The present invention relates to the technical field of low-voltage distribution networks, and in particular, to a method for identifying consumer phase connectivity in low-voltage distribution network based on voltage correlation characteristics.
The intelligent development of the current low-voltage distribution network is limited by the lack or inaccuracy of the physical topology connection information of the low-voltage distribution network. The lack of accurate low-voltage topology relation will lead to difficulties in three-phase unbalance treatment, abnormal line loss statistics, and untimely repairs for power outages. The topology identification of low-voltage distribution network is an important problem to be solved urgently by current power grid companies. The connection relation of user phase sequence, as an important part of low-voltage topology identification, has received wide attention.
Conventional methods include manual detection, installation of a signal receiving device, etc. Manual detection methods are time-consuming, inefficient, and prone to errors. The signal receiving device has a high accuracy, but the capital investment and subsequent operation and maintenance pressure of the device are high. The data analysis method has the advantages of small transformation amount and large input-output ratio, etc., and has become an important technical direction to solve the problems of household transformer relationship verification and user phase sequence identification in topology identification of a low-voltage distribution network.
The objective of the present invention is to solve the problem of identifying consumer phase connectivity in low-voltage distribution network when user data is incomplete, which helps to improve the operation efficiency and customer satisfaction index of power grid enterprises.
Limited by power flow constraints, users with a close electrical distance have voltage association characteristics, and there are also association characteristics between users and a low-voltage bus in a phase sequence where the users are located. Based on this, in the present invention, firstly, classifying users by means of the voltage association characteristics among the users. Further, determining an initial consumer phase connectivity by means of voltage association characteristics between the users and the three-phase buses on the low-voltage side of the low-voltage distribution network. Finally, verifying the initial consumer phase connectivity according to the voltage association characteristics among the users, so as to obtain a final consumer phase connectivity identification result. Compared with other identification methods, the present invention only uses voltage data, and can solve the problem of identifying consumer phase connectivity in low-voltage distribution network when user data is incomplete, without adding an additional terminal device. Therefore, the present invention has the characteristics of being convenient to operate, reducing the human cost of an electric power company and increasing efficiency.
The objective of the present invention is achieved by at least one of the following technical solutions.
A method for identifying consumer phase connectivity in low-voltage distribution network based on voltage association characteristics, comprising the following steps:
(1) acquiring users to be identified and voltage time series data of three-phase buses on the low-voltage side of the low-voltage distribution network where the users to be identified are located;
(2) calculating voltage time series curve correlation coefficients among the users, and classifying a user having the maximum voltage time series curve correlation value with respect to the user into one category so as to form a user category set;
(3) based on the user classifications, determining an initial consumer phase connectivity according to the voltage association characteristics between the users and the three-phase buses on the low-voltage side of the low-voltage distribution network; and
(4) verifying the initial consumer phase connectivity according to the voltage association characteristics among the users, so as to obtain a final consumer phase connectivity identification result.
Further, in the step (2), calculating voltage time series curve correlation coefficients among the users, and classifying the user having the maximum voltage time series curve correlation value with respect to the user into one category so as to form the user category set, specifically comprises:
step (2-1): calculating a voltage curve correlation coefficient matrix R included in a meter reading directory of the low-voltage distribution network, wherein elements in the u-th row of the matrix are voltage time series curve correlation coefficients between the user u and all users;
wherein M represents a total number of users included in the meter reading directory of the low-voltage distribution network; Θ is users included in the meter reading directory of the low-voltage distribution network; ruv represents a voltage time series correlation coefficient between the user u and a user v, specifically as follows:
in the formula, Uut and Uvt are respectively voltage values of the users u and v at time t, u, v∈Θ, t=1, 2, . . . , T
step (2-2): based on the matrix R, classifying each user having the maximum time series curve correlation with respect to other user except the user itself into one category, so as to obtain
Q double-table classifications in total;
step (2-3): performing union processing on classifications containing same user, and finally obtaining a user category set Ωcla containing N categories in total, and ending the user classification.
Further, based on the user category set Ωcla, determining an initial consumer phase connectivity according to voltage association characteristics between the users and the three-phase buses on the low-voltage side of the low-voltage distribution network, specifically refers to:
step (3-1): calculating an average value of a voltage of each user, as shown below,
in the formula, Uu
for the user category set Ωcla, extracting a user having the maximum voltage average value in each classification to constitute a user set ξ, and at this time, an element in ξ being the user closest to a head end in each classification;
step (3-2): calculating a voltage time series curve correlation coefficient between each user and the three-phase buses on the low-voltage side of the low-voltage distribution network in ξ, so as to obtain a matrix R1,
in the formula, rA, ξ(h), rB, ξ(h), and rC, ξ(h) are respectively voltage time series curve correlation coefficients between the h-th user in the set ξ and bus of phase A on the low-voltage side of the low-voltage distribution network, between the h-th user in the set ξ and bus of phase B on the low-voltage side of the low-voltage distribution network and between the h-th user in the set ξ and bus of phase C on the low-voltage side of the low-voltage distribution network in the set ξ;
step (3-3): for the h-th user in the set ξ, the phase sequence of the bus on the low-voltage side of the low-voltage distribution network corresponding to max{rA,ξ(h), rB,ξ(h), rC,ξ(h)} serves as a phase sequence of the h-th user in the set ξ, and a phase sequence of each user in ξ is the phase sequence of all the users in the classification where the users is located, so as to obtain an initial consumer phase connectivity result Θ0.
Further, a calculation method of the matrix elements rA, ξ(h), rB,ξ(h), rC,ξ(h) is as follows:
in the formula, Uξ(h)t is the voltage value of the h-th user in the set ξ at the time t, and Uφt is a voltage value of bus of phase φ on the low-voltage side of the low-voltage distribution network at the time t.
Further, in the step (4), verifying the initial consumer phase connectivity according to the voltage association characteristics among the users so as to obtain a final consumer phase connectivity identification result, specifically comprising:
step (4-1): ranking users according to the average voltages from high to low, setting a first threshold coefficient τ, and extracting previous [τ*M] users in the user ranking result to form a set d as the user set closest to the head end on the low-voltage side of the low-voltage distribution network, wherein M is a total number of users included in a meter reading directory of the low-voltage distribution network;
step (4-2): for the user category set Ωcla formed in step (2), extracting a user having the minimum voltage average value in each classification to constitute a user set χ, and at this time, an element in χ being the user closest to the bottom end in each classification;
step (4-3): making χ1={u|u∈χ, and u∉d}, and extracting correlation coefficients between each user and other users in χ1 from a matrix R of voltage curve correlation coefficients among the users, so as to obtain O=|χ1| vectors, and further for elements in each vector, ranking users according to the values from high to low;
step (4-4): setting a second threshold coefficient τ1; if in an initial consumer phase connectivity result, previous τ1 users having the maximum correlation coefficient of a voltage curve with respect to a certain user in χ1 is not in a same phase with the certain user, listing the user as an initial suspicious user, and adding the initial suspicious user into an initial suspicious user set χ2;
step (4-5): in an initial suspicious user set χ2, if a user having the maximum correlation of a voltage curve with respect to a certain user is not in the same phase with the certain user, determining the user to be an out-of-phase user; if a user having the maximum correlation with respect to the certain user also belongs to χ2, listing the user in a suspicious user set χ3;
step (4-6): in the suspicious user set χ3, if a user having the maximum correlation of a voltage curve of with respect to the certain user also belongs to χ3, determining the user to be an out-of-phase user; and
step (4-7): for the out-of-phase users in step (4-5) and step (4-6), updating the phase sequences of the out-of-phase users to be the phase sequences of the previous τ1 users whose phase sequences are different from the phase sequences of the out-of-phase users so as to obtain a final consumer phase identification result, and ending the identification.
Further, the first threshold coefficient τ∈[0,0.5].
Further, the second threshold coefficient τ1 is given according to expert experience.
The present invention has the following beneficial effects:
(1) only using voltage data, the present invention is suitable for identifying consumer phase connectivity in low-voltage distribution network when user data is incomplete, and is beneficial to improve the accuracy of identifying consumer phase connectivity in low-voltage distribution network in practical applications;
(2) there is no need to add an acquisition terminal in a low-voltage distribution network, and therefore the present invention has the advantages of low cost and low engineering amount.
Specific implementations of the present invention are further described below with reference to the accompanying drawings and embodiments.
(1) acquiring users to be identified and voltage time series data of three-phase buses on the low-voltage side of the low-voltage distribution network where the users to be identified are located;
Exemplarily, in view of
(2) calculating voltage time series curve correlation coefficients among the users, and classifying a user having the maximum voltage time series curve correlation value with respect to the user into one category so as to form a user category set Ωcla, specifically comprises:
step (2-1): calculating a voltage curve correlation coefficient matrix R included in a meter reading directory of the low-voltage distribution network, wherein elements in the u-th row of the matrix are voltage time series curve correlation coefficients between a user u and all users;
wherein r11, ruu, rvv and rMM respectively represent a voltage time series curve correlation coefficient between a user 1 and the user 1 itself, a voltage time series curve correlation coefficient between a user u and the user u itself, a voltage time series curve correlation coefficient between a user v and the user v itself, and a voltage time series curve correlation coefficient between a user M and the user M itself, and are all 1; r1M represents the voltage time series correlation coefficient between the user 1 and the user M; rM1 represents the voltage time series correlation coefficient between the user M and the user 1; M represents the total number of users included in a meter reading directory of the low-voltage distribution network; Θ is the users included in the meter reading directory of the low-voltage distribution network; ruv=rvu, ruv represents the voltage time series correlation coefficient between the user u and the user v, specifically as follows:
in the formula, Uut and Uvt are respectively voltage values of the user u and v at the time t, u, v∈Θ, t=1, 2, . . . , T.
step (2-2): based on the matrix R, classifying each user having the maximum time series curve correlation with respect to other user except the user itself into one category, so as to obtain Q double-table classifications in total; and
step (2-3): performing union processing on the classifications containing the same users, and finally obtaining a user category set Ωcla containing N categories in total, and ending the user classification.
The user category set obtained thereby is as follows:
(3) based on the user classifications, determining an initial consumer phase connectivity according to voltage association characteristics between the users and the three-phase buses on the low-voltage side of the low-voltage distribution network, specifically referring to:
step (3-1): calculating an average value of the voltage of each user, as shown below,
in the formula, Uu
for the user category set Ωcla formed in step 2, extracting a user having the minimum voltage average value in each classification to constitute a user set ξ, and at this time, an element in ξ being the user closest to the bottom end in each classification;
step (3-2): calculating a voltage time series curve correlation coefficient between each user in ξ and the three-phase buses on the low-voltage side of the low-voltage distribution network, so as to obtain a matrix R1,
rA,ξ(N), rB, ξ(N), and rC, ξ(N) are respectively voltage time series curve correlation coefficients between the N-th user in the set ξ and bus of phase A of three-phase on the low-voltage side of the low-voltage distribution network, between the h-th user in the set ξ and bus of phase B of three-phase on the low-voltage side of the low-voltage distribution network, and between the h-th user in the set ξ and bus of phase C of three-phase on the low-voltage side of the low-voltage distribution network, wherein h<N, a calculation method of the matrix elements rA, ξ(h), rB, ξ(h), rC and ξ(h) is as follows:
in the formula, Uξ(h)t is the voltage value of the h-th user in the set ξ at the time t, and Uφt is the voltage value of bus of phase φ on the low-voltage side of the low-voltage distribution network at the time t.
step (3-3): for the h-th user in the set ξ, the phase sequence of the bus on the low-voltage side of the low-voltage distribution network corresponding to max{rA,ξ(h), rB,ξ(h), rC,ξ(h)} serves as the phase sequence of the h-th user in the set ξ, and the phase sequence of each user in ξ is the phase sequence of all the users in the classification where the users are located, so as to obtain an initial phase relationship result Θ0, as shown in table 2.
(4) verifying the initial consumer phase connectivity according to the voltage association characteristics among the users, so as to obtain a final consumer phase connectivity identification result, specifically comprises:
step (4-1): ranking all users according to the average voltages from high to low, setting a first threshold coefficient τ∈[0,0.5], and extracting previous [τ*M] users in the user ranking result to form a set d as the user set closest to the head end on the low-voltage side of the low-voltage distribution network, wherein M is the total number of users included in a meter reading directory of the low-voltage distribution network;
step (4-2): for the user category set Ωcla formed in step (2), extracting a user having the minimum voltage average value in each classification to constitute a user set χ, and at this time, an element in χ being the user closest to the bottom end in each classification;
step (4-3): making χ1={u|u∈χ, and u∉d}, and extracting correlation coefficients between each user and other users in χ1 from a matrix R of voltage curve correlation coefficients among the users, so as to obtain O=|χ1| vectors, and further for elements in each vector, ranking users in each vector according to the values from high to low;
step (4-4): setting a second threshold coefficient τ1, wherein the value of the second threshold coefficient is given by expert experience; in the present embodiment, τ1=3; if in an initial consumer phase connectivity result, previous τ1 users having the maximum correlation coefficient of a voltage curve with respect to a certain user in χ1 is not in the same phase with the certain user, listing the user (i.e., the aforesaid certain user) as an initial suspicious user, and adding the initial suspicious user into an initial suspicious user set χ2;
step (4-5): in an initial suspicious user set χ2, if a user having the maximum correlation of a voltage curve with respect to a certain user is not in the same phase with the certain user, determining the user (i.e., the aforesaid certain user) to be an out-of-phase user; if a user having the maximum of the certain user also belongs to χ2, listing the user (i.e., the aforesaid certain user) in a suspicious user set χ3;
step (4-6): in the suspicious user set χ3, if a user having the maximum correlation of a voltage curve with respect to a certain user also belongs to χ3, determining the user (i.e., the aforesaid certain user) to be an out-of-phase user; and
step (4-7): for the out-of-phase users in step (4-5) and step (4-6), updating the phase sequences of the out-of-phase users to be the phase sequences of the first user in the previous τ1 users whose phase sequences are different from the phase sequences of the out-of-phase users so as to obtain a final consumer phase identification result.
The meters identified incorrectly in the initial consumer phase connectivity result are S80, S106, T102, S81, S82, S83, S84, S85, S86. The phase sequence of these users is changed from phase A to phase C, and finally the consumer phase identification relationship of the low-voltage distribution network is as shown in the following table:
It can be determined in conjunction with
In conclusion, the foregoing examples illustrate the effectiveness of a method for identifying consumer phase connectivity in low-voltage distribution network based on voltage association characteristics provided by the embodiments of the present invention.
The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments, and any other modification, decoration, substitution, combination and simplification made without departing from the spirit and principle of the present invention shall all be equivalent substitution, and shall belong to the scope of protection of the present invention.
Number | Date | Country | Kind |
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202010550359.1 | Jun 2020 | CN | national |
Filing Document | Filing Date | Country | Kind |
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PCT/CN2020/142540 | 12/31/2020 | WO |