CN115712811A - Impedance calculation model based on low-voltage topological power distribution network - Google Patents
Impedance calculation model based on low-voltage topological power distribution network Download PDFInfo
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Abstract
The invention relates to an impedance calculation model based on a low-voltage topological power distribution network. And (4) judging success rate at intervals of extraction time, calculating the similarity between single-phase users and three-phase voltage curve data of the user meter and the general meter, and taking the station area with the highest similarity and the phase as the actual attribution relationship of the user topology. And based on the information of the low-voltage distribution electric cabinet, the voltage and current data of the user electric appliance are combined to calculate the sectional impedance. The method adopts the sectional calculation and the quick response to obtain the intuitive and effective impedance parameters. The accuracy and the rationality of the impedance data obtained through verification and calculation are greatly improved.
Description
Technical Field
The invention relates to an impedance calculation model based on a low-voltage topological power distribution network, and belongs to the technical field of power distribution networks.
Background
Line impedance is an important parameter for line state sensing and monitoring of the running state of a power distribution station area. Therefore, the method is an important index in the construction of the intelligent power distribution network. The impedance parameter can not only give specific correlation performance in the aspects of line aging, breakage, cracking and the like, but also give positive correlation characteristics in the aspect of theoretical line loss. The method can shorten the time for fault location and reason diagnosis when the power distribution network has faults. This provides accurate parameter basis for the line health and the operation analysis of the whole power system.
At present, methods for calculating impedance include an empirical estimation method, an actual measurement estimation method, an equivalent model estimation method, and the like. However, in a distribution network under a topological structure, the impedance values measured and calculated by the methods are either insufficient in accuracy or high in cost, and accurate and reasonable impedance data are difficult to calculate under a complex distribution network. Meanwhile, the power distribution network with a topological structure often has the problem that the impedance data has great errors due to the fact that the files are not aligned with the files caused by the fact that the files are lost or the topological relation is not updated in time.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the existing problems and defects, the invention aims to provide an impedance calculation model based on a low-voltage topological power distribution network, which solves the topological structure under the complex environment through 'family-phase-change' matching, obtains the impedance data of branch lines and trunk lines of the whole circuit through a segmentation algorithm, and finally counts the abnormal impedance data of the whole circuit system; the calculation model not only saves cost, but also can quickly respond to obtain intuitive and effective impedance parameters; meanwhile, the accuracy and the reasonability of the impedance data obtained through verification and calculation are greatly improved, and the method plays an important role in the construction of the smart grid.
The technical scheme is as follows: in order to realize the purpose, the invention adopts the following technical scheme:
an impedance calculation model based on a low-voltage topological power distribution network comprises the following steps:
step 1: data acquisition: collecting the operation data of the household meter and the general meter according to the time periods every day, and respectively obtaining the operation data of the household meter and the general meter as the U sub1 、U sub2 、U sub3 ... U subN And general table U master1 、U master2 、U master3 ... U masterN；
Step 2: selecting an analysis period: reading the information of the distribution transformer and the low-voltage distribution cabinet and the voltage and current data of the user electrical appliance in each period;
and 3, step 3: judging the success rate: the success rate judgment is carried out on the data extraction time periods of the voltage and the current in the step 2 for a plurality of times at intervals, and the step 4 is carried out if the acquisition success rate of the extraction time periods is higher than a data completion threshold; if the acquisition success rate in the extraction time period is lower than the data completeness threshold value, reselecting the analysis time period;
and 4, step 4: and (3) comparing the similarity: the phase in the file has three phases A, B and C, and six combination conditions exist: the method comprises the following steps of A, ABC, ACB, BAC, BCA, CAB and CBA, wherein N points are taken in a time-sharing period in one day, similarity calculation between single-phase users and three-phase voltage curve data passing through a user table and a general table is carried out, and a station area with the highest similarity and a phase are taken as the actual attribution relation of the user topology;
and 5: and (3) carrying out impedance calculation by sections: based on the low-voltage distribution cabinet information in the step 2, carrying out sectional impedance calculation by combining voltage and current data of a user electrical appliance;
and 6: calculating to obtain the loop impedance of the user by a constrained binary linear regression method;
and 7: adding the trunk line impedance and the branch line impedance obtained in the step 6 to be used as the loop impedance of the user, and taking the impedance abnormity threshold value as an impedance abnormity judgment standard;
and 8: and (4) collecting the judgment data obtained in the step (7), and obtaining impedance data and abnormal impedance data of the whole distribution room through a statistical program.
Furthermore, in the step 3, the data of the voltage and the current in the step 2 are taken 96 times at intervals of 15 minutes to perform success rate judgment.
Further, the data completeness threshold in step 3 is 90%.
Further, the similarity algorithm in step 4 is a pearson algorithm.
Further, the step 5 and step 6 of calculating the segmented impedance establishes an equation set and a regression equation as follows:
wherein the content of the first and second substances,
calculating the current loop impedance for the user;
td is a voltage value and a current value at a certain moment in a corresponding time period;
and then calculating the loop impedance of the user in a regression mode, wherein the formula is as follows:
wherein, UT: a phase-change phase voltage, V, in phase with user U2;
u2: u2 user voltage, V;
n: representing the number of voltage points in the corresponding time period;
ti: representing a voltage value at a time within a corresponding time period;
Further, the impedance abnormality threshold value in the step 7 is 0.2 ± 0.05.
Has the beneficial effects that: compared with the prior art, the invention has the following advantages: therefore, the cost is reduced, accurate and reasonable impedance data are obtained, and the method plays an important role in stable operation of the whole power system and abnormal analysis of the whole line; meanwhile, a perfect intelligent calculation mode is provided for the low-voltage distribution network under the complex topological structure. According to the method, under the technical dependence of big data (pyspark + python), voltage and current data are obtained by monitoring users and distribution transformers in a time-by-time segmented mode every day through single-phase and three-phase user-to-user-phase-transformer re-matching (by adopting a Pearson similarity method), then an equation set is obtained by utilizing a kirchhoff voltage law equation to calculate circuit trunk line and branch line data [ xx ] in a segmented mode, and finally abnormal impedance and abnormal reasons are obtained rapidly through the judgment standard of impedance abnormity and the impedance statistics of the whole low-voltage power distribution network.
Drawings
FIG. 1 is a flow diagram of the overall calculation of an embodiment of the present invention;
fig. 2 is a schematic diagram of a user-phase-variant matching matrix process according to an embodiment of the present invention.
Detailed Description
The present invention is further illustrated by the following figures and specific examples, which are to be understood as illustrative only and not as limiting the scope of the invention, which is to be given the full breadth of the appended claims and any and all equivalent modifications thereof which may occur to those skilled in the art upon reading the present specification.
As shown in fig. 1, an impedance calculation model based on a low-voltage topology power distribution network is used for detailed description of the technical solution of the present invention through the following low-voltage power topology identification, impedance calculation and anomaly judgment of a certain cell in a Nanjing Jiangning district.
Step 1: acquiring current and voltage of a cell transformer outlet terminal in a 15-minute period, and attaching a data time scale to obtain a transformer operation data set UT1, UT2, UT3,. UT96 with time scale information; acquiring current and voltage of a cell household meter incoming line end in a 15-minute period, and attaching a data time scale to obtain a household meter operation data set U1, U2 and U3 with time scale information;
and 2, step: for the data sets U1 to U96 and UT1 to UT96, respectively, pearson's calculation method comparison is performed through corresponding time scale values, and a new time series characteristic data set is extracted and obtained as shown in fig. 2;
and step 3: taking one week time as a time window, respectively calculating the impedance from the general table to the user table every day (flow 1 impedance calculation core algorithm), and calculating the impedance MEAN value of the corresponding branch line (ZX _ MEAN) and main line (GX _ MEAN) through a kirchhoff voltage equation set and a parameterized regression equation set, wherein the whole flow is shown as a figure 1;
and 4, step 4: the abnormal impedance and the abnormal cause are counted by a big data statistical procedure and a judgment criterion (threshold 0.2) of the impedance abnormality, as shown in fig. 2.
And (3) calculating an algorithm: an impedance calculation section:
The main current consists of two parts, namely (a) the daily average voltage is higher than the current calculation user and (b) the daily average voltage does not exceed the current calculation user are superposed:
And selecting a calculation formula.
For one day
Current data for points (96, 48 or 24 points).
A. Current of household meter in one day
Is recorded not less than
A binary regression equation is selected.
B. Current of household meter in one day
Is recorded not less than
And selecting a unitary regression equation. I.e. Iun is 0.
Solving an equation set:
from the above formula, the following system of equations can be obtained:
or
Solving an equation system by adopting a curve fitting method (scipy. Optimum. Curve _ fit ()); constraint conditions (0, 5) are added for ZZX and ZGX, and loop impedances of A, B and C phases are respectively calculated for three-phase users.
Claims (6)
1. An impedance calculation model based on a low-voltage topological distribution network is characterized in that: the method comprises the following steps:
step 1: data acquisition: collecting the operation data of the household meter and the general meter according to the time periods every day, and respectively obtaining the operation data of the household meter and the general meter as the U sub1 、U sub2 、U sub3 ... U subN And general table U master1 、U master2 、U master3 ... U masterN；
And 2, step: selecting an analysis period: reading the information of the distribution transformer and the low-voltage distribution cabinet and the voltage and current data of the user electrical appliance in each period;
and step 3: judging the success rate: the success rate judgment is carried out on the data extraction time interval of the voltage and the current in the step 2 for a plurality of times at intervals, and if the acquisition success rate of the extraction time interval is higher than a data completion threshold, the step 4 is carried out; if the acquisition success rate in the extraction time period is lower than the data completeness threshold value, reselecting the analysis time period;
and 4, step 4: and (3) comparing the similarity: the phase in the file has three phases A, B and C, and six combination conditions exist: the method comprises the following steps of A, ABC, ACB, BAC, BCA, CAB and CBA, wherein N points are taken in a time-sharing period in one day, similarity calculation between single-phase users and three-phase voltage curve data passing through a user table and a general table is carried out, and a station area with the highest similarity and a phase are taken as the actual attribution relation of the user topology;
and 5: and (3) carrying out impedance calculation in a segmented manner: based on the information of the low-voltage power distribution cabinet in the step 2, combining voltage and current data of a user electrical appliance, writing a loop impedance equation of the user under multiple sections in a row mode to form an equation set;
and 6: calculating to obtain the loop impedance of the user by a constrained binary linear regression method;
and 7: adding the trunk line impedance and the branch line impedance obtained in the step 6 to be used as the loop impedance of the user, and taking an impedance abnormity threshold as an impedance abnormity judgment standard;
and 8: and (4) collecting the judgment data obtained in the step (7), and obtaining impedance data and abnormal impedance data of the whole distribution room through a statistical program.
2. The model for calculating impedance under the distribution network based on the low-voltage topology of claim 1, wherein: and in the step 3, the data of the voltage and the current in the step 2 are taken 96 times at intervals of 15 minutes to carry out success rate judgment.
3. The impedance calculation model based on the low-voltage topological distribution network according to claim 1, is characterized in that: the data completeness threshold in step 3 is 90%.
4. The impedance calculation model based on the low-voltage topological distribution network according to claim 1, is characterized in that: the similarity algorithm in the step 4 is a pearson algorithm.
5. The impedance calculation model based on the low-voltage topological distribution network according to claim 1, is characterized in that: in the step 5, the sectional impedance is calculated, and the following equation set is established:
wherein, the first and the second end of the pipe are connected with each other,
calculating the current loop impedance for the user;
td is a voltage value and a current value at a certain moment in a corresponding time period;
and then calculating the loop impedance of the user in a regression mode, wherein the formula is as follows:
wherein, UT: a phase-change phase voltage, V, in phase with the user U2;
u2: u2 user voltage, V;
n: representing the number of times the voltage is tapped within the corresponding time period;
ti: representing a voltage value at a time within a corresponding time period;
6. The impedance calculation model based on the low-voltage topological distribution network according to claim 1, is characterized in that: the impedance abnormality threshold value in the step 7 is 0.2 +/-0.05.
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| CN111062176A (en) * | 2019-12-09 | 2020-04-24 | 国网山西省电力公司长治供电公司 | Low-voltage user loop impedance binary linear model construction and solving method |
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| CN111062176A (en) * | 2019-12-09 | 2020-04-24 | 国网山西省电力公司长治供电公司 | Low-voltage user loop impedance binary linear model construction and solving method |
| CN111062176B (en) * | 2019-12-09 | 2023-09-22 | 国网山西省电力公司长治供电公司 | Low-voltage user loop impedance binary linear model construction and solving method |
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