A Method and System for Evaluating the Operation Status of Distribution Area Energy Meters Based on Multi-Node Voltage Difference

Abstract

This disclosure provides a method and system for evaluating the operational status of electricity meters in a distribution area based on multi-node voltage differences. It belongs to the field of online status monitoring technology for electricity meters. The scheme constructs a model based on information from all electricity meters and line nodes in the distribution area. It pre-collects the output voltage and current signals of all electricity meters during normal operation, establishes a temperature calculation model function based on the conductor thermal balance equation, and uses an iterative method to determine the conductor temperature, thereby determining the conductor resistivity. After measuring the line length, it establishes the line resistance equation; after establishing the voltage equation at the nodes, it obtains the voltage difference state characteristic quantity; it establishes an offline state characteristic quantity dataset of voltage differences for all nodes in the entire distribution area; and it determines the operational status of the electricity meters by comparing the offline and real-time state characteristic quantity datasets. This invention fully utilizes the node voltage difference information of different lines in the distribution area to establish a characteristic quantity model and monitor the operational status of electricity meters in real time, effectively ensuring the accuracy and reliability of electricity metering in the power system.

Description

Technical Field

[0001] This disclosure belongs to the field of online status monitoring technology for electricity meters, and particularly relates to a method and system for evaluating the operating status of electricity meters in distribution areas based on multi-node voltage differences. Background Technology

[0002] The statements in this section are merely background information relating to this disclosure and do not necessarily constitute prior art.

[0003] The power industry is a pillar industry of the national economy, and electricity metering is an important component of the power economy. Electricity metering devices are used to measure electricity consumption on both the power supply side and the user side. The accuracy and reliability of their metering results are of great significance for the safe and efficient operation of the power system and for trade settlement. Accurate acquisition of the operating status of electricity metering devices is a prerequisite for establishing a fair electricity market and an important guarantee for the safety of the power system.

[0004] The inventors discovered that current multi-index correlation analysis methods for electricity meter operating status mainly include data-driven methods and model analysis methods. Data-driven methods rely on a large amount of historical operating data collected from electricity meters. Algorithms analyze the correlations between data points, selecting an empirical model suitable for data analysis as the evaluation criterion. The actual operating data is then analyzed using this empirical model to determine the electricity meter's operating status. However, the selected empirical model does not consider the electrical and physical topology and characteristics of the actual operating conditions of the distribution area, relying entirely on the collected data. The model's applicability is limited by historical data; when the model's applicability decreases, the accuracy of electricity meter status determination also declines. Model analysis is a physical or mathematical model for assessing the state of a power grid in a distribution area. Evaluation indicators are determined based on the model, and the operating status of the electricity meter is judged according to these indicators. However, the accuracy of this method largely depends on the accuracy of the model. Currently, most evaluation methods are based on the principle of energy conservation to establish energy balance equations on the power supply and consumption sides to obtain the operating error of the electricity meter. In modeling, it is assumed that line losses remain constant or only change very little within the analysis time range. However, in actual operation, the conductor temperature is affected by factors such as the load in the distribution area and the ambient temperature, causing fluctuations in line losses. This leads to errors in assessing the operating status of the electricity meter, making it difficult to guarantee accuracy. Summary of the Invention

[0005] To address the aforementioned problems, this disclosure provides a method and system for evaluating the operating status of transformer substation energy meters based on multi-node voltage differences. The scheme combines precise modeling and data-driven approaches. It constructs a model based on the physical and electrical relationships of the transformer substation, builds a temperature calculation model function based on the heat balance equation, updates conductor temperature in real time, and determines the real-time line resistance based on the current conductor temperature. This ensures the accuracy of line impedance during the analysis process and improves the accuracy of the constructed model. While ensuring model accuracy, it establishes transformer substation node voltage difference equations based on historical operating data of the energy meters and the constructed model, and sets offline voltage difference state characteristic quantity evaluation indicators. Actual operating data is used to generate new actual operating state characteristic quantity evaluation indicators through the constructed model. By comparing the compatibility between the two, the operating status of the energy meters can be accurately determined.

[0006] According to a first aspect of the embodiments of this disclosure, a method for evaluating the operating status of a distribution area energy meter based on multi-node voltage difference is provided, including:

[0007] A transformer substation energy meter model is constructed based on the line topology of user energy meters within the substation area, and an energy meter operation error calculation model is constructed based on the transformer substation energy meter model.

[0008] Based on the energy meter operation error calculation model, a line temperature calculation model function is constructed according to the line heat balance equation, and the actual line temperature is obtained through iterative loop based on the line temperature calculation model function.

[0009] Based on the actual temperature of the line, the resistance of each level of the line in the distribution area is obtained; and the voltage equation at the node is constructed according to the voltage and current signals output by each user-side energy meter and the obtained resistance of each level of the line.

[0010] Based on the voltage equation at the node, an offline state feature dataset is established according to the voltage and current signals collected by each meter in the transformer area during normal and fault conditions.

[0011] The output voltage and current signals of all electricity meters in the region are acquired during actual operation, real-time sampling status features are constructed, and compared with the offline status feature dataset to determine the real-time operating status of the electricity meters.

[0012] Furthermore, the construction of the offline state feature dataset is specifically as follows:

[0013] Define state characteristic F i,j,j′ The difference in the equations for the voltages at the i-th node of the transformer area obtained from the j-th and j′-th branches is expressed as: F i,j,j′ =(V i,j +R i,j I i,j )-(V i,j′ +R i,j′ Ii,j′ (i = 1, 2…m, j = 1, 2…n) i j′=1,2…n i ,j′≠j);

[0014] Define the state feature dataset Let the difference matrix of the voltage equations obtained from different branches at the i-th node of the transformer area be represented as:

[0015] By determining the state feature dataset at the i-th node of the transformer area when the meter is at different fault levels, the offline state feature dataset of all nodes in the transformer area can be determined.

[0016] Among them, I i,j I i,j′ (i = 1, 2, ..., m, j = 1, 2, ..., n) i R represents the current from the i-th node to the j,j′-th user-side meter in the second level. i,j R i,j′ (i = 1, 2, ..., m, j = 1, 2, ..., n) i ) is its line resistance, V i,j V i,j′ (i = 1, 2, ..., m, j = 1, 2, ..., n) i ) represents the voltage collected by the j-th and j′-th user-side meters connected to the i-th node of the second level.

[0017] Furthermore, the process of comparing the offline state feature dataset to determine the real-time operating status of the electricity meter specifically involves: constructing a multi-dimensional space based on the offline state feature dataset built by a single node; and determining the operating status of the electricity meter based on the distribution of the real-time sampled state features in the multi-dimensional space.

[0018] Furthermore, the construction of the electricity meter operation error calculation model is specifically as follows: taking all the electricity meters in a distribution area as a cluster, and all lines in the distribution area as purely resistive lines, an electricity meter operation error calculation model with tree topology as the basic unit is established based on the line topology relationship in the electricity meter model of the distribution area.

[0019] Furthermore, the line temperature calculation model function is constructed based on the line thermal balance state, as specifically expressed below:

[0020] t(θ)=t(θ0)+t′(θ0)(θ-θ0)

[0021] Where θ is the line temperature and θ0 is the initial line temperature.

[0022] Furthermore, the process of obtaining the actual temperature of the circuit through iterative loops specifically involves:

[0023] make but

[0024] Set the maximum number of iterations and the calculation precision. When the calculation error is less than the preset precision, exit the loop and return the actual temperature value of the circuit.

[0025] Furthermore, the offline status feature dataset includes normal operation data of each user-side electricity meter and operation data of each user-side electricity meter under different fault levels.

[0026] According to a second aspect of the present disclosure, a system for evaluating the operational status of distribution area energy meters based on multi-node voltage differences is provided, comprising:

[0027] The model building unit is used to build a power meter model for the distribution area based on the line topology of the user's power meter in the distribution area, and to build a power meter operation error calculation model based on the power meter model for the distribution area.

[0028] The line temperature calculation unit is used to construct a line temperature calculation model function based on the line heat balance equation according to the energy meter operation error calculation model, and obtain the actual line temperature through iterative loop based on the line temperature calculation model function.

[0029] The line resistance calculation unit is used to obtain the line resistance of each level in the transformer area based on the actual temperature of the line; and to construct the voltage equation at the node based on the voltage and current signals output by each user-side energy meter and the obtained line resistance of each level.

[0030] The state feature quantity dataset construction unit is used to establish an offline state feature quantity dataset based on the voltage equation at the node and the voltage and current signals collected by each meter in the transformer area during normal and fault conditions.

[0031] The operating status determination unit is used to acquire the output voltage and current signals of all energy meters in the area during actual operation, construct real-time sampled status feature quantities, compare them with the offline status feature quantity dataset, and realize the determination of the real-time operating status of the energy meters.

[0032] According to a third aspect of the present disclosure, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and running on the memory. When the processor executes the program, it implements the aforementioned method for evaluating the operating status of a transformer substation energy meter based on multi-node voltage difference.

[0033] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the aforementioned method for evaluating the operating status of a transformer substation energy meter based on multi-node voltage difference.

[0034] Compared with the prior art, the beneficial effects of this disclosure are:

[0035] The present disclosure provides a method and system for evaluating the operating status of transformer substation energy meters based on multi-node voltage differences. This method combines precise modeling and data-driven approaches. It constructs a model based on the physical and electrical relationships of the transformer substation, builds a temperature calculation model function based on the heat balance equation, updates conductor temperature in real time, and determines the real-time line resistance based on the current conductor temperature. This ensures the accuracy of line impedance during the analysis process and improves the accuracy of the constructed model. While ensuring model accuracy, it establishes transformer substation node voltage difference equations based on historical operating data of the energy meters and the constructed model, and sets offline voltage difference state characteristic quantity evaluation indicators. Actual operating data is used to generate new actual operating state characteristic quantity evaluation indicators through the constructed model. By comparing the compatibility between the two, the operating status of the energy meters can be accurately determined.

[0036] Advantages of this disclosure in additional aspects will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this disclosure. Attached Figure Description

[0037] The accompanying drawings, which form part of this disclosure, are used to provide a further understanding of this disclosure. The illustrative embodiments of this disclosure and their descriptions are used to explain this disclosure and do not constitute an undue limitation of this disclosure.

[0038] Figure 1 This is a flowchart of the method for evaluating the operating status of a distribution area energy meter based on multi-node voltage difference as described in the embodiments of this disclosure;

[0039] Figure 2 This is a schematic diagram of a transformer substation energy meter model based on a tree topology, as described in an embodiment of this disclosure.

[0040] Figure 3 This is a schematic diagram of the electricity meter operating error calculation model described in the embodiments of this disclosure;

[0041] Figure 4 This is a schematic diagram of a transformer substation energy meter model in a specific application embodiment described in this disclosure.

[0042] Figure 5 This is a schematic diagram of the electricity meter operation error calculation model in a specific application embodiment described in this disclosure. Detailed Implementation

[0043] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0044] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation of this disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains.

[0045] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this disclosure. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0046] Where there is no conflict, the embodiments and features described herein can be combined with each other.

[0047] Example 1:

[0048] The purpose of this embodiment is to provide a method for evaluating the operating status of distribution area energy meters based on multi-node voltage differences.

[0049] A method for evaluating the operational status of distribution area energy meters based on multi-node voltage differences includes:

[0050] A transformer substation energy meter model is constructed based on the line topology of user energy meters within the substation area, and an energy meter operation error calculation model is constructed based on the transformer substation energy meter model.

[0051] Based on the energy meter operation error calculation model, a line temperature calculation model function is constructed according to the line heat balance equation, and the actual line temperature is obtained through iterative loop based on the line temperature calculation model function.

[0052] Based on the actual temperature of the line, the resistance of each level of the line in the distribution area is obtained; and the voltage equation at the node is constructed according to the voltage and current signals output by each user-side energy meter and the obtained resistance of each level of the line.

[0053] Based on the voltage equation at the node, an offline state feature dataset is established according to the voltage and current signals collected by each meter in the transformer area during normal and fault conditions.

[0054] The output voltage and current signals of all electricity meters in the region are acquired during actual operation, real-time sampling status features are constructed, and compared with the offline status feature dataset to determine the real-time operating status of the electricity meters.

[0055] Furthermore, the construction of the offline state feature dataset is specifically as follows:

[0056] Define state characteristic F i,j,j′The difference in the equations for the voltages at the i-th node of the transformer area obtained from the j-th and j′-th branches is expressed as: F i,j,j′ =(V i,j +R i,j I i,j )-(V i,j′ +R i,j′ I i,j′ (i = 1, 2…m, j = 1, 2…n) i j′=1,2…n i ,j′≠j);

[0057] Define the state feature dataset Let the difference matrix of the voltage equations obtained from different branches at the i-th node of the transformer area be represented as:

[0058] By determining the state feature dataset at the i-th node of the transformer area when the meter is at different fault levels, the offline state feature dataset of all nodes in the transformer area can be determined.

[0059] Among them, I i,j I i,j′ (i = 1, 2, ..., m, j = 1, 2, ..., n) i R represents the current from the i-th node to the j,j′-th user-side meter in the second level. i,j R i,j′ (i = 1, 2, ..., m, j = 1, 2, ..., n) i ) is its line resistance, V i,j V i,j′ (i = 1, 2, ..., m, j = 1, 2, ..., n) i ) represents the voltage collected by the j-th and j′-th user-side meters connected to the i-th node of the second level.

[0060] Furthermore, the process of comparing the offline state feature dataset to determine the real-time operating status of the electricity meter specifically involves: constructing a multi-dimensional space based on the offline state feature dataset built by a single node; and determining the operating status of the electricity meter based on the distribution of the real-time sampled state features in the multi-dimensional space.

[0061] Furthermore, the construction of the electricity meter operation error calculation model is specifically as follows: taking all the electricity meters in a distribution area as a cluster, and all lines in the distribution area as purely resistive lines, an electricity meter operation error calculation model with tree topology as the basic unit is established based on the line topology relationship in the electricity meter model of the distribution area.

[0062] Furthermore, the line temperature calculation model function is constructed based on the line thermal balance state, as specifically expressed below:

[0063] t(θ)=t(θ0)+t′(θ0)(θ-θ0)

[0064] Where θ is the line temperature and θ0 is the initial line temperature.

[0065] Furthermore, the process of obtaining the actual temperature of the circuit through iterative loops specifically involves:

[0066] make but

[0067] Set the maximum number of iterations and the calculation precision. When the calculation error is less than the preset precision, exit the loop and return the actual temperature value of the circuit.

[0068] Furthermore, the offline status feature dataset includes normal operation data of each user-side electricity meter and operation data of each user-side electricity meter under different fault levels.

[0069] Specifically, for ease of understanding, the following detailed description of the solution in this embodiment is provided in conjunction with the accompanying drawings:

[0070] like Figure 1 As shown, this embodiment provides a method for evaluating the operating status of a distribution area energy meter based on multi-node voltage difference, including:

[0071] Taking all the electricity meters in a transformer area as a cluster, an electricity meter operation error calculation model with tree topology as the basic unit is established. All lines in the transformer area are regarded as pure resistive lines. The transformer area's main meter is the power supply meter, and its accuracy level is higher than that of the user-side electricity meter.

[0072] The output voltage and current signals of all electricity meters in the area are collected during actual operation. The output voltage and current signals are the normal operation data of each user-side electricity meter.

[0073] Based on the established transformer substation model, the conductor temperature is determined by establishing a line temperature calculation model function, thereby determining the conductor resistivity. After measuring the line length, the line resistance equation is established.

[0074] Based on the node count information of all tree topologies in this distribution area, voltage equations at the nodes are established according to the voltage and current signals output by the electricity meters on each user side and the line parameters.

[0075] Define a state feature quantity F, which is a dataset of voltage differences at all nodes in the transformer area; based on the voltage and current signals collected when each meter is normal and faulty, establish an offline state feature quantity F dataset, which includes normal operation data of each user-side meter and operation data of each user-side meter under different fault levels.

[0076] Collect the output voltage and current signals of all electricity meters in the area during actual operation to construct real-time sampling status characteristic quantities. The real-time operating status of the electricity meter is determined based on the set offline state feature quantity F dataset.

[0077] Furthermore, the process of establishing a calculation model for the operating error of an energy meter based on a tree topology includes:

[0078] Step 101: Taking all the electricity meters in a transformer substation as a cluster, establish a transformer substation electricity meter model with a tree topology as the basic unit, as follows: Figure 2 As shown.

[0079] Step 102: Determine the number of branches and node information in the transformer substation model. Based on the aforementioned transformer substation energy meter model diagram, establish an energy meter operation error calculation model as follows: Figure 3 As shown, according to the model, the tree topology has m branches at the first level and n branches at each of the second levels. i (i = 1, 2, ..., m) branches.

[0080] Furthermore, establishing the line resistance equation includes:

[0081] Step 201: Establish the heat balance equation for the circuit.

[0082] The thermal balance state of a power line is achieved by the balance between the heat gained and lost by the surrounding environment and the electrical load. The thermal balance equation is:

[0083] q j +q s =q c +q r

[0084] In the formula, q j For the Joule thermal gain of the circuit, q s For the solar thermal gain of the line, q c For heat dissipation through convection in the circuit, q r To dissipate heat from the circuit.

[0085] Step 202: Establish the line temperature calculation model function.

[0086] t(θ)=q j +q s -q c -q r

[0087] t(θ)=t(θ0)+t′(θ0)(θ-θ0)

[0088] In the formula, θ is the line temperature and θ0 is the initial line temperature.

[0089] Step 203: The actual temperature of the line is determined by an iterative loop method.

[0090] make but

[0091] Set the maximum number of iterations and the calculation precision. When the calculation error is less than the preset precision, exit the loop and return the actual temperature value of the circuit.

[0092] Step 204: Calculate the line resistance of the transformer area.

[0093] Given that the resistance of the metal wire is

[0094]

[0095] In the formula, ρ is the resistivity of the conductor, S is the nominal cross-sectional area of ​​the current-carrying part of the conductor, and l is the length of the line.

[0096] Resistivity ρ is related to factors such as material and temperature. Within a range where temperature changes are not significant, ρ = ρ0(1 + at), where t is the temperature in Celsius, ρ0 is the resistivity at 0℃, and a is the temperature coefficient of resistivity.

[0097] Furthermore, the process of establishing the node voltage equations includes:

[0098] Step 301: Based on the energy meter operating error calculation model, the voltage equation at the second-level node can be established, which is...

[0099] V i =V i,j +R i,j I i,j (i = 1, 2, ..., m, j = 1, 2, ..., n) i )

[0100] In the formula, I i,j (i = 1, 2, ..., m, j = 1, 2, ..., n) i R represents the current from the i-th node of the second-level node to each user-side meter. i,j (i = 1, 2, ..., m, j = 1, 2, ..., n) i ) is its line resistance, V i (i = 1, 2, ..., m) represents the voltage at the i-th node of the second stage, V. i,j (i = 1, 2, ..., m, j = 1, 2, ..., n) i ) represents the voltage collected by the user-side meter connected to the i-th node of the second level.

[0101] Furthermore, the process of setting the state characteristic quantity F includes:

[0102] Step 401, determine the state characteristic quantity F i,j,j′ .

[0103] Step 402: Determine the state feature dataset at the i-th node of the transformer area.

[0104] Step 403: Determine the dataset F of state feature quantities at the i-th node of the transformer area when the meter is at different fault levels. i The offline status feature data F of all nodes in the transformer area is determined.

[0105] Step 401 includes:

[0106] Define state characteristic F i,j,j′ The difference in equations for the voltages at the i-th node of the transformer area obtained from the j-th and j′-th branches is, in other words, the difference between these equations.

[0107] F i,j,j ′=(V i,j + i,j I i,j )-(V i,j ′+ i,j ′I i,j (i = 1, 2…m, j = 1, 2…n) i j′=1,2…n i ,j′≠j)

[0108] In the formula, I i,j I i,j′ (i = 1, 2, ..., m, j = 1, 2, ..., n) i R represents the current from the i-th node to the j,j′-th user-side meter in the second level. i,j R i,j′ (i = 1, 2, ..., m, j = 1, 2, ..., n) i ) is its line resistance, V i,j V i,j′ (i = 1, 2, ..., m, j = 1, 2, ..., n) i ) represents the voltage collected by the j-th and j′-th user-side meters connected to the i-th node of the second level.

[0109] Step 402 includes:

[0110] Define the state feature dataset Let be the difference matrix of the equations for the voltages obtained from different branches at the i-th node of the transformer area, which is [equation missing].

[0111]

[0112] Specifically, for the same node, the node voltage obtained by tracing back from the user-side meter along the tree branches to the node should be equal. However, the user-side meter may have some error, and the state characteristic quantity... It is actually a constant matrix.

[0113] Step 403 includes:

[0114] Step 40301: Determine the voltage range during normal operation of the electricity meter. Let W be the voltage range of the first user-side electricity meter connected to the i-th node. i,1 The voltage is V during normal operation i,1 The maximum voltage deviation of the meter during normal operation within its error range is The voltage of each user's meter is then...

[0115] Step 40302: Determine the dataset F of all state feature quantities of the i-th node under different faults of the meter. i Assuming the maximum voltage deviation due to a meter malfunction is e, different voltage deviation values ​​are determined based on the severity of the meter malfunction. Establish a fault voltage level dataset V i,1 +e1, V i,1 +e2,…,V i,1 +e n Assuming other meters are operating normally, based on meter W i,1 From the fault voltage level dataset, the dataset F of all state feature quantities of the i-th node can be obtained according to the method described. i .

[0116] Step 40303: Following the method described in step 40302, a dataset F of all state feature quantities can be established when all meters in the transformer area experience individual failures. i That is, a dataset of offline state features F for all nodes in the transformer area was established and saved to memory.

[0117] Furthermore, the construction of real-time sampling state feature quantities The process includes:

[0118] Step 501: During actual operation, the output voltage and current signals of all electricity meters in the area are collected, and the real-time sampling status characteristic quantity F of each node in the distribution area is constructed according to the method described above. i The dataset is generated based on the sampling time (t0, t1). Data matrix

[0119] Where m is the number of sampling points.

[0120] Step 502: The real-time sampling status feature quantities of all nodes in the transformer area can be established according to the method described in step 501.

[0121] Furthermore, the process of determining the real-time operating status of the electricity meter includes:

[0122] Step 601, based on the offline state feature dataset F established by a single node iBuild 3D space.

[0123] Step 602, based on real-time sampling state feature quantities The distribution of the meter in space determines its operating status.

[0124] The process of step 601 includes:

[0125] Based on the voltage and current signals obtained from the information of the i-th node in the transformer area, the desired F is calculated. i,j,j′ If considered as a point in space, then the state feature dataset established by the method... That is A point in 3D space. When all meters in the distribution area fail individually, the offline state characteristic dataset F is established based on the deviation e determined by the degree of voltage failure of the meters connected to the second-level branch. i for Several in dimensional space Vitality.

[0126] The process of step 602 includes:

[0127] Based on the real-time sampling state feature quantity obtained in step 402 The dataset contains real-time sampled state features of all transformer nodes. The set. The real-time sampling state feature quantity For m data points within the time interval (t0, t1) A point in 3D space, based on the point's position in... The distribution in 3D space can be used to determine the operating status of the meters, and based on the sampling time corresponding to that point, it can be determined whether the user-side meter connected to the i-th node in the distribution area has malfunctioned, and a determination signal is sent to the main controller. The operating status of user-side meters connected to all nodes in the distribution area can be determined using this method.

[0128] Furthermore, the following combination Figure 4 and Figure 5 Specific examples will be used to illustrate the solution described in this embodiment:

[0129] like Figure 4 The diagram shown is a model of a power meter distribution area based on a tree topology, provided by the present invention. Based on the node information in the model, an offline state feature dataset F and a real-time state feature dataset F are constructed to determine the real-time operating status of each power meter on the user side.

[0130] Step 101: Taking all the electricity meters in a distribution area as a cluster, establish an electricity meter operation error calculation model with a tree topology as the basic unit, as follows: Figure 5As shown in the figure. According to the model, the first level of the tree topology has 3 branches, and the second level has 2, 3, and 2 branches respectively.

[0131] Step 201: After determining the line materials, establish the line heat balance equation based on factors such as line load, ambient temperature, solar radiation intensity, and ambient wind speed. The heat balance equation is as follows:

[0132] q j +q s =q c +q r

[0133] In the formula, q j For the Joule thermal gain of the circuit, q s For the solar thermal gain of the line, q c For heat dissipation through convection in the circuit, q r To dissipate heat from the circuit.

[0134] Step 202: Establish the line temperature calculation model function.

[0135] t(θ)=q j +q d -q c -q r

[0136] t(θ)=t(θ0)+t′(θ0)(θ-θ0)

[0137] In the formula, θ is the line temperature and θ0 is the initial line temperature.

[0138] Step 203: The actual temperature of the line is determined by an iterative loop method.

[0139] make but

[0140] Set the maximum number of iterations N=10 and the calculation accuracy ε=1e-8. When the calculation error is less than the preset accuracy, the loop will exit and the actual temperature value of the circuit will be returned.

[0141] Step 204: Calculate the line resistance of the transformer area.

[0142] Given that the resistance of the metal wire is

[0143]

[0144] In the formula, ρ is the resistivity of the conductor, S is the nominal cross-sectional area of ​​the current-carrying part of the conductor, and l is the length of the line.

[0145] Resistivity ρ is related to factors such as material and temperature. Within a range where temperature changes are not significant, ρ = ρ0(1 + at), where t is the temperature in Celsius, ρ0 is the resistivity at 0℃, and a is the temperature coefficient of resistivity.

[0146] The obtained resistance parameters are shown in Table 1. Based on the above parameters, a calculation model for the operating error of the electricity meter is established according to the model diagram of the electricity meter in the described area. Figure 5 As shown.

[0147] Table 1 shows the resistance parameters obtained.

[0148]

[0149] Step 301: Based on the energy meter operating error calculation model, the voltage equations at the second-level nodes can be established, respectively.

[0150] V1 = V 1,1 +R 1.1 I 1.1 =V 1,2 +R 1.2 I 1.2

[0151] V2 = V 2,1 +R 2.1 I 1.1 =V 2,2 +R 2.2 I 2.2 =V 2,3 +R 2.3 I 2.3

[0152] V3 = V 3,1 +R 3.1 I 3.1 =V 3.2 +R 3.2 I 3.2

[0153] Step 401, determine the state characteristic quantity F i,j,j′ According to the state characteristic quantity F i,j,j′ Defined, can be obtained

[0154] Table 2 State characteristics of different nodes

[0155]

[0156] Step 402: Determine the state characteristic quantities of each node. Based on the information of all tree-structured topology nodes in the distribution area, the state characteristic quantities of each node are obtained when each user's meter is operating normally. Based on the state feature quantity dataset By definition, we can obtain

[0157]

[0158]

[0159]

[0160] Step 403: Establish the offline status feature dataset F for all nodes in the transformer area.

[0161] Specifically, step 403 includes:

[0162] Step 40301: Given that the accuracy class of the user-side electricity meter is 2.0 and its maximum allowable deviation is ±2%, assuming that the meter current calibration is completely correct, the voltage of the meter during normal operation is (220(1-2%), 220(1-2%)).

[0163] Step 40302: Assuming that electricity meter 1 is faulty while other meters are operating normally, and the maximum voltage deviation of the faulty meter is ±5%, different voltage deviation levels are determined according to the degree of meter fault: A (-5% to -4%), B (-4% to -3%), C (-3% to -2%), D (2% to 3%), E (3% to 4%), and F (4% to 5%), thus establishing a fault voltage level dataset. Based on the fault voltage level dataset of electricity meter 1, a state feature dataset F1 can be established for the first node when the fault degree of electricity meter 1 is different. Similarly, state feature datasets F2 and F3 for the second and third nodes can be obtained, that is, an offline state feature dataset F for all nodes in the transformer area when electricity meter 1 fails is created.

[0164] Step 40303 allows the creation of an offline state feature dataset F for all nodes when all individual meters in the transformer area experience a fault.

[0165] Step 501: During actual operation, the output voltage and current signals of all electricity meters in the area are collected, and the real-time sampling status characteristic quantity F of each node in the distribution area is constructed according to the method described above. i The dataset is generated based on the sampling time (t0, t1). Dataset,

[0166] Where m is the number of sampling points, and here m = 100.

[0167] Step 502: The real-time sampling status feature quantities of the second and third nodes of the transformer area can be established according to the method described in step 401. Dataset,

[0168] Where m is the number of sampling points, and here m = 100.

[0169] Step 601: Construct one-dimensional, three-dimensional, and one-dimensional spaces based on the offline state feature datasets F1, F2, and F3 established by a single node.

[0170] Specifically, step 601 includes the following processes:

[0171] Based on the voltage and current signals obtained from the information of the first node in the transformer area, the desired F is calculated. 1,1,2 If considered as a point in space, then the state feature dataset established by the method... That is, a line segment in one-dimensional space. Similarly, That is, a cube in three-dimensional space. That is, a line segment in one-dimensional space.

[0172] Step 602, based on real-time sampling state feature quantities The distribution of the meter in space determines its operating status.

[0173] Specifically, step 602 includes the following processes:

[0174] After acquiring the voltage and current signals from each user side in real time, the real-time sampling state characteristic quantities are obtained according to the method described above. The dataset contains real-time sampled state features of all transformer nodes. The set of real-time sampling state features Given 100 points in a one-dimensional space within a time interval (0, 6000s), the operating status of the electricity meter can be determined based on the distribution of these points in the one-dimensional space. If a point is located within the normal operating state characteristic dataset... If the point is within the line segment, it indicates that the meter is operating normally at that moment; if the point is located within the fault operation state feature data set... If the point is within the line segment, it indicates that the meter is malfunctioning at that moment, and the fault severity is determined based on the location of that point within the segment. The fault level can be determined by the line segment, and a judgment signal is sent to the main controller. The operating status of all user-side meters connected to all nodes in the distribution area can be determined using the described method.

[0175] Example 2:

[0176] The purpose of this embodiment is to provide a system for evaluating the operating status of distribution area energy meters based on multi-node voltage differences.

[0177] A system for evaluating the operational status of distribution transformer energy meters based on multi-node voltage differences, comprising:

[0178] The model building unit is used to build a power meter model for the distribution area based on the line topology of the user's power meter in the distribution area, and to build a power meter operation error calculation model based on the power meter model for the distribution area.

[0179] The line temperature calculation unit is used to construct a line temperature calculation model function based on the line heat balance equation according to the energy meter operation error calculation model, and obtain the actual line temperature through iterative loop based on the line temperature calculation model function.

[0180] The line resistance calculation unit is used to obtain the line resistance of each level in the transformer area based on the actual temperature of the line; and to construct the voltage equation at the node based on the voltage and current signals output by each user-side energy meter and the obtained line resistance of each level.

[0181] The state feature quantity dataset construction unit is used to establish an offline state feature quantity dataset based on the voltage equation at the node and the voltage and current signals collected by each meter in the transformer area during normal and fault conditions.

[0182] The operating status determination unit is used to acquire the output voltage and current signals of all energy meters in the area during actual operation, construct real-time sampled status feature quantities, compare them with the offline status feature quantity dataset, and realize the determination of the real-time operating status of the energy meters.

[0183] Furthermore, the system described in this embodiment corresponds to the method described in Embodiment 1, and its technical details have been described in detail in Embodiment 1, so they will not be repeated here.

[0184] In further embodiments, the following is also provided:

[0185] An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor. When executed by the processor, the computer instructions perform the method described in Embodiment 1. For brevity, further details are omitted here.

[0186] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0187] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0188] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in Embodiment 1.

[0189] The method in Embodiment 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0190] Those skilled in the art will recognize that the units, i.e., algorithm steps, of the various examples described in connection with this embodiment can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0191] The above embodiments provide a method and system for evaluating the operating status of distribution area energy meters based on multi-node voltage differences, which is feasible and has broad application prospects.

[0192] The above description is merely a preferred embodiment of this disclosure and is not intended to limit this disclosure. Various modifications and variations can be made to this disclosure by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for evaluating the operating status of distribution area energy meters based on multi-node voltage difference, characterized in that, include: A transformer substation energy meter model is constructed based on the line topology of user energy meters within the substation area, and an energy meter operation error calculation model is constructed based on the transformer substation energy meter model. Specifically, the construction of the electricity meter operation error calculation model is as follows: taking all the electricity meters in a distribution area as a cluster, and all the lines in the distribution area as purely resistive lines, an electricity meter operation error calculation model with tree topology as the basic unit is established based on the line topology relationship in the electricity meter model of the distribution area. Based on the energy meter operation error calculation model, a line temperature calculation model function is constructed according to the line heat balance equation, and the actual line temperature is obtained through iterative loop based on the line temperature calculation model function. Based on the actual temperature of the line, the resistance of each level of the line in the distribution area is obtained; and the voltage equation at the node is constructed according to the voltage and current signals output by each user-side energy meter and the obtained resistance of each level of the line. Based on the voltage equation at the node, an offline state feature dataset is established according to the voltage and current signals collected by each meter in the transformer area during normal and fault conditions. The construction of the offline state feature dataset specifically involves: Define state features For the i-th node in the distribution area, the first... j , The difference in the equations for the voltages obtained from each branch is expressed as: i=1,2…m,j=1,2… , =1,2… , ; Define the state feature dataset Let the difference matrix of the voltage equations obtained from different branches at the i-th node of the transformer area be represented as: ; By determining the state feature dataset at the i-th node of the transformer area when the meter is at different fault levels, the offline state feature dataset of all nodes in the transformer area can be determined. in, , For the second level, the i-th node to the i-th node j , Current of each user-side electricity meter , Its line resistance, , The second level i-th node connected to the first j , The voltage collected by each user-side electricity meter; The output voltage and current signals of all electricity meters in the region are acquired during actual operation, and real-time sampling state feature quantities are constructed. By comparing these with the offline state feature quantity dataset, the real-time operating status of the electricity meters is determined. A multi-dimensional space is constructed based on the offline state feature quantity dataset constructed by a single node. The operating status of the electricity meters is determined based on the distribution of the real-time sampling state feature quantities in the multi-dimensional space.

2. The method for evaluating the operating status of a distribution area energy meter based on multi-node voltage difference as described in claim 1, characterized in that, The line temperature calculation model function is constructed based on the line thermal balance state, and is specifically expressed as follows: ； in, For line temperature, This represents the initial temperature of the circuit.

3. The method for evaluating the operating status of a distribution area energy meter based on multi-node voltage difference as described in claim 1, characterized in that, The method of obtaining the actual temperature of the line through iterative loops is as follows: make ,but ; Set the maximum number of iterations and the calculation precision. When the calculation error is less than the preset precision, exit the loop and return the actual temperature value of the circuit.

4. The method for evaluating the operating status of a distribution area energy meter based on multi-node voltage difference as described in claim 1, characterized in that, The offline status feature dataset includes normal operation data of each user-side electricity meter and operation data of each user-side electricity meter under different fault levels.

5. A system for evaluating the operating status of distribution area energy meters based on multi-node voltage difference, employing the method for evaluating the operating status of distribution area energy meters based on multi-node voltage difference as described in claim 1, characterized in that, include: The model building unit is used to build a power meter model for the distribution area based on the line topology of the user's power meter in the distribution area, and to build a power meter operation error calculation model based on the power meter model for the distribution area. The line temperature calculation unit is used to construct a line temperature calculation model function based on the line heat balance equation according to the energy meter operation error calculation model, and obtain the actual line temperature through iterative loop based on the line temperature calculation model function. A line resistance calculation unit is used to obtain the resistance of each level of the line within the transformer area based on the actual temperature of the line. The voltage equations at the nodes are constructed based on the voltage and current signals output by the energy meters on each user side and the obtained line resistances at each level. The state feature quantity dataset construction unit is used to establish an offline state feature quantity dataset based on the voltage equation at the node and the voltage and current signals collected by each meter in the transformer area during normal and fault conditions. The operating status determination unit is used to acquire the output voltage and current signals of all energy meters in the area during actual operation, construct real-time sampled status feature quantities, compare them with the offline status feature quantity dataset, and realize the determination of the real-time operating status of the energy meters.

6. The system for evaluating the operating status of distribution area energy meters based on multi-node voltage difference as described in claim 5, characterized in that, The line temperature calculation model function is constructed based on the line thermal balance state, and is specifically expressed as follows: ； in, For line temperature, This represents the initial temperature of the circuit.

7. The system for evaluating the operating status of distribution area energy meters based on multi-node voltage difference as described in claim 5, characterized in that, The method of obtaining the actual temperature of the line through iterative loops is as follows: make ,but ; Set the maximum number of iterations and the calculation precision. When the calculation error is less than the preset precision, exit the loop and return the actual temperature value of the circuit.

8. The system for evaluating the operating status of distribution area energy meters based on multi-node voltage difference as described in claim 5, characterized in that, The offline status feature dataset includes normal operation data of each user-side electricity meter and operation data of each user-side electricity meter under different fault levels.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and running thereon, wherein the processor executes the program to implement a method for evaluating the operating status of a transformer substation energy meter based on multi-node voltage difference as described in any one of claims 1-4.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for evaluating the operating status of a transformer substation energy meter based on multi-node voltage difference as described in any one of claims 1-4.

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