discharge power of the energy storage, represent the remaining electric quantity of the energy storage, is the discharge coefficient of the energy storage device, and respectively represent the maximum and minimum storage electric quantity of the energy storage device. Establishing the gas turbine power supply model can be wherein, represent the gas turbine active power output, and respectively represent the maximum and minimum active power output of the gas turbine.

[0047] As an optional embodiment, based on the power supply model and the fault rate model corresponding to the nodes in the power distribution network, the weakness degree corresponding to the nodes in the power distribution network is determined, comprising: obtaining the weights corresponding to a plurality of load types respectively; based on the weights corresponding to a plurality of load types respectively, according to the load type corresponding to the nodes in the power distribution network, determining the total load corresponding to the nodes in the power distribution network; according to the total load corresponding to the nodes in the power distribution network and the power supply model corresponding to the nodes in the power distribution network, determining the load loss corresponding to the nodes in the power distribution network; according to the load loss corresponding to the nodes in the power distribution network and the fault rate model corresponding to the nodes in the power distribution network, determining the weakness degree corresponding to the nodes in the power distribution network.

[0048] Optionally, the weights corresponding to a plurality of load types respectively can be obtained. For example, the nodes of the power distribution network are divided into primary load, secondary load and tertiary load according to the load type, and the weights are respectively 100, 10 and 1, and the load grade identification parameters of each node are , and All variables are 0-1. Basic power facilities can be considered as primary loads, i.e., relatively important loads. The primary load may differ in different regions. Generally, industrial and commercial electricity consumption is considered very important loads because they are crucial for maintaining economic operation and social life. If industrial facilities and commercial establishments in a region experience a power outage, it will severely impact local production, transportation, communication, and other aspects. The total load corresponding to each node in the distribution network is determined based on the load type of that node. Specifically, the load weight of each node is... It can be Based on the total load corresponding to a node in the distribution network and the power supply model corresponding to the node, the load loss corresponding to node i in the distribution network can be determined as follows: in, This represents the node-weighted load loss. This indicates the power required by the node load under normal operating conditions. Represents a node Upstream node transmission power, Represents a node Power is transmitted to lower-level nodes. To determine the active power output of wind turbines under the current record-breaking wind speeds, Represents a node Electric vehicle reverse power supply during disasters Indicates the energy storage's disaster recovery discharge power. This represents the active power output of the gas turbine during disasters. After determining the load loss, the vulnerability level of the corresponding node can be determined based on the load loss and failure rate model.

[0049] By comprehensively considering the line failure rate, the weighted load loss of nodes under line failure, and the incentive cost of reverse energy supply from electric vehicles under typhoon disasters, a sequential weakness index for distribution network lines under typhoon disasters is established to assess the weakness of each line, which can more comprehensively evaluate the resilience of the power grid.

[0050] As an optional embodiment, the wind information of the distribution network area includes wind information of the distribution network area at multiple historical moments, wherein the wind information includes at least one of the following: wind speed, wind outlet location, and size of the wind-affected area.

[0051] Optionally, the acquired wind information can include wind speed, wind gap location, and the size of the wind-affected area at multiple historical moments. Typically, typhoons have a center, and the location of the typhoon center and the radius of maximum wind speed can also be obtained; these values ​​all reflect the magnitude of the wind.

[0052] As an optional embodiment, the weak link of the power distribution network is determined based on the weakness degree corresponding to the nodes in the power distribution network, comprising: sorting the nodes in the power distribution network based on the weakness degree corresponding to the nodes in the power distribution network to obtain a node sequence; and determining the weak link of the power distribution network according to the node sequence.

[0053] Optionally, the nodes in the power distribution network can be sorted according to the weakness degree corresponding to the nodes in the power distribution network to obtain a node sequence. Then the weak link of the power distribution network can be determined according to the node sequence. Specifically, the obtained power distribution network line disaster sequence weak index (weakness degree) is sorted, and the larger the weak index value is, the higher the line weakness degree is, thereby identifying the weak link of the power distribution network line.

[0054] It should be noted that, for the foregoing method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited by the action sequence described, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily necessary for the present application.

[0055] Through the description of the above embodiments, those skilled in the art can clearly understand that the weak link determination method according to the above embodiments can be realized by means of software and the necessary general hardware platform, of course, it can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes a plurality of instructions for making a terminal device (which can be a mobile phone, computer, server, or network device, etc.) execute the method described in each embodiment of the present application.

[0056] According to the embodiments of the present application, a weak link determination device for implementing the above weak link determination method is also provided, Figure 3 The structure block diagram of the weak link determination device provided by the embodiments of the present application is shown in Figure 3 As shown in the figure, the weak link determination device comprises an acquisition module 302, a first construction module 304, a second construction module 306, a first determination module 308 and a second determination module 310, and the weak link determination device will be described below.

[0057] The acquisition module 302 is used for acquiring the position information of the nodes in the power distribution network and the wind information of the area where the power distribution network is located.

[0058] The first construction module 304 is connected with the acquisition module 302, and is configured to construct a fault rate model corresponding to the nodes in the power distribution network according to the wind power information and the position information of the nodes in the power distribution network, wherein the fault rate model is a model for predicting the probability of the power distribution network failure caused by the wind power factor.

[0059] The second construction module 306 is connected with the first construction module 304, and is configured to construct a power supply model corresponding to the nodes in the power distribution network.

[0060] The first determination module 308 is connected with the second construction module 306, and is configured to determine the weakness degree of the nodes in the power distribution network based on the power supply model and the fault rate model corresponding to the nodes in the power distribution network.

[0061] The second determination module 310 is connected with the first determination module 308, and is configured to determine the weak link of the power distribution network based on the weakness degree of the nodes in the power distribution network.

[0062] It should be noted that the acquisition module 302, the first construction module 304, the second construction module 306, the first determination module 308 and the second determination module 310 correspond to steps S202 to S210 in the embodiments, and the multiple modules have the same instances and application scenarios as the corresponding steps, but are not limited to the contents disclosed in the above embodiments. It should be noted that the above modules as part of the device can run in the computer terminal 10 provided in the embodiments.

[0063] The embodiments of the present application can provide a computer device. Optionally, in the present embodiment, the computer device can be located in at least one network device of multiple network devices of a computer network. The computer device comprises a memory and a processor.

[0064] The memory can be used to store software programs and modules, such as program instructions / modules corresponding to the weak link determination method and device in the embodiments of the present application. The processor executes the software programs and modules stored in the memory, thereby performing various functional applications and data processing, i.e., implementing the above-mentioned weak link determination method. The memory can include a high-speed random access memory, and can further include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory can further include a memory remotely arranged with respect to the processor, and the remote memory can be connected to the computer terminal through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0065] The processor can call information and application programs stored in the memory through the transmission device to execute the following steps: obtaining position information of nodes in the power distribution network and wind information of an area where the power distribution network is located; constructing a failure rate model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network, wherein the failure rate model is a model for predicting the probability of the power distribution network failure caused by wind factors; constructing a power supply model corresponding to the nodes in the power distribution network; determining the weakness degree corresponding to the nodes in the power distribution network based on the power supply model and the failure rate model corresponding to the nodes in the power distribution network; and determining the weak link of the power distribution network based on the weakness degree corresponding to the nodes in the power distribution network.

[0066] Optionally, the processor can further execute program codes of the following steps: constructing the failure rate model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network, comprising: constructing a wind change model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network; obtaining the maximum bearable wind corresponding to the nodes in the power distribution network; and constructing the failure rate model corresponding to the nodes in the power distribution network based on the wind change model corresponding to the nodes in the power distribution network and the maximum bearable wind corresponding to the nodes in the power distribution network.

[0067] Optionally, the processor can further execute program codes of the following steps: the power supply model corresponding to the nodes in the power distribution network comprises at least one of the following: a wind turbine power supply model, an electric vehicle reverse power supply model, an energy storage device power supply model, and a gas turbine power supply model.

[0068] Optionally, the processor can further execute program codes of the following steps: in the case that the power supply model corresponding to the nodes in the power distribution network comprises the wind turbine power supply model, further comprising: constructing a wind change model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network; and determining the wind turbine power supply model corresponding to the nodes in the power distribution network according to the wind change model corresponding to the nodes in the power distribution network and the operation information of the wind turbine corresponding to the nodes in the power distribution network.

[0069] Optionally, the processor can further execute program codes of the following steps: determining the weakness degree corresponding to the nodes in the power distribution network based on the power supply model and the failure rate model corresponding to the nodes in the power distribution network, comprising: obtaining weights corresponding to a plurality of load types respectively; determining total load corresponding to the nodes in the power distribution network according to the load type corresponding to the nodes in the power distribution network based on the weights corresponding to the plurality of load types respectively; determining load loss corresponding to the nodes in the power distribution network according to the total load corresponding to the nodes in the power distribution network and the power supply model corresponding to the nodes in the power distribution network; and determining the weakness degree corresponding to the nodes in the power distribution network according to the load loss corresponding to the nodes in the power distribution network and the failure rate model corresponding to the nodes in the power distribution network.

[0070] Optionally, the processor can further execute program codes of the following steps: the wind information of the area where the power distribution network is located comprises wind information of the area where the power distribution network is located at a plurality of historical time points, wherein the wind information comprises at least one of the following: wind speed, wind port position, and size of a wind force affected area.

[0071] Optionally, the processor can further execute program codes of the following steps: determining the weak link of the power distribution network based on the weakness degree corresponding to the nodes in the power distribution network, comprising: sorting the nodes in the power distribution network based on the weakness degree corresponding to the nodes, to obtain a node sequence; and determining the weak link of the power distribution network according to the node sequence.

[0072] By adopting the embodiment of the present application, a weak link determination method is provided, which obtains the position information of the nodes in the power distribution network and the wind information of the area where the power distribution network is located; constructs a failure rate model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network, wherein the failure rate model is a model for predicting the probability of the wind factor causing the failure of the power distribution network; constructs a power supply model corresponding to the nodes in the power distribution network; determines the weakness degree corresponding to the nodes in the power distribution network based on the power supply model and the failure rate model corresponding to the nodes in the power distribution network; and determines the weak link of the power distribution network based on the weakness degree corresponding to the nodes in the power distribution network, so as to achieve the purpose of determining the positions in the power distribution network which are easily affected by the wind, thereby realizing the technical effect of effectively improving the resilience of the power distribution network and reducing the loss, and further solving the technical problem that the influence of the wind factor on the operation of the power distribution network is caused due to the failure to consider the weak link of the power distribution network.

[0073] Those skilled in the art can understand that all or part of the steps in the above-mentioned embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a non-volatile storage medium, which can include a flash disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0074] The embodiment of the present application further provides a non-volatile storage medium. Optionally, in the present embodiment, the non-volatile storage medium can be used to save the program codes executed by the weak link determination method provided by the above-mentioned embodiments.

[0075] Optionally, in the present embodiment, the non-volatile storage medium can be located in any one of the computer terminal in the computer terminal group in the computer network, or in any one of the mobile terminal in the mobile terminal group.

[0076] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: obtaining location information of nodes in the power distribution network and wind information of an area where the power distribution network is located; constructing a failure rate model corresponding to the nodes in the power distribution network according to the wind information and the location information of the nodes in the power distribution network, wherein the failure rate model is a model for predicting a probability of a power distribution network failure caused by wind factors; constructing a power supply model corresponding to the nodes in the power distribution network; determining a weakness degree corresponding to the nodes in the power distribution network based on the power supply model and the failure rate model corresponding to the nodes in the power distribution network; and determining a weak link of the power distribution network based on the weakness degree corresponding to the nodes in the power distribution network.

[0077] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: constructing a failure rate model corresponding to the nodes in the power distribution network according to the wind information and the location information of the nodes in the power distribution network, comprising: constructing a wind change model corresponding to the nodes in the power distribution network according to the wind information and the location information of the nodes in the power distribution network; obtaining a maximum bearable wind corresponding to the nodes in the power distribution network; and constructing the failure rate model corresponding to the nodes in the power distribution network based on the wind change model corresponding to the nodes in the power distribution network and the maximum bearable wind corresponding to the nodes in the power distribution network.

[0078] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: the power supply model corresponding to the nodes in the power distribution network comprises at least one of the following: a wind turbine power supply model, an electric vehicle reverse power supply model, an energy storage device power supply model, and a gas turbine power supply model.

[0079] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: in the case that the power supply model corresponding to the nodes in the power distribution network comprises the wind turbine power supply model, further comprising: constructing a wind change model corresponding to the nodes in the power distribution network according to the wind information and the location information of the nodes in the power distribution network; and determining the wind turbine power supply model corresponding to the nodes in the power distribution network according to the wind change model corresponding to the nodes in the power distribution network and operation information of the wind turbine corresponding to the nodes in the power distribution network.

[0080] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the weakness degree corresponding to the nodes in the power distribution network based on the power supply model and the failure rate model corresponding to the nodes in the power distribution network, comprising: obtaining a weight corresponding to each of a plurality of load types; determining a total load corresponding to the nodes in the power distribution network according to the load type corresponding to the nodes in the power distribution network based on the weight corresponding to each of the plurality of load types; determining a load loss corresponding to the nodes in the power distribution network according to the total load corresponding to the nodes in the power distribution network and the power supply model corresponding to the nodes in the power distribution network; and determining the weakness degree corresponding to the nodes in the power distribution network according to the load loss corresponding to the nodes in the power distribution network and the failure rate model corresponding to the nodes in the power distribution network.

[0081] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: the wind information of the region where the power distribution network is located includes wind information of the region where the power distribution network is located at a plurality of historical time points, wherein the wind information includes at least one of the following: wind speed, wind port position, and size of the wind force affected area.

[0082] Optionally, in the embodiment, the non-volatile storage medium is configured to store program code for performing the following steps: determining the weak link of the power distribution network based on the weakness degree corresponding to the nodes in the power distribution network, comprising: sorting the nodes in the power distribution network based on the weakness degree corresponding to the nodes, to obtain a node sequence; and determining the weak link of the power distribution network according to the node sequence.

[0083] The embodiment of the application also provides a computer program product comprising a computer program, and optionally, in the embodiment, the computer program can be executed by a processor to achieve the following: obtaining position information of nodes in a power distribution network and wind information of a region where the power distribution network is located; constructing a failure rate model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network, wherein the failure rate model is a model for predicting the probability of power distribution network failure caused by wind factors; constructing a power supply model corresponding to the nodes in the power distribution network; determining the weakness degree corresponding to the nodes in the power distribution network based on the power supply model and the failure rate model corresponding to the nodes in the power distribution network; and determining the weak link of the power distribution network based on the weakness degree corresponding to the nodes in the power distribution network.

[0084] The above-mentioned serial numbers of the embodiments of the application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0085] In the above-mentioned embodiments of the application, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the related description of other embodiments.

[0086] In several embodiments provided in the present application, it should be understood that the disclosed technical contents can be implemented by other ways. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division way, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interfaces, units or modules, which can be electrical or other forms.

[0087] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0088] In addition, each functional unit in various embodiments of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0089] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a non-volatile storage medium. Based on this understanding, the technical solutions of the present application or the part of the present application that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in various embodiments of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various program code storage media.

[0090] The above is only the preferred embodiment of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A weak link determination method characterized by, The method comprises: obtaining position information of nodes in a power distribution network and wind information of a region where the power distribution network is located; constructing a failure rate model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network, wherein the failure rate model is a model for predicting a probability of the power distribution network failing due to wind factors; constructing a power supply model corresponding to the nodes in the power distribution network; determining a weakness degree corresponding to the nodes in the power distribution network based on the power supply model corresponding to the nodes in the power distribution network and the failure rate model; determining a weak link of the power distribution network based on the weakness degree corresponding to the nodes in the power distribution network; wherein, in the case that the power supply model corresponding to the nodes in the power distribution network comprises a wind turbine power supply model, further comprising: constructing a wind change model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network; and determining the wind turbine power supply model corresponding to the nodes in the power distribution network according to the wind change model corresponding to the nodes in the power distribution network and operation information of wind turbines corresponding to the nodes in the power distribution network; wherein, the power supply model corresponding to the nodes in the power distribution network comprises at least one of the following: a wind turbine power supply model, an electric vehicle reverse power supply model, an energy storage device power supply model, and a gas turbine power supply model; wherein, the wind change model is an effective disaster wind speed change model, and the effective disaster wind speed change model is: ， ， wherein, is a 0-1 variable used to determine whether the line is in the center of the typhoon, at the moment compared to the position of the maximum wind speed radius point, is the distance from to , is the center position of the distribution network line , is the center position of the typhoon at the current moment , is the maximum wind speed radius, is the angle between the line and the wind direction, is the effective typhoon wind speed of the line at the moment , is the intensity attenuation coefficient, is the wind speed at the maximum wind speed radius; the relationship between the line typhoon failure rate and the line typhoon wind speed ratio is wherein, is the line typhoon failure rate, and is the line typhoon experience parameter, is the line typhoon wind speed ratio, is the line design wind speed; The determining the weakness degree of the node in the power distribution network based on the power supply model and the failure rate model corresponding to the node comprises: obtaining weights corresponding to a plurality of load types respectively; determining total load corresponding to the node in the power distribution network based on the weights corresponding to the plurality of load types respectively according to the load type corresponding to the node in the power distribution network; determining load loss corresponding to the node in the power distribution network according to the total load corresponding to the node in the power distribution network and the power supply model corresponding to the node in the power distribution network; and determining the weakness degree corresponding to the node in the power distribution network according to the load loss corresponding to the node in the power distribution network and the failure rate model corresponding to the node in the power distribution network, wherein the load loss corresponding to the node in the power distribution network is wherein, represents the node weighted load loss amount, represents the power required by the node load under normal operation, represents the node the upper node transmission power, represents the node the lower node power transmission, is the active power output of the wind turbine under the current disaster wind speed, represents the node the electric vehicle disaster reverse power supply, represents the energy storage disaster discharge power, represents the gas turbine disaster active power output.

2. The method of claim 1, wherein, the constructing a failure rate model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network comprises: constructing a wind change model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network; obtaining maximum bearable wind power corresponding to the nodes in the power distribution network; constructing a failure rate model corresponding to the nodes in the power distribution network based on the wind change model corresponding to the nodes in the power distribution network and the maximum bearable wind power corresponding to the nodes in the power distribution network.

3. The method of claim 1, wherein, The wind information of the region where the power distribution network is located comprises wind information of the region where the power distribution network is located at a plurality of historical time points, wherein the wind information comprises at least one of the following: wind speed, wind port position, and size of a wind force affected area.

4. The method according to any one of claims 1 to 3, characterized in that, The determining a weak link of the power distribution network based on the weakness degree corresponding to the nodes in the power distribution network comprises: sorting the nodes in the power distribution network based on the weakness degree corresponding to the nodes in the power distribution network to obtain a node sequence; determining the weak link of the power distribution network according to the node sequence.

5. A weak link determination apparatus characterized by comprising: The method comprises: a obtaining module, configured to obtain position information of nodes in a power distribution network and wind information of a region where the power distribution network is located; a first constructing module, configured to construct a failure rate model corresponding to the nodes in the power distribution network according to the wind information and the position information of the nodes in the power distribution network, wherein the failure rate model is a model for predicting a probability of the power distribution network failing due to wind factors; a second constructing module, configured to construct a power supply model corresponding to the nodes in the power distribution network; a first determining module, configured to determine a weakness degree corresponding to the nodes in the power distribution network based on the power supply model corresponding to the nodes in the power distribution network and the failure rate model; The second determining module is configured to determine the weak link of the power distribution network based on the weakness of the node in the power distribution network. In a case where the power supply model corresponding to the node in the power distribution network comprises a wind turbine power supply model, the device is further configured to: construct a wind force change model corresponding to the node in the power distribution network according to the wind force information and the position information of the node in the power distribution network; and determine the wind turbine power supply model corresponding to the node in the power distribution network according to the wind force change model corresponding to the node in the power distribution network and operation information of the wind turbine corresponding to the node in the power distribution network. The power supply model corresponding to the node in the power distribution network comprises at least one of the following: a wind turbine power supply model, an electric vehicle reverse power supply model, an energy storage device power supply model, and a gas turbine power supply model. The wind force change model is an effective disaster wind speed change model, and the effective disaster wind speed change model is: ， ， wherein, is a 0-1 variable used to determine whether the line center is in the maximum wind speed radius point position at the time, is the distance from to , is the center position of the distribution network line , is the center position of the typhoon at the current time , is the maximum wind speed radius, is the angle between the line and the wind direction, is the effective typhoon wind speed of the line at the time , is the intensity attenuation coefficient, is the wind speed at the maximum wind speed radius; the relationship between the line typhoon failure rate and the line typhoon wind speed ratio is wherein, is the line typhoon failure rate, and is the line typhoon empirical parameter, is the line typhoon wind speed ratio, is the line design wind speed; The first determining module is configured to obtain a weight corresponding to each of a plurality of load types; determine a total load corresponding to a node in the power distribution network according to a load type corresponding to the node in the power distribution network based on the weight corresponding to each of the plurality of load types; determine a load loss corresponding to the node in the power distribution network according to a power supply model corresponding to the node in the power distribution network and the total load corresponding to the node in the power distribution network; and determine a weakness degree corresponding to the node in the power distribution network according to a failure rate model corresponding to the node in the power distribution network and the load loss corresponding to the node in the power distribution network, wherein the load loss corresponding to the node in the power distribution network is wherein, represents a node weighted load loss amount, represents a power required by a node load in a normal operation, represents a node a superior node transmission power, represents a node a subordinate node power transmission, is an active power output of a wind turbine under a current disaster wind speed, represents a node an electric vehicle disaster reverse power supply, represents a disaster discharge power of energy storage, represents a disaster active power output of a gas turbine.

6. A non-volatile storage medium, comprising: The non-volatile storage medium comprises a stored program, wherein the program controls the device in which the non-volatile storage medium is located to execute the weak link determination method in any one of claims 1 to 4 when the program is running.

7. A computer device, characterized in that, Comprise: A memory and a processor, The memory stores a computer program; The processor is configured to execute the computer program stored in the memory, and the computer program makes the processor execute the weak link determination method in any one of claims 1 to 4 when running.

8. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the weak link determination method in any one of claims 1 to 4.

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