A low-voltage line anomaly diagnosis method based on impedance interpretability

Abstract

The application discloses a low-voltage line abnormality diagnosis method based on impedance interpretability, estimates upstream line resistance and reactance characteristic values based on operation measurement data, generates a possible power supply transformer and a power supply path set, establishes a path impedance parameter model and a path length deviation model, and generates resistance and reactance normal interpretability ranges of a target electric meter under each possible power supply path. The resistance and reactance characteristic values of the target electric meter are matched with the corresponding normal interpretability ranges, the line is judged to be normal or abnormal, and the abnormal relationship is further classified. The method can exclude the normal influence of long-distance power supply on the resistance and reactance characteristic values through impedance interpretability matching of the possible power supply path, reduce long-line misjudgment, and improve the accuracy and reliability of low-voltage line abnormality diagnosis.

Description

Technical Field

[0001] This invention relates to the field of power technology, and in particular to a method for diagnosing low-voltage line anomalies based on impedance interpretability. Background Technology

[0002] In low-voltage power distribution lines, the line impedance will cause a corresponding voltage drop with the load current. When the power factor is close to 1 and the voltage and current are essentially in phase, the change in the effective value of the line voltage can be approximated as being mainly caused by the voltage drop due to the line resistance. In this case, the formula can be used based on the changes in the effective values ​​of the voltage and current measured by the meters. Characterizing the effect of resistance in the power supply path, when When the reading exceeds the preset range, it may indicate that the power supply path has issues such as excessively long lines, loose connections, oxidation, or aging, leading to increased resistance. It could also be due to bypass current theft, causing the meter reading to be less than the actual current change, thus increasing the line impedance. It appears to be on the larger side.

[0003] Patent document CN109374995B, entitled "Low-voltage power distribution system, line aging and anti-electricity theft monitoring method and corresponding system," discloses a low-voltage power distribution system, a line aging and anti-electricity theft monitoring method and corresponding system. This method calculates the impedance value of the user's power distribution line corresponding to the smart meter based on the voltage and current values ​​of the smart meter, and compares it with a set impedance threshold. If the calculated impedance value is greater than or equal to the set impedance threshold, the user's power distribution line corresponding to the smart meter is determined to be aging. Therefore, this method can monitor line aging online, identify the degree of line aging in a timely manner, thereby improving the proactive operation and maintenance level of low-voltage power distribution and improving the reliability of user power supply. Furthermore, if a sudden and continuous increase in the impedance value of the user's power distribution line is detected, it indicates that the meter in the user's power distribution line may be short-circuited, which can determine that the user is suspected of electricity theft. Therefore, this monitoring method can also be used for anti-electricity theft monitoring to protect the safety of electrical property. The core technical solution of this document is: using the change in voltage and current (ΔV / ΔI) at adjacent moments to approximately reflect the impedance of the user's power distribution line. When the impedance value exceeds a set threshold, it is determined that the line may have issues such as loose connections, oxidation, or aging leading to increased resistance. If the impedance value continuously increases within a set time period, it is determined that the user's power distribution line may have bypass shunting or meter short-circuiting, suggesting electricity theft. Multiple impedance measurements are averaged by reversing the negative values ​​to reduce the impact of measurement errors and voltage fluctuations on the judgment. This method can be executed periodically to achieve online monitoring of aging low-voltage user power distribution lines and electricity theft.

[0004] In low-voltage distribution networks, smart meters can estimate the equivalent impedance of upstream lines based on voltage and current changes, and can be used to identify potential problems such as poor contact and high-resistance overheating. However, existing methods have the following issues:

[0005] 1) Impedance mixing problem: The voltage drop in low-voltage lines is not only caused by line resistance, but also affected by changes in line reactance and load power factor. When the power factor is not 1, relying solely on changes in the effective values ​​of voltage and current to judge resistance anomalies can easily lead to the mixing of reactance voltage drop effects, making it difficult to accurately identify poor contact or high resistance hazards;

[0006] 2) Threshold adaptability problem: Traditional fixed impedance thresholds are difficult to adapt to different power supply paths. Long-line users are prone to misjudging abnormalities, while local high impedance of short-line users may be missed.

[0007] 3) Interference factors: Abnormalities such as bypass shunting and electricity theft can also cause an increase in reverse impedance, which can be easily confused with long lines or poor contact, affecting the accuracy of judgment.

[0008] Therefore, there is an urgent need for a low-voltage line anomaly diagnosis method that can establish a normal interpretable range of resistance and reactance by combining candidate power supply paths, under the condition that ordinary smart meters only have non-phasor data such as voltage RMS value, current RMS value and power factor, and distinguish abnormal types such as normal long lines, poor contact due to line aging and bypass shunting based on the matching relationship between the resistance and reactance estimated by the target meter and this range. Summary of the Invention

[0009] The technical problem to be solved by this application is to provide a low-voltage line anomaly diagnosis method that can establish a normal interpretable range of resistance and reactance by combining candidate power supply paths under the condition that ordinary smart meters only have non-phasor data such as voltage RMS value, current RMS value and power factor, and distinguish abnormal types such as normal long lines, poor contact due to line aging and bypass shunting based on the matching relationship between the resistance and reactance estimated by the target meter and the range.

[0010] This application discloses a low-voltage line anomaly diagnosis method based on impedance interpretability, including the following steps:

[0011] S10, the meter estimates the characteristic values ​​of the resistance and reactance of the upstream line based on the operational measurement data and uploads it to the main station. The operational measurement data includes the effective value of voltage, the effective value of current, and the power factor.

[0012] S20, the main station generates a set of possible power supply transformers for each target meter, and generates possible power supply paths for each possible power supply transformer, forming a set of possible power supply paths for the target meter.

[0013] S30, the main station establishes a path impedance parameter model based on the upstream line resistance characteristic value, reactance characteristic value and corresponding possible power supply path length of multiple meters. The path impedance parameter model is used to characterize the correspondence between the possible power supply path length and the resistance and reactance. The path impedance parameter model includes unit length resistance parameter, unit length reactance parameter and bias parameter.

[0014] S40, the main station establishes a path length deviation model based on the path type and path length of each possible power supply path, and determines the upper and lower bounds of the length of each possible power supply path based on the path length deviation model; substitutes the upper and lower bounds of the length into the path impedance parameter model to generate the normal interpretable range of resistance and normal interpretable range of reactance of the target meter under each possible power supply path.

[0015] S50, the main station matches the upstream line resistance characteristic value and reactance characteristic value uploaded by the target meter with the normal interpretable range of resistance and normal interpretable range of reactance corresponding to each possible power supply path in its set of possible power supply paths, and determines whether the resistance characteristic value and the reactance characteristic value can be explained by at least one possible power supply path.

[0016] S60, if the resistance characteristic value and the reactance characteristic value can be explained by at least one possible power supply path, then the line is determined to be normal and the line diagnosis ends; otherwise, proceed to step S70.

[0017] S70, if the resistance characteristic value exceeds the corresponding normal interpretable range while the reactance characteristic value does not exceed the range, it is determined to be an abnormal aging of the line or an abnormal poor contact of the line; if both the resistance characteristic value and the reactance characteristic value exceed the corresponding normal interpretable range, it is determined to be a suspected bypass shunting or a suspected under-metering.

[0018] According to some embodiments, step S10, where the meter estimates the characteristic values ​​of the upstream line resistance and reactance based on operational measurement data, includes the following steps:

[0019] S101, the meter terminal obtains the effective value of voltage, effective value of current and power factor according to the set sampling period;

[0020] S102, the meter extracts multiple load current change events within a set time window, and calculates the change in active current for each load current change event. Changes in reactive current and the change in the effective value of voltage ;

[0021] S103, perform identifiable screening on the load current change events;

[0022] S104, for each load current change event that passes the identifiability screening, according to the formula... The characteristic values ​​of the resistance and reactance of the upstream line are obtained, where This is the characteristic resistance value of the upstream line. The characteristic value of the reactance of the upstream line, This is due to unavoidable measurement errors or external interference.

[0023] S105, Based on all load current change events that pass the identifiability screening within the preset time window, a data point set is formed. The resistance characteristic value and the reactance characteristic value are obtained by fitting; the identifiability screening includes the following steps:

[0024] S10301, Perform active current threshold screening on the samples, active current change amount Not lower than the set threshold Load events are filtered;

[0025] S10302, Calculate the reactive power ratio and divide the interval. For load current change events that pass the threshold screening, calculate the reactive power ratio. It is divided into low reactive power ratio range, medium reactive power ratio range and high reactive power ratio range.

[0026] S10303, if the load current change event samples cover at least two different reactive power ratio intervals, and the number of valid events in each interval is... If the load current change event passes the screening, then Nmin is a preset quantity threshold.

[0027] According to some embodiments, the fitting method described in step S105 includes least squares fitting, robust regression fitting, or quantile fitting.

[0028] According to some embodiments, the low reactive power ratio range in step S10302 is: The range of reactive power ratio is as follows: The high reactive power ratio range is .

[0029] According to some embodiments, the step S20, in which the master station generates a set of possible power supply transformers for each target meter and generates possible power supply paths for each possible power supply transformer to form a set of possible power supply paths for the target meter, includes:

[0030] The main site is targeting the first Target electricity meter The possible set of power supply transformers generated is , Let N be an integer within the interval [1, N1], where N1 is the total number of target meters. Includes one or more potential power supply transformers, wherein each potential power supply transformer is denoted as . ; The first globally numbered system One power supply transformer, The integer is within the interval [1, N2], where N2 is the total number of power supply transformers;

[0031] for Each of the possible power supply transformers in The main site generates from To the target meter Identify one or more possible power supply paths and record the corresponding path lengths to form the target electricity meter. Set of possible power supply paths , ,in For transformer To the target meter The The length of the possible power supply path, This refers to the method or type of path generation. For transformer To the target meter The number of possible power supply paths; the length of the power supply path Determined based on Euclidean distance or distance along the street path.

[0032] According to some embodiments, the path impedance parameter model in step S30 includes a single unit length parameter model, a piecewise unit length parameter model, or a fitting model with physical constraints, and the fitting method of the path impedance parameter model includes least squares fitting, weighted fitting, or robust regression fitting.

[0033] According to some embodiments, the segmented unit length parameter model includes:

[0034] For transformers To the target meter The Possible power supply path The main station divides the path length into three segment length components: near end, middle segment, and far end. The near end segment length component is... The segment length component of the middle section is The length component of the far segment is , The first distance threshold, The second distance threshold, ;

[0035] The main station establishes a system for each transformer based on the segment length. The path impedance parameter model is as follows: , , The characteristic value of the upstream line resistance. The characteristic value of the reactance of the upstream line. , , Transformers The unit length resistance parameters corresponding to the near-end segment length, middle segment length, and far-end segment length. , , Transformers The reactance per unit length corresponding to the lower proximal segment length, middle segment length, and distal segment length; , For transformer The bias parameters include the impedance contribution of the transformer, service segment, or other approximately fixed factors.

[0036] According to some embodiments, the distance threshold and the second distance threshold It is determined based on the design parameters of the low-voltage line and the type of power supply area.

[0037] According to some embodiments, in the path impedance parameter model, the transformer The relationship between the unit length resistance parameters corresponding to the near-end segment length, middle segment length, and far-end segment length is as follows: .

[0038] According to some embodiments, the path length deviation model in step S40 is as follows: ,in and The proportional deviation coefficient and fixed deviation amount are respectively set according to the path type. Different proportional deviation coefficients and fixed deviation amounts are set for Euclidean distance and road-along path distance.

[0039] The step of determining the upper and lower bounds of the length of each possible power supply path in step S40 includes:

[0040] Based on total path length and path length deviation Determine the upper and lower bounds of the path length. and : , .

[0041] The technical solution disclosed in this application first estimates the resistance and reactance characteristic values ​​of the upstream line based on operational measurement data at the meter end and uploads them to the main station. The main station generates a set of possible power supply transformers and power supply paths for each target meter. Based on the resistance and reactance characteristic values ​​of multiple meters and the length of possible power supply paths, it establishes a path impedance parameter model and further establishes a path length deviation model to generate the normal interpretable range of resistance and reactance of the target meter under each possible power supply path. The main station matches the resistance and reactance characteristic values ​​of the target meter with the corresponding normal interpretable range to determine whether there is at least one possible power supply path that can explain the resistance and reactance characteristic values ​​of the meter. If it can be explained normally, it is determined to be a normal power supply state; if it cannot be explained, it is classified according to the abnormal relationship between resistance and reactance relative to the normal interpretable range, and outputs diagnostic results such as line aging, poor contact, or suspected bypass shunting. The technical solution disclosed in this application, through impedance interpretability matching of possible power supply paths, can eliminate the normal influence of long-distance power supply on resistance and reactance characteristic values, reduce misjudgments of long lines, and improve the accuracy and reliability of low-voltage line anomaly diagnosis. Specific beneficial effects are explained below:

[0042] (1) Reduce misjudgment of long-distance lines and improve the adaptability and accuracy of impedance judgment.

[0043] Traditional impedance-based upstream line anomaly identification methods typically use fixed impedance thresholds for judgment. However, the power supply distance from low-voltage users to transformers varies significantly. Long-distance users often have higher normal line impedances, making them prone to misjudgment as poor contact or high-resistance anomalies. Conversely, even if short-distance users have localized poor contact, they may be missed because the impedance does not exceed a large fixed threshold. This application's technical solution, based on a model of possible power supply path lengths and path impedance parameters, generates normally interpretable ranges for resistance and reactance under the corresponding power supply path for the target meter. This allows the judgment threshold to change with the power supply path, thus eliminating the influence of normal impedance increases caused by long-distance power supply. Furthermore, line impedance includes both resistive and reactant components. When the load power factor is not 1, the influence of reactance on voltage changes cannot be ignored. Traditional methods relying solely on a single impedance or resistance threshold are easily affected by power factor variations. This application's technical solution generates characteristic values ​​for upstream line resistance and reactance based on meter operation measurement data, and establishes normally interpretable ranges for resistance and reactance at the main station side. This eliminates reliance on a single impedance indicator for anomaly judgment, improving adaptability to different load power factor scenarios.

[0044] (2) It can distinguish between different abnormal types such as poor contact and bypass shunting.

[0045] Traditional methods of judging based solely on impedance rise can easily confuse issues such as line aging, poor contact, long power supply lines, and bypass shunting. This application's technical solution utilizes both resistance and reactance characteristic values ​​for interpretative matching, and classifies cases where interpretation is incomplete based on the relationship between these two values ​​and their exceeding of the normal interpretable upper limit. When the main manifestation is abnormal resistance characteristic values ​​while reactance is not significantly abnormal, line aging, loose terminals, poor contact, or localized high resistance risks can be identified. When both resistance and reactance characteristic values ​​are abnormal, bypass shunting, under-metering, or abnormal current sampling can be identified, thereby improving the specificity of anomaly type judgment. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 A flowchart illustrating a low-voltage line anomaly diagnosis based on impedance interpretability is shown according to an example embodiment. Detailed Implementation

[0048] The embodiments of this application will now be described in detail with reference to the accompanying drawings. It should be understood that the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0049] Those skilled in the art should understand that the following specific embodiments or implementation methods are a series of optimized configurations listed in this application to further explain the specific application content. These configuration methods can be combined or used in conjunction with each other, unless this application explicitly states that some or a specific embodiment or implementation method cannot be associated with or used in conjunction with other embodiments or implementation methods. Furthermore, the following specific embodiments or implementation methods are only considered as optimized configurations and are not intended to limit the scope of protection of this application.

[0050] Example 1

[0051] Figure 1 A flowchart illustrating a low-voltage line anomaly diagnosis based on impedance interpretability, according to an example embodiment, is shown. Figure 1 As shown, a low-voltage line anomaly diagnosis method based on impedance interpretability includes the following steps.

[0052] In step S100, the meter acquires operational measurement data such as the effective value of voltage, the effective value of current, and the power factor according to a set sampling period, and extracts multiple load current change events within a set time window. For each load current change event, the change in active current is calculated. Changes in reactive current and the change in the effective value of voltage The system estimates the upstream resistance and reactance characteristics of the meter based on multiple current change events and uploads the results to the main station.

[0053] In step S100, the active current threshold of the sample is screened: the change in active current for each load event. Not lower than the set threshold This is to ensure that the voltage change is sufficiently significant. For events that pass the threshold screening, the reactive power ratio is calculated: And divide the events according to preset intervals, for example: low reactive power ratio interval: The range of reactive power ratio: High reactive power ratio range: Determine whether the selected event sample covers at least two different reactive power ratio intervals, and require the number of valid events in each interval. Establish the following approximate relation:

[0054]

[0055] in, and These represent the characteristic values ​​of resistance and reactance of the upstream line of the meter, respectively. It characterizes unavoidable measurement errors or external disturbances. A set of data points is formed based on multiple load events within a preset time window. Based on multiple load current change events, the characteristic values ​​of resistance and reactance are obtained through fitting, and these characteristic values ​​are periodically uploaded to the main station system. The fitting method can be least squares, robust regression, quantile fitting, or other feasible fitting methods.

[0056] Step S200: The master station targets each target meter. Generate a set of transformers that can provide power, and further generate the target meter. The power supply path and its length between the target meter and each possible power supply transformer. This step does not require determining the power supply transformer to which the target meter uniquely belongs, nor does it require obtaining the complete low-voltage topology. Instead, it provides one or more possible power supply paths for establishing the normal interpretable range of resistance and reactance.

[0057] In step S200, the first Target electricity meter The possible set of power supply transformers is , Includes one or more potential power supply transformers, wherein each potential power supply transformer is denoted as . ; The first globally numbered system A transformer.

[0058] for Each of the possible power supply transformers in The main site generates from To the target meter Identify one or more possible power supply paths and record the corresponding path lengths to form the target electricity meter. Set of possible power supply paths The set of possible power supply paths can be represented as: ,in Indicates transformer To the target meter The The length of the possible power supply path, This indicates the method or type of path generation. Indicates transformer To the target meter The number of possible power supply paths.

[0059] When a low-voltage meter uses power line carrier communication or other power line communication methods, the target meter can record the identification information of the concentrators, distribution terminals, or other power supply-side communication devices that it can receive, and upload this identification information to the master station. The master station then queries the associated power supply transformer information based on the communication device identification, thereby generating a set of transformers that the target meter may supply. This method generates a set of possible power supply transformers solely based on communication-aware relationships. This step does not require starting from... The system determines a unique transformer and does not output the low-voltage topology connection relationship of the target meter. Instead, it retains one or more possible power supply transformers and their possible path lengths for subsequent determination of whether the resistance and reactance characteristic values ​​of the target meter can be explained by at least one normal power supply path.

[0060] When communication-aware information is lacking or unavailable, the master station can generate a set of potential power supply transformers based on the spatial relationship between the target meter and surrounding transformers. For example, the main station selects several transformers closest to the target meter based on the geographical coordinates of the target meter and the transformers; or it selects transformers less than a set threshold away from the target meter as a set of transformers that may supply power. .

[0061] For each transformer that can supply power The main station further generates its data to the target meter. power supply path set The length of the power supply path The distance can be determined based on Euclidean distance, distance along the street path, etc. The same path type must be used for the same transformer, for example, all Euclidean distance or all street path length.

[0062] Step S300: The main station targets each possible power supply transformer. With the target meter Set of possible power supply paths The system obtains the upstream line resistance and reactance characteristic values ​​of multiple meters associated with the transformer, as well as the length and type of each possible power supply path. Based on the relationship between the resistance and reactance characteristic values ​​and the path length and type, the main station establishes a unit parameter model for the power supply path corresponding to the transformer, and fits the unit length resistance parameter, unit length reactance parameter, and bias parameter to characterize the impedance characteristics of the normal power supply path. The bias parameter is used to represent the influence of fixed or approximately fixed parts such as the low-voltage side of the transformer, low-voltage outgoing lines, common sections, or service lines on the resistance and reactance. The fitting model can be a single unit length parameter model, a segmented unit length parameter model, a fitting model with physical constraints, or other models that can characterize the relationship between path length and resistance and reactance. The fitting method can be least squares, weighted fitting, robust regression, or other feasible methods. The fitted unit parameters and bias are used to subsequently establish the normal interpretable range of resistance and reactance of the target meter under possible power supply paths, providing a basis for anomaly diagnosis.

[0063] The segmented unit length parameter model is as follows, for transformers To the target meter The Possible power supply path The main station divides the path length into three segment length components: near end, middle section, and far end, and sets a first distance threshold. Second distance threshold ,in The segment length is defined as follows:

[0064] Proximal segment length components: ,

[0065] Middle segment length components: ,

[0066] Distant segment length component: ,

[0067] Among them, distance threshold Second distance threshold The parameters are determined based on engineering experience parameters such as low-voltage line design experience and power supply area type.

[0068] For any meter The characteristic value of the upstream line resistance uploaded by it is denoted as The characteristic value of the upstream line reactance is denoted as The main station establishes a system for each transformer based on the segment length. The following path impedance parameter model:

[0069] ,

[0070] ,

[0071] , , Transformers The unit length resistance parameters corresponding to different segment lengths are as follows. , , Transformers Reactance per unit length corresponding to different segment lengths; , For transformer The bias parameters include the impedance contributions of transformers, service segments, or other approximately fixed factors. To ensure the fitting results reflect the physical characteristics of low-voltage power supply paths where the near-end trunk line is thicker and the impedance contribution of far-end branches or detour paths may increase, constraints are set on the segmented unit parameters. The fitting method employs least squares, weighted fitting, robust regression, or other feasible approaches.

[0072] Step S400, the main station is based on the transformer The path impedance parameter model and target meter are as follows. Set of possible power supply paths ,right For each possible power supply path, calculate the estimated resistance and reactance values. For example, for the target meter... With possible power supply transformer Between the first A possible power supply path is provided, and the master station determines the path length accordingly. The reference values ​​for resistance and reactance along this path are obtained. However, due to differences in different embodiments... The distance can be determined by different path types, such as Euclidean distance and distance along the street. Different path types approximate the actual power supply path to varying degrees, resulting in different length estimation errors. Therefore, this embodiment further considers different path types. Establish a path length deviation model, determine the upper and lower bounds of the path length, and substitute these length upper and lower bounds into the path impedance parameter model to generate the resistance of the possible power supply path. Reactance The normal interpretable range.

[0073] The path length deviation model is as follows: ,in, and These are the proportional deviation coefficient and fixed deviation amount corresponding to the path type. Different deviation coefficients can be set for Euclidean distance and street-side path distance. Based on the total path length. and the length estimation bias corresponding to the path type Determine the upper and lower bounds of the path length. and : , .

[0074] Then and Substitute the path impedance parameter model into the given parameters to calculate the normal interpretable range of resistance and reactance under this path, which will be used for subsequent matching and anomaly diagnosis.

[0075] In step S500, the master station, based on the normal interpretable range of resistance and reactance, sets the target meter... Uploaded upstream line resistance characteristic value Reactance Its possible power supply path set The normal interpretable range corresponding to each possible power supply path is matched. In this embodiment, the upper bound of the normal interpretable range is used for matching.

[0076] Step S600: Determine whether the target resistance and reactance characteristic values ​​are normal and interpretable. For Any possible power supply path If the resistance corresponding to this path is normal, the upper bound can be interpreted as follows: Normal reactance can be interpreted as the upper limit being And satisfy as well as Then determine the target meter. The upstream resistance and reactance characteristic values ​​can be interpreted from the possible power supply path, proceed to step S700. If If no possible power supply path simultaneously meets the above conditions, then the target meter is determined to be... If the upstream resistance and reactance characteristic values ​​cannot be explained by the normal power supply path, proceed to step S800. Compared to traditional anomaly judgment schemes based solely on fixed resistance thresholds, this embodiment generates a normal interpretable upper bound based on possible power supply paths for matching, naturally considering the impact of path length on resistance and reactance. Even if the target meter is located on a long-distance line or in a long-distance power supply situation, and its resistance characteristic value is high, as long as it does not exceed the normal interpretable upper bound of the corresponding power supply path, it will not be misjudged as an anomaly, thereby reducing the possibility of misjudgment for long lines and improving diagnostic accuracy.

[0077] Step S700: Determine that the line is normal (including long-distance power supply).

[0078] Step S800: Determine line anomaly. The master station further determines the anomaly type based on the relationship between resistance and reactance exceeding the normal interpretable upper limit. If the target meter mainly exhibits an abnormal resistance characteristic value, while the reactance characteristic value does not show a corresponding abnormality, then proceed to step S900; if both the resistance and reactance characteristic values ​​of the target meter are amplified relative to the normal interpretable upper limit or even synchronously, then proceed to step S1100.

[0079] Step S900: Determine that the upstream line of the meter has the risk of aging, loose terminals, poor contact, or overheating.

[0080] Step S1100: Determine that the meter may have issues such as bypassing current or under-measuring.

[0081] In this embodiment, for the target meter any possible power supply path When satisfied and If the upstream circuit of the meter is found to be aging, has loose terminals, poor contact, or is at risk of overheating, then it is determined that the upstream circuit of the meter has issues such as aging, loose terminals, poor contact, or overheating. A fixed threshold is set for resistance exceeding the limit. This is the allowable deviation threshold for reactance.

[0082] When satisfied And satisfy If so, it is determined that the resistance and reactance are both abnormal, and there is suspicion of output bypass shunting, under-metering, or abnormal current sampling. and Determined based on historical operating data, on-site verification results, or engineering experience.

[0083] Since this embodiment has established a normal interpretable upper bound based on possible power supply paths, the excess threshold is used to measure the additional excess of the target meter relative to its interpretable upper bound, and therefore can be smaller than the abnormal threshold in traditional fixed impedance threshold methods. Traditional methods need to take into account the normal impedance of long-distance lines, and the threshold is usually large; this embodiment has explained the impact of long lines through the power supply path, so it can more sensitively identify anomalies such as poor contact and bypass shunting, while reducing the possibility of misjudgment of long lines.

[0084] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for diagnosing low-voltage line anomalies based on impedance interpretability, characterized in that, Includes the following steps: S10, the meter estimates the characteristic values ​​of the resistance and reactance of the upstream line based on the operational measurement data and uploads it to the main station. The operational measurement data includes the effective value of voltage, the effective value of current, and the power factor. S20, the main station generates a set of possible power supply transformers for each target meter, and generates possible power supply paths for each possible power supply transformer, forming a set of possible power supply paths for the target meter. S30, the main station establishes a path impedance parameter model based on the upstream line resistance characteristic value, reactance characteristic value and corresponding possible power supply path length of multiple meters. The path impedance parameter model is used to characterize the correspondence between the possible power supply path length and the resistance and reactance. The path impedance parameter model includes unit length resistance parameter, unit length reactance parameter and bias parameter. S40, the main station establishes a path length deviation model based on the path type and path length of each possible power supply path, and determines the upper and lower bounds of the length of each possible power supply path based on the path length deviation model; substitutes the upper and lower bounds of the length into the path impedance parameter model to generate the normal interpretable range of resistance and normal interpretable range of reactance of the target meter under each possible power supply path. S50, the main station matches the upstream line resistance characteristic value and reactance characteristic value uploaded by the target meter with the normal interpretable range of resistance and normal interpretable range of reactance corresponding to each possible power supply path in its set of possible power supply paths, and determines whether the resistance characteristic value and the reactance characteristic value can be explained by at least one possible power supply path. S60, if the resistance characteristic value and the reactance characteristic value can be explained by at least one possible power supply path, then the line is determined to be normal and the line diagnosis ends. Otherwise, proceed to step S70; S70, if the resistance characteristic value exceeds the corresponding normal interpretable range while the reactance characteristic value does not exceed the range, it is determined to be an abnormal aging of the line or an abnormal poor contact of the line. If both the resistance characteristic value and the reactance characteristic value exceed the corresponding normal interpretable range, it is determined to be suspected of bypass shunting or under-metering.

2. The low-voltage line anomaly diagnosis method based on impedance interpretability according to claim 1, characterized in that, Step S10, which involves estimating the upstream line resistance and reactance characteristics based on operational measurement data at the meter terminal, includes the following steps: S101, the meter terminal obtains the effective value of voltage, effective value of current and power factor according to the set sampling period; S102, the meter extracts multiple load current change events within a set time window, and calculates the change in active current for each load current change event. Changes in reactive current and the change in the effective value of voltage ; S103, perform identifiable screening on the load current change events; S104, for each load current change event that passes the identifiability screening, according to the formula... The characteristic values ​​of the resistance and reactance of the upstream line are obtained, where This is the characteristic resistance value of the upstream line. The characteristic value of the reactance of the upstream line, This is due to unavoidable measurement errors or external interference; S105, Based on all load current change events that pass the identifiability screening within the preset time window, a data point set is formed. The resistance characteristic value and the reactance characteristic value are obtained by fitting. The identifiability screening includes the following steps: S10301, Perform active current threshold screening on the samples, active current change amount Not lower than the set threshold Load events are filtered; S10302, Calculate the reactive power ratio and divide the interval. For load current change events that pass the threshold screening, calculate the reactive power ratio. It is divided into low reactive power ratio range, medium reactive power ratio range and high reactive power ratio range. S10303, if the load current change event samples cover at least two different reactive power ratio intervals, and the number of valid events in each interval is... Then the load current change event passes the screening, where N min This is a preset quantity threshold.

3. The low-voltage line anomaly diagnosis method based on impedance interpretability according to claim 2, characterized in that, The fitting method described in step S105 includes least squares fitting, robust regression fitting, or quantile fitting.

4. The low-voltage line anomaly diagnosis method based on impedance interpretability according to claim 3, characterized in that, The low reactive power ratio range mentioned in step S10302 is The range of reactive power ratio is as follows: The high reactive power ratio range is .

5. The low-voltage line anomaly diagnosis method based on impedance interpretability according to claim 1, characterized in that, In step S20, the main station generates a set of possible power supply transformers for each target meter and generates possible power supply paths for each possible power supply transformer, forming a set of possible power supply paths for the target meter. The main site is targeting the first Target electricity meter The possible set of power supply transformers generated is , Let N be an integer within the interval [1, N1], where N1 is the total number of target meters. Includes one or more potential power supply transformers, wherein each potential power supply transformer is denoted as . ; The first globally numbered system One power supply transformer, The integer is within the interval [1, N2], where N2 is the total number of power supply transformers; for Each of the possible power supply transformers in The main site generates from To the target meter Identify one or more possible power supply paths and record the corresponding path lengths to form the target electricity meter. Set of possible power supply paths , ,in For transformer To the target meter The The length of the possible power supply path, This refers to the method or type of path generation. For transformer To the target meter The number of possible power supply paths; the length of the power supply path Determined based on Euclidean distance or distance along the street path.

6. The low-voltage line anomaly diagnosis method based on impedance interpretability according to claim 5, characterized in that, The path impedance parameter model mentioned in step S30 includes a single unit length parameter model, a piecewise unit length parameter model, or a fitting model with physical constraints. The fitting method for the path impedance parameter model includes least squares fitting, weighted fitting, or robust regression fitting.

7. The low-voltage line anomaly diagnosis method based on impedance interpretability according to claim 6, characterized in that, The segmented unit length parameter model includes: For transformers To the target meter The Possible power supply path The main station divides the path length into three segment length components: near end, middle segment, and far end. The near end segment length component is... The segment length component of the middle section is The far-end segment length component is , The first distance threshold, The second distance threshold, ; The main station establishes a system for each transformer based on the segment length. The path impedance parameter model is as follows: , , The characteristic value of the upstream line resistance. The characteristic value of the reactance of the upstream line. , , Transformers The unit length resistance parameters corresponding to the near-end segment length, middle segment length, and far-end segment length. , , Transformers The reactance per unit length corresponding to the lower proximal segment length, middle segment length, and distal segment length; , For transformer The bias parameters include the impedance contribution of the transformer, service segment, or other approximately fixed factors.

8. The low-voltage line anomaly diagnosis method based on impedance interpretability according to claim 7, characterized in that, The distance threshold and the second distance threshold It is determined based on the design parameters of low-voltage lines and the type of power supply area.

9. The low-voltage line anomaly diagnosis method based on impedance interpretability according to claim 7, characterized in that, In the path impedance parameter model, the transformer The relationship between the unit length resistance parameters corresponding to the near-end segment length, middle segment length, and far-end segment length is as follows: .

10. The low-voltage line anomaly diagnosis method based on impedance interpretability according to claim 7, characterized in that, The path length deviation model mentioned in step S40 is ,in and The proportional deviation coefficient and fixed deviation amount are respectively set according to the path type. Different proportional deviation coefficients and fixed deviation amounts are set for Euclidean distance and road-along path distance. The step of determining the upper and lower bounds of the length of each possible power supply path in step S40 includes: Based on total path length and path length deviation Determine the upper and lower bounds of the path length. and : , .

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