CN114024308A - Power distribution network platform relationship identification method and system - Google Patents
Power distribution network platform relationship identification method and system Download PDFInfo
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- CN114024308A CN114024308A CN202111320185.0A CN202111320185A CN114024308A CN 114024308 A CN114024308 A CN 114024308A CN 202111320185 A CN202111320185 A CN 202111320185A CN 114024308 A CN114024308 A CN 114024308A
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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
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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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
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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Abstract
The invention discloses a power distribution network station relationship identification method and a power distribution network station relationship identification system, which are used for acquiring power distribution network distribution transformer voltage data and low-voltage user voltage data, calculating correlation coefficients of low-voltage users and station account transformers after the data cleaning and the data reconstruction are carried out on the distribution transformer voltage data and the low-voltage user voltage data, judging whether the station relationship of the station accounts is correct according to the correlation coefficients of the low-voltage users and the station account transformers, and solving the technical problems that the traditional manual identification method and the method for identifying the station relationship by using special station area identification equipment are low in intelligence degree and cannot meet the intelligent development requirement of a power distribution network station area.
Description
Technical Field
The invention relates to the technical field of power distribution network data analysis, in particular to a power distribution network user relationship identification method and system.
Background
The distribution network area has a large number of users and a complex network structure, and after the wiring of the users is changed or a power grid company carries out line transformation for load balanced distribution, the records of the affiliation relationship between the incoming line end of the users and the concentrator are not accurate, the relationship between the users and the concentrator is not consistent with the reality due to reasons such as untimely recording or authority adjustment, and the like, and the problem that the archives of the area, such as the affiliation of the area is difficult to define, of the cable power supply users is disordered.
The traditional station-user relationship identification method has the identification modes of manual identification and special station identification equipment, the manual identification mode needs power personnel to check the affiliation condition of station users on site one by one, the efficiency is low, the special station equipment identification mode mainly uses a carrier communication method or a pulse current method, the carrier communication method has the problem of 'station area stringing', the pulse current method cannot carry out two-way communication, the carrier communication method is used as auxiliary communication for matching, in addition, the potential safety hazard problem exists in the process of identifying the power distribution station users by adopting current clamps, the cost of the special station equipment is higher, and the intelligent development requirement of the power distribution network station cannot be met. Therefore, it is desirable to provide a new method for identifying relationships between power distribution network users, which avoids the problems of the conventional method for identifying relationships between power distribution network users and improves the intelligence of identifying relationships between power distribution network users.
Disclosure of Invention
The embodiment of the invention provides a power distribution network station relationship identification method and system, which are used for solving the technical problems that the traditional method for identifying the station relationship by manual identification and special station area identification equipment is low in intelligent degree and cannot meet the intelligent development requirement of a power distribution network station area.
In view of the above, the present invention provides a method for identifying relationships between power distribution network users, comprising the following steps:
s1, acquiring distribution transformer voltage data and low-voltage user voltage data of the power distribution network;
s2, carrying out data cleaning on the distribution transformer voltage data and the low-voltage user voltage data, wherein the data cleaning comprises data abnormal value standard processing and data missing value supplementing processing;
s3, carrying out data reconstruction on the distribution transformer voltage data and the low-voltage user voltage data after data cleaning to obtain a distribution transformer voltage time sequence and a low-voltage user voltage time sequence which accord with preset lengths;
s4, calculating a correlation coefficient of the low-voltage user and the distribution transformer according to the distribution transformer voltage time sequence and the low-voltage user voltage time sequence;
and S5, judging whether the standing book is correct according to the correlation coefficient of the low-voltage user and the transformer of the standing book, wherein if the correlation coefficient of the low-voltage user and the transformer of the standing book is not less than a first threshold value, the standing book relationship is correct.
Optionally, step S5 is followed by:
and S6, if the correlation coefficient of the low-voltage user and the transformer of the account book is smaller than the first threshold value, judging whether the correlation coefficient of the low-voltage user and the most relevant transformer is larger than the second threshold value and is larger than the correlation coefficient of the secondary relevant transformer by more than a preset difference value, and if so, judging that the account relation of the account book is correct.
Optionally, step S6 is followed by:
and S7, if the correlation coefficient of the low-voltage user and the most relevant transformer is not larger than a second threshold value, or the correlation coefficient of the low-voltage user and the most relevant transformer is not larger than a preset difference value, or the most relevant transformer and the account transformer are inconsistent, calculating a voltage error caused by the fact that the low-voltage user belongs to a specific transformer, selecting the transformer with the minimum error as a calculation result, judging whether the transformer with the minimum error is consistent with the account transformer, and if so, judging that the account relationship of the account is correct.
Optionally, step S7 is followed by:
and S8, if the transformer with the minimum error in the step S7 is inconsistent with the transformer of the account, calculating the distance between the correct section of the account and the low-voltage user who does not determine the account relationship, selecting the transformer corresponding to the section with the closest distance, and if the transformer corresponding to the section with the closest distance is consistent with the transformer of the account, determining the account relationship of the account is correct, wherein the distance between the correct section of the account and the low-voltage user who does not determine the account relationship is defined as 1 minus the correlation coefficient between the low-voltage user and the transformer of the confirmed section of the account.
Optionally, step S8 is followed by:
and S9, if the transformer corresponding to the nearest parcel is inconsistent with the transformer of the account in the step S8, calculating the correlation coefficient between the low-voltage users and the low-voltage users, screening all the determined users of which the correlation coefficient with the undetermined users is greater than a first threshold value, voting one ticket for the subordinate transformer of each determined user, winning the transformer with the highest vote, and if the transformer with the highest vote is consistent with the transformer of the account, determining that the account relationship of the account is correct.
Optionally, step S9 is followed by:
and S10, if the transformer with the highest voting rate is inconsistent with the transformer of the standing book, selecting the transformer with the largest correlation coefficient for each undetermined user, and if the transformer with the largest correlation coefficient is consistent with the transformer of the standing book, determining that the standing relation of the standing book is correct.
Optionally, step S9 is followed by:
and S10, if the transformer with the highest voting rate is inconsistent with the transformer of the standing book, selecting the transformer with the largest correlation coefficient for each undetermined user, and if the transformer with the largest correlation coefficient is consistent with the transformer of the standing book, determining that the standing relation of the standing book is correct.
Optionally, in step S4, the correlation coefficient between the low-voltage user and the distribution transformer is a pearson correlation coefficient.
Optionally, in step S2, the data cleansing further includes a normalization process and a principal component analysis process;
normalization was done using Z-score normalization.
The second aspect of the present invention further provides a power distribution network subscriber relationship identification system, which includes the following modules:
the data acquisition module is used for acquiring distribution transformer voltage data and low-voltage user voltage data of the power distribution network;
the data cleaning module is used for cleaning the distribution transformer voltage data and the low-voltage user voltage data, and the data cleaning comprises data abnormal value standard processing and data missing value supplementing processing;
the data reconstruction module is used for carrying out data reconstruction on the distribution transformer voltage data and the low-voltage user voltage data after data cleaning to obtain a distribution transformer voltage time sequence and a low-voltage user voltage time sequence which accord with preset lengths;
the correlation coefficient calculation module is used for calculating the correlation coefficient between the low-voltage user and the distribution transformer according to the distribution transformer voltage time sequence and the low-voltage user voltage time sequence;
and the account relation identification module is used for judging whether the account is correct or not according to the correlation coefficient of the low-voltage user and the transformer of the account, wherein if the correlation coefficient of the low-voltage user and the transformer of the account is not less than a first threshold value, the account relation of the account is correct.
Optionally, the table-user relationship identifying module is further configured to:
if the correlation coefficient of the low-voltage user and the transformer of the account book is smaller than the first threshold value, whether the correlation coefficient of the low-voltage user and the most relevant transformer is larger than the second threshold value and larger than the correlation coefficient of the secondary relevant transformer by more than a preset difference value is judged, and meanwhile, the most relevant transformer and the transformer of the account book are consistent, if yes, the account relation of the account book is correct.
According to the technical scheme, the embodiment of the invention has the following advantages:
the power distribution network station relationship identification method provided by the embodiment of the invention is used for acquiring power distribution network distribution transformer voltage data and low-voltage user voltage data, calculating the correlation coefficient of a low-voltage user and a station account transformer after the data cleaning and data reconstruction are carried out on the distribution transformer voltage data and the low-voltage user voltage data, judging whether the station relationship of the station account is correct according to the correlation coefficient of the low-voltage user and the station account transformer, and solving the technical problems that the conventional manual identification and a method for identifying the station relationship by using special station area identification equipment are low in intelligence degree and cannot meet the intelligent development requirement of a power distribution network station area.
Drawings
Fig. 1 is a schematic flow chart of a method for identifying relationships between power distribution network users according to an embodiment of the present invention;
fig. 2 is another schematic flow chart of a method for identifying relationships between power distribution network users according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a distribution network subscriber relationship identification system according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
For easy understanding, please refer to fig. 1, an embodiment of a power distribution network subscriber relationship identification method provided in the present invention includes the following steps:
s1, acquiring distribution transformer voltage data and low-voltage user voltage data of the power distribution network;
s2, carrying out data cleaning on the distribution transformer voltage data and the low-voltage user voltage data, wherein the data cleaning comprises data abnormal value standard processing and data missing value supplementing processing;
s3, carrying out data reconstruction on the distribution transformer voltage data and the low-voltage user voltage data after data cleaning to obtain a distribution transformer voltage time sequence and a low-voltage user voltage time sequence which accord with preset lengths;
s4, calculating a correlation coefficient of the low-voltage user and the distribution transformer according to the distribution transformer voltage time sequence and the low-voltage user voltage time sequence;
and S5, judging whether the standing book is correct according to the correlation coefficient of the low-voltage user and the transformer of the standing book, wherein if the correlation coefficient of the low-voltage user and the transformer of the standing book is not less than a first threshold value, the standing book relationship is correct.
It should be noted that, in the embodiment of the present invention, first, power distribution network distribution transformer voltage data and low-voltage user voltage data are obtained, and then, data cleaning is performed on the power distribution network distribution transformer voltage data and the low-voltage user voltage data, where the data cleaning includes data abnormal value specification processing, where the specification abnormal data is between the upper limit and the lower limit, and on the other hand, data missing values are filled, and the data missing is filled according to the distribution transformer data corresponding to the ledger. The data cleaning can also include normalization processing and principal component analysis processing of the data. Considering the power inertia of low-voltage users, the variance of the mean value of the power data does not change greatly, and the Z-score normalization has better performance when the distance is used to measure the similarity in the classification and clustering algorithm or the principal component analysis technique is used to perform dimensionality reduction, so the Z-score normalization is used for normalization, that is:
wherein x is*The sample values after normalization, x, μ, and σ are the mean values and standard deviations of all sample data.
Aiming at the problem that the data dimension is large and the calculation amount is large, the multidimensional voltage data can be converted into a few principal components for analysis through a dimension reduction technology, and the dimension-reduced components can well express most information of the original multidimensional data. The specific procedure for performing the principal component analysis treatment is as follows:
(1) forming a matrix by the voltage data of the low-voltage side of the transformer area and the voltage data of the low-voltage user ammeter:
wherein the content of the first and second substances,
voltage data of 1 st to l-th transformers are shown,
voltage data of 1 st to m low-voltage users are shown.
(2) All voltage data were de-centered:
wherein X' is the number of all the decentralized voltagesFrom the composed new sample matrix, XidThe d-th voltage data is the ith voltage data.
(3) Calculating a covariance matrix C of the samples:
C＝X'X'T
(4) and carrying out eigenvalue decomposition on the covariance matrix C.
(5) Extracting the eigenvectors (w) corresponding to the largest n' eigenvalues1,...wn') All the eigenvectors are normalized to form an eigenvector matrix W.
(6) For each sample X in the sample set, converting into a new sample Z ═ WTX, obtaining a matrix after dimensionality reduction
Wherein Z isf＝[zf1,zf2,...,zfn]T,f∈[1,l]∪[1,m]，zf1～zfnIs an element for representing the voltage value after dimensionality reduction.
Each row vector in the matrix Z can well express most information of each corresponding row vector (voltage data of the transformer and the user electric meter) in the original matrix X, namely, the Z matrix can be used for classification and analysis subsequently, and therefore the user identification of the transformer area is achieved.
And performing data reconstruction on the data after data cleaning, namely data segmentation and segment segmentation. Each distribution transformer and each low-voltage user adopt integral point data, and each data index obtains a voltage time sequence with the length of 720 points according to 24 points every day for 1 month and 30 days.
Calculating the correlation coefficient of the low-voltage user and the distribution transformer according to the distribution transformer voltage time sequence and the low-voltage user voltage time sequence, and adopting a Pearson correlation coefficient, wherein the calculation formula is as follows:
wherein R isijIs the correlation coefficient, x, of the voltage of the ith user and the voltage data of the jth useriIs the voltage vector of the ith user, xjIs the voltage vector for the jth user,
is a unit row vector.
After the correlation coefficient of the low-voltage user and the distribution transformer is calculated, loose criteria are adopted to judge the correctness of the platform account relation of the platform account, and the loose criteria are as follows: and if the correlation coefficient of the low-voltage user and the transformer of the standing book is not less than the first threshold value, the standing relation of the standing book is correct. The first threshold value is 0.8.
The power distribution network station relationship identification method provided by the embodiment of the invention is used for acquiring power distribution network distribution transformer voltage data and low-voltage user voltage data, calculating the correlation coefficient of a low-voltage user and a station account transformer after the data cleaning and data reconstruction are carried out on the distribution transformer voltage data and the low-voltage user voltage data, judging whether the station relationship of the station account is correct according to the correlation coefficient of the low-voltage user and the station account transformer, and solving the technical problems that the conventional manual identification and a method for identifying the station relationship by using special station area identification equipment are low in intelligence degree and cannot meet the intelligent development requirement of a power distribution network station area.
Referring to fig. 2, in an embodiment, after step S5, the method further includes:
and S6, if the correlation coefficient of the low-voltage user and the transformer of the account book is smaller than the first threshold value, judging whether the correlation coefficient of the low-voltage user and the most relevant transformer is larger than the second threshold value and is larger than the correlation coefficient of the secondary relevant transformer by more than a preset difference value, and if so, judging that the account relation of the account book is correct.
After step S5, for the case that the correlation coefficient between the low-voltage user and the transformer of the standing book is not less than the first threshold, it can be determined that the standing book relationship is correct, but for the case that the correlation coefficient between the low-voltage user and the transformer of the standing book is less than the first threshold, it can be further determined by using the correlation coefficient criterion, that is, when the correlation coefficient between the low-voltage user and the most relevant transformer is greater than the second threshold (0.7) and greater than the correlation coefficient of the next relevant transformer by a preset difference (0.08) or more, and the most relevant transformer and the transformer of the standing book are consistent, it is determined that the standing book relationship is correct.
Referring to fig. 2, in an embodiment, after step S6, the method may further include:
and S7, if the correlation coefficient of the low-voltage user and the most relevant transformer is not larger than a second threshold value, or the correlation coefficient of the low-voltage user and the most relevant transformer is not larger than a preset difference value, or the most relevant transformer and the account transformer are inconsistent, calculating a voltage error caused by the fact that the low-voltage user belongs to a specific transformer, selecting the transformer with the minimum error as a calculation result, judging whether the transformer with the minimum error is consistent with the account transformer, and if so, judging that the account relationship of the account is correct.
After step S6, it may be determined that the account relationship of the account is correct for the case where the transformer with the smallest error is consistent with the account transformer, but further determination may be performed by using an error criterion for the case where the transformer with the smallest error is inconsistent with the account transformer, that is, a voltage error caused by the low-voltage user attributing to a specific transformer is calculated, the transformer with the smallest error is selected as a calculation result, and it is determined whether the transformer with the smallest error is consistent with the account transformer, if so, the account relationship of the account is correct.
Calculating the voltage error caused by the low-voltage user after the low-voltage user belongs to the specific transformer according to the distribution transformer voltage time sequence and the low-voltage user voltage time sequence, wherein the calculation formula is as follows:
wherein e isijFor the ith voltage time sequence and the jth powerError of the pressure time series, xiFor the ith low-voltage user voltage time series, yjFor the jth distribution voltage time series, diag (x)i) For, the element on the diagonal is xiElements not on the diagonal are all diagonal arrays of 0.
Referring to fig. 2, in an embodiment, after step S7, the method may further include:
and S8, if the transformer with the minimum error in the step S7 is inconsistent with the transformer of the account, calculating the distance between the correct section of the account and the low-voltage user who does not determine the account relationship, selecting the transformer corresponding to the section with the closest distance, and if the transformer corresponding to the section with the closest distance is consistent with the transformer of the account, determining the account relationship of the account is correct, wherein the distance between the correct section of the account and the low-voltage user who does not determine the account relationship is defined as 1 minus the correlation coefficient between the low-voltage user and the transformer of the confirmed section of the account.
After step S7, it may be determined that the account relationship of the account is correct for the case where the transformer corresponding to the nearest zone is consistent with the transformer of the account, but for the case where the transformer corresponding to the nearest zone is inconsistent with the transformer of the account, a distance criterion may be used to further determine, that is, calculate the distance between the zone where the account is confirmed to be correct and the low-voltage user whose account relationship is not determined (which refers to the user whose account relationship is still not determined to be correct after steps S5, S6, and S7), select the transformer corresponding to the nearest zone, and if the transformer corresponding to the nearest zone is consistent with the transformer of the account, the account relationship of the account is correct.
Referring to fig. 2, in an embodiment, after step S8, the method may further include:
and S9, if the transformer corresponding to the nearest parcel is inconsistent with the transformer of the account in the step S8, calculating the correlation coefficient between the low-voltage users and the low-voltage users, screening all the determined users of which the correlation coefficient with the undetermined users is greater than a first threshold value, voting one ticket for the subordinate transformer of each determined user, winning the transformer with the highest vote, and if the transformer with the highest vote is consistent with the transformer of the account, determining that the account relationship of the account is correct.
After step S8, it may be determined that the account relationship of the account is correct for the case where the transformer corresponding to the nearest parcel is consistent with the transformer of the account, but for the case where the transformer corresponding to the nearest parcel is inconsistent with the transformer of the account, a hand-in-hand criterion may be used for further determination, that is, all determined users whose correlation coefficients with the undetermined users are greater than the first threshold are obtained by screening, each determined user throws a vote for its own subordinate transformer, and the transformer with the highest vote wins out, and if the transformer with the highest vote is consistent with the transformer of the account, the account relationship of the account is correct.
Referring to fig. 2, in an embodiment, after step S9, the method may further include:
and S10, if the transformer with the highest voting rate is inconsistent with the transformer of the standing book, selecting the transformer with the largest correlation coefficient for each undetermined user, and if the transformer with the largest correlation coefficient is consistent with the transformer of the standing book, determining that the standing relation of the standing book is correct.
After step S9, it may be determined that the account relationship of the account is correct for the case where the transformer with the highest vote is consistent with the account transformer, but further determination may be performed by using a one-handed criterion for the case where the transformer with the highest vote is inconsistent with the account transformer, that is, for each undetermined user, the transformer with the largest correlation coefficient is selected, and if the transformer with the largest correlation coefficient is consistent with the account transformer, the account relationship of the account is correct.
The method for identifying the power distribution network station relationship provided by the invention provides 6 criteria for judgment, and uses the 6 criteria according to a sequential judgment mode, wherein the order of the criteria is as follows: 1. the method comprises the following steps of loose criterion, 2 correlation coefficient criterion, 3 error criterion, 4 distance criterion, 5 hand-in-hand criterion and 6 single-hand criterion, wherein the number of the criteria can be selected in sequence by a person skilled in the art according to actual requirements, and the judgment is stopped as long as the current criterion is met, and the result is returned: the standing book is correct; if the current criterion is not satisfied, continuing to judge; if the last criterion is reached, the machine account still cannot be judged to be correct, and at this moment, the machine account is judged to be wrong, namely, a result is returned: standing account is wrong. The platform-user relationship identification based on the multidimensional criterion can reduce the requirement on the size of a sample on the basis of ensuring the accuracy of the algorithm, and obtain a prediction and analysis result which is relatively in line with the actual engineering.
For ease of understanding, referring to fig. 3, an embodiment of a power distribution network subscriber relationship identification system is provided in the present invention, which includes the following modules:
the data acquisition module 301 is used for acquiring distribution network distribution transformer voltage data and low-voltage user voltage data;
and the data cleaning module 302 is used for performing data cleaning on the distribution transformer voltage data and the low-voltage user voltage data, wherein the data cleaning comprises data abnormal value standard processing and data missing value supplementing processing. The data washing further comprises a normalization process and a principal component analysis process, wherein the normalization process adopts Z-score standardization.
The data reconstruction module 303 is configured to perform data reconstruction on the distribution transformer voltage data and the low-voltage user voltage data after data cleaning, so as to obtain a distribution transformer voltage time sequence and a low-voltage user voltage time sequence which meet preset lengths;
and the correlation coefficient calculation module 304 is configured to calculate a correlation coefficient between the low-voltage user and the distribution transformer according to the distribution transformer voltage time series and the low-voltage user voltage time series, where the correlation coefficient is a pearson correlation coefficient.
And the account relation identification module 305 is configured to determine whether the account is correct according to the correlation coefficient between the low-voltage user and the transformer of the account, where the account relation of the account is correct if the correlation coefficient between the low-voltage user and the transformer of the account is not less than the first threshold.
The table-user relationship identification module 305 is further configured to:
if the correlation coefficient of the low-voltage user and the transformer of the account book is smaller than the first threshold value, whether the correlation coefficient of the low-voltage user and the most relevant transformer is larger than the second threshold value and larger than the correlation coefficient of the secondary relevant transformer by more than a preset difference value is judged, and meanwhile, the most relevant transformer and the transformer of the account book are consistent, if yes, the account relation of the account book is correct.
The table-user relationship identification module 305 is further configured to:
and if the correlation coefficient of the low-voltage user and the most relevant transformer is not larger than a second threshold value, or the correlation coefficient of the low-voltage user and the most relevant transformer is not larger than a preset difference value, or the most relevant transformer and the transformer of the account book are inconsistent, calculating a voltage error caused by the fact that the low-voltage user belongs to a specific transformer, selecting the transformer with the minimum error as a calculation result, judging whether the transformer with the minimum error is consistent with the transformer of the account book, and if so, judging the account relation of the account book is correct.
The table-user relationship identification module 305 is further configured to:
if the transformer with the minimum error is inconsistent with the transformer of the account, calculating the distance between the section which confirms the correct account and the low-voltage user which does not confirm the account relationship, selecting the transformer corresponding to the section which is closest to the transformer, and if the transformer corresponding to the section which is closest to the transformer is consistent with the transformer of the account, confirming the account relationship of the account, wherein the distance between the section which confirms the correct account and the low-voltage user which does not confirm the account relationship is defined as 1 minus the correlation coefficient of the transformer of the section which confirms the low-voltage user and the account.
The table-user relationship identification module 305 is further configured to:
if the transformer corresponding to the nearest parcel is inconsistent with the transformer of the account, calculating the correlation coefficient between the low-voltage users and the low-voltage users, screening to obtain all the confirmed users of which the correlation coefficient is larger than a first threshold value with the undetermined users, and throwing one vote for the own subordinate transformer by each confirmed user, wherein the transformer with the highest vote wins out, and if the transformer with the highest vote is consistent with the transformer of the account, the account relation of the account is correct.
The table-user relationship identification module 305 is further configured to:
and if the transformer with the highest voting is inconsistent with the transformer of the standing book, selecting the transformer with the largest correlation coefficient for each undetermined user, and if the transformer with the largest correlation coefficient is consistent with the transformer of the standing book, determining that the standing relation of the standing book is correct.
The power distribution network station relationship identification system provided by the embodiment of the invention obtains power distribution network distribution transformer voltage data and low-voltage user voltage data, calculates the correlation coefficient of a low-voltage user and a station account transformer after performing data cleaning and data reconstruction on the distribution transformer voltage data and the low-voltage user voltage data, judges whether the station relationship of the station account is correct according to the correlation coefficient of the low-voltage user and the station account transformer, does not need manual identification, does not need to rely on a special identification device to identify by using a carrier communication method or a pulse current method, has high intelligent degree, and solves the technical problems that the traditional manual identification method and the method for identifying the station relationship by using the special station area identification device have low intelligent degree, and cannot meet the intelligent development requirement of a power distribution network station area.
The power distribution network subscriber relationship identification system provided in the embodiment of the present invention is configured to execute the power distribution network subscriber relationship identification method in the foregoing embodiment, and the working principle of the power distribution network subscriber relationship identification system is the same as that of the power distribution network subscriber relationship identification method in the foregoing embodiment, so that the same technical effect can be obtained, and further description is omitted here.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A power distribution network platform relationship identification method is characterized by comprising the following steps:
s1, acquiring distribution transformer voltage data and low-voltage user voltage data of the power distribution network;
s2, carrying out data cleaning on the distribution transformer voltage data and the low-voltage user voltage data, wherein the data cleaning comprises data abnormal value standard processing and data missing value supplementing processing;
s3, carrying out data reconstruction on the distribution transformer voltage data and the low-voltage user voltage data after data cleaning to obtain a distribution transformer voltage time sequence and a low-voltage user voltage time sequence which accord with preset lengths;
s4, calculating a correlation coefficient of the low-voltage user and the distribution transformer according to the distribution transformer voltage time sequence and the low-voltage user voltage time sequence;
and S5, judging whether the standing book is correct according to the correlation coefficient of the low-voltage user and the transformer of the standing book, wherein if the correlation coefficient of the low-voltage user and the transformer of the standing book is not less than a first threshold value, the standing book relationship is correct.
2. The method for identifying relationships between power distribution network users according to claim 1, wherein step S5 is followed by further comprising:
and S6, if the correlation coefficient of the low-voltage user and the transformer of the account book is smaller than the first threshold value, judging whether the correlation coefficient of the low-voltage user and the most relevant transformer is larger than the second threshold value and is larger than the correlation coefficient of the secondary relevant transformer by more than a preset difference value, and if so, judging that the account relation of the account book is correct.
3. The method for identifying relationships between power distribution network bays as claimed in claim 2, wherein step S6 is followed by further comprising:
and S7, if the correlation coefficient of the low-voltage user and the most relevant transformer is not larger than a second threshold value, or the correlation coefficient of the low-voltage user and the most relevant transformer is not larger than a preset difference value, or the most relevant transformer and the account transformer are inconsistent, calculating a voltage error caused by the fact that the low-voltage user belongs to a specific transformer, selecting the transformer with the minimum error as a calculation result, judging whether the transformer with the minimum error is consistent with the account transformer, and if so, judging that the account relationship of the account is correct.
4. The method for identifying relationships between power distribution network users according to claim 3, wherein step S7 is followed by further comprising:
and S8, if the transformer with the minimum error in the step S7 is inconsistent with the transformer of the account, calculating the distance between the correct section of the account and the low-voltage user who does not determine the account relationship, selecting the transformer corresponding to the section with the closest distance, and if the transformer corresponding to the section with the closest distance is consistent with the transformer of the account, determining the account relationship of the account is correct, wherein the distance between the correct section of the account and the low-voltage user who does not determine the account relationship is defined as 1 minus the correlation coefficient between the low-voltage user and the transformer of the confirmed section of the account.
5. The method for identifying relationships between power distribution network users according to claim 4, wherein step S8 is followed by further comprising:
and S9, if the transformer corresponding to the nearest parcel is inconsistent with the transformer of the account in the step S8, calculating the correlation coefficient between the low-voltage users and the low-voltage users, screening all the determined users of which the correlation coefficient with the undetermined users is greater than a first threshold value, voting one ticket for the subordinate transformer of each determined user, winning the transformer with the highest vote, and if the transformer with the highest vote is consistent with the transformer of the account, determining that the account relationship of the account is correct.
6. The method for identifying relationships between power distribution network bays as claimed in claim 5, wherein step S9 is followed by further comprising:
and S10, if the transformer with the highest voting rate is inconsistent with the transformer of the standing book, selecting the transformer with the largest correlation coefficient for each undetermined user, and if the transformer with the largest correlation coefficient is consistent with the transformer of the standing book, determining that the standing relation of the standing book is correct.
7. The method of claim 1, wherein in step S4, the correlation coefficient between the low voltage users and the distribution transformer is a pearson correlation coefficient.
8. The method for identifying relationships between power distribution network users according to claim 1, wherein in step S2, the data cleansing further includes a normalization process and a principal component analysis process;
normalization was done using Z-score normalization.
9. A power distribution network platform family relation identification system is characterized by comprising the following modules:
the data acquisition module is used for acquiring distribution transformer voltage data and low-voltage user voltage data of the power distribution network;
the data cleaning module is used for cleaning the distribution transformer voltage data and the low-voltage user voltage data, and the data cleaning comprises data abnormal value standard processing and data missing value supplementing processing;
the data reconstruction module is used for carrying out data reconstruction on the distribution transformer voltage data and the low-voltage user voltage data after data cleaning to obtain a distribution transformer voltage time sequence and a low-voltage user voltage time sequence which accord with preset lengths;
the correlation coefficient calculation module is used for calculating the correlation coefficient between the low-voltage user and the distribution transformer according to the distribution transformer voltage time sequence and the low-voltage user voltage time sequence;
and the account relation identification module is used for judging whether the account is correct or not according to the correlation coefficient of the low-voltage user and the transformer of the account, wherein if the correlation coefficient of the low-voltage user and the transformer of the account is not less than a first threshold value, the account relation of the account is correct.
10. The electrical distribution network subscriber relationship identification system of claim 1, wherein the subscriber relationship identification module is further configured to:
if the correlation coefficient of the low-voltage user and the transformer of the account book is smaller than the first threshold value, whether the correlation coefficient of the low-voltage user and the most relevant transformer is larger than the second threshold value and larger than the correlation coefficient of the secondary relevant transformer by more than a preset difference value is judged, and meanwhile, the most relevant transformer and the transformer of the account book are consistent, if yes, the account relation of the account book is correct.
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