CN112202248A - Low-voltage distribution network topology branch refining identification method - Google Patents
Low-voltage distribution network topology branch refining identification method Download PDFInfo
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00001—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by the display of information or by user interaction, e.g. supervisory control and data acquisition systems [SCADA] or graphical user interfaces [GUI]
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
Abstract
The invention relates to a low-voltage distribution network topology branch refining identification method, which belongs to the technical field of intelligent power grids and comprises the following steps: (1) acquiring all voltage data sequences to be analyzed from electricity utilization information acquisition data, analyzing to obtain a daily three-phase voltage data sequence of an electricity meter box, (2) calculating cosine similarity, (3) obtaining a most relevant electricity meter box by a strongly relevant electricity meter box judgment method, (4) obtaining a preliminary analysis result of a dependent branch number by a relevant island judgment method, and (5) obtaining a final analysis result of the dependent branch number by a multi-day comprehensive optimization method. According to the method, branch monitoring equipment is not required to be added, the topology of the low-voltage distribution network can be refined only by carrying out data association analysis on the collected data, and the archive management capability and the operation and maintenance capability of the distribution network are improved.
Description
Technical Field
The invention relates to a low-voltage distribution network topology branch refining identification method, and belongs to the technical field of intelligent power grids. In particular to a topology identification method for refining topology branches of a low-voltage distribution network by a data sequence similarity analysis and association matching method based on a voltage data sequence acquired by a power utilization information acquisition system.
Background
The power distribution network is an important public infrastructure for national economy and social development. In recent years, the construction investment of power distribution networks in China is continuously increased, the development of the power distribution networks has remarkable effect, but the power utilization level is still different from the international advanced level, the development of urban and rural areas is unbalanced, and the power supply quality needs to be improved. The method has the advantages of building urban and rural overall, safe and reliable, economic and efficient, advanced in technology and environment-friendly distribution network facilities and service systems, not only ensuring the residents and promoting the investment, but also driving the level of the manufacturing industry to be improved, providing powerful support for adapting to energy interconnection and promoting the development of the Internet +, and having important significance for stable growth, reform promotion, structure adjustment and people improvement. The power distribution network is composed of overhead lines, cables, towers, distribution transformers, isolating switches, reactive power compensators, a plurality of accessory facilities and the like, plays a role in distributing electric energy in the power network, and is an important public infrastructure for national economy and social development. With the continuous development of power distribution networks, the types of power supply equipment of the power grids are more and more, and data and information data related to the power grids are more and more complex. The statistics of the distribution network needs to be performed and analyzed by planners who converge to a local city in each county, and due to the large data volume and the large number of models of the distribution network, the workload and the period of the operation and maintenance personnel performing the statistics and analysis are large, the problems of the data are difficult to find, the problem data are possibly generated to participate in the calculation by taking the problem data as the original quantity, the distribution network planning result is not accurate enough or problems occur, and the operation and maintenance are difficult.
The low-voltage distribution transformer area is the minimum unit and the data source of the power distribution network, and has the outstanding problems of disordered connection files of a transformer substation, low active sensing level of power failure events, low automation degree of abnormal line loss positioning, low real-time monitoring level of equipment states and the like for a long time, so that a series of consequences of difficult line loss management, long rush repair time, high equipment failure rate and the like are caused. The accuracy of topology identification is the basis of other functions, but the prior art cannot realize the detailed identification of the low-voltage distribution network topology according to branches on the premise of lacking of branch monitoring, so that the accurate positioning of faults, the lean analysis of line loss and the sectional calculation of impedance are limited. Meanwhile, the current intelligent electric meter is only limited to remote automatic meter reading, the non-metering application of the operation and maintenance of the support area is still weak, the value of power utilization information acquisition data is fully mined, and the support topology identification capability is improved.
Disclosure of Invention
In order to solve the technical problems, the invention provides a low-voltage distribution network topology branch refining identification method, which comprises the following specific technical scheme:
step 1: acquiring voltage data sequences of all electric energy meters to be analyzed from electricity utilization information acquisition data, wherein each electric energy meter is set as an electric energy meter to be analyzed, all the electric energy meters to be analyzed are electric energy meter sets to be analyzed, the subordinate electric meter boxes of the electric energy meters to be analyzed are electric meter boxes to be analyzed, all the electric meter boxes to be analyzed are electric meter box sets to be analyzed, and analyzing to obtain a daily three-phase voltage data sequence of each electric meter box to be analyzed, and setting the daily three-phase voltage data sequence as a daily three-phase voltage data sequence;
step 2: calculating cosine similarity among the daily three-phase voltage data sequences of all the electric meter boxes to be analyzed;
and step 3: obtaining the most relevant ammeter box of each ammeter box to be analyzed according to a strong relevant ammeter box judging method;
and 4, step 4: obtaining a preliminary analysis result of the serial number of the subordinate branch of each ammeter box to be analyzed according to the association island judgment method;
and 5: and obtaining a final analysis result of the serial number of the subordinate branch of each electric meter box to be analyzed according to a multi-day comprehensive optimization method.
Further, the specific steps of obtaining the daily three-phase voltage data sequence of each electric meter box to be analyzed in the step one are as follows:
step 1.1: acquiring the file number of an electric meter box set to be analyzed to obtain a voltage data sequence of all electric energy meters in a low-voltage distribution network to be calculated by a target;
step 1.2: according to the subordinate relation and the phase relation of the electric energy meter to be analyzed and the electric meter box to be analyzed, taking a certain electric meter box to be analyzed as an object, calculating the average value of all voltage data sequences of the electric meter box to be analyzed in each phase by A, B, C three phases, and taking the average value as a daily three-phase voltage data sequence of the electric meter box to be analyzed;
step 1.3: and traversing the ammeter box set to be analyzed to obtain all daily three-phase voltage data sequences in the ammeter box set to be analyzed.
Further, the formula for calculating the cosine similarity is as follows:
in the formula (I), the compound is shown in the specification,
expressing cosine similarity values of a voltage data sequence A and a voltage data sequence B, wherein A is the voltage data sequence of the electric energy meter to be analyzed, B is the voltage data sequence of other electric energy meters to be analyzed, N is the dimension of the voltage data sequence, i is the number of the electric meter box to be analyzed, i is numbered from 1 and is the maximum Nmax。
Further, the method for judging the strongly-associated electricity meter box in the step 3 specifically comprises the following steps:
step 3.1: obtaining a voltage data sequence with the highest cosine similarity value according to three phase voltage data sequences in one ammeter box to be analyzed and the three-phase cosine similarity of other ammeter boxes to be analyzed;
step 3.2: acquiring the ammeter box file number to which the corresponding phase voltage data sequence of the ammeter box to be analyzed with the highest cosine similarity value belongs, and setting the ammeter box file number as the ammeter box with the most similar corresponding phase;
step 3.3: this treat three phase place voltage data sequence of analysis ammeter case and obtain three most similar ammeter case of corresponding phase place, acquire the archives serial number of three most similar ammeter case of corresponding phase place, establish the most similar ammeter case that archives serial number appears the number of times 2-3 and be the most relevant ammeter case.
Further, the specific steps of the associated island determination method in step 4 are as follows:
step 4.1: starting the ammeter to be analyzed from 1 to N according to the file number imaxArranged in descending order (i =1,2, … …, N)max) Carrying out the subsequent steps in the sequence of i;
step 4.2: the subordinate branch number k is set from 1 to small (k =1,2, … …, N)max）；
Step 4.3: when the subordinate branch number k = j, the file number with the minimum number without the subordinate branch number is taken to be analyzedThe meter box is provided with a subordinate branch number j (j is 1-N)maxIn the range of j starting from 1);
step 4.4: when the serial number of the subordinate branch is k = j, when the most relevant ammeter box of the ammeter box to be analyzed with the branch serial number of j is an ammeter box n, the serial number of the subordinate branch of the ammeter box to be analyzed with the branch serial number of j is set as j;
step 4.5: traversing all the ammeter boxes to be analyzed, obtaining the most relevant ammeter box with the file number of m of the ammeter boxes to be analyzed as the ammeter box to be analyzed with the file number of N, obtaining the most relevant ammeter box with the file number of m of the ammeter boxes to be analyzed as the ammeter box to be analyzed j, and obtaining the most relevant ammeter box with the file number of p of the ammeter boxes to be analyzed as the ammeter box to be analyzed j, wherein the serial numbers of the meter boxes to be analyzed m and the subordinate branches of the ammeter boxes to be analyzed p are j (m, NmaxWithin a range of (a);
step 4.6: traversing all the electric meter boxes to be analyzed, wherein the number of the sub-branch of the electric meter box to be analyzed, which is consistent with 4.3-4,5, is j, until the number of the electric meter boxes to be analyzed of the sub-branch is not increased;
step 4.7: and (4) analyzing the number j +1 of the next subordinate branch, repeating the steps 4.2-4.6 until the number of the electric meter boxes of the subordinate branch is not increased any more, and traversing the next number until all the electric meter boxes to be analyzed have the numbers of the subordinate branches.
Further, the multi-day comprehensive optimization method in the step 5 comprises the following specific steps:
step 5.1: calculating the probability value of the serial numbers of all the subordinate branches in the ammeter box set to be analyzed in the previous ten days, wherein the calculation method comprises the following steps: the number of days numbered by the respective dependent branch of each meter box to be analyzed is divided by 10.
Step 5.2: and setting the serial number of the subordinate branch with the highest probability value as a final analysis result of the serial number of the subordinate branch, and setting the probability value as a confidence coefficient.
The invention has the beneficial effects that: branch monitoring equipment does not need to be added, the topology of the low-voltage distribution network can be refined only by carrying out data association analysis by using collected data, and the archive management capability and the operation and maintenance capability of the distribution network are improved.
Drawings
Figure 1 is a flow chart of the method of the present invention,
fig. 2 is a concrete example analysis object association diagram.
Detailed Description
The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic views illustrating only the basic structure of the present invention in a schematic manner, and thus show only the constitution related to the present invention.
As shown in fig. 1, the method comprises the following specific steps:
the method comprises the following steps: the method comprises the steps of acquiring voltage data sequences of all electric energy meters to be analyzed from electricity utilization information acquisition data, setting each electric energy meter to be an electric energy meter to be analyzed, setting all electric energy meters to be analyzed to be electric energy meter sets to be analyzed, setting the subordinate electric energy meter boxes of the electric energy meters to be electric energy meter boxes to be analyzed, setting all electric energy meter boxes to be analyzed to be electric energy meter sets to be analyzed, analyzing to obtain daily three-phase voltage data sequences of each electric energy meter box, and setting the daily three-phase voltage data sequences to be daily three-phase voltage data sequences.
The first step is as follows:
step 1.1: and acquiring the file number of the ammeter box set to be analyzed to obtain the voltage data sequence of all the electric energy meters in the low-voltage distribution network to be calculated by the target.
Step 1.2: according to the subordinate relation and the phase relation of the electric energy meter to be analyzed and the electric meter box to be analyzed, a certain electric meter box to be analyzed is taken as an object, the average value of all voltage data sequences of the electric meter box to be analyzed in each phase is calculated according to A, B, C three phases, and the average value is taken as the daily three-phase voltage data sequence of the electric meter box to be analyzed.
Step 1.3: and traversing the ammeter box set to be analyzed to obtain all daily three-phase voltage data sequences in the ammeter box set to be analyzed.
Step 2: and calculating cosine similarity between the daily three-phase voltage data sequences of all the electric meter boxes.
The cosine similarity calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
expressing cosine similarity values of a voltage data sequence A and a voltage data sequence B, wherein A is the voltage data sequence of the electric energy meter to be analyzed, B is the voltage data sequence of other electric energy meters to be analyzed, N is the dimension of the voltage data sequence, i is the number of the electric meter box to be analyzed, i is numbered from 1 and is the maximum Nmax。
And step 3: and obtaining the most relevant electric meter box of each electric meter box according to the strong relevant electric meter box judgment method.
The method for judging the strongly-associated electric meter box comprises the following specific steps:
step 3.1: and obtaining a voltage data sequence with the highest cosine similarity value according to the three phase voltage data sequences in one ammeter box to be analyzed and the three-phase cosine similarity of other ammeter boxes to be analyzed.
Step 3.2: and acquiring the ammeter box file number to which the corresponding phase voltage data sequence of the ammeter box to be analyzed with the highest cosine similarity value belongs, and setting the ammeter box to be the most similar ammeter box with the corresponding phase.
Step 3.3: this treat three phase place voltage data sequence of analysis ammeter case and obtain three most similar ammeter case of corresponding phase place, acquire the archives serial number of three most similar ammeter case of corresponding phase place, establish the most similar ammeter case that archives serial number appears the number of times 2-3 and be the most relevant ammeter case.
And 4, step 4: and obtaining a preliminary analysis result of the serial number of the subordinate branch of each ammeter box to be analyzed according to the association island judgment method.
The method for judging the associated island comprises the following specific steps:
step 4.1: starting the ammeter to be analyzed from 1 to N according to the file number imaxArranged in descending order (i =1,2, … …, N)max) Carrying out the subsequent steps in the sequence of i;
step 4.2: the subordinate branch number k is set from 1 to small (k =1,2, … …, N)max）；
Step 4.3: when the serial number of the subordinate branch is k = j, taking the ammeter box to be analyzed with the smallest file serial number without the serial number of the subordinate branch, and setting the serial number of the subordinate branch as j (j is 1-N)maxIn the range of j starting from 1);
step 4.4: when the serial number of the subordinate branch is k = j, when the most relevant ammeter box of the ammeter box to be analyzed with the branch serial number of j is an ammeter box n, the serial number of the subordinate branch of the ammeter box to be analyzed with the branch serial number of j is set as j;
step 4.5: traversing all the ammeter boxes to be analyzed, obtaining the most relevant ammeter box with the file number of m of the ammeter boxes to be analyzed as the ammeter box to be analyzed with the file number of N, obtaining the most relevant ammeter box with the file number of m of the ammeter boxes to be analyzed as the ammeter box to be analyzed j, and obtaining the most relevant ammeter box with the file number of p of the ammeter boxes to be analyzed as the ammeter box to be analyzed j, wherein the serial numbers of the meter boxes to be analyzed m and the subordinate branches of the ammeter boxes to be analyzed p are j (m, NmaxWithin a range of (a);
step 4.6: traversing all the electric meter boxes to be analyzed, wherein the number of the sub-branch of the electric meter box to be analyzed, which is consistent with 4.3-4,5, is j, until the number of the electric meter boxes to be analyzed of the sub-branch is not increased;
step 4.7: and (4) analyzing the number j +1 of the next subordinate branch, repeating the steps 4.2-4.6 until the number of the electric meter boxes of the subordinate branch is not increased any more, and traversing the next number until all the electric meter boxes to be analyzed have the numbers of the subordinate branches.
And 5: and obtaining the final analysis result of the serial number of the subordinate branch of each electric meter box to be analyzed according to a multi-day comprehensive optimization method.
Step 5.1: calculating the probability value of each subordinate branch number of each electric meter box to be analyzed in the previous ten days, wherein the calculation method comprises the following steps: the number of days numbered by the respective dependent branch of each meter box to be analyzed is divided by 10.
Step 5.2: and setting the serial number of the subordinate branch with the highest probability value as a final analysis result of the serial number of the subordinate branch, and setting the probability value as a confidence coefficient.
Specific analysis is performed by taking a certain low-voltage transformer area as an example, and fig. 2 shows a box transformer dependency relationship diagram of an analysis object of a specific example.
The electric energy meter to be analyzed is set as { electric energy meter 1, electric energy meter 2, electric energy meter 3, electric energy meter 4, electric energy meter 5, electric energy meter 6, electric energy meter 7, electric energy meter 8, electric energy meter 9, electric energy meter 10, electric energy meter 11, electric energy meter 12, electric energy meter 13, electric energy meter 14, electric energy meter 15, electric energy meter 16, electric energy meter 17, electric energy meter 18, electric energy meter 19, electric energy meter 20, electric energy meter 21, electric energy meter 22, electric energy meter 23, electric energy meter 24, electric energy meter 25, electric energy meter 26, electric energy meter 27, electric energy meter 28, electric energy meter 29, electric energy meter 30, electric energy meter 31, electric energy meter 32, electric energy meter 33, electric energy meter 34, electric energy meter 35 and electric energy meter 36 }. The ammeter box to be analyzed is integrated into { ammeter box 1, ammeter box 2, ammeter box 3, ammeter box 4, ammeter box 5, ammeter box 6 }. Wherein:
{ electric energy meter 1, electric energy meter 2, electric energy meter 3, electric energy meter 4, electric energy meter 5 and electric energy meter 6} belong to electric energy meter box 1, and { electric energy meter 1 and electric energy meter 4} are accessed to phase A, { electric energy meter 2 and electric energy meter 5} are accessed to phase B, and { electric energy meter 3 and electric energy meter 6} are accessed to phase C;
{ electric energy meter 7, electric energy meter 8, electric energy meter 9, electric energy meter 10, electric energy meter 11, electric energy meter 12} belong to electric energy meter box 2, and { electric energy meter 7, electric energy meter 10} is connected to phase A, { electric energy meter 8, electric energy meter 11} is connected to phase B, and { electric energy meter 9, electric energy meter 12} is connected to phase C;
the { electric energy meter 13, the electric energy meter 14, the electric energy meter 15, the electric energy meter 16, the electric energy meter 17 and the electric energy meter 18} belong to the electric meter box 3, the { electric energy meter 13 and the electric energy meter 16} is connected to the phase A, the { electric energy meter 14 and the electric energy meter 17} is connected to the phase B, and the { electric energy meter 15 and the electric energy meter 18} is connected to the phase C;
{ electric energy meter 19, electric energy meter 20, electric energy meter 21, electric energy meter 22, electric energy meter 23, electric energy meter 24} belongs to electric energy meter box 4, and { electric energy meter 19, electric energy meter 22} is connected to phase A, { electric energy meter 20, electric energy meter 23} is connected to phase B, and { electric energy meter 21, electric energy meter 24} is connected to phase C;
{ electric energy meter 25, electric energy meter 26, electric energy meter 27, electric energy meter 28, electric energy meter 29, electric energy meter 30} is subordinate to electric energy meter box 5, and { electric energy meter 25, electric energy meter 28} is connected to phase a, { electric energy meter 26, electric energy meter 29} is connected to phase B, and { electric energy meter 27, electric energy meter 30} is connected to phase C;
{ electric energy meter 31, electric energy meter 32, electric energy meter 33, electric energy meter 34, electric energy meter 35, electric energy meter 36} is subordinate to electric energy meter box 6, and { electric energy meter 31, electric energy meter 34} is connected to phase a, { electric energy meter 32, electric energy meter 35} is connected to phase B, and { electric energy meter 33, electric energy meter 36} is connected to phase C.
Step 1: according to the subordinate relation and the phase relation of the electric energy meter to be analyzed and the electric meter box to be analyzed, a certain electric meter box to be analyzed is taken as an object, the average value of all voltage data sequences of the electric meter box to be analyzed in each phase is calculated according to A, B, C three phases, and the average value is taken as the daily three-phase voltage data sequence of the electric meter box to be analyzed. And traversing the ammeter box set to be analyzed to obtain all daily three-phase voltage data sequences in the ammeter box set to be analyzed.
Step 2: calculating the cosine similarity between the daily three-phase voltage data sequences of all the electricity meter boxes by taking one day as an example, and obtaining the following results:
and step 3: and obtaining the most relevant electric meter box of each electric meter box according to the strong relevant electric meter box judgment method.
According to three phase voltage data sequences in an electric meter box to be analyzed and the three-phase cosine similarity of other electric meter boxes to be analyzed, obtaining a voltage data sequence with the highest cosine similarity, obtaining the electric meter box file number to which the phase voltage data sequence corresponding to the electric meter box to be analyzed with the highest cosine similarity belongs, and setting the electric meter box to be the electric meter box with the most similar corresponding phase. This gives:
the most similar voltage sequence of the A phase of the ammeter box 1 is the A phase of the ammeter box 4, and the most similar ammeter box is the ammeter box 4; the most similar voltage sequence of the B phase of the ammeter box 1 is the B phase of the ammeter box 2, and the most similar ammeter box is the ammeter box 2; the C-phase most similar voltage sequence of the ammeter box 1 is the C-phase of the ammeter box 2, and the most similar ammeter box is the ammeter box 2;
the most similar voltage sequence of the A phase of the ammeter box 2 is the A phase of the ammeter box 3, and the most similar ammeter box is the ammeter box 3; the most similar voltage sequence of the B phase of the ammeter box 2 is the B phase of the ammeter box 4, and the most similar ammeter box is the ammeter box 4; the C-phase most similar voltage sequence of the ammeter box 2 is the C-phase of the ammeter box 3, and the most similar ammeter box is the ammeter box 3;
the most similar voltage sequence of the A phase of the ammeter box 3 is the A phase of the ammeter box 2, and the most similar ammeter box is the ammeter box 2; the most similar voltage sequence of the B phase of the ammeter box 3 is the B phase of the ammeter box 4, and the most similar ammeter box is the ammeter box 4; the C-phase most similar voltage sequence of the ammeter box 3 is the C-phase of the ammeter box 2, and the most similar ammeter box is the ammeter box 2;
the most similar voltage sequence of the A phase of the ammeter box 4 is the A phase of the ammeter box 1, and the most similar ammeter box is the ammeter box 1; the most similar voltage sequence of the B phase of the ammeter box 4 is the B phase of the ammeter box 3, and the most similar ammeter box is the ammeter box 3; the C-phase most similar voltage sequence of the electric meter box 4 is the C-phase of the meter box 1, and the most similar electric meter box is the meter box 1;
the most similar voltage sequence of the A phase of the ammeter box 5 is the A phase of the ammeter box 6, and the most similar ammeter box is the ammeter box 6; the most similar voltage sequence of the B phase of the ammeter box 5 is the B phase of the ammeter box 6, and the most similar ammeter box is the ammeter box 6; the C-phase most similar voltage sequence of the ammeter box 5 is the C-phase of the ammeter box 6, and the most similar ammeter box is the ammeter box 6;
the most similar voltage sequence of the A phase of the ammeter box 6 is the A phase of the ammeter box 5, and the most similar ammeter box is the ammeter box 5; the most similar voltage sequence of the B phase of the ammeter box 6 is the B phase of the ammeter box 5, and the most similar ammeter box is the ammeter box 5; the C-phase most similar voltage sequence of the electric meter box 6 is the C-phase of the meter box 5, and the most similar electric meter box is the meter box 5.
This treat three phase place voltage data sequence of analysis ammeter case and obtain three most similar ammeter case of corresponding phase place, acquire the archives serial number of three most similar ammeter case of corresponding phase place, establish the most similar ammeter case that archives serial number appears the number of times 2-3 and be the most relevant ammeter case, obtain from this and show
The most relevant ammeter box of the ammeter boxes 1 is an ammeter box 2, and the outgoing is performed for 2 times;
the most relevant ammeter box of the ammeter boxes 2 is an ammeter box 3, and the outgoing is performed for 2 times;
the most relevant ammeter box of the ammeter boxes 3 is the ammeter box 2, and the outgoing is performed for 2 times;
the most relevant ammeter box of the ammeter boxes 4 is the ammeter box 1, and the outgoing is performed for 2 times;
the most relevant ammeter box of the ammeter boxes 5 is the ammeter box 6, and the outgoing lines are 3 times;
the most relevant ammeter box of the ammeter boxes 6 is the ammeter box 5, and the outgoing lines are 3 times;
and 4, step 4: and obtaining a preliminary analysis result of the serial number of the subordinate branch of each ammeter box to be analyzed according to the association island judgment method.
The method for judging the associated island comprises the following specific steps:
step 4.1: starting the ammeter to be analyzed from 1 to N according to the file number imaxArranged in descending order (i =1,2, … …, N)max) Carrying out the subsequent steps in the sequence of i;
step 4.2: the subordinate branch number k is set from 1 to small (k =1,2, … …, N)max）；
Step 4.3: when the serial number of the subordinate branch is k = j, taking the ammeter box to be analyzed with the smallest file serial number without the serial number of the subordinate branch, and setting the serial number of the subordinate branch as j (j is 1-N)maxIn the range of j starting from 1);
step 4.4: when the serial number of the subordinate branch is k = j, when the most relevant ammeter box of the ammeter box to be analyzed with the branch serial number of j is an ammeter box n, the serial number of the subordinate branch of the ammeter box to be analyzed with the branch serial number of j is set as j;
step 4.5: traversing all the ammeter boxes to be analyzed, obtaining the most relevant ammeter box with the file number of m of the ammeter boxes to be analyzed as the ammeter box to be analyzed with the file number of N, obtaining the most relevant ammeter box with the file number of m of the ammeter boxes to be analyzed as the ammeter box to be analyzed j, and obtaining the most relevant ammeter box with the file number of p of the ammeter boxes to be analyzed as the ammeter box to be analyzed j, wherein the serial numbers of the meter boxes to be analyzed m and the subordinate branches of the ammeter boxes to be analyzed p are j (m, NmaxWithin a range of (a);
step 4.6: traversing all the electric meter boxes to be analyzed, wherein the number of the sub-branch of the electric meter box to be analyzed, which is consistent with 4.3-4,5, is j, until the number of the electric meter boxes to be analyzed of the sub-branch is not increased;
step 4.7: and (4) analyzing the number j +1 of the next subordinate branch, repeating the steps 4.2-4.6 until the number of the electric meter boxes of the subordinate branch is not increased any more, and traversing the next number until all the electric meter boxes to be analyzed have the numbers of the subordinate branches.
Repeating for the first time:
firstly, an electric meter box 1 is arranged in a branch with the subordinate branch number of 1, the most relevant electric meter box is an electric meter box 2, and the subordinate branch number of the electric meter box 2 is 1;
traversing all the ammeter boxes to obtain: the most relevant ammeter box of the ammeter boxes 3 is the ammeter box 2, the most relevant ammeter box of the ammeter boxes 4 is the ammeter box 1, the dependent branches of the ammeter boxes 1 and 2 are both numbered as 1, and the dependent branches of the ammeter boxes 3 and 4 are set as 1;
the number of the electric meter boxes with the subordinate branch number of 1 is changed from 1 to 4, and the second repetition is carried out.
And repeating for the second time:
the branch with the subordinate branch number of 1 is provided with an ammeter box 1, an ammeter box 2, an ammeter box 3 and an ammeter box 4, and the most relevant ammeter boxes determine that the subordinate branch number is 1.
And traversing all the ammeter boxes, wherein the serial number of the subordinate branch of the most relevant ammeter box without a new ammeter box is 1.
The number of the electric meter boxes with the subordinate branch number of 1 is still 4, the electric meter boxes are not increased any more, the repetition is stopped, and the next step is carried out.
Step 4.3: when the serial number of the subordinate branch is k = j, taking the ammeter box to be analyzed with the smallest file serial number without the serial number of the subordinate branch, and setting the serial number of the subordinate branch as j (j is 1-N)maxIn the range of j starting from 1);
the minimum number for determining the serial number of the undetermined subordinate branch is written as a table box 6, and the relationship of the subordinate branch is set to be 2.
Repeating for the first time:
firstly, an electric meter box 5 is arranged in a branch with the subordinate branch number of 2, the most relevant electric meter box is an electric meter box 6, and the subordinate branch number of the electric meter box 6 is set as 1;
traversing all the ammeter boxes to obtain: the dependent branch of the most relevant meter box of the new meter box is numbered 2.
The number of the electric meter boxes with the subordinate branch number of 2 is changed from 1 to 2, and the second repetition is carried out.
And repeating for the second time:
the branch with the subordinate branch number of 2 is provided with an electric meter box 5 and an electric meter box 6, and the most relevant electric meter boxes determine that the subordinate branch number of 2.
And secondly, traversing all the ammeter boxes, wherein the serial number of the subordinate branch of the most relevant ammeter box without a new ammeter box is 2.
The number of the electric meter boxes with the subordinate branch number of 1 is still 4, the electric meter boxes are not increased any more, the repetition is stopped, and the next step is carried out.
Step 4.4: when the serial number of the subordinate branch is k = j, when the most relevant ammeter box of the ammeter box to be analyzed with the branch serial number of j is an ammeter box n, the serial number of the subordinate branch of the ammeter box to be analyzed with the branch serial number of j is set as j;
at this point, all of the boxes have determined the dependent branch number. And (6) ending.
And 5: and obtaining the final analysis result of the serial number of the subordinate branch of each electric meter box to be analyzed according to a multi-day comprehensive optimization method.
Step 5.1: calculating the probability value of each subordinate branch number of each electric meter box to be analyzed in the previous ten days, wherein the calculation method comprises the following steps: the number of days numbered by the respective dependent branch of each meter box to be analyzed is divided by 10.
Step 5.2: and setting the serial number of the subordinate branch with the highest probability value as a final analysis result of the serial number of the subordinate branch, and setting the probability value as a confidence coefficient.
The following results were obtained:
in light of the foregoing description of the preferred embodiment of the present invention, many modifications and variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. The technical scope of the present invention is not limited to the content of the specification, and must be determined according to the scope of the claims.
Claims (6)
1. A low-voltage distribution network topology branch refining identification method is characterized by comprising the following steps: the method comprises the following steps:
step 1: acquiring voltage data sequences of all electric energy meters to be analyzed from electricity utilization information acquisition data, wherein each electric energy meter is set as an electric energy meter to be analyzed, all the electric energy meters to be analyzed are electric energy meter sets to be analyzed, the subordinate electric meter boxes of the electric energy meters to be analyzed are electric meter boxes to be analyzed, all the electric meter boxes to be analyzed are electric meter box sets to be analyzed, and analyzing to obtain a daily three-phase voltage data sequence of each electric meter box to be analyzed, and setting the daily three-phase voltage data sequence as a daily three-phase voltage data sequence;
step 2: calculating cosine similarity among the daily three-phase voltage data sequences of all the electric meter boxes to be analyzed;
and step 3: obtaining the most relevant ammeter box of each ammeter box to be analyzed according to a strong relevant ammeter box judging method;
and 4, step 4: obtaining a preliminary analysis result of the serial number of the subordinate branch of each ammeter box to be analyzed according to the association island judgment method;
and 5: and obtaining a final analysis result of the serial number of the subordinate branch of each electric meter box to be analyzed according to a multi-day comprehensive optimization method.
2. The low-voltage distribution network topology branch refinement identification method according to claim 1, characterized in that: the method comprises the following specific steps of obtaining a daily three-phase voltage data sequence of each ammeter box to be analyzed in the first step:
step 1.1: acquiring the file number of an electric meter box set to be analyzed to obtain a voltage data sequence of all electric energy meters in a low-voltage distribution network to be calculated by a target;
step 1.2: according to the subordinate relation and the phase relation of the electric energy meter to be analyzed and the electric meter box to be analyzed, taking a certain electric meter box to be analyzed as an object, calculating the average value of all voltage data sequences of the electric meter box to be analyzed in each phase by A, B, C three phases, and taking the average value as a daily three-phase voltage data sequence of the electric meter box to be analyzed;
step 1.3: and traversing the ammeter box set to be analyzed to obtain all daily three-phase voltage data sequences in the ammeter box set to be analyzed.
3. The low-voltage distribution network topology branch refinement identification method according to claim 2, characterized in that:
cosine similarity meterThe calculation formula is as follows:
in the formula (I), the compound is shown in the specification,
expressing cosine similarity values of a voltage data sequence A and a voltage data sequence B, wherein A is the voltage data sequence of the electric energy meter to be analyzed, B is the voltage data sequence of other electric energy meters to be analyzed, N is the dimension of the voltage data sequence, i is the number of the electric meter box to be analyzed, i is numbered from 1 and is the maximum Nmax。
4. The low-voltage distribution network topology branch refinement identification method according to claim 3, characterized in that: the method for judging the strongly-associated ammeter box in the step 3 comprises the following specific steps:
step 3.1: obtaining a voltage data sequence with the highest cosine similarity value according to three phase voltage data sequences in one ammeter box to be analyzed and the three-phase cosine similarity of other ammeter boxes to be analyzed;
step 3.2: acquiring the ammeter box file number to which the corresponding phase voltage data sequence of the ammeter box to be analyzed with the highest cosine similarity value belongs, and setting the ammeter box file number as the ammeter box with the most similar corresponding phase;
step 3.3: this treat three phase place voltage data sequence of analysis ammeter case and obtain three most similar ammeter case of corresponding phase place, acquire the archives serial number of three most similar ammeter case of corresponding phase place, establish the most similar ammeter case that archives serial number appears the number of times 2-3 and be the most relevant ammeter case.
5. The low-voltage distribution network topology branch refinement identification method according to claim 4, characterized in that: the method for judging the associated island in the step 4 comprises the following specific steps:
step 4.1: starting the ammeter to be analyzed from 1 to N according to the file number imaxArranged in descending order (i =1,2, … …, N)max) Carrying out the subsequent steps in the sequence of i;
step 4.2: the subordinate branch number k is set from 1 to small (k =1,2, … …, N)max）；
Step 4.3: when the serial number of the subordinate branch is k = j, taking the ammeter box to be analyzed with the smallest file serial number without the serial number of the subordinate branch, and setting the serial number of the subordinate branch as j (j is 1-N)maxIn the range of j starting from 1);
step 4.4: when the serial number of the subordinate branch is k = j, when the most relevant ammeter box of the ammeter box to be analyzed with the branch serial number of j is an ammeter box n, the serial number of the subordinate branch of the ammeter box to be analyzed with the branch serial number of j is set as j;
step 4.5: traversing all the ammeter boxes to be analyzed, obtaining the most relevant ammeter box with the file number of m of the ammeter boxes to be analyzed as the ammeter box to be analyzed with the file number of N, obtaining the most relevant ammeter box with the file number of m of the ammeter boxes to be analyzed as the ammeter box to be analyzed j, and obtaining the most relevant ammeter box with the file number of p of the ammeter boxes to be analyzed as the ammeter box to be analyzed j, wherein the serial numbers of the meter boxes to be analyzed m and the subordinate branches of the ammeter boxes to be analyzed p are j (m, NmaxWithin a range of (a);
step 4.6: traversing all the electric meter boxes to be analyzed, wherein the number of the sub-branch of the electric meter box to be analyzed, which is consistent with 4.3-4,5, is j, until the number of the electric meter boxes to be analyzed of the sub-branch is not increased;
step 4.7: and (4) analyzing the number j +1 of the next subordinate branch, repeating the steps 4.2-4.6 until the number of the electric meter boxes of the subordinate branch is not increased any more, and traversing the next number until all the electric meter boxes to be analyzed have the numbers of the subordinate branches.
6. The low-voltage distribution network topology branch refinement identification method according to claim 5, characterized in that: the multi-day comprehensive optimization method in the step 5 comprises the following specific steps:
step 5.1: calculating the probability value of the serial numbers of all the subordinate branches in the ammeter box set to be analyzed in the previous ten days, wherein the calculation method comprises the following steps: dividing the number of days of each subordinate branch number of each electric meter box to be analyzed by 10;
step 5.2: and setting the serial number of the subordinate branch with the highest probability value as a final analysis result of the serial number of the subordinate branch, and setting the probability value as a confidence coefficient.
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