Topological identification method, device and system based on optimal combination and probability statistics

Abstract

The application provides a topological identification method, device and system based on optimal combination and probability statistics. The method comprises the following steps: obtaining effective power of each first-level device and each second-level device at different time points, the first-level device belonging to the second-level device; calculating optimal combination of weights of the first-level device at all time points according to the effective power of each first-level device and each second-level device at different time points; and obtaining the topological relationship between the first-level device and the second-level device by probability statistics according to the optimal combination of weights of the first-level device at all time points. According to the theory that the step sum of the upper device is equal to the step weighted sum of each lower device, the optimal combination scheme of the lower device is obtained, the accurate calculation of the topology is realized according to the probability statistics, the arbitrary two-level topological identification is realized, and no new equipment is needed.

Description

Technical Field

[0001] The present invention relates to the field of automatic identification of low-voltage topology of power grids, and in particular to a topology identification method based on optimal combination and probability statistics, a topology identification device based on optimal combination and probability statistics, and a topology identification system based on optimal combination and probability statistics. Background Art

[0002] In the new generation of power systems, the number of intelligent terminals such as distribution automation and electricity consumption information collection is increasing, and the connection relationships and connectivity between terminals are becoming increasingly complex. The accurate acquisition of network topology information is conducive to the lean management of the increasingly complex distribution network.

[0003] The topology of a low-voltage substation provides information about the connections between feeders, distribution transformers, distributors, and users. This connectivity is crucial for line loss analysis, outage assessment, and effective management of distribution network outages. Furthermore, accurate topological information, including network branches, user-to-user relationships, and phase affiliations, is essential for reliable status assessment of each node in the distribution network and maintaining three-phase load and voltage balance on distribution transformers and feeders.

[0004] CN 111462470 A discloses an intelligent topology identification method. This method utilizes the attenuation characteristics of power line carrier signals and the step-by-step transmission strategy of the power line carrier signal from a topology identification device to determine the physical connection relationship between nodes. This method enables low-voltage topology identification without injecting high-power or high-frequency signals into the power grid. This topology identification solution requires the installation of an intelligent topology identification device at the meter end. Topology identification is achieved by analyzing the carrier signal emitted by the device. However, adding a device at the end is difficult, and the analysis process is relatively cumbersome. Summary of the Invention

[0005] The purpose of the embodiments of the present invention is to provide a topology identification method, device and system based on optimal combination and probability statistics. According to the theory that the total power of the meter box is equal to the weighted sum of the power of each meter, the optimal combination scheme of the meters is obtained, and the topology is accurately calculated based on probability statistics to realize arbitrary secondary topology identification. Compared with other topology identification schemes, this method does not require new equipment and is simple to arrange.

[0006] In order to achieve the above object, the first aspect of the present invention provides a method for automatic topology recognition based on optimal combination and probability statistics, the method comprising:

[0007] Obtaining effective power of each first-level device and each second-level device in the power grid at different times, wherein the first-level device is subordinate to the second-level device;

[0008] Calculate the optimal combination of weights of the first-stage devices at all times based on the effective power of each first-stage device and each second-stage device at different times;

[0009] According to the optimal combination of the weights of the first-level devices at all times, the topological relationship between the first-level devices and the second-level devices is obtained by using probability statistics.

[0010] Furthermore, the obtaining of the effective power of each first-level device and each second-level device in the power grid at different times includes:

[0011] Under time alignment conditions, the active power of each first-level and second-level device in the power grid is obtained at different times. Under time alignment conditions, the sum of the second-level device steps equals the weighted sum of each first-level device. This is the fundamental theory for calculating the optimal combination of first-level device weights based on step power.

[0012] Optionally, the step of calculating the optimal combination of weights of the first-stage devices at all times based on the effective power of each first-stage device and each second-stage device at different times includes:

[0013] Determine the weight combination of the first-stage devices that meet the preset conditions according to the effective power of each first-stage device at different times and the effective power of each second-stage device at different times ;

[0014] The total set of weight combinations of all first-level devices is formed by transposing the weight combinations of the first-level devices ;

[0015] According to the column vectors of all matrices in the total set, determine the vectors of all first-level devices that are subordinate to the second-level devices ;

[0016] All vectors Form a new matrix , represents the optimal combination of weights of the first-level devices at time t;

[0017] Repeat the above steps to calculate the optimal combination of the weights of the first-level devices at different times, and combine the optimal combination of the weights of the first-level devices at different times into the optimal combination of the weights of the first-level devices at all times. .

[0018] Optionally, the weight combination of the first-level devices that meet the preset conditions is determined based on the effective power of each first-level device at different times and the effective power of each second-level device at different times. ,include:

[0019] Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1;

[0020] Traverse the different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters ;

[0021] Calculate the total effective power of the first-stage device under different value combinations of weight parameters according to the first weight matrix : ;in, The matrix representing the effective power of each first-stage device, i=1, 2, ..., N;

[0022] Calculate the difference between the total effective power of the first stage device and the effective power of each second stage device: , confirm that Weight combination , where c satisfies The number of weight combinations, j=1, 2, ..., M.

[0023] Optionally, the weight combination of the first-level devices that meet the preset conditions is determined based on the effective power of each first-level device at different times and the effective power of each second-level device at different times. ,include:

[0024] Calculate the step power of each first-stage device at different times based on the effective power of each first-stage device at different times : ;in, represents the effective power of the i-th first-stage device at time t, i = 1, 2, ..., N;

[0025] Calculate the step power of each second-stage device at different times based on the effective power of each second-stage device at different times : ;in, represents the effective power of the jth second-stage device at time t, j = 1, 2, ..., M;

[0026] Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1;

[0027] Traverse the different value combinations of weight parameters to obtain the first weight matrix composed of weight parameters ;

[0028] Calculate the total step power of the first-stage device under different value combinations of weight parameters according to the first weight matrix : ;in, A matrix representing the step power components of each first-stage device;

[0029] Calculate the difference between the total step power of the first stage device and the step power of each second stage device: , confirm that Weight combination , where c satisfies The number of weight combinations.

[0030] Optional. The vectors of all first-level devices belonging to the second-level devices are determined based on the column vectors of all matrices in the total set. ,include:

[0031] Get the total set Perform XOR operation on the column vectors of all matrices in the matrix to obtain a vector whose all elements are 1 after XOR : .

[0032] Optionally, the vectors of all first-level devices belonging to the second-level devices are determined based on the column vectors of all matrices in the total set. ,include:

[0033] Traverse the total collection The weight value of the corresponding position of each matrix in the matrix is ​​used to determine whether the two weight values ​​of the corresponding positions are the same. If they are the same, they are recorded as 0, and if they are not the same, they are recorded as 1. After traversing, the vectors with the corresponding positions of all matrices as 1 are obtained. : By calculating the XOR of the weights between the first-level devices, the weight vector of the first-level devices whose elements are all 1 after XOR is obtained, and then the optimal combination scheme between the first-level devices is obtained. The optimal combination is one of the alternative schemes for determining the topology structure.

[0034] Optionally, the obtaining of the topological relationship between each first-level device and each second-level device by using probability statistics based on the optimal combination of weights of the first-level devices at all times includes:

[0035] Calculate the optimal combination of weights of the first-level devices at all times The number of combinations m in ;

[0036] Calculate the optimal combination of weights of the first-level devices at all times The i-th first-stage device The number of combinations n belonging to the jth second-level device, then the i-th first-level device The number of combinations that do not belong to the jth second-level device is mn;

[0037] Compare n and mn. If n>mn, then the i-th first-level device belongs to the jth second-level device; otherwise, the i-th first-level device Not subordinate to the jth second-level device;

[0038] Traverse all first-level devices and obtain the topological relationship between the first-level devices and the second-level devices.

[0039] Optionally, the first-level device is a branch and the second-level device is a substation; or the first-level device is a meter box and the second-level device is a branch; or the first-level device is an electric meter and the second-level device is a meter box. The method of the present application can realize the identification of any secondary topology from substation to branch, from branch to meter box, and from meter box to electric meter.

[0040] A second aspect of the present invention provides a topology automatic recognition system based on optimal combination and probability statistics, the system comprising:

[0041] a data acquisition module, configured to acquire the effective power of each first-level device and each second-level device in the power grid at different times, wherein the first-level device is subordinate to the second-level device;

[0042] an optimal combination calculation module for electric meter weights, for calculating the optimal combination of weights of the first-level devices at all times based on the effective power of each first-level device and each second-level device at different times; and

[0043] The probability statistics comparison module is used to obtain the topological relationship between the first-level devices and the second-level devices using probability statistics according to the optimal combination of the weights of the first-level devices at all times.

[0044] Optionally, the step of calculating the optimal combination of weights of the first-stage devices at all times based on the effective power of each first-stage device and each second-stage device at different times includes:

[0045] Determine the weight combination of the first-stage devices that meet the preset conditions according to the effective power of each first-stage device at different times and the effective power of each second-stage device at different times ;

[0046] The total set of weight combinations of all first-level devices is formed by transposing the weight combinations of the first-level devices ;

[0047] According to the column vectors of all matrices in the total set, determine the vectors of all first-level devices that are subordinate to the second-level devices ;

[0048] All vectors Form a new matrix , represents the optimal combination of weights of the first-level devices at time t;

[0049] Repeat the above steps to calculate the optimal combination of the weights of the first-level devices at different times, and combine the optimal combination of the weights of the first-level devices at different times into the optimal combination of the weights of the first-level devices at all times. .

[0050] Optionally, the weight combination of the first-level devices that meet the preset conditions is determined based on the effective power of each first-level device at different times and the effective power of each second-level device at different times. ,include:

[0051] Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1;

[0052] Traverse the different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters ;

[0053] Calculate the total effective power of the first-stage device under different value combinations of weight parameters according to the first weight matrix : ;in, The matrix representing the effective power of each first-stage device, i=1, 2, ..., N;

[0054] Calculate the difference between the total effective power of the first stage device and the effective power of each second stage device: , confirm that Weight combination , where c satisfies The number of weight combinations, j=1, 2, ..., M.

[0055] Optionally, the weight combination of the first-level devices that meet the preset conditions is determined based on the effective power of each first-level device at different times and the effective power of each second-level device at different times. ,include:

[0056] Calculate the step power of each first-stage device at different times based on the effective power of each first-stage device at different times : ;in, represents the effective power of the i-th first-stage device at time t, i = 1, 2, ..., N;

[0057] Calculate the step power of each second-stage device at different times based on the effective power of each second-stage device at different times : ;in, represents the effective power of the jth second-stage device at time t, j = 1, 2, ..., M;

[0058] Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1;

[0059] Traverse the different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters ;

[0060] Calculate the total step power of the first-stage device under different value combinations of weight parameters according to the first weight matrix : ;in, A matrix representing the step power components of each first-stage device;

[0061] Calculate the difference between the total step power of the first stage device and the step power of each second stage device: , confirm that Weight combination , where c satisfies The number of weight combinations.

[0062] Optionally, the vectors of all first-level devices belonging to the second-level devices are determined based on the column vectors of all matrices in the total set. ,include:

[0063] Get the total set Perform XOR operation on the column vectors of all matrices in the matrix to obtain a vector whose all elements are 1 after XOR : .

[0064] Optionally, the vectors of all first-level devices belonging to the second-level devices are determined based on the column vectors of all matrices in the total set. ,include:

[0065] Traverse the total collection The weight value of the corresponding position of each matrix in the matrix is ​​used to determine whether the two weight values ​​of the corresponding positions are the same. If they are the same, they are recorded as 0, and if they are not the same, they are recorded as 1. After traversing, the vectors with the corresponding positions of all matrices as 1 are obtained. : .

[0066] Optionally, the obtaining of the topological relationship between each first-level device and each second-level device by using probability statistics based on the optimal combination of weights of the first-level devices at all times includes:

[0067] Calculate the optimal combination of weights of the first-level devices at all times The number of combinations m in ;

[0068] Calculate the optimal combination of weights of the first-level devices at all times The i-th first-stage device The number of combinations n belonging to the jth second-level device, then the i-th first-level device The number of combinations that do not belong to the jth second-level device is mn;

[0069] Compare n and mn. If n>mn, then the i-th first-level device belongs to the jth second-level device; otherwise, the i-th first-level device Not subordinate to the jth second-level device;

[0070] Traverse all first-level devices and obtain the topological relationship between the first-level devices and the second-level devices.

[0071] A third aspect of the present invention provides a device for automatic topology recognition based on optimal combination and probability statistics, the device comprising:

[0072] memory for storing computer programs;

[0073] A processor is used to run the computer program to execute the automatic topology recognition method based on optimal combination and probability statistics.

[0074] On the other hand, the present invention provides a machine-readable storage medium having instructions stored thereon, the instructions being used to enable a machine to execute the above-mentioned automatic topology recognition method based on optimal combination and probability statistics.

[0075] Through the above technical solution, under the condition of time alignment, the total power of the second-level devices is equal to the weighted sum of the power of each first-level device. Through the XOR calculation of the weights between the first-level devices, the weight vector of the first-level devices with all elements equal to 1 after XOR is obtained, and then the optimal combination scheme between the first-level devices is obtained. This optimal combination is one of the alternative schemes for determining the topological structure. Then, the probability and statistical methods are further combined to realize the accurate calculation of the topology. This method can realize the identification of any secondary topology from the substation to the branch, from the branch to the meter box, and from the meter box to the meter. Compared with other topology identification methods, this scheme does not require new equipment, and the application of step power data is more in line with the data feature requirements of the optimal combination theory. It is further verified with probability statistics, thereby obtaining a higher accuracy.

[0076] By calculating the step power and then taking the weighted sum of the step power of each first-stage device as the sum of the step power of the second-stage device, the optimal combination scheme between the first-stage devices can be obtained, which can effectively reduce the amount of calculation and improve the calculation accuracy.

[0077] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0079] Figure 1 This is a flow chart of a method for automatic topology recognition based on optimal combination and probability statistics provided by one embodiment of the present invention;

[0080] Figure 2 This is a flow chart of a method for automatically identifying substation and branch topologies based on optimal combination and probability statistics provided by one embodiment of the present invention;

[0081] Figure 3 This is a flow chart of a method for automatically identifying branch and meter box topologies based on optimal combination and probability statistics, provided by one embodiment of the present invention;

[0082] Figure 4 This is a flow chart of a method for automatically identifying meter box and meter topology based on optimal combination and probability statistics provided by an embodiment of the present invention.

[0083] Figure 5 This is a block diagram of a topology automatic recognition system based on optimal combination and probability statistics provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0084] The following describes the specific embodiments of the present invention in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present invention and are not intended to limit the present invention.

[0085] Figure 1 This is a flow chart of a method for automatic topology recognition based on optimal combination and probability statistics provided by an embodiment of the present invention. Figure 1 As shown, the method includes:

[0086] Step 1: Obtain the active power of each first-level device and each second-level device in the power grid at different times. In this embodiment, the active power of each first-level device and each second-level device at different times must be obtained under time alignment. Under time alignment, the step sum of the second-level devices equals the weighted sum of each first-level device. This is the fundamental theory for calculating the optimal combination of first-level device weights based on step power.

[0087] Step 2: Calculate the optimal combination of weights of the first-stage devices at all times based on the effective power of each first-stage device and each second-stage device at different times, specifically including:

[0088] 1) Determine the weight combination of the first-level devices that meet the preset conditions based on the effective power of each first-level device at different times and the effective power of each second-level device at different times .

[0089] In this embodiment, the weight combination of the first-level devices that meet the preset conditions is determined , specifically including:

[0090] 1-1) Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1, and a weight value of 1 represents that the first-level device is subordinate to the current second-level device. In this embodiment, All parameters in are initialized to 1, then, =[1,1,1,...,1].

[0091] 1-2) Traverse different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters , the combination of 0 and 1 of N first-level devices will produce 2 N situation.

[0092] 1-3) Calculating the total effective power of the first-stage device under different combinations of weight parameters according to the first weight matrix : ;in, The matrix representing the effective power of each first-stage device, i=1, 2, ..., N;

[0093] 1-4) Calculate the difference between the total effective power of the first-stage device and the effective power of each second-stage device: , confirm that Weight combination , where c satisfies The number of weight combinations is j = 1, 2, ..., M. Since the step power of each first-stage device is different, c is a non-fixed variable. The minimum error method is used to obtain the weight combination, so that the optimal combination of the weights of the first-stage devices obtained at the end is more accurate.

[0094] 2) Combine the weights of the first-level devices Transpose The total set of weight combinations that make up all first-level devices : ;

[0095] 3) Based on the column vectors of all matrices in the total set, determine the vectors of all first-level devices that are subordinate to the second-level devices .

[0096] In some embodiments, determining a vector where all first-level devices are subordinate to second-level devices , including: taking the total set Perform XOR operation on the column vectors of all matrices in the matrix to obtain a vector whose all elements are 1 after XOR : .

[0097] In some other embodiments, determining a vector in which all first-level devices are subordinate to second-level devices , including: traversing the total set The weight value of the corresponding position of each matrix in the matrix is ​​used to determine whether the two weight values ​​of the corresponding positions are the same. If they are the same, they are recorded as 0, and if they are not the same, they are recorded as 1. After traversing, the vectors with the corresponding positions of all matrices as 1 are obtained. : In actual data processing, there will be multiple groups After satisfying the XOR, all elements are 1. All elements being 1 means that all first-level devices can find their own second-level devices. If there are 0s, it means that some first-level devices cannot find their own second-level devices, which means that there must be a wrong match.

[0098] 4) All vectors Form a new matrix , Represents the optimal combination of weights of the first-level devices at time t.

[0099] 5) Repeat the above steps to calculate the optimal combination of the weights of the first-level devices at different times, and combine the optimal combination of the weights of the first-level devices at different times to form the optimal combination of the weights of the first-level devices at all times By calculating the XOR of the weights between the first-level devices, a first-level device weight vector is obtained in which all elements are 1 after XOR, and then the optimal combination scheme between the first-level devices is obtained. This optimal combination is one of the alternative schemes for determining the topology structure.

[0100] Step 3: Based on the optimal combination of the weights of the first-level devices at all times, use probability statistics to obtain the topological relationship between the first-level devices and the second-level devices, specifically including:

[0101] Calculate the optimal combination of weights of the first-level devices at all times The number of combinations m in ;

[0102] Calculate the optimal combination of weights of the first-level devices at all times The i-th first-stage device The number of combinations n belonging to the jth second-level device, then the i-th first-level device The number of combinations that do not belong to the jth second-level device is mn;

[0103] Compare n and mn. If n>mn, then the i-th first-level device belongs to the jth second-level device; otherwise, the i-th first-level device Not subordinate to the jth second-level device;

[0104] Traverse all first-level devices and obtain the topological relationship between the first-level devices and the second-level devices.

[0105] In steps 1 to 4 above, the first-level device is subordinate to the second-level device. For example, if the first-level device is a branch, the second-level device is the different substations to which these branches belong; if the first-level device is a meter box, the second-level device is the different branches to which these meter boxes belong; if the first-level device is an electricity meter, the second-level device is the different meter boxes to which these meters belong. The method of the present application can achieve arbitrary second-level topology identification from substation to branch, from branch to meter box, and from meter box to meter.

[0106] Another embodiment of the present invention provides a flow chart of a method for automatic topology identification based on optimal combination and probability statistics. The method includes:

[0107] Step 1: Obtain the active power of each first-level device and each second-level device in the power grid at different times. In this embodiment, the active power of each first-level device and each second-level device at different times must be obtained under time alignment. Under time alignment, the step sum of the second-level devices equals the weighted sum of each first-level device. This is the fundamental theory for calculating the optimal combination of first-level device weights based on step power.

[0108] Step 2: Calculate the optimal combination of weights of the first-stage devices at all times based on the effective power of each first-stage device and each second-stage device at different times, specifically including:

[0109] 1) Determine the weight combination of the first-level devices that meet the preset conditions based on the effective power of each first-level device at different times and the effective power of each second-level device at different times .

[0110] In this embodiment, the weight combination of the first-level devices that meet the preset conditions is determined , such as specifically including:

[0111] 1-1) Calculate the step power of each first-stage device at different times based on the effective power of each first-stage device at different times : ;in, Represents the effective power of the i-th first-stage device at time t, i=1, 2, ..., N.

[0112] 1-2) Calculate the step power of each second-stage device at different times based on the effective power of each second-stage device at different times : ;in, Represents the effective power of the jth second-stage device at time t, j=1, 2, ..., M.

[0113] 1-3) Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1, and a weight value of 1 represents that the first-level device is subordinate to the current second-level device. In this embodiment, All parameters in are initialized to 1, then, =[1,1,1,...,1].

[0114] 1-4) Traverse different value combinations of the weight parameters to obtain a first weight matrix composed of the weight parameters , the combination of 0 and 1 of N first-level devices will produce 2 N situation.

[0115] 1-5) Calculate the total step power of the first stage device under different combinations of weight parameters based on the first weight matrix : ;in, A matrix representing the step power components of each first-stage device.

[0116] 1-6) Calculate the difference between the total step power of the first stage device and the step power of each second stage device: , confirm that Weight combination , where c satisfies Since the step power of each first-stage device is different, c is a non-fixed variable. The minimum error method is used to obtain the weight combination, so that the optimal combination of the weights of the first-stage devices obtained at the end is more accurate.

[0117] 2) Combine the weights of the first-level devices Transpose The total set of weight combinations that make up all first-level devices : ;

[0118] 3) Based on the column vectors of all matrices in the total set, determine the vectors of all first-level devices that are subordinate to the second-level devices .

[0119] In some embodiments, determining a vector where all first-level devices are subordinate to second-level devices , including: taking the total set Perform XOR operation on the column vectors of all matrices in the matrix to obtain a vector whose all elements are 1 after XOR : .

[0120] In some other embodiments, determining a vector in which all first-level devices are subordinate to second-level devices , including: traversing the total set The weight value of the corresponding position of each matrix in the matrix is ​​used to determine whether the two weight values ​​of the corresponding positions are the same. If they are the same, they are recorded as 0, and if they are not the same, they are recorded as 1. After traversing, the vectors with the corresponding positions of all matrices as 1 are obtained. : In actual data processing, there will be multiple groups After satisfying XOR, all elements are 1.

[0121] 4) All vectors Form a new matrix , Represents the optimal combination of weights of the first-level devices at time t.

[0122] 5) Repeat the above steps to calculate the optimal combination of the weights of the first-level devices at different times, and combine the optimal combination of the weights of the first-level devices at different times to form the optimal combination of the weights of the first-level devices at all times By calculating the XOR of the weights between the first-level devices, a first-level device weight vector is obtained in which all elements are 1 after XOR, and then the optimal combination scheme between the first-level devices is obtained. This optimal combination is one of the alternative schemes for determining the topology structure.

[0123] Step 3: Based on the optimal combination of the weights of the first-level devices at all times, use probability statistics to obtain the topological relationship between the first-level devices and the second-level devices, specifically including:

[0124] Calculate the optimal combination of weights of the first-level devices at all times The number of combinations m in ;

[0125] Calculate the optimal combination of weights of the first-level devices at all times The i-th first-stage device The number of combinations n belonging to the jth second-level device, then the i-th first-level device The number of combinations that do not belong to the jth second-level device is mn;

[0126] Compare n and mn. If n>mn, then the i-th first-level device belongs to the jth second-level device; otherwise, the i-th first-level device Not subordinate to the jth second-level device;

[0127] Traverse all first-level devices and obtain the topological relationship between the first-level devices and the second-level devices.

[0128] In steps 1 to 4 above, the first-level device is subordinate to the second-level device. For example, if the first-level device is a branch, the second-level device is the different substations to which these branches belong; if the first-level device is a meter box, the second-level device is the different branches to which these meter boxes belong; if the first-level device is an electricity meter, the second-level device is the different meter boxes to which these meters belong. The method of the present application can achieve arbitrary second-level topology identification from substation to branch, from branch to meter box, and from meter box to meter.

[0129] Example 1

[0130] like Figure 2 FIG. 1 is a flow chart of a method for automatically identifying substation and branch topologies based on optimal combination and probability statistics according to an embodiment of the present invention. Figure 2 As shown, the method includes:

[0131] Step 1: Under time alignment conditions, obtain the active power of each branch within the grid at different times, as well as the active power of each substation at different times. Under time alignment conditions, the total step power of the substation is equal to the weighted sum of each branch. This is the basic theory for calculating the optimal combination of branch weights based on step power.

[0132] Step 2: Calculate the optimal combination of weights for each branch at all times based on the effective power of each branch at different times in the power grid and the effective power of each substation at different times, specifically including:

[0133] 1) Determine the weight combination of branches that meet the preset conditions based on the effective power of each branch at different times and the effective power of each area at different times .

[0134] In this embodiment, the weight combination of the branches that meet the preset conditions is determined. , specifically including:

[0135] 1-1) Set the weight parameters of each branch : ,in, is a binary matrix of 0 and 1, and a weight value of 1 represents that the branch belongs to the current station area. In this embodiment, All parameters in are initialized to 1, then, =[1,1,1,...,1].

[0136] 1-2) Traverse different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters , the combination of 0 and 1 of N branches will produce 2 N situation.

[0137] 1-3) Calculate the total effective power of the branch under different value combinations of weight parameters according to the first weight matrix : ;in, The matrix representing the effective power of each branch, i=1, 2, ..., N;

[0138] 1-4) Calculate the difference between the total effective power of the branch and the effective power of each area: , confirm that Weight combination , where c satisfies The number of weight combinations is j = 1, 2, ..., M. Since the step power of each branch is different, c is a non-fixed variable. The minimum error method is used to obtain the weight combination, so that the optimal combination of branch weights obtained at the end is more accurate.

[0139] 2) Combine the weights of the branches Transpose The total set of weight combinations that make up all branches : ;

[0140] 3) According to the column vectors of all matrices in the total set, determine the vectors to which all branches belong .

[0141] In this embodiment, it is determined that all branches belong to the vector , including: taking the total set Perform XOR operation on the column vectors of all matrices in the matrix to obtain a vector whose all elements are 1 after XOR : In actual data processing, there will be multiple groups After satisfying XOR, all elements are 1.

[0142] 4) All vectors Form a new matrix , Represents the optimal combination of branch weights at time t.

[0143] 5) Repeat the above steps to calculate the optimal combination of branch weights at different times, and combine the optimal combination of branch weights at different times to form the optimal combination of branch weights at all times. By calculating the XOR of the weights between branches, a branch weight vector with all elements equal to 1 is obtained, and then the optimal combination of branches is obtained. This optimal combination is one of the alternative solutions for determining the topology structure.

[0144] Step 3: Based on the optimal combination of branch weights at all times, use probability statistics to obtain the topological relationship between each branch and each substation, specifically including:

[0145] Count the optimal combination of branch weights at all times The number of combinations m in ;

[0146] Count the optimal combination of branch weights at all times The i-th branch The number of combinations belonging to the jth station area is n, then the i-th branch The number of combinations that do not belong to the jth station is mn;

[0147] Compare n and mn. If n>mn, then the i-th branch Belongs to the jth station; otherwise, the i-th branch Not belonging to the jth station;

[0148] Traverse all branches and obtain the topological relationship between branches and stations.

[0149] Example 2

[0150] like Figure 3 FIG. 1 is a flow chart of a method for automatically identifying branch and meter box topologies based on optimal combination and probability statistics according to an embodiment of the present invention. Figure 3 As shown, the method includes:

[0151] Step 1: Under time alignment conditions, obtain the active power of each meter box in the grid at different times, as well as the active power of each branch at different times. Under time alignment conditions, the total step sum of the branch equals the weighted sum of each meter box. This is the basic theory for calculating the optimal combination of meter box weights based on step power.

[0152] Step 2: Calculate the optimal combination of weights for all meter boxes at all times based on the effective power of each meter box and each branch at different times, specifically including:

[0153] 1) Determine the weight combination of branches that meet the preset conditions based on the effective power of each meter box at different times and the effective power of each branch at different times .

[0154] In this embodiment, the weight combination of the branches that meet the preset conditions is determined. , specifically including:

[0155] 1-1) Calculate the step power of each meter box at different times based on the effective power of each meter box at different times : ;in, Represents the effective power of the i-th meter box at time t, i=1, 2, ..., N.

[0156] 1-2) Calculate the step power of each branch at different times based on the effective power of each branch at different times : ;in, Represents the effective power of the j-th branch at time t, j=1, 2, ..., M.

[0157] 1-3) Set the weight parameters of each meter box : ,in, is a binary matrix of 0 and 1. In this embodiment, All parameters in are initialized to 1, then, =[1,1,1,...,1].

[0158] 1-4) Traverse different value combinations of weight parameters to obtain the first weight matrix composed of weight parameters , the combination of 0 and 1 in N meter boxes will produce 2 N situation.

[0159] 1-5) Calculate the total step power of the meter box under different combinations of weight parameters based on the first weight matrix : ;in, A matrix representing the step power of each meter box.

[0160] 1-6) Calculate the difference between the total step power of the meter box and the step power of each branch: , confirm that Weight combination , where c satisfies The number of weight combinations. Since the step power of each meter box is different, c is an unfixed variable.

[0161] 2) Combination based on the weight of each branch Transpose , get the total set of all branches : .

[0162] 3) Based on the column vectors of all matrices in the total set, determine the vectors of the branches to which all bins belong .

[0163] In this embodiment, it is determined that all bins belong to the vector of the branch , including: traversing the total set The weight value of the corresponding position of each matrix in the matrix is ​​used to determine whether the two weight values ​​of the corresponding positions are the same. If they are the same, they are recorded as 0, and if they are not the same, they are recorded as 1. After traversing, the vectors with the corresponding positions of all matrices as 1 are obtained. : In actual data processing, there will be multiple groups After satisfying XOR, all elements are 1.

[0164] 4) All vectors Form a new matrix , represents the optimal combination of schedule box weights at time t.

[0165] 5) Repeat the above steps to calculate the optimal combination of different timetable box weights. The optimal combination of different timetable box weights constitutes the optimal combination of all timetable box weights. By calculating the XOR of the weights between the boxes, we can obtain the box weight vector whose elements are all 1 after XOR, and then obtain the optimal combination of the boxes. This optimal combination is one of the alternative solutions for determining the topology structure.

[0166] Step 3: Based on the optimal combination of weights of all timetable boxes, use probability statistics to obtain the topological relationship between each box and each branch, including:

[0167] Calculate the optimal combination of weights for all timetable boxes The number of combinations m in ;

[0168] Calculate the optimal combination of weights for all timetable boxes The i-th meter box The number of combinations belonging to the j-th branch is n, then the i-th table box The number of combinations that do not belong to the j-th branch is mn;

[0169] Compare n and mn. If n>mn, then the i-th table box belongs to the jth branch; otherwise, the i-th table box Not belonging to the jth branch;

[0170] Traverse all table boxes and obtain the topological relationship between table boxes and branches.

[0171] Example 3

[0172] like Figure 4FIG. 1 is a flow chart of a method for automatically identifying meter box and meter topology based on optimal combination and probability statistics provided by an embodiment of the present invention. Figure 4 As shown, the method includes:

[0173] Step 1: Under time alignment conditions, obtain the active power of each meter in the grid at different times, as well as the active power of each meter box at different times. Under time alignment conditions, the total step power of the meter box is equal to the weighted sum of each meter. This is the basic theory for calculating the optimal combination of meter weights based on step power.

[0174] Step 2: Calculate the optimal combination of meter weights at all times based on the effective power of each meter and each meter box at different times, specifically including:

[0175] 1) Determine the weight combination of meters that meet the preset conditions based on the effective power of each meter at different times and the effective power of each meter box at different times .

[0176] In this embodiment, the weight combination of the electric meters that meet the preset conditions is determined. , specifically including:

[0177] 1-1) Calculate the step power of each meter at different times based on the effective power of each meter at different times : ;in, Represents the effective power of the i-th meter at time t, i=1, 2, ..., N.

[0178] 1-2) Calculate the step power of each meter box at different times based on the effective power of each meter box at different times : ;in, Represents the effective power of the jth meter box at time t, j=1, 2, ..., M.

[0179] 1-3) Set the weight parameters of each meter : ,in, is a binary matrix of 0 and 1. In this embodiment, All parameters in are initialized to 1, then, =[1,1,1,...,1].

[0180] 1-4) Traverse different value combinations of weight parameters to obtain the first weight matrix composed of weight parameters , the combination of 0 and 1 of N meters will produce 2 N situation.

[0181] 1-5) Calculate the total step power of the meter under different combinations of weight parameters based on the first weight matrix : ;in, A matrix representing the step power of each meter.

[0182] 1-6) Calculate the difference between the total step power of the meter and the step power of each meter box: , confirm that Weight combination , where c satisfies Since the step power of each meter is different, c is an unfixed variable.

[0183] 2) According to the weight combination of each meter box Transpose , get the total set of all table boxes : .

[0184] 3) Based on the column vectors of all matrices in the total set, determine the vectors that all meters belong to the meter box .

[0185] In this embodiment, it is determined that all electric meters belong to the vector of the meter box. , including: traversing the total set The weight value of the corresponding position of each matrix in the matrix is ​​used to determine whether the two weight values ​​of the corresponding positions are the same. If they are the same, they are recorded as 0, and if they are not the same, they are recorded as 1. After traversing, the vectors with the corresponding positions of all matrices as 1 are obtained. : In actual data processing, there will be multiple groups After satisfying XOR, all elements are 1.

[0186] 4) All vectors Form a new matrix , represents the optimal combination of meter weights at time t.

[0187] 5) Repeat the above steps to calculate the optimal combination of meter weights at different times. The optimal combination of meter weights at different times constitutes the optimal combination of meter weights at all times. By performing XOR calculation on the weights between the electricity meters, a meter weight vector is obtained in which all elements after XOR are 1, and then the optimal combination scheme between the electricity meters is obtained. This optimal combination is one of the alternative schemes for determining the topology structure.

[0188] Step 3: Based on the optimal combination of meter weights at all times, use probability statistics to obtain the topological relationship between each meter and each meter box, including:

[0189] Calculate the optimal combination of weights of electricity meters at all times The number of combinations m in ;

[0190] Calculate the optimal combination of weights of electricity meters at all times The i-th meter The number of combinations n belonging to the jth meter box is then the i-th meter The number of combinations that do not belong to the jth table box is mn;

[0191] Compare n and mn. If n>mn, then the i-th meter Belongs to the jth meter box; otherwise, the i-th meter Not belonging to the jth table box;

[0192] Traverse all electricity meters and obtain the topological relationship between the electricity meters and meter boxes.

[0193] Example 4

[0194] This embodiment provides a topology automatic recognition system based on optimal combination and probability statistics, such as Figure 5 As shown, the system includes:

[0195] a data acquisition module, configured to acquire the effective power of each first-level device and each second-level device in the power grid at different times, wherein the first-level device is subordinate to the second-level device;

[0196] an optimal combination calculation module for electric meter weights, for calculating the optimal combination of weights of the first-level devices at all times based on the effective power of each first-level device and each second-level device at different times; and

[0197] The probability statistics comparison module is used to obtain the topological relationship between the first-level devices and the second-level devices using probability statistics according to the optimal combination of the weights of the first-level devices at all times.

[0198] In this embodiment, the calculation of the optimal combination of weights of the first-stage devices at all times based on the effective power of each first-stage device and each second-stage device at different times includes:

[0199] Determine the weight combination of the first-stage devices that meet the preset conditions according to the effective power of each first-stage device at different times and the effective power of each second-stage device at different times ;

[0200] The total set of weight combinations of all first-level devices is formed by transposing the weight combinations of the first-level devices ;

[0201] According to the column vectors of all matrices in the total set, determine the vectors of all first-level devices that are subordinate to the second-level devices ;

[0202] All vectors Form a new matrix , represents the optimal combination of weights of the first-level devices at time t;

[0203] Repeat the above steps to calculate the optimal combination of the weights of the first-level devices at different times, and combine the optimal combination of the weights of the first-level devices at different times into the optimal combination of the weights of the first-level devices at all times. .

[0204] In some embodiments, the weight combination of the first-level devices that meet the preset conditions is determined based on the effective power of each first-level device at different times and the effective power of each second-level device at different times. ,include:

[0205] Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1;

[0206] Traverse the different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters ;

[0207] Calculate the total effective power of the first-stage device under different value combinations of weight parameters according to the first weight matrix : ;in, The matrix representing the effective power of each first-stage device, i=1, 2, ..., N;

[0208] Calculate the difference between the total effective power of the first stage device and the effective power of each second stage device: , confirm that Weight combination , where c satisfies The number of weight combinations, j=1, 2, ..., M.

[0209] In some embodiments, the weight combination of the first-level devices that meet the preset conditions is determined based on the effective power of each first-level device at different times and the effective power of each second-level device at different times. ,include:

[0210] Calculate the step power of each first-stage device at different times based on the effective power of each first-stage device at different times : ;in, represents the effective power of the i-th first-stage device at time t, i = 1, 2, ..., N;

[0211] Calculate the step power of each second-stage device at different times based on the effective power of each second-stage device at different times : ;in, represents the effective power of the jth second-stage device at time t, j = 1, 2, ..., M;

[0212] Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1;

[0213] Traverse the different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters ;

[0214] Calculate the total step power of the first-stage device under different value combinations of weight parameters according to the first weight matrix : ;in, A matrix representing the step power components of each first-stage device;

[0215] Calculate the difference between the total step power of the first stage device and the step power of each second stage device: , confirm that Weight combination , where c satisfies The number of weight combinations.

[0216] In some embodiments, the vectors of all first-level devices belonging to the second-level devices are determined based on the column vectors of all matrices in the total set. ,include:

[0217] Get the total set Perform XOR operation on the column vectors of all matrices in the matrix to obtain a vector whose all elements are 1 after XOR : .

[0218] In some embodiments, the vectors of all first-level devices belonging to the second-level devices are determined based on the column vectors of all matrices in the total set. ,include:

[0219] Traverse the total collection The weight value of the corresponding position of each matrix in the matrix is ​​used to determine whether the two weight values ​​of the corresponding positions are the same. If they are the same, they are recorded as 0, and if they are not the same, they are recorded as 1. After traversing, the vectors with the corresponding positions of all matrices as 1 are obtained. : .

[0220] In some embodiments, the method of obtaining the topological relationship between each first-level device and each second-level device using probability statistics based on the optimal combination of weights of the first-level devices at all times includes:

[0221] Calculate the optimal combination of weights of the first-level devices at all times The number of combinations m in ;

[0222] Calculate the optimal combination of weights of the first-level devices at all times The i-th first-stage device The number of combinations n belonging to the jth second-level device, then the i-th first-level device The number of combinations that do not belong to the jth second-level device is mn;

[0223] Compare n and mn. If n>mn, then the i-th first-level device belongs to the jth second-level device; otherwise, the i-th first-level device Not subordinate to the jth second-level device;

[0224] Traverse all first-level devices and obtain the topological relationship between the first-level devices and the second-level devices

[0225] The present invention also provides a device for automatic topology recognition based on optimal combination and probability statistics, the device comprising:

[0226] memory for storing computer programs;

[0227] A processor is used to run the computer program to execute the automatic topology recognition method based on optimal combination and probability statistics.

[0228] An embodiment of the present invention further provides a machine-readable storage medium having instructions stored thereon, the instructions being used to enable a machine to execute the above-mentioned automatic topology recognition method based on optimal combination and probability statistics.

[0229] The automatic identification method of substation topology in this application does not require new equipment. The application of step power data is more in line with the data feature requirements of the optimal combination theory. The minimum error method is used to obtain the optimal combination, and further verification is performed in conjunction with probability statistics to achieve identification of substation topology with higher accuracy.

[0230] Those skilled in the art will appreciate that all or part of the steps in the methods described in the aforementioned embodiments can be performed by instructing the relevant hardware through a program. The program, stored in a storage medium, includes instructions for causing a microcontroller, chip, or processor to execute all or part of the steps in the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0231] The above describes in detail the optional embodiments of the present invention in conjunction with the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the technical concept of the embodiments of the present invention, a variety of simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the scope of protection of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner unless there is any contradiction. In order to avoid unnecessary repetition, the embodiments of the present invention will no longer describe the various possible combinations separately.

[0232] In addition, the various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the embodiments of the present invention, they should also be regarded as the contents disclosed in the embodiments of the present invention.

Claims

1. A method for automatic topology recognition based on optimal combination and probability statistics, characterized in that: The method comprises: Obtaining effective power of each first-level device and each second-level device in the power grid at different times, wherein the first-level device is subordinate to the second-level device; The optimal combination of weights of the first-stage devices at all times is calculated based on the effective power of each first-stage device and each second-stage device at different times, including: Determine the weight combination of the first-stage devices that meet the preset conditions according to the effective power of each first-stage device at different times and the effective power of each second-stage device at different times ; The total set of weight combinations of all first-level devices is formed by transposing the weight combinations of the first-level devices ; According to the column vectors of all matrices in the total set, determine the vectors of all first-level devices that are subordinate to the second-level devices : ; All vectors Form a new matrix , represents the optimal combination of weights of the first-level devices at time t; Repeat the above steps to calculate the optimal combination of the weights of the first-level devices at different times, and combine the optimal combination of the weights of the first-level devices at different times into the optimal combination of the weights of the first-level devices at all times. , a weight value of 1 represents that the first-level device is subordinate to the current second-level device; According to the optimal combination of the weights of the first-level devices at all times, the topological relationship between the first-level devices and the second-level devices is obtained by using probability statistics.

2. The method according to claim 1, characterized in that The obtaining of the effective power of each first-level device and each second-level device in the power grid at different times includes: Under the condition of time alignment, the effective power of each first-level device and each second-level device in the power grid at different times is obtained.

3. The method according to claim 1, characterized in that The weight combination of the first-level devices that meet the preset conditions is determined according to the effective power of each first-level device at different times and the effective power of each second-level device at different times. ,include: Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1; Traverse the different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters ; Calculate the total effective power of the first-stage device under different value combinations of weight parameters according to the first weight matrix : ;in, The matrix representing the effective power of each first-stage device, i=1, 2, ..., N; Calculate the difference between the total effective power of the first stage device and the effective power of each second stage device: , confirm that Weight combination , where c satisfies The number of weight combinations, j = 1, 2, ..., M, M is the number of second-level devices.

4. The method according to claim 1, wherein The weight combination of the first-level devices that meet the preset conditions is determined according to the effective power of each first-level device at different times and the effective power of each second-level device at different times. ,include: Calculate the step power of each first-stage device at different times based on the effective power of each first-stage device at different times : ;in, represents the effective power of the i-th first-stage device at time t, i = 1, 2, ..., N; Calculate the step power of each second-stage device at different times based on the effective power of each second-stage device at different times : ;in, represents the effective power of the jth second-stage device at time t, j = 1, 2, ..., M; Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1; Traverse the different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters ; Calculate the total step power of the first-stage device under different value combinations of weight parameters according to the first weight matrix : ;in, A matrix representing the step power components of each first-stage device; Calculate the difference between the total step power of the first stage device and the step power of each second stage device: , confirm that Weight combination , where c satisfies The number of weight combinations.

5. The method according to claim 1, wherein The vectors of all first-level devices belonging to the second-level devices are determined based on the column vectors of all matrices in the total set. ,include: Get the total set Perform XOR operation on the column vectors of all matrices in the matrix to obtain a vector whose all elements are 1 after XOR .

6. The method according to claim 1, characterized in that The vectors of all first-level devices belonging to the second-level devices are determined based on the column vectors of all matrices in the total set. ,include: Traverse the total collection The weight value of the corresponding position of each matrix in the matrix is ​​used to determine whether the two weight values ​​of the corresponding positions are the same. If they are the same, they are recorded as 0, and if they are not the same, they are recorded as 1. After traversing, the vectors with the corresponding positions of all matrices as 1 are obtained. .

7. The method according to claim 1, characterized in that The method of obtaining the topological relationship between each first-level device and each second-level device by using probability statistics based on the optimal combination of weights of the first-level devices at all times includes: Calculate the optimal combination of weights of the first-level devices at all times The number of combinations m in ; Calculate the optimal combination of weights of the first-level devices at all times The i-th first-stage device The number of combinations n belonging to the jth second-level device, then the i-th first-level device The number of combinations that do not belong to the jth second-level device is mn; Compare n and mn. If n>mn, then the i-th first-level device belongs to the jth second-level device; otherwise, the i-th first-level device Not subordinate to the jth second-level device; Traverse all first-level devices and obtain the topological relationship between the first-level devices and the second-level devices.

8. The method according to claim 1, characterized in that The first-level device is a branch, and the second-level device is a station; or The first-level device is the meter box and the second-level device is the branch; or The first-level device is the electricity meter, and the second-level device is the meter box.

9. A topology automatic recognition system based on optimal combination and probability statistics, characterized in that: The system comprises: a data acquisition module, configured to acquire the effective power of each first-level device and each second-level device in the power grid at different times, wherein the first-level device is subordinate to the second-level device; an optimal combination calculation module for electric meter weights, for calculating the optimal combination of weights of the first-level devices at all times based on the effective power of each first-level device and each second-level device at different times; and A probability statistics comparison module is used to obtain the topological relationship between the first-level devices and the second-level devices using probability statistics according to the optimal combination of the weights of the first-level devices at all times; The step of calculating the optimal combination of weights of the first-stage devices at all times based on the effective power of each first-stage device and each second-stage device at different times includes: Determine the weight combination of the first-stage devices that meet the preset conditions according to the effective power of each first-stage device at different times and the effective power of each second-stage device at different times ; The total set of weight combinations of all first-level devices is formed by transposing the weight combinations of the first-level devices ; According to the column vectors of all matrices in the total set, determine the vectors of all first-level devices that are subordinate to the second-level devices : ; All vectors Form a new matrix , represents the optimal combination of weights of the first-level devices at time t; Repeat the above steps to calculate the optimal combination of the weights of the first-level devices at different times, and combine the optimal combination of the weights of the first-level devices at different times into the optimal combination of the weights of the first-level devices at all times. , a weight value of 1 represents that the first-level device is subordinate to the current second-level device.

10. The system according to claim 9, characterized in that The weight combination of the first-level devices that meet the preset conditions is determined according to the effective power of each first-level device at different times and the effective power of each second-level device at different times. ,include: Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1; Traverse the different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters ; Calculate the total effective power of the first-stage device under different value combinations of weight parameters according to the first weight matrix : ;in, The matrix representing the effective power of each first-stage device, i=1, 2, ..., N; Calculate the difference between the total effective power of the first stage device and the effective power of each second stage device: , confirm that Weight combination , where c satisfies The number of weight combinations, j = 1, 2, ..., M, M is the number of second-level devices.

11. The system according to claim 9, wherein: The weight combination of the first-level devices that meet the preset conditions is determined according to the effective power of each first-level device at different times and the effective power of each second-level device at different times. ,include: Calculate the step power of each first-stage device at different times based on the effective power of each first-stage device at different times : ;in, represents the effective power of the i-th first-stage device at time t, i = 1, 2, ..., N; Calculate the step power of each second-stage device at different times based on the effective power of each second-stage device at different times : ;in, represents the effective power of the jth second-stage device at time t, j = 1, 2, ..., M; Set the weight parameters of each first-level device : ,in, is a binary matrix of 0 and 1; Traverse the different value combinations of the weight parameters to obtain the first weight matrix composed of the weight parameters ; Calculate the total step power of the first-stage device under different value combinations of weight parameters according to the first weight matrix : ;in, A matrix representing the step power components of each first-stage device; Calculate the difference between the total step power of the first stage device and the step power of each second stage device: , confirm that Weight combination , where c satisfies The number of weight combinations.

12. The system according to claim 9, wherein: The vectors of all first-level devices belonging to the second-level devices are determined based on the column vectors of all matrices in the total set. ,include: Get the total set Perform XOR operation on the column vectors of all matrices in the matrix to obtain a vector whose all elements are 1 after XOR .

13. The system according to claim 9, wherein: The vectors of all first-level devices belonging to the second-level devices are determined based on the column vectors of all matrices in the total set. ,include: Traverse the total collection The weight value of the corresponding position of each matrix in the matrix is ​​used to determine whether the two weight values ​​of the corresponding positions are the same. If they are the same, they are recorded as 0, and if they are not the same, they are recorded as 1. After traversing, the vectors with the corresponding positions of all matrices as 1 are obtained. .

14. The system according to claim 9, wherein: The method of obtaining the topological relationship between each first-level device and each second-level device by using probability statistics based on the optimal combination of weights of the first-level devices at all times includes: Calculate the optimal combination of weights of the first-level devices at all times The number of combinations m in ; Calculate the optimal combination of weights of the first-level devices at all times The i-th first-stage device The number of combinations n belonging to the jth second-level device, then the i-th first-level device The number of combinations that do not belong to the jth second-level device is mn; Compare n and mn. If n>mn, then the i-th first-level device belongs to the jth second-level device; otherwise, the i-th first-level device Not subordinate to the jth second-level device; Traverse all first-level devices and obtain the topological relationship between the first-level devices and the second-level devices.

15. A topology automatic recognition device based on optimal combination and probability statistics, characterized in that: The device comprises: memory for storing computer programs; A processor, configured to run the computer program to execute the method for automatic topology recognition based on optimal combination and probability statistics according to any one of claims 1 to 8.

16. A machine-readable storage medium having instructions stored thereon, the instructions being used to enable a machine to execute the automatic topology recognition method based on optimal combination and probability statistics according to any one of claims 1 to 8.

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