10 kV line load reversal method and system

Abstract

The present invention provides a 10 kV line load reversal method and system, which relates to the field of electric power technology. The specific implementation scheme is: based on the load distribution characteristics of each node in the 10 kV line radial network, multiple first candidate load reversal nodes are determined in each node, and the corresponding simulation model is respectively used for the load reversal process under each first candidate node, and the line operation status of each transmission line in the network during the simulated load reversal process is monitored to obtain the line loss and load reversal allocation time of each transmission line when the simulation model performs load reversal under each first candidate node; based on this simulation data, multiple second candidate nodes are determined from multiple first candidate nodes; based on the location of the fault point in the network and the important load, a target load reversal node whose important load transfer rate meets the preset conditions is selected from multiple second candidate nodes to perform load reversal on the fault point in the 10 kV line radial network.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a 10 kV line load reversal method and system. Background Art

[0002] In a radial distribution network, such as a 10 kV radial distribution network, when performing rapid load reversal, one faces the technical challenge of how to select the optimal load reversal node.

[0003] Under the radial network topology, the load distribution of the line shows the characteristic of gradually decreasing from the power source point to the end. Different load-reversing node selection will directly affect the line loss and load-reversing time during the deployment process. If a starting point far away from the fault point is selected for load-reversing, although the important load near the fault point can be quickly transferred, the long-distance load transfer will lead to increased line loss and may cause uneven network voltage distribution, affecting the power supply quality. If a starting point close to the fault point is selected for load-reversing, although the line loss can be reduced and the load-reversing time can be shortened, it may be difficult to completely transfer the important load near the fault point, affecting the power supply reliability of important users.

[0004] Therefore, how to comprehensively consider factors such as line load distribution characteristics, fault point location, and important load distribution, optimize the selection of load reversal nodes, and while ensuring the transfer of important loads, reduce line losses and shorten load reversal time is a key technical issue in achieving rapid load reversal on 10 kV lines. Summary of the invention

[0005] The present invention provides a 10 kV line load reversal method, device, system and storage medium, which can solve at least one of the above technical problems.

[0006] According to one aspect of the present invention, a 10 kV line load reversal method is provided, comprising:

[0007] Determine the load distribution characteristics of each line node based on the load distribution data of each line node in the 10 kV line radial network;

[0008] Based on the load distribution characteristics of each of the line nodes, determining a plurality of first candidate load-reversing nodes in each of the line nodes;

[0009] For each of the first candidate load-reversal nodes, respectively simulate the load-reversal process of the simulation model corresponding to the 10 kV line radial network at the first candidate load-reversal node, and monitor the line operation status of each transmission line in the 10 kV line radial network during the simulated load-reversal process, so as to obtain the line loss and load-reversal allocation time of each of the transmission lines when the simulation model performs load-reversal at the first candidate load-reversal node;

[0010] Determine a plurality of second candidate load shedding nodes from the plurality of first candidate load shedding nodes based on the line loss and load shedding allocation time of each of the transmission lines when the simulation model performs load shedding at each of the first candidate load shedding nodes;

[0011] Based on the location of the fault point and the important load in the 10 kV line radial network, a target load-reversing node whose important load transfer rate meets the preset conditions is selected from the plurality of second candidate load-reversing nodes;

[0012] Based on the target load-reversal node, load is reversed on the fault point in the 10 kV line radial network.

[0013] According to another aspect of the present invention, there is provided a 10 kV line load reversal device, comprising:

[0014] A load characteristic determination module, for determining the load distribution characteristics of each line node based on the load distribution data of each line node in the 10 kV line radial network;

[0015] A first node screening module, configured to determine a plurality of first candidate load-reversing nodes in each of the line nodes based on the load distribution characteristics of each of the line nodes;

[0016] A load reversal simulation module, for simulating the load reversal process of the simulation model corresponding to the 10 kV line radial network at the first candidate load reversal node for each of the first candidate load reversal nodes, and monitoring the line operation status of each transmission line in the 10 kV line radial network during the simulated load reversal process, so as to obtain the line loss and load reversal allocation time of each of the transmission lines when the simulation model performs load reversal at the first candidate load reversal node;

[0017] A second node screening module, configured to determine a plurality of second candidate load-reversing nodes from the plurality of first candidate load-reversing nodes based on the line loss and load-reversing dispatching time of each of the transmission lines under each of the first candidate load-reversing nodes;

[0018] A third node screening module is used to select a target load-reversing node whose important load transfer rate meets preset conditions from among the plurality of second candidate load-reversing nodes based on the location of the fault point and the important load in the 10 kV line radial network;

[0019] The load-reversing working module is used to perform load-reversing on the fault point in the 10 kV line radial network based on the target load-reversing node.

[0020] According to another aspect of the present invention, there is provided an electronic device, comprising:

[0021] at least one processor; and

[0022] a memory communicatively connected to the at least one processor; wherein,

[0023] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any 10 kV line load reversal method in the embodiments of the present invention.

[0024] According to another aspect of the present invention, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute any 10 kV line load reversal method according to the embodiments of the present invention.

[0025] According to the technical solution of the present invention, based on the load distribution data of each line node in the 10 kV line radial network, the load distribution characteristics of each line node are determined; based on the load distribution characteristics of each line node, multiple first candidate load reversal nodes are determined in each line node; for each first candidate load reversal node, the load reversal process of the simulation model corresponding to the 10 kV line radial network under the first candidate load reversal node is simulated respectively, and the line operation status of each transmission line in the 10 kV line radial network during the simulated load reversal process is monitored to obtain the line loss and load reversal allocation time of each transmission line when the simulation model performs load reversal under the first candidate load reversal node; based on the line loss and load reversal allocation time of each transmission line under each first candidate load reversal node, multiple second candidate load reversal nodes are determined from multiple first candidate load reversal nodes; based on the location of the fault point and the important load in the 10 kV line radial network, a target load reversal node whose important load transfer rate meets the preset conditions is selected from multiple second candidate load reversal nodes; based on the target load reversal node, the fault point in the 10 kV line radial network is subjected to load reversal. In this way, we can comprehensively consider factors such as line load distribution characteristics, fault point location, and important load distribution, optimize the selection of load reversal nodes, and take into account reducing line losses and shortening load reversal time while ensuring the transfer of important loads.

[0026] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings are used to better understand the present invention and do not constitute a limitation of the present invention.

[0028] Figure 1is a flow chart of a 10 kV line load reversal method according to an embodiment of the present invention;

[0029] Figure 2 It is a structural block diagram of a circulating heat management device of liquid flow conduction according to an embodiment of the present invention;

[0030] Figure 3 The block diagram is a block diagram of an electronic device for implementing the method according to the embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be appreciated by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present invention. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0032] Figure 1 It is a flow chart of a 10 kV line load reversal method according to an embodiment of the present invention.

[0033] like Figure 1 As shown, the 10 kV line load reversal method may include:

[0034] S110, determining a load distribution characteristic of each line node based on load distribution data of each line node in the 10 kV line radial network;

[0035] S120, determining a plurality of first candidate load-reversing nodes in each line node based on the load distribution characteristics of each line node;

[0036] S130, for each first candidate load-reversal node, respectively simulate the load-reversal process of the simulation model corresponding to the 10 kV line radial network at the first candidate load-reversal node, and monitor the line operation status of each transmission line in the 10 kV line radial network during the simulated load-reversal process, so as to obtain the line loss and load-reversal allocation time of each transmission line when the simulation model performs load-reversal at the first candidate load-reversal node;

[0037] S140, determining a plurality of second candidate load shedding nodes from a plurality of first candidate load shedding nodes based on the line loss and load shedding allocation time of each transmission line when load shedding is performed at each first candidate load shedding node according to the simulation model;

[0038] S150, based on the location of the fault point and the important load in the 10 kV line radial network, selecting a target load-reversing node whose important load transfer rate meets preset conditions from a plurality of second candidate load-reversing nodes;

[0039] S160, based on the target load-reversing node, the fault point in the 10 kV line radial network is subjected to load reversal.

[0040] Understandably, load reversal is also called "load relocation" or "load shedding". By changing the operation mode of the power system, the power load is transferred from one power source node (such as a transformer, line, substation or system) to another power source node (such as a transformer, line, substation or system).

[0041] Exemplarily, the load distribution data of the line node may include the load value at each time point. For example, the load of the line node is collected every 15 minutes, and the load values ​​at 96 time points in a day can be obtained.

[0042] Exemplarily, the load distribution feature may be a load feature distributed over time, and may include a peak-to-valley ratio, a maximum load rate, a minimum load value, a load mean square error, a median load value, a quartile load, and the like.

[0043] Exemplarily, based on the load distribution characteristics of each line node, a line node that meets the load reversal condition is determined among multiple line nodes, and the line node is used as the first candidate load reversal node.

[0044] Exemplarily, a simulation model corresponding to a 10 kV line radial network is constructed in the simulation software. A power supply node is set in the simulation model. When simulating the load dumping process, the load of the power supply node is transferred to the first candidate load dumping node. Thus, the first candidate load dumping node supplies power to the user node in the 10 kV line radial network.

[0045] Exemplarily, the line operation status may include the voltage, current, impedance, etc. of the transmission line at various times.

[0046] Exemplarily, the line loss of the transmission line during the load reversal process can be calculated through the voltage, current and impedance of the transmission line at various times during the load reversal process, as well as the original load power of the power supply node.

[0047] Exemplarily, the load-reversal adjustment time can be determined by the voltage, current and impedance of the transmission line at various times during the load-reversal process. For example, the difference between the time when the current jumps from zero to a specific value and the time when the current jumps from a specific value to zero can be the load-reversal adjustment time.

[0048] Exemplarily, based on the line loss and load reversal dispatch time of each transmission line when the simulation model performs load reversal at the first candidate load reversal node, among multiple first candidate load reversal nodes, the first candidate load reversal node corresponding to which the line loss of each transmission line meets the preset line loss condition and the load reversal dispatch time of each transmission line meets the preset load reversal dispatch time condition is determined, and the first candidate load reversal node is used as the second candidate load reversal node.

[0049] Exemplarily, based on the line loss and load-reversal dispatching time of each transmission line when the simulation model performs load-reversal at the first candidate load-reversal node, the first candidate load-reversal node is scored as being permissible for load-reversal. Thus, based on the permissible load-reversal scores of each first candidate load-reversal node, a plurality of second candidate load-reversal nodes are determined from a plurality of first candidate load-reversal nodes.

[0050] According to the above implementation mode, based on the load distribution data of each line node in the 10 kV line radial network, the load distribution characteristics of each line node are determined; based on the load distribution characteristics of each line node, multiple first candidate load reversal nodes are determined in each line node; for each first candidate load reversal node, the load reversal process of the simulation model corresponding to the 10 kV line radial network under the first candidate load reversal node is simulated respectively, and the line operation status of each transmission line in the 10 kV line radial network during the simulated load reversal process is monitored to obtain the line loss and load reversal allocation time of each transmission line when the simulation model performs load reversal under the first candidate load reversal node; based on the line loss and load reversal allocation time of each transmission line under each first candidate load reversal node, multiple second candidate load reversal nodes are determined from multiple first candidate load reversal nodes; based on the location of the fault point and the important load in the 10 kV line radial network, a target load reversal node whose important load transfer rate meets the preset conditions is selected from multiple second candidate load reversal nodes; based on the target load reversal node, the fault point in the 10 kV line radial network is subjected to load reversal. In this way, we can comprehensively consider factors such as line load distribution characteristics, fault point location, and important load distribution, optimize the selection of load reversal nodes, and take into account reducing line losses and shortening load reversal time while ensuring the transfer of important loads.

[0051] In one embodiment, based on the load distribution data of each line node in a 10 kV line radial network, the load distribution characteristics of each line node are determined, including: normalizing and wavelet transforming the load data of each line node in the 10 kV line radial network to obtain the load curve of each line node; extracting the load distribution characteristics of each line node from the load curve of each line node, wherein the load distribution characteristics include load peak-to-valley ratio, maximum load rate, load mean square deviation and quartile load.

[0052] Exemplarily, the normalization process may include mapping each load to a preset interval value, for example, the interval [0, 1].

[0053] For example, a 4th-order db wavelet transform may be used to remove noise from the normalized load sequence to obtain a smooth load curve.

[0054] For example, the load distribution characteristics may reflect the power consumption pattern of the line nodes.

[0055] It can be understood that the load peak-to-valley ratio is the ratio of the maximum load to the minimum load, and is used to characterize the intensity of load fluctuation.

[0056] It can be understood that the maximum load rate is the ratio of the average load to the maximum load, and is used to characterize the load utilization rate.

[0057] It can be understood that the load mean square error is used to describe the dispersion degree of load fluctuation.

[0058] It can be understood that quartile load is used to describe the load distribution shape. For example, the distance (difference) between the upper quartile load and the lower quartile load can reflect the concentration of the load.

[0059] According to the above-mentioned implementation mode, the load distribution characteristics of each line node are determined by using the load distribution data of each line node.

[0060] In one embodiment, based on the load distribution characteristics of each line node, multiple first candidate load reversal nodes are determined in each line node, including: for each line node, based on the mapping functions corresponding to the load peak-to-valley ratio, maximum load rate, load mean square deviation and quartile load of the line node, respectively, the load peak-to-valley ratio, maximum load rate, load mean square deviation and quartile load of the line node are numerically mapped, and the mapped values ​​are weighted calculated to obtain an allowable load reversal score of the line node; based on the allowable load reversal score of each line node, multiple first candidate load reversal nodes are determined in each line node.

[0061] Exemplarily, the mapping function corresponding to the load peak-to-valley ratio is used to describe the relationship between the load peak-to-valley ratio and the load fluctuation intensity. The larger the load peak-to-valley ratio, the greater the load fluctuation intensity, and the smaller the corresponding allowable reverse load score. Therefore, the larger the load peak-to-valley ratio, the smaller the corresponding mapped value.

[0062] Exemplarily, the mapping function corresponding to the maximum load rate is used to describe the relationship between the maximum load rate and the load fluctuation utilization rate. The larger the maximum load rate, the higher the load fluctuation utilization rate, and the smaller the corresponding allowable reverse load score. Therefore, the larger the maximum load rate, the larger the corresponding mapped value.

[0063] Exemplarily, the mapping function corresponding to the load mean square deviation is used to describe the relationship between the load mean square deviation and the discreteness of the load fluctuation. The larger the load mean square deviation, the greater the discreteness of the load fluctuation, and the smaller the corresponding allowable reverse load score. Therefore, the larger the load mean square deviation, the smaller the corresponding mapped value.

[0064] Exemplarily, the quartile load includes the upper quartile load and the lower quartile load. The quartile load is used to describe the relationship between the spacing between the upper quartile load and the lower quartile load and the concentration of the load. The larger the spacing between the upper quartile load and the lower quartile load, the lower the concentration of the load, and the smaller the corresponding allowable inverted load score. Therefore, the larger the spacing between the upper quartile load and the lower quartile load, the smaller the corresponding mapped value.

[0065] Exemplarily, the mapping function may be a linear function, or an exponential function, or a polynomial function.

[0066] For example, the weight coefficients of the load peak-to-valley ratio, the maximum load rate, the load mean square error and the quartile load may be the same or different, and the sum of the four weight coefficients is 1.

[0067] Exemplarily, based on the respective weight coefficients of the load peak-to-valley ratio, the maximum load rate, the load mean square error and the quartile load, the values ​​obtained by the respective mappings are weighted summed to obtain the allowable reverse load score of the line node.

[0068] Exemplarily, based on the allowable load shedding score of each line node, a plurality of first candidate load shedding nodes whose scores meet a preset score interval are determined in each line node.

[0069] According to the above embodiment, based on the load distribution characteristics of each line node, each line node is scored to obtain the allowable load reversal score of each line node. Therefore, based on the allowable load reversal score of each line node, multiple first candidate load reversal nodes can be accurately determined in each line node.

[0070] In one embodiment, based on the line loss and load reversal dispatch time of each transmission line when the simulation model performs load reversal at each first candidate load reversal node, multiple second candidate load reversal nodes are determined from multiple first candidate load reversal nodes, including: performing the following operations for each first candidate load reversal node: sorting the line loss of each transmission line when the simulation model performs load reversal at the first candidate load reversal node, and scoring the line loss of each transmission line based on the result of the sorting to obtain the line loss score of each transmission line; sorting the load reversal dispatch time of each transmission line when the simulation model performs load reversal at the first candidate load reversal node, and scoring the load reversal dispatch time of each transmission line based on the result of the sorting to obtain the load reversal dispatch time score of each transmission line; and determining the comprehensive load reversal score of the first candidate load reversal node based on the line loss score and the load reversal dispatch time score of each transmission line; and determining multiple second candidate load reversal nodes from multiple first candidate load reversal nodes based on the comprehensive load reversal scores of each first candidate load reversal node.

[0071] Exemplarily, the line losses of the transmission lines may be ranked from large to small, or may be ranked from small to large.

[0072] Exemplarily, taking the example of ranking the line losses of the power transmission lines from large to small, the higher the ranking of the line loss of the power transmission line, the lower its line loss score.

[0073] Exemplarily, the load reversal dispatching times of the transmission lines may be sorted from large to small, or may be sorted from small to large.

[0074] For example, taking the example of ranking the load reversal dispatch time of the transmission lines from large to small, the higher the ranking of the load reversal dispatch time of the transmission line, the lower the load reversal dispatch time score.

[0075] Exemplarily, based on the line loss weight and the load reversal dispatch time weight, the line loss score and the load reversal dispatch time score of each transmission line are weighted and summed to obtain the comprehensive load reversal score of the first candidate load reversal node.

[0076] Exemplarily, based on the comprehensive load shedding scores of the first candidate load shedding nodes, a first candidate load shedding node whose score meets a preset score range is determined among multiple first candidate load shedding nodes, and the first candidate load shedding node is used as the second candidate load shedding node.

[0077] According to the above-mentioned implementation, based on the line loss and load reversal allocation time of each transmission line when the simulation model performs load reversal at each first candidate load reversal node, the comprehensive load reversal score of each first candidate load reversal node is determined, and among multiple first candidate load reversal nodes, multiple second candidate load reversal nodes can be accurately determined.

[0078] In one embodiment, based on the location of the fault point and the important load in the 10 kV line radial network, a target load reversal node whose important load transfer rate meets the preset conditions is selected from multiple second candidate load reversal nodes, including: for each second candidate load reversal node, based on the important load of the fault point, performing load reversal simulation transmission on the transmission line between the fault point and the second candidate load reversal node to obtain the important load transfer rate of the second candidate load reversal node; based on the important load transfer rate of each second candidate load reversal node, selecting a target load reversal node whose important load transfer rate meets the preset conditions from multiple second candidate load reversal nodes.

[0079] It can be understood that the important load at the fault point refers to the important load user node near the fault point.

[0080] It can be understood that the fault point supplies power to important load user nodes nearby.

[0081] For example, during the simulation transmission process, the second candidate load-reversing node supplies power to the important load user node near the fault point, and the important load transfer rate of the second candidate load-reversing node is calculated using the power supply data of the power supply process. For example, based on the load utilization rate of each important load user node, the important load transfer rate of the second candidate load-reversing node is determined.

[0082] Exemplarily, the preset condition may be that the important load transfer rate is within a preset transfer rate range.

[0083] According to the above implementation, the target load shedding node is selected by considering the important load transfer rate of each second candidate load shedding node to the fault point, so that the load transfer capacity of the target load shedding node can be improved.

[0084] Figure 2 It is a structural block diagram of a 10 kV line load reversal device according to an embodiment of the present invention.

[0085] like Figure 2 As shown, the 10 kV line load-reversing device comprises:

[0086] A load characteristic determination module 210, for determining the load distribution characteristics of each line node based on the load distribution data of each line node in the 10 kV line radial network;

[0087] A first node screening module 220, configured to determine a plurality of first candidate load-reversing nodes in each of the line nodes based on the load distribution characteristics of each of the line nodes;

[0088] The load reversal simulation module 230 is used to simulate the load reversal process of the simulation model corresponding to the 10 kV line radial network at the first candidate load reversal node for each of the first candidate load reversal nodes, and monitor the line operation status of each transmission line in the 10 kV line radial network during the simulated load reversal process, so as to obtain the line loss and load reversal allocation time of each of the transmission lines when the simulation model performs load reversal at the first candidate load reversal node;

[0089] A second node screening module 240, configured to determine a plurality of second candidate load-reversing nodes from the plurality of first candidate load-reversing nodes based on the line loss and load-reversing dispatching time of each of the transmission lines under each of the first candidate load-reversing nodes;

[0090] A third node screening module 250 is used to select a target load-reversing node whose important load transfer rate meets preset conditions from among the plurality of second candidate load-reversing nodes based on the location of the fault point and the important load in the 10 kV line radial network;

[0091] The load shedding working module 260 is used to shedding load on the fault point in the 10 kV line radial network based on the target load shedding node.

[0092] In one implementation, the load characteristic determination module includes:

[0093] A load curve determination unit, used for performing normalization processing and wavelet transformation on the load data of each line node in the 10 kV line radial network to obtain a load curve of each line node;

[0094] The load characteristic determination unit extracts the load distribution characteristics of each of the line nodes from the load curves of each of the line nodes, wherein the load distribution characteristics include load peak-to-valley ratio, maximum load rate, load mean square error and quartile load.

[0095] In one implementation, the first node screening module includes:

[0096] A first scoring unit is used for performing numerical mapping on the load peak-to-valley ratio, maximum load rate, load mean square deviation and quartile load of each line node based on the mapping functions corresponding to the load peak-to-valley ratio, maximum load rate, load mean square deviation and quartile load of the line node, and performing weighted calculation on the mapped values ​​to obtain the allowable reverse load score of the line node;

[0097] The first node screening unit is used to determine a plurality of first candidate load-reducing nodes in each of the line nodes based on the allowable load-reducing scores of each of the line nodes.

[0098] In one implementation, the second node screening module 240 includes:

[0099] The second scoring unit is configured to perform the following operations on each of the first candidate load unloading nodes:

[0100] Sorting the line losses of each of the transmission lines when the simulation model performs load shedding at the first candidate load shedding node, and scoring the line losses of each of the transmission lines based on the ranking results to obtain a line loss score of each of the transmission lines;

[0101] sorting the load reversal dispatching time of each of the transmission lines when the simulation model performs load reversal at the first candidate load reversal node, and scoring the load reversal dispatching time of each of the transmission lines based on the sorting result to obtain the load reversal dispatching time score of each of the transmission lines; and

[0102] Determine the comprehensive load-reversal score of the first candidate load-reversal node based on the line loss score and the load-reversal dispatch time score of each of the transmission lines;

[0103] The second node screening unit is used to determine a plurality of second candidate load shedding nodes from the plurality of first candidate load shedding nodes based on the comprehensive load shedding scores of the first candidate load shedding nodes.

[0104] In one implementation, the third node screening module 250 includes:

[0105] a load transfer rate determination unit, configured to perform load transfer simulation transmission on the transmission line between the fault point and the second candidate load transfer node based on the important load of the fault point for each of the second candidate load transfer nodes, so as to obtain the important load transfer rate of the second candidate load transfer node;

[0106] The third node screening unit is used to select a target load-reducing node whose important load transfer rate meets preset conditions from among the plurality of second candidate load-reducing nodes based on the important load transfer rate of each of the second candidate load-reducing nodes.

[0107] For the description of specific functions and examples of each module and submodule of the device in the embodiment of the present invention, reference can be made to the relevant description of the corresponding steps in the above method embodiment, which will not be repeated here.

[0108] In the technical solution of the present invention, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0109] According to an embodiment of the present invention, the present invention also provides a system and a readable storage medium.

[0110] Figure 3 A schematic block diagram of an example electronic device 800 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0111] like Figure 3 As shown, the device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 to a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0112] A number of components in the device 800 are connected to the I / O interface 805, including: an input unit 806, such as a keyboard, a mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a disk, an optical disk, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0113] The computing unit 801 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 801 performs the various methods and processes described above, such as the 10 kV line load shedding method. For example, in some embodiments, the 10 kV line load shedding method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the 10 kV line load shedding method described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the 10 kV line load shedding method in any other suitable manner (eg, by means of firmware).

[0114] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code can be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0116] In the context of the present invention, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0117] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0118] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0119] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0120] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in the present invention can be achieved, and this document does not limit this.

[0121] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A 10 kV line load reversal method, characterized in that: include: Determine the load distribution characteristics of each line node based on the load distribution data of each line node in the 10 kV line radial network; Based on the load distribution characteristics of each of the line nodes, determining a plurality of first candidate load-reversing nodes in each of the line nodes; For each of the first candidate load-reversal nodes, respectively simulate the load-reversal process of the simulation model corresponding to the 10 kV line radial network at the first candidate load-reversal node, and monitor the line operation status of each transmission line in the 10 kV line radial network during the simulated load-reversal process, so as to obtain the line loss and load-reversal allocation time of each of the transmission lines when the simulation model performs load-reversal at the first candidate load-reversal node; Determine a plurality of second candidate load shedding nodes from the plurality of first candidate load shedding nodes based on the line loss and load shedding allocation time of each of the transmission lines when the simulation model performs load shedding at each of the first candidate load shedding nodes; Based on the location of the fault point and the important load in the 10 kV line radial network, a target load-reversing node whose important load transfer rate meets the preset conditions is selected from the plurality of second candidate load-reversing nodes; Based on the target load-reversal node, load is reversed on the fault point in the 10 kV line radial network.

2. The method according to claim 1, characterized in that The load distribution data of each line node in the 10 kV line radial network is used to determine the load distribution characteristics of each line node, including: Normalizing and wavelet transforming the load data of each line node in the 10 kV line radial network to obtain a load curve of each line node; The load distribution characteristics of each of the line nodes are extracted from the load curves of each of the line nodes, wherein the load distribution characteristics include load peak-to-valley ratio, maximum load rate, load mean square error and quartile load.

3. The method according to claim 2, characterized in that The determining of a plurality of first candidate load-reversing nodes in each of the line nodes based on the load distribution characteristics of each of the line nodes comprises: For each of the line nodes, numerical mapping is performed on the load peak-to-valley ratio, maximum load rate, load mean square deviation and quartile load of the line node based on the mapping functions corresponding to the load peak-to-valley ratio, maximum load rate, load mean square deviation and quartile load of the line node, and weighted calculation is performed on the mapped values ​​to obtain the allowable reverse load score of the line node; Based on the allowable load shedding scores of the line nodes, a plurality of first candidate load shedding nodes are determined in the line nodes.

4. The method according to claim 1, characterized in that The determining of a plurality of second candidate load shedding nodes from the plurality of first candidate load shedding nodes based on the line loss and load shedding allocation time of each of the transmission lines when load shedding is performed at each of the first candidate load shedding nodes according to the simulation model comprises: The following operations are performed for each of the first candidate load unloading nodes: Sorting the line losses of each of the transmission lines when the simulation model performs load shedding at the first candidate load shedding node, and scoring the line losses of each of the transmission lines based on the ranking results to obtain a line loss score of each of the transmission lines; sorting the load reversal dispatching time of each of the transmission lines when the simulation model performs load reversal at the first candidate load reversal node, and scoring the load reversal dispatching time of each of the transmission lines based on the sorting result to obtain the load reversal dispatching time score of each of the transmission lines; and Determine the comprehensive load-reversal score of the first candidate load-reversal node based on the line loss score and the load-reversal dispatch time score of each of the transmission lines; Based on the comprehensive load shedding scores of the first candidate load shedding nodes, a plurality of second candidate load shedding nodes are determined from the plurality of first candidate load shedding nodes.

5. The method according to claim 1, characterized in that The selecting, based on the location of the fault point and the important load in the 10 kV line radial network, a target load-reversing node whose important load transfer rate meets preset conditions from among the plurality of second candidate load-reversing nodes comprises: For each of the second candidate load-reversing nodes, based on the important load of the fault point, a load-reversing simulation transmission is performed on the transmission line between the fault point and the second candidate load-reversing node to obtain an important load transfer rate of the second candidate load-reversing node; Based on the important load transfer rates of each of the second candidate load unloading nodes, a target load unloading node whose important load transfer rate meets preset conditions is selected from the plurality of second candidate load unloading nodes.

6. A 10 kV line load reversal device, characterized in that: include: A load characteristic determination module, for determining the load distribution characteristics of each line node based on the load distribution data of each line node in the 10 kV line radial network; A first node screening module, configured to determine a plurality of first candidate load-reversing nodes in each of the line nodes based on the load distribution characteristics of each of the line nodes; A load reversal simulation module, for simulating the load reversal process of the simulation model corresponding to the 10 kV line radial network at the first candidate load reversal node for each of the first candidate load reversal nodes, and monitoring the line operation status of each transmission line in the 10 kV line radial network during the simulated load reversal process, so as to obtain the line loss and load reversal allocation time of each of the transmission lines when the simulation model performs load reversal at the first candidate load reversal node; A second node screening module is used to determine a plurality of second candidate load shedding nodes from the plurality of first candidate load shedding nodes based on the line loss and load shedding dispatching time of each of the transmission lines when the simulation model performs load shedding at each of the first candidate load shedding nodes; A third node screening module is used to select a target load-reversing node whose important load transfer rate meets preset conditions from among the plurality of second candidate load-reversing nodes based on the location of the fault point and the important load in the 10 kV line radial network; The load-reversing working module is used to perform load-reversing on the fault point in the 10 kV line radial network based on the target load-reversing node.

7. The device according to claim 6, characterized in that The load characteristic determination module comprises: A load curve determination unit, used for performing normalization processing and wavelet transformation on the load data of each line node in the 10 kV line radial network to obtain a load curve of each line node; The load characteristic determination unit extracts the load distribution characteristics of each of the line nodes from the load curves of each of the line nodes, wherein the load distribution characteristics include load peak-to-valley ratio, maximum load rate, load mean square error and quartile load.

8. The device according to claim 7, characterized in that The first node screening module includes: A first scoring unit is used for performing numerical mapping on the load peak-to-valley ratio, maximum load rate, load mean square deviation and quartile load of each line node based on the mapping functions corresponding to the load peak-to-valley ratio, maximum load rate, load mean square deviation and quartile load of the line node, and performing weighted calculation on the mapped values ​​to obtain the allowable reverse load score of the line node; The first node screening unit is used to determine a plurality of first candidate load-reducing nodes in each of the line nodes based on the allowable load-reducing scores of each of the line nodes.

9. A 10 kV line load reversal system, comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-5.

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