Zero line fault analysis method based on metering data of electric energy meter

Abstract

The invention discloses a zero line fault analysis method based on metering data of an electric energy meter, and the method comprises the following steps: obtaining the metering data of the electric energy meter, and analyzing which time intervals accord with a zero line fault phenomenon in the day through the voltage difference between a transformer area general meter and the electric energy meter and the current fluctuation condition of the electric energy meter; and clustering the user and transformer voltage in the time interval, analyzing whether a zero line fault phenomenon exists in the transformer area, and finally deducing the user influence range of the zero line fault. According to the zero line fault analysis method based on the electric energy meter measurement data, acquisition equipment does not need to be added, on-site troubleshooting manpower does not need to be added, low-voltage transformer area zero line fault analysis can be achieved only by performing data association analysis through the acquired data, and the fault operation and maintenance capacity of a power distribution network can be improved.

Description

Technical Field

[0001] The present invention relates to a method for analyzing neutral line faults based on electricity meter measurement data, and belongs to the technical field of low-voltage substation line fault identification. Background Art

[0002] The low-voltage distribution substation is the smallest unit and data source of the power distribution network. There are long-term neutral line faults in some old substations, which will bring serious electrical appliance use problems to residential users and also pose safety problems. The conventional method is to conduct on-site inspections of the lines. This method is difficult and complex to implement, and large-scale inspections are not practically meaningful. Electricity meter measurement data is conventional data collected by power supply companies, which is easy to analyze and obtain. However, there are few methods for identifying neutral line faults in substations based on measurement data.

[0003] Therefore, a method for analyzing neutral line faults based on electricity meter measurement data is needed to solve the above problems. Summary of the Invention

[0004] Object of the Invention: Aiming at the problems existing in the prior art, the present invention provides a method for analyzing neutral line faults based on electricity meter measurement data.

[0005] A method for analyzing neutral line faults based on electricity meter measurement data includes the following steps:

[0006] Step 1: Obtain the measurement data of the electricity meter, where the measurement data includes the instantaneous voltage effective value and instantaneous current effective value of the total meter in the substation within time T0, and the instantaneous voltage effective value and instantaneous current effective value of the electricity meters of the subordinate users;

[0007] Step 2: Calculate the voltage difference between the three-phase voltage of the total meter in the substation and the voltage of the user's electricity meter at time t b Put all the t moments that meet the condition into a set to obtain set T b ; b ;

[0008] Step 3: Calculate the difference ΔI t between the current of the user's electricity meter at time t and the average current of the user's electricity meter within time T0, where t ∈ T b . Save all the moments t that meet |ΔI t | ∈ [β, +∞] to set T s . Save the moments t that meet the condition to set T s . Save the moments t that meet the condition to set T s . Among them, is the single-phase electricity meter in T bThe set of current magnitudes at the aggregation moment, is the maximum current value of the single-phase watt-hour meter at T b in the aggregation moment, is the set of the magnitudes of the three-phase currents of phases A, B, and C of the three-phase watt-hour meter at T b in the aggregation moment, is the maximum value of the three-phase currents of phases A, B, and C of the three-phase watt-hour meter at T b in the aggregation moment;

[0009] Step 4: Cluster the voltage data of the user watt-hour meter and the substation main meter within the set T s Based on voltage correlation. When the user watt-hour meter and the substation main meter cannot be clustered into the same category, it indicates that there is a neutral wire fault in the user watt-hour meter.

[0010] Furthermore, when the watt-hour meter is a single-phase meter in Step 2:

[0011]

[0012] When the watt-hour meter is a three-phase meter:

[0013]

[0014] In the formula, U TA , U TB and U TC are the three-phase voltages of phases A, B, and C of the substation main meter respectively; U is the voltage of the single-phase meter; U A , U B and U C are the three-phase voltages of phases A, B, and C of the three-phase meter.

[0015] When |ΔU| ∈ [α, +∞), it is determined that there may be a phenomenon of excessive voltage difference caused by a neutral wire fault at the moment t b in this moment.

[0016] Furthermore, when the watt-hour meter is a single-phase meter in Step 3:

[0017] ΔI t = max(I t - I mean )

[0018] When the watt-hour meter is a three-phase meter:

[0019] ΔI t = max(I At - I Amean , I Bt - I Bmean , I Ct - I Cmean )

[0020] In the formula, It is the current of the single-phase energy meter at time t, I mean is the average current of the single-phase energy meter within time T0, I At 、I Bt and I Ct are the currents of phases A, B, and C of the three-phase energy meter at time t, I Amean 、I Bmean and I Cmean are the average currents of phases A, B, and C of the three-phase energy meter within time T0.

[0021] Furthermore, in step four, the voltage data of the user energy meter and the total meter of the low-voltage area within the set T s is clustered based on voltage correlation specifically as follows: when L(U m , U n ) ∈ [0, γ], the m-th energy meter and the n-th energy meter are clustered into one category, where L(U m , U n ) is calculated by the following formula:

[0022]

[0023] where L(U m , U n ) is the distance between the voltage sequences of the energy meters numbered m and n, U m is the voltage data sequence of the energy meter numbered m, U n is the voltage data sequence of the energy meter numbered n, u m,i is the i-th voltage value of the m-th energy meter, u n,i is the i-th voltage value of the n-th energy meter, where n is a positive integer from 1 to M, m is a positive integer from 1 to M, and M is the number of energy meters.

[0024] Furthermore, in step two, α = 10.

[0025] Furthermore, in step three, β = 10 and χ = 15.

[0026] Furthermore, in step γ = 0.5.

[0027] Furthermore, in step one, the time T0 is one day.

[0028] Beneficial effects: The method for analyzing neutral line faults based on the metering data of energy meters of the present invention does not require adding acquisition equipment or increasing on-site troubleshooting manpower, and can realize the analysis of neutral line faults in low-voltage areas only through data correlation analysis of the power consumption and acquisition data, which helps to improve the fault operation and maintenance ability of the distribution network. Description of the Drawings

[0029] Figure 1, Flow chart of the neutral line fault analysis method based on the electricity meter measurement data;

[0030] Figure 2 , Clustering results of the neutral line fault based on the electricity meter measurement data. Detailed implementation manner

[0031] The preferred implementation manner of the present invention will be described below in conjunction with the accompanying drawings to more clearly and completely elaborate the technical solution of the present invention.

[0032] Please refer to Figure 1-2 As shown, the neutral line fault analysis method based on the electricity meter measurement data of the present invention includes the following steps:

[0033] Step 1: The obtained measurement data includes the instantaneous effective value data of the voltage and current at each hour moment t of the total meter in the substation area within one day, and the instantaneous effective value data of the voltage and current at each hour moment t of 54 electricity meters under the substation area. Where t b ∈T0; in the present invention, T0 is one day. b The voltage and current instantaneous effective value data of the 54 electricity meters under the substation area at each hour moment t. Where t b ∈T0; in the present invention, T0 is one day.

[0034] Step 2: Calculate the voltage difference between the three-phase voltage of the total meter in the substation area and the electricity meter voltage at each hour moment t, as follows:

[0035] When the electricity meter is a single-phase meter:

[0036] ΔU = max(U TA -U, U TB -U, U TC -U)

[0037] When the electricity meter is a three-phase meter:

[0038] ΔU = max(U TA -U A , U TB -U B , U TC -U C )

[0039] When |ΔU| ∈ [α, +∞], it is determined that there may be a phenomenon of excessive voltage difference caused by a neutral line fault at the moment t that meets the above conditions, where: U TA , U TB And U TC Are the A, B, and C three-phase voltages of the total meter in the substation area respectively; U is the single-phase meter voltage; U A , U B And U C Are the A, B, and C three-phase voltages of the three-phase meter; Record the moment t as the set T b . In the present invention, α = 10.

[0040] The moments that meet the above conditions in the present invention are:

[0041] T b = [2, 3, 4, 5, 6, 7, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23], and there is a phenomenon of excessive voltage difference at these 19 moments.

[0042] Step 3: Select the current data I of each electric energy meter under the power grid area at each moment t ∈ T in the above set b for analysis and calculation to determine whether the moments of voltage change in this set are related to the current. The calculation method is as follows: t When the electric energy meter is a single-phase meter:

[0043] ΔI

[0044] ΔI t = max(I t - I mean )

[0045] When the electric energy meter is a three-phase meter:

[0046] ΔI t = max(I At - I Amean , I Bt - I Bmean , I Ct - I Cmean )

[0047] where: I mean is the average current of the single-phase electric energy meter on that day; I Amean , I Bmean , I Cmean are the average phase currents of each phase of the three-phase electric energy meter on that day;

[0048] When |ΔI| ∈ [β, +∞), save the moment t to the set T s ; when or , save the moment t to the set T s . In the present invention, β = 10 and χ = 15.

[0049] Among the 19 moments calculated in Step 2, except for 2 o'clock, the other moments meet the above current phenomenon. Therefore, T s = [3, 4, 5, 6, 7, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20, 21, 22, 23];

[0050] Step 4: Cluster the voltage data of the user's electric energy meter and the total power grid area meter at the above T s moment set based on voltage correlation. When L(Um , U n When ) ∈ [0, γ], the m-th and n-th electricity meters are grouped into one category, thus obtaining the subordinate clustering number. In the present invention, γ = 0.5. Among them, L(U m , U n ) is calculated by the following formula:

[0051]

[0052] Among them, L(U m , U n ) is the distance of the voltage sequence between the electricity meters numbered m and n. The variable U m is the voltage data sequence of the electricity meter with the serial number m, and the number U n is the voltage data sequence of the electricity meter with the serial number n. n is a positive integer from 1 to M, m is a positive integer from 1 to M, M is the number of electricity meters, u m,i , u n,i is the i-th voltage value of the m-th and n-th electricity meters.

[0053] Step Five: After obtaining the above clustering results in Step Four, obtain the user set H that is not grouped with the voltage of the substation main meter. As Figure 2 shown, H is the user with a neutral line fault or a neutral line fault upstream of the line.

Claims

1. A neutral line fault analysis method based on the metering data of an electric energy meter, characterized in that, It includes the following steps: Step 1: Obtain the metering data of the electricity meter. The metering data includes the instantaneous voltage effective value and the instantaneous current effective value of the main meter in the substation area within the time T0, as well as the instantaneous voltage effective value and the instantaneous current effective value of the electricity meters of the subordinate users. Step 2: Calculate t b The voltage difference between the three-phase voltage of the total meter in the substation area and the voltage of the user's electricity meter at time t Put all The t that meets the requirements b At the moment, put it into the set to obtain the set T b ; Step 3: Calculate the difference ΔI between the current of the user's electricity meter at time t and the average value of the current of the user's electricity meter within time T0, where t ∈ T t , where t ∈ T b , and save all the times t that satisfy |ΔI t | ∈ [β, +∞] to the set T s . Save the times t that satisfy to the set T s . Save the times t that satisfy to the set T s . Among them, is the set of the magnitudes of the currents of the single-phase electricity meter at the times in the set T b , is the maximum current value of the single-phase electricity meter at the times in the set T b , is the set of the magnitudes of the three-phase currents A, B, and C of the three-phase electricity meter at the times in the set T b , is the maximum value of the three-phase currents A, B, and C of the three-phase electricity meter at the times in the set T b ; Step 4. Cluster the voltage data of the user electricity meter and the substation master meter in set T s based on voltage correlation. When the user electricity meter and the substation master meter cannot be clustered into the same category, it indicates that there is a neutral line fault in the user electricity meter.

2. The zero-line fault analysis method based on the electricity meter measurement data according to claim 1, wherein In Step 2, when the electricity meter is a single-phase meter: When the electricity meter is a three-phase meter: where U TA , U TB and U TC are the phase A, phase B and phase C voltages of the main meter in the transformer area, respectively; U is the voltage of a single-phase meter; U A , U B and U C are the three-phase voltages of phases A, B, and C of a three-phase meter.

3. The zero-line fault analysis method based on the metering data of the electric energy meter according to claim 1, wherein, In Step 3, when the electricity meter is a single-phase meter: ΔI t = max(I t - I mean ) When the electricity meter is a three-phase meter: ΔI t = max(I At - I Amean , I Bt - I Bmean , I Ct - I Cmean ) Where, I t is the current of the single-phase watt-hour meter at time t, and I mean is the average value of the current of the single-phase watt-hour meter within time T0. I At , I Bt and I Ct are the currents of phases A, B, and C of the three-phase watt-hour meter at time t, and I Amean , I Bmean and I Cmean are the average values of the currents of phases A, B, and C of the three-phase watt-hour meter within time T0.

4. The zero-line fault analysis method based on the power meter measurement data according to claim 1, characterized in that In Step 4, the voltage data of the user's electricity meter and the total meter of the transformer substation in the set T s is clustered based on voltage correlation specifically as follows: When L(U m , U n ) ∈ [0, γ], the m-th electricity meter and the n-th electricity meter are clustered into one category. Among them, L(U m , U n ) is calculated by the following formula: where, L(U m , U n ) is the distance of the voltage sequences between the watt-hour meters numbered m and n, U m is the voltage data sequence of the watt-hour meter numbered m, U n is the voltage data sequence of the watt-hour meter numbered n, u m，i is the i-th voltage value of the m-th watt-hour meter, u n，i is the i-th voltage value of the n-th watt-hour meter, where n is a positive integer from 1 to M, m is a positive integer from 1 to M, and M is the number of watt-hour meters.

5. The zero-line fault analysis method based on the electricity meter measurement data according to claim 1, wherein In Step 2, α = 10.

6. The zero-line fault analysis method based on the electricity meter measurement data according to claim 1, characterized in that, In Step 3, β = 10 and χ = 15.

7. The method for analyzing neutral line faults based on the metering data of electric energy meters according to claim 4, characterized in that, Step γ = 0.

5.

8. The zero-line fault analysis method based on the electricity meter measurement data according to claim 1, wherein In Step 1, the time T0 is one day.

Images