Transformer area electric energy meter verification method, sampling inspection sample number determination method and system, and adjustment coefficient determination method

Abstract

The invention relates to a transformer area electric energy meter verification method, a method and system for determining the number of sampling inspection samples, and a method for determining an adjustment coefficient, and belongs to the field of electric energy meter verification. According to the method, when the number of sampling inspection samples of the transformer area is calculated, the proportion of the electric energy meters with problems is considered in a sample adjustment coefficient, and corresponding weights are distributed to the proportion, so that the number of the samples is dynamically adjusted, namely, when the proportion of the electric energy meters with the problems is small, the number of the sampling inspection samples is reduced; when the proportion of the electric energy meters with problems is large, the number of sampling inspection samples is increased, and the cost can be reduced while the sampling inspection requirement is guaranteed.

Description

Technical Field

[0001] The present invention relates to a method for calibrating power meters in a substation area, a method and system for determining the number of sampled inspection samples, and a method for determining an adjustment coefficient, belonging to the field of power meter calibration. Background Art

[0002] As the service time of power meters increases, the internal components may age or wear, resulting in a decrease in metering accuracy. At this time, the power meters need to be replaced. The batch update of power meters is an important power management task, aiming to ensure the accuracy, reliability, and fairness of power metering for the same batch. The power meters in a substation area generally belong to the same batch. Before batch update, it is necessary to calibrate the power meters in the substation area, and judge whether it is necessary to replace all the power meters in the substation area according to the calibration results. For example, if the number of faulty power meters exceeds 2 / 3 of the total number of power meters in the substation area, batch update is carried out.

[0003] In the existing methods for determining the sampled inspection samples of power meters in a substation area, the operating conditions of power meters are not considered, and a fixed number of sampled inspection samples is directly adopted. Although the larger the number of sampled inspection samples, the more accurate the evaluation result, it also increases the detection cost and workload; if the number of sampled inspection samples is small, it cannot reflect the actual situation of all power meters in the substation area. Summary of the Invention

[0004] The purpose of the present invention is to provide a method for calibrating power meters in a substation area, a method and system for determining the number of sampled inspection samples, and a method for determining an adjustment coefficient, so as to solve the problem of how to dynamically reduce or increase the number of sampled inspection samples according to the actual operating conditions of the power meter batch.

[0005] To achieve the above purpose, the solution of the present invention includes:

[0006] A method for determining an adjustment coefficient of the number of sampled inspection samples of power meters in a substation area according to the present invention includes the following steps: obtaining the operating failure rate and the operating calibration overlimit rate of the current power meters in the substation area, and assigning corresponding weights to the operating failure rate and the operating calibration overlimit rate, and the sum of the corresponding assigned weights is 1; obtaining the sample adjustment coefficient for determining the number of sampled inspection samples of power meters in the substation area according to the result of weighted summation of the operating failure rate and the operating calibration overlimit rate according to the corresponding weights; the operating calibration overlimit value is that the operating error of the power meter exceeds the set allowable error value of the power meter.

[0007] Furthermore, an environmental impact coefficient is also preset, and a corresponding weight is assigned to the environmental impact coefficient; the product of multiplying the environmental impact coefficient by the corresponding weight assigned to the environmental impact coefficient is also accumulated to the result to obtain the sample adjustment coefficient.

[0008] Further, the weights corresponding to the operation failure rate, the operation calibration overlimit rate, and the environmental impact coefficient are the ratios of their own values to the sum of the operation failure rate, the operation calibration overlimit rate, and the environmental impact coefficient.

[0009] Further, the operation failures include the failure of the electricity meter to fly away, the failure of the electricity meter to run backward, and the uneven indication value of the electricity meter; as long as any one of the failure of the electricity meter to fly away, the failure of the electricity meter to run backward, and the uneven indication value of the electricity meter occurs, it is determined that the electricity meter has an operation failure.

[0010] Further, the operation error of the electricity meter is obtained through the following steps:

[0011] Establish an analysis formula for the operation error of the electricity meters in the distribution transformer area according to the law of conservation of energy:

[0012]

[0013] where y(i) is the total power supply of the main power supply meter in the measurement period i; P is the total number of electricity meters in the distribution transformer area; is the measured value of the electricity meter j in the measurement period i; ε j is the operation error of the electricity meter j; ε y is the line loss rate of the distribution transformer area; ε0 is the fixed loss of the distribution transformer area;

[0014] After at least P + 2 cycles of power consumption data of the distribution transformer area are accumulated, substitute them into the analysis formula for the operation error of the electricity meters in the distribution transformer area to obtain a system of equations and solve for the operation error.

[0015] A method for determining the number of samples for sampling inspection of electricity meters in a distribution transformer area includes the following steps: multiplying the total number of electricity meters currently in operation in the distribution transformer area by the sample adjustment coefficient as the number of samples for sampling inspection; obtaining the sample adjustment coefficient through the method for determining the sample adjustment coefficient of the number of samples for sampling inspection of electricity meters in the distribution transformer area as described above.

[0016] A method for calibrating electricity meters in a distribution transformer area includes the following steps: obtaining the number of samples for sampling inspection of the electricity meters in the distribution transformer area, calibrating the electricity meters in the distribution transformer area according to the number of samples for sampling inspection, and judging whether it is necessary to replace all the electricity meters in the distribution transformer area according to the calibration results; the number of samples for sampling inspection is obtained through the method for determining the number of samples for sampling inspection of electricity meters in the distribution transformer area as described above.

[0017] A system for determining the number of samples for sampling inspection of electricity meters in a distribution transformer area includes a processor, and the processor executes a computer program to execute the steps of the method for determining the number of samples for sampling inspection of electricity meters in the distribution transformer area as described above.

[0018] The beneficial effects of the present invention are as follows: The present invention is an exploratory invention. When calculating the number of sampled samples in the power distribution area, by considering the proportion of faulty energy meters in the sample adjustment coefficient and assigning corresponding weights to these proportions, the number of samples can be dynamically adjusted. That is, when the proportion of faulty energy meters is small, the number of sampled samples is reduced; when the proportion of faulty energy meters is large, the number of sampled samples is increased. While ensuring the sampling requirements, the cost can also be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a schematic flow chart of a method for determining the number of samples of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0020] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the drawings and embodiments.

[0021] The concept of the present invention lies in dynamically adjusting the number of sampled samples based on the number of faulty energy meters. That is, the more the number of faulty energy meters in the current power distribution area, the more the number of sampled samples to be corresponding increased, so as to reflect the overall situation of the energy meters in the power distribution area, and then determine whether to replace the energy meters in the entire power distribution area. The present invention can dynamically adjust the number of sampled samples. When there are more faulty energy meters, the number of samples increases, thereby making the test results accurate; when there are fewer faulty energy meters, the number of samples decreases, thereby reducing the test cost.

[0022] Method Embodiment 1:

[0023] This embodiment provides a method for determining the number of sampled samples of energy meters in a power distribution area, as Figure 1 shown. First, obtain the operation failure rate of the energy meters currently in operation in the power distribution area. By collecting the metering functions of the energy meters in operation for online monitoring and diagnosis, when any one of the following faults is detected in the energy meter, it is determined that the energy meter has a fault:

[0024] For the energy meter flying-away fault EF, the determination method is:

[0025] EF = E1 - E2 (1)

[0026] where E1 is the daily power consumption of the energy meter; E2 is the maximum possible daily power consumption of the user, which can be obtained by analyzing the historical daily power consumption; when EF > 1, it is determined as the energy meter flying-away fault.

[0027] For the energy meter running backward fault ED, the determination method is:

[0028] ED = E3 - E4 (2)

[0029] Among them, E3 is the indicated value of the total forward active energy frozen daily by the electricity meter; the indicated value of the total forward active energy frozen daily by the electricity meter on the previous day; when ED < 0, it is determined as a reverse-running fault of the electricity meter.

[0030] For the fault ES of uneven indicated values of the electricity meter, the determination method is:

[0031] ES = |E - ∑E n | - m × 0.01 (3)

[0032] Among them, E is the indicated value of the total active energy frozen daily by the electricity meter; E n is the indicated value of the electricity energy with a power rate of n frozen daily by the electricity meter; m is the number of power rates of the electricity meter; when ES > 0, it is determined as a fault of uneven indicated values of the electricity meter.

[0033] Then, divide the number of electricity meters with the above-mentioned operation faults by the total number of electricity meters in the transformer substation area to obtain the operation failure rate Px of the electricity meters in the transformer substation area.

[0034] Furthermore, obtain the operation calibration overlimit rate Py of the electricity meters in the transformer substation area:

[0035] After excluding the electricity meters with operation faults, according to the law of conservation of energy in the transformer substation area, use the regularly frozen electricity quantities of the main meter and the electricity meters to be calibrated in the transformer substation area to establish a system of equations and solve to obtain the operation error of the electricity meters. According to the law of conservation of energy, "the power supply of the main meter in the transformer substation area" = "the sum of the electricity consumption of all sub-meters" + "line loss" + "fixed loss in the transformer substation area", and we can get:

[0036]

[0037] Among them, p is the total number of electricity meters in the transformer substation area; y(i) is the total power supply of the main meter in the i-th measurement period; is the measured value of the electricity meter j in the i-th measurement period; ε j is the operation error of the electricity meter j; ε y is the line loss rate in the transformer substation area; ε0 is the fixed loss in the transformer substation area.

[0038] When n cycles are accumulated in the transformer substation area, a system of equations consisting of n equations can be obtained:

[0039]

[0040] In the system of equations, and y(i) are known quantities, including a total of n equations. When n is greater than or equal to p + 2, the unknown quantities ε j 、ε y and ε0 can be solved, so as to obtain the operation error ε jWhen the operating error of the electricity meter exceeds the allowable error value of the electricity meter (online monitoring warning line), it is determined that the electricity meter has a fault of exceeding the limit value of operating calibration. Then, the number of electricity meters with the fault of exceeding the limit value of operating calibration is divided by the total number of electricity meters in the area to obtain the operating calibration over-limit rate Py of the electricity meters in the area.

[0041] During the actual operation of the electricity meter, it is also affected by the environment. Since the environments of different areas are different, the set environmental impact coefficient Pz is obtained according to a large amount of historical data of the electricity meter in different environments.

[0042] Then, corresponding weights are assigned to the operating failure rate Px, the operating calibration over-limit rate Py, and the environmental impact coefficient Pz. The weight Kx of the operating failure rate Px is:

[0043] Kx = Px / (Px + Py + Pz) (6)

[0044] The weight Ky of the operating calibration over-limit rate Py is:

[0045] Ky = Py / (Px + Py + Pz) (7)

[0046] The weight Kz of the environmental impact coefficient Pz is:

[0047] Kz = Pz / (Px + Py + Pz) (8)

[0048] Kx, Ky, and Kz should satisfy Kx + Ky + Kz = 1. Then, the operating failure rate Px, the operating calibration over-limit rate Py, and the environmental impact coefficient Pz are further normalized to obtain x, y, and z respectively, so that they can be calculated and compared under the same dimension. Furthermore, the formula f(x, y, z) corresponding to the sample adjustment coefficient is obtained:

[0049] f(x, y, z) = k x *x + k y *y + k z *z (9)

[0050] For the electricity meters in a certain area, the operating failure rate, the operating calibration over-limit rate, and the environmental impact coefficient are obtained in real time. Then, the sample adjustment coefficient can be obtained according to formula (9). Furthermore, by multiplying the sample adjustment coefficient by the total number of electricity meters currently in operation in the area, the corresponding number of samples to be inspected can be obtained. Then, based on this sample quantity, the area is inspected to determine whether the electricity meter batch needs to be updated.

[0051] This embodiment also provides the definition of electricity meters belonging to the same batch:

[0052] Have the same characteristics such as nominal voltage, current, maximum current, accuracy level, etc.; be produced according to the same production standards and technical requirements; the verification years should not exceed 12 months from each other; the installation and use conditions should meet the requirements formulated by the electricity meter manufacturer, and the operating environment should be similar; meet certain quantity conditions.

[0053] Method Embodiment 2:

[0054] This embodiment provides a method for determining the adjustment coefficient of the sampling inspection sample number of the area electricity meters. The adjustment coefficient of this embodiment increases with the increase in the number of problematic electricity meters of the area electricity meters. Since the acquisition process of this adjustment coefficient has been introduced clearly enough in Method Embodiment 1, it will not be elaborated here.

[0055] Method Embodiment 3:

[0056] This embodiment provides a method for verifying area electricity meters. The electricity meters in the area are verified according to the obtained sampling inspection sample number. When the number of problematic electricity meters under the sampling inspection sample number exceeds the set threshold, the electricity meters in the entire area are replaced. Since the acquisition process of the sampling inspection sample number has been introduced clearly enough in Method Embodiment 1, it will not be elaborated here.

[0057] System Embodiment:

[0058] This embodiment provides a system for determining the sampling inspection sample number of area electricity meters, including a processor. The computer program executed by this processor is designed by using the method introduced in Method Embodiment 1. Since the introduction of this method has been clear enough, it will not be elaborated here.

[0059] Finally, it should be noted that: The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: It is still possible to modify the specific implementation manners of the present invention or make equivalent substitutions. Any modification or equivalent substitution without departing from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A method for determining the adjustment coefficient of the number of samples of electric energy meters in a substation, characterized in that: The method comprises the following steps: obtaining the operation failure rate and the operation calibration over-limit value rate of the current electric energy meter in the substation, and assigning corresponding weights to the operation failure rate and the operation calibration over-limit value rate, wherein the sum of the corresponding assigned weights is 1; performing weighted summation of the operation failure rate and the operation calibration over-limit value rate according to the corresponding weights to obtain a sample adjustment coefficient for determining the number of random inspection samples of the electric energy meter in the substation; the operation calibration over-limit value means that the operation error of the electric energy meter exceeds the set allowable error value of the electric energy meter.

2. The method for determining the adjustment coefficient of the number of samples of electric energy meters in a substation according to claim 1 is characterized in that: An environmental impact coefficient is also preset, and a corresponding weight is assigned to the environmental impact coefficient; the product of the environmental impact coefficient and the corresponding weight assigned to the environmental impact coefficient is added to the result to obtain the sample adjustment coefficient.

3. The method for determining the adjustment coefficient of the number of samples of electric energy meters in a substation according to claim 2 is characterized in that: The weights corresponding to the operation failure rate, the operation calibration limit value rate and the environmental impact coefficient are the proportions of their own values ​​to the sum of the operation failure rate, the operation calibration limit value rate and the environmental impact coefficient.

4. The method for determining the adjustment coefficient of the number of samples of electric energy meters in a substation according to claim 1 is characterized in that: Operational faults include an electric energy meter flying away fault, an electric energy meter running backwards fault and an electric energy value uneven fault; as long as any one of the electric energy meter flying away fault, the electric energy meter running backwards fault and the electric energy value uneven fault occurs, the electric energy meter is determined to have an operational fault.

5. The method for determining the adjustment coefficient of the number of samples of electric energy meters in a substation according to claim 1, characterized in that: The operation error of the electric energy meter can be obtained by the following steps: According to the law of conservation of energy, the formula for analyzing the operation error of the electric energy meter in the substation is established: Among them, y(i) is the total power supply of the power supply meter in the metering period i; P is the total number of power meters in the substation; is the measurement value of electric energy meter j in measurement period i; ε j is the operating error of electric energy meter j; ε y is the line loss rate of the substation area; ε0 is the fixed loss of the substation area; When the power data of at least P+2 cycles is accumulated in the substation, the operation error analysis formula of the power meter in the substation is substituted into the equation group to obtain the operation error.

6. A method for determining the number of samples for random inspection of electric energy meters in a substation, characterized in that: The method comprises the following steps: taking the product of the total number of electric energy meters currently in operation in the substation and the sample adjustment coefficient as the number of random inspection samples; and obtaining the sample adjustment coefficient by the method for determining the adjustment coefficient of the number of random inspection samples of electric energy meters in the substation as described in any one of claims 1 to 5.

7. A method for verifying electric energy meters in a substation, characterized in that: The method comprises the following steps: obtaining the number of random inspection samples of electric energy meters in the substation, calibrating the electric energy meters in the substation according to the number of random inspection samples, and judging whether it is necessary to replace the electric energy meters in the entire substation according to the calibration results; the number of random inspection samples is obtained by the method for determining the number of random inspection samples of electric energy meters in the substation as described in claim 6.

8. A system for determining the number of samples of electric energy meters in a substation, comprising a processor, characterized in that: The processor executes the computer program to perform the steps of the method for determining the number of samples for random inspection of electric energy meters in an area as described in claim 6.

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