Method for differentiating power distribution areas and phases by using voltage characteristics

Abstract

A method for differentiating power distribution areas and phases by using voltage characteristics, where the method includes performing similarity comparison on a voltage curve of a node to be determined and a voltage curve recorded by a concentrator to determine whether the node belongs to a current power distribution area. Using the method for identifying power distribution areas and phases according to voltage characteristics, the problem of inaccurate electric power measurement due to power distribution area archive errors, communication crosstalk, and others is effectively resolved, a collection success rate and meter reading stability of a power distribution area are improved, a line loss rate of a power distribution area is moderately reduced, correctness of ammeter archive information of an SG186 system is ensured, occurrences of power distribution area crossing of carrier communications and ammeter archive errors are eradicated, and delicacy management of a marketing system is realized.

Claims

1. A method for differentiating power distribution areas and phases by using voltage characteristics, comprising: performing similarity comparison on a voltage curve of a node to be determined and a voltage curve recorded by a concentrator to determine whether the node belongs to a current power distribution area, including the following specific steps: step a: a concentrator continuously collects a voltage curve of a node to be determined and stores the voltage curve; step b: perform similarity comparison on a voltage curve recorded by the concentrator and the voltage curve obtained in step a; step c: if a similarity absolute value is greater than a set value, determine that the node belongs to a current power distribution area, and if the similarity absolute value is less than or equal to the set value, kick out the node so that the node becomes a free node; and step d: repeat steps a to c, until all nodes to be determined are traversed.

2. The method for differentiating power distribution areas and phases by using voltage characteristics according to claim 1, wherein the method further comprises: step e: search for a free node, and perform similarity comparison with the voltage curve recorded by the concentrator; step f: if a similarity absolute value is greater than the set value, determine that the node belongs to the current power distribution area, and if the similarity absolute value is less than or equal to the set value, kick the node into a free node library; and step g: repeat steps e to f, until all free nodes are traversed.

3. The method for differentiating power distribution areas and phases by using voltage characteristics according to claim 2, wherein a method for the similarity comparison uses a Pearson correlation coefficient algorithm.

4. The method for differentiating power distribution areas and phases by using voltage characteristics according to claim 3, wherein the set value is 0.6 to 0.8.

5. The method for differentiating power distribution areas and phases by using voltage characteristics according to claim 4, wherein the set value is 0.8.

6. The method for differentiating power distribution areas and phases by using voltage characteristics according to claim 1, wherein a method for the similarity comparison uses a Pearson correlation coefficient algorithm.

7. The method for differentiating power distribution areas and phases by using voltage characteristics according to claim 6, wherein the set value is 0.6 to 0.8.

8. The method for differentiating power distribution areas and phases by using voltage characteristics according to claim 7, wherein the set value is 0.8.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

(1) FIG. 1 is a block diagram of a wireless centralized meter reading system,

(2) FIG. 2(a) is a voltage characteristic curve of a phase A of a power distribution area that is collected by a first concentrator;

(3) FIG. 2(b) is a voltage characteristic curve of the phase A of the power distribution area that is collected by a second concentrator;

(4) FIG. 3(a) is a voltage characteristic curve of a phase A of Fangzhong Mansion that is collected by a concentrator;

(5) FIG. 3(b) is a voltage characteristic curve of a phase B of Fangzhong Mansion that is collected by the concentrator;

(6) FIG. 3(c) is a voltage characteristic curve of a phase C of Fangzhong Mansion that is collected by the concentrator;

(7) FIG. 4(a) is a voltage characteristic curve of a phase A of Xincheng Science and Technology Park that is collected by the concentrator;

(8) FIG. 4(b) is a voltage characteristic curve of a phase B of Xincheng Science and Technology Park that is collected by the concentrator;

(9) FIG. 4(c) is a voltage characteristic curve of a phase C of Xincheng Science and Technology Park that is collected by the concentrator; and

(10) FIG. 5 is a flowchart of a method for differentiating power distribution areas and phases by using voltage characteristic curves.

DETAILED DESCRIPTION

(11) The present invention is further described below with reference to embodiments, but the protection scope of the present invention is not limited thereto.

(12) The present invention is described in detail below with reference to the accompanying drawings and specific examples.

(13) By using the specific examples, the present invention explains that different power distribution areas and phases have different voltage characteristics and a same power distribution area and phase has a similar voltage characteristic. Two actual power distribution areas, that is, (1) Fangzhong Mansion and (2) Xincheng Science and Technology Park, are selected. Voltage data of the two power distribution areas is continuously collected and stored by using a concentrator. Corresponding voltage characteristic curves drawn according to the collected data are respectively shown in FIG. 2, FIG. 3, and FIG. 4. FIG. 2 gives voltage characteristic curves of a same power distribution area and a same phase that are respectively collected by using two concentrators. FIG. 3 and FIG. 4 respectively give voltage characteristic curves of different power distribution areas and different phases that are collected by using a concentrator. It can be known from FIG. 2 to FIG. 4 that, different power distribution areas and phases have respective unique voltage characteristics, while a same power distribution area and phase has a similar voltage characteristic.

(14) According to the foregoing conclusion, voltage curves of ammeters that are recorded by a concentrator may be compared with a voltage curve that is collected by the concentrator. If an absolute value of a similarity between a voltage curve of an ammeter and the voltage curve collected by the concentrator exceeds a set similarity threshold, it is determined that the ammeter does not belong to a current power distribution area and the ammeter is kicked out so that the ammeter becomes a free node, and the ammeter that is kicked out is marked, in an archive of the power distribution area, as an ammeter that does not belong to the current power distribution area. A node in a free state is searched for and compared with the archive in the concentrator, and a free node that has a similarity falling within a set range and has not been added to a free node library or a free node that has been kicked out for a specified time is added to the free node library. The foregoing process is repeated until there is no free node when power distribution area allocation is ended. Similarity verification of a voltage characteristic curve is performed by using a correlation coefficient algorithm. A similarity algorithm is selected herein for a brief description, but should not be considered as a limitation to the technical solutions of the present invention. Other similarity algorithms employed by a person of ordinary skill in the art shall fall within the protection scope of the present application.

(15) A case in which a Pearson correlation coefficient algorithm is employed for similarity verification is used as an example, where the algorithm is defined as follows:

(16) A Pearson correlation coefficient describes the closeness of a relation between two interval scale variables, and is used to measure a correlation (linear correlation) between two variables X and Y, and falls between 1 and 1, and is generally denoted by r, and a calculation formula is

(17) $r_{\mathrm{xy}}=\frac{n\stackrel{}{.Math.}\mathrm{XY}-\stackrel{}{.Math.}X.Math.Y}{\sqrt{\left[n.Math.X^2-{\left(.Math.X\right)}^2\right]\left[n.Math.Y^2-{\left(.Math.Y\right)}^2\right]}},$
where

(18) n is a sample size, and X and Y are respectively observed values of two variables.

(19) If r>0, it indicates that the two variables are positively correlated, that is, as a value of one variable increases, a value of the other variable increases; if r<0, it indicates that the two variables are negatively correlated, that is, as the value of one variable increases, the value of the other variable decreases instead. A larger absolute value of r indicates a stronger correlation.

(20) Effects of the algorithm in identification of a voltage characteristic similarity are verified through experiments and tests.

(21) Voltage curve data of one concentrator and 30 ammeters is collected, and whether an ammeter belongs to a current power distribution area is verified according to a Pearson correlation coefficient. Similarities (positive correlation) between the voltage data of the concentrator and the voltage data of the ammeters are calculated, and the obtained data correlation coefficients are shown in FIG. 1 and FIG. 2.

(22) TABLE-US-00001 TABLE 1 Results of similarities calculated for the former 15 ammeters by using the two types of voltage data according to the algorithm Ammeter Algorithm 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1 0.92 0.95 0.91 0.89 0.94 0.90 0.88 0.91 0.82 0.93 0.90 0.85 0.88 0.86 0.91

(23) TABLE-US-00002 TABLE 2 Results of similarities calculated for the latter 15 ammeters by using the two types of voltage data according to the algorithm Ammeter Algorithm 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 1 0.2 0.15 0.26 0.3 0.12 0.14 0.19 0.35 0.33 0.25 0.36 0.38 0.21 0.35 0.27

(24) Power distribution areas to which the foregoing 30 ammeters actually belong are shown in table 3.

(25) TABLE-US-00003 TABLE 3 Power distribution areas to which the 30 ammeters actually belong Ammeter 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Power distribution area 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Ammeter 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Power distribution area 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2

(26) It can be seen by comparison with the power distribution areas to which the 30 ammeters actually belong that, the ammeters are correctly allocated to different power distribution areas by using the Pearson correlation coefficient algorithm. It can further be seen that, when a set value is selected as any value within the range 0.6 to 0.8, allocation of the 30 ammeters to power distribution areas are all correct, and accuracy of power distribution area allocation reaches up to 100%.

(27) Although the present invention is described with reference to the accompanying drawings and the preferred examples, various modifications and variations may be made to the present invention by a person of skill in the art. The various modifications and variations to the present invention and equivalents thereof are covered by the content of the accompanying claims.