High resistance problem classification and locating method based on voltage fluctuation and historical analysis

Abstract

The application discloses a high-resistance problem classification and positioning method based on voltage fluctuation and historical analysis, comprising the following steps: S1, selecting a high-resistance user identified by voltage transient; S2, judging whether the high-resistance user is a terminal user of a transformer area by at least one of the following modes; S3, for the high-resistance user determined as a non-terminal user, analyzing voltage waveform fitting conditions and access point ID information of the high-resistance user and users in the same transformer area, and identifying group defects. The high-resistance problem classification and positioning method based on voltage fluctuation and historical analysis disclosed by the application can distinguish terminal users from pre-meter defect users and locate group defects without relying on complete transformer area topology data, so that the defect elimination efficiency and power supply reliability are improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power system operation and maintenance, and particularly relates to a high-resistance problem classification and positioning method based on voltage fluctuation and historical analysis. BACKGROUND

[0002] In a low-voltage power system, a high-resistance problem in front of a meter can easily cause a significant voltage drop during high load of a user, affecting normal power consumption. High-resistance defects are divided into emergency defects (such as joint oxidation and cable bulging) and non-emergency defects (such as excessively long power supply radius and excessively thin wire diameter), and need to be arranged according to the emergency degree.

[0003] In the prior art, the end users (non-emergency defects) and the users in front of the meter (emergency defects) are usually distinguished according to the substation topology data, but due to incomplete topology data, accurate classification cannot be achieved, resulting in unreasonable defect elimination plan; at the same time, the existing inspection of the fault in front of the meter needs to check all connection points between the user and the transformer, the inspection range is large and the time is long, and the defects of the upper nodes (such as tap boxes and wire clamps) of group users are difficult to find, once evolved into a fault, the influence range is wide. Therefore, it is urgent to use existing power data to realize accurate classification and group defect positioning of high-resistance problems. SUMMARY

[0004] The main purpose of the application is to provide a high-resistance problem classification and positioning method based on voltage fluctuation and historical analysis, which can distinguish end users and users in front of the meter without relying on complete substation topology data, and locate group defects, thereby improving defect elimination efficiency and power supply reliability.

[0005] To achieve the above purpose, the application provides a high-resistance problem classification and positioning method based on voltage fluctuation and historical analysis, comprising the following steps:

[0006] Step S1: selecting a high-resistance user identified by voltage transient;

[0007] Step S2: judging whether the high-resistance user is a substation end user by at least one of the following ways:

[0008] Step S2.1: calculating the average voltage difference between the user and the transformer during low load of the user and high load of the transformer, and judging whether it is an end user according to the comparison result of the average voltage difference and the first threshold value;

[0009] Step S2.2: for three-phase users in the high-resistance user, calculating the average value of each phase resistance corresponding to the voltage transient and the resistance gap coefficient, and judging whether it is an end user according to the comparison result of the average value and the second threshold value, and the resistance gap coefficient and the third threshold value;

[0010] Step S2.3: Based on the resistance array corresponding to the voltage transient event in a certain period, the resistance fluctuation rate is calculated, and whether it is an end user is judged according to the resistance fluctuation rate and the range of the fourth threshold value and the resistance average value;

[0011] Step S2.4: According to the difference between the user historical risk value and the current risk value calculated by the analytic hierarchy process algorithm, whether it is an end user is judged in combination with the user repair or maintenance record;

[0012] Step S2.5: The user access point description is identified by regular expression or RAG enhanced semantics, and whether it is an end user is judged according to the comparison result of the line pole number of the access point and the sixth threshold value;

[0013] Step S3: For high resistance users determined as non-end users, analyze the voltage waveform fitting condition and access point ID information of the same area users to identify group defects.

[0014] As a further preferred technical solution of the above technical solution, the calculation of the average voltage difference of step S2.1 is specifically implemented as:

[0015] Step S2.1.1: Obtain a list of time points less than the maximum current preset value in the high resistance user load measurement point, and eliminate the measurement points whose total distributed photovoltaic power in the area is greater than the threshold value;

[0016] Step S2.1.2: Obtain the area three-phase current and the maximum N measurement points in the measurement point list, and calculate the difference between the user voltage Uu and the area total meter voltage Ut of each measurement point, and take the average value to obtain the average voltage difference Udif;

[0017] Step S2.1.3: If it is a single-phase user, the above average value is directly used; if it is a three-phase user, the three-phase average value is taken after calculating each phase separately; when the average voltage difference Udif is greater than the first threshold value, it is determined as an end user.

[0018] As a further preferred technical solution of the above technical solution, step S2.2 is specifically implemented as:

[0019] The resistance corresponding to the three-phase user voltage transient is , the average value of Ra, Rb and Rc in a certain time range is calculated;

[0020] When , it is determined as a non-end user;

[0021] When , the resistance difference coefficient is calculated, wherein:

[0022] If Cr is greater than the third threshold value, it is determined as an oxidation fault and an end user; if Cr is less than the third threshold value, it is determined as a simple end user.

[0023] As a further preferred technical solution of the above technical solution, step S2.3 is specifically implemented as:

[0024] The resistance array Ar is a set of resistances corresponding to a plurality of voltage sag events in a certain period, and after removing the records in Ar by a preset value, the standard deviation Sa and the resistance fluctuation rate are calculated

[0025] When Br is less than the fourth threshold value and the average resistance of Ar is between a preset range, it is determined to be an end user.

[0026] As a further preferred technical solution of the above technical solution, step S2.4 is specifically implemented as:

[0027] Take the data of the month close to the electricity consumption M years ago as the comparison object;

[0028] The historical risk value is calculated by an analytic hierarchy process algorithm;

[0029] If the difference between the current risk value NowFX and the risk value corresponding to the month close to the electricity consumption M years ago is less than a fifth threshold value, and there is no repair or maintenance record in the recent M years, it is determined to be an end user; otherwise, it is determined to be a pre-table fault user.

[0030] As a further preferred technical solution of the above technical solution, the identification of the group defect in step S3 is specifically implemented as:

[0031] Step S3.1: For non-end high resistance users, obtain a set of all sag event times T in a week, and mark the users in the same area as the user at T time point within a preset value of high and low voltage difference as the same drop users;

[0032] Step S3.2: Mark the non-end high resistance users in the same area belonging to the same access point and having a risk value greater than a seventh threshold value as the same access point users, and mark the non-end high resistance users in the same area belonging to the same meter box and having a risk value greater than the seventh threshold value as the same meter box users;

[0033] Step S3.3: Group the same drop users, the same access point users and the same meter box users, respectively calculate the voltage average and the current total value of the users in the group, when the current total value of the users in the group increases by more than the eighth threshold value of the average value of the maximum five points in a certain range of the group current total value and the voltage average of the users in the group decreases by more than a threshold value, it is determined to be a group sag event, and it is determined to be high risk by the sag event combined with an analytic hierarchy process algorithm, then the front side of the group users is a group fault, the fault position is the common nearest topology node of the user set, and the topology is gradually upwards using the data of the meter account in the order of meter box-access point-low voltage distribution box-low voltage branch four levels. ​

[0034] The beneficial effects of the present application are:

[0035] 1. Without relying on the topology data of the transformer area, the end and front defects are accurately classified, the emergency and non-emergency defects are distinguished, and the defect elimination plan is optimized;

[0036] 2. Accurate positioning of group defects, reducing the time-consuming of patrol, and reducing the influence range of faults;

[0037] 3. Improve power supply reliability and user satisfaction, and provide technical support for power supply in key periods such as peak summer. BRIEF DESCRIPTION OF DRAWINGS

[0038] Fig. 1 is a flowchart of the present application.

[0039] Fig. 2 is a schematic diagram of the comparison of power consumption in the high load period.

[0040] Fig. 3 is a schematic diagram of the oxidation fault identification and positioning of the front end of the group user. DETAILED DESCRIPTION

[0041] The following description is used to disclose the present application so that those skilled in the art can implement the present application. The preferred embodiments in the following description are only used as examples, and other obvious modifications can be thought by those skilled in the art. The basic principles of the present application defined in the following description can be applied to other embodiments, modifications, improvements, equivalents and other technical solutions without departing from the spirit and scope of the present application.

[0042] In the preferred embodiments of the present application, those skilled in the art should note that the transformer and the like involved in the present application can be regarded as prior art.

[0043] Preferred embodiments.

[0044] As shown in Figs. 1-3 , the present application discloses a high resistance problem classification and positioning method based on voltage fluctuation and historical analysis, comprising the following steps:

[0045] Step S1: selecting high resistance users identified by voltage transient;

[0046] Step S2: judging whether the high resistance user is a transformer area end user by at least one of the following ways:

[0047] Step S2.1: calculating the average voltage difference of the user and the transformer in the low load period of the user and the high load period of the transformer, and judging whether it is an end user according to the comparison result of the average voltage difference and the first threshold value;

[0048] Step S2.2: For three-phase users in high-resistance users, calculate the average value of each phase resistance corresponding to the voltage transient and the resistance gap coefficient, and determine whether it is an end user according to the comparison results of the average value and the second threshold value, and the resistance gap coefficient and the third threshold value;

[0049] Step S2.3: Based on the resistance array corresponding to the voltage transient event in a certain period, calculate the resistance fluctuation rate, and determine whether it is an end user according to the comparison results of the resistance fluctuation rate and the fourth threshold value, and the range of the resistance average value;

[0050] Step S2.4: According to the difference between the user historical risk value and the current risk value calculated by the analytic hierarchy process algorithm, and the user repair or maintenance record, determine whether it is an end user;

[0051] Step S2.5: Determine whether it is an end user according to the comparison results of the line pole number of the access point and the sixth threshold value by regular expression or semantic recognition of the access point description based on RAG enhancement (when the access point description is "xx line N# pole branch" and N> Sixth threshold value 6, it is determined to be an end user);

[0052] Step S3: For high-resistance users determined to be non-end users, analyze their voltage waveform fitting with users in the same area and access point ID information to identify group defects.

[0053] Specifically, the calculation of the average voltage difference in step S2.1 is specifically implemented as:

[0054] Step S2.1.1: Obtain the list of time points (Tumin) in the high-resistance user load (7 days) measurement points (96 measurement points per day) that are less than the maximum current preset value (5%) (at this time, the user is basically not using electricity), and eliminate the measurement points with distributed photovoltaic power greater than the threshold value (10%) (to prevent the influence of end voltage rise caused by large distributed photovoltaic power), to obtain the measurement point list (Ttmax);

[0055] Step S2.1.2: Obtain the three-phase current of the measurement point list (since there is no user corresponding phase in the existing user data, the three-phase current is used to represent the voltage division caused by large load on the power side of the user's phase) and the maximum N measurement points (10 can be taken, to obtain the measurement points with the maximum load of the user without electricity and photovoltaic power generation), and calculate the difference between the user voltage Uu and the total meter voltage Ut of each measurement point, and take the average value to obtain the average voltage difference Udif (Udif=Uu-Ut, representing whether there is a large voltage difference between the user and the transformer during the period when the user is not using electricity and the transformer is under high load);

[0056] ​Step S2.1.3: If it is a single-phase user, directly use the average value; if it is a three-phase user, calculate each phase separately and take the average of the three; when the average pressure difference Udif is greater than the first threshold value (which can be 4V), it is determined to be an end user.

[0057] More specifically, step S2.2 is implemented as:

[0058] The resistance corresponding to the voltage sag of each phase of the three-phase user is , and the average value of Ra, Rb, and Rc in a certain time range is calculated;

[0059] When (the fourth threshold value can be 0.2Ω), it is determined to be a non-end user (non-end oxidation failure);

[0060] When , the resistance difference coefficient Cr is calculated , where:

[0061] If Cr is greater than the third threshold value (which can be 0.5), it is determined to be an oxidation failure and an end user; if Cr is less than the third threshold value, it is determined to be a simple end user (there is no oxidation, and the theoretical basis is that if there is oxidation in a three-phase user, the resistance generated by oxidation will cause different resistances between different phases).

[0062] Further, step S2.3 is implemented as:

[0063] The resistance array Ar is a set of resistances corresponding to multiple voltage sag events in a certain period, and after removing the first preset value (20%) of records in Ar, the standard deviation Sa and the resistance fluctuation rate Br are calculated ;

[0064] When Br is less than the fourth threshold value (which can be 0.2) and the average resistance of Ar is between the preset range (0.2Ω-1Ω), it is determined to be an end user.

[0065] Further, step S2.4 is implemented as:

[0066] Take the monthly data of the closest year as the comparison object;

[0067] The historical risk value is calculated by the analytic hierarchy process algorithm (covering eighteen dimensions of resistance, pressure difference, frequency, etc.);

[0068] If the current risk value NowFX is close to the risk value of the month M years ago (preferably 2 years ago) (close means that the power is within the threshold % range) and the difference between the two is less than the fifth threshold value (preferably 30), and there is no repair or maintenance record in the past M years, and the resistance does not increase obviously, and the anti-correlation does not change obviously, then it is determined that the end user; otherwise, it is determined that the front of the table is a fault user (the theoretical basis is that after 2 years of peak summer high load period, if there is an oxidation point, it has evolved into a fault or deterioration caused by an increase in risk value, and if the risk value remains constant, it represents a relatively stable end problem).

[0069] Preferably, the identification of the population defect in step S3 is implemented as follows:

[0070] Step S3.1: For non-end high resistance users, obtain a set of all transient event time moments T within a week, and mark the users in the same area whose high point and low point voltage difference at T time is within the preset value (±1.5V) as the same drop users (the proportion is more than 80%, and the purpose of 80% is to avoid the problem of time error of the meter clock);

[0071] Step S3.2: Mark the non-end high resistance users in the same area belonging to the same access point and having a risk value greater than the seventh threshold value (preferably 150) as the same access point users, and mark the non-end high resistance users in the same area belonging to the same meter box and having a risk value greater than the seventh threshold value as the same meter box users;

[0072] Step S3.3: Group the same drop users, the same access point users and the same meter box users, respectively calculate the voltage average and current total value of the users in the group, and when the current total value of the two measuring points before and after the grouped set increases by more than the eighth threshold value (preferably 10%) of the average value of the maximum five points in a certain range of the grouped current total value and the voltage average of the users in the group decreases by more than the threshold value (preferably 5V), it is determined that it is a grouped transient event, and through the transient event combined with the analytic hierarchy process algorithm, it is determined that it is high risk, then the front side of the grouped users is a group fault, and the fault position is the common nearest topology node (generally a tap box or a common line clamp fault) of the user set, and through the order of meter box-access point-low voltage tap box-low voltage branch four levels and using the accurate data of the account to topologically expand upwards (for example, if more than 30% of the users in the same meter box and the same access point have voltage drop phenomenon, it is determined that the meter box and the access point are front side faults, and if multiple meter boxes or multiple access points meet the conditions, it is determined that multiple meter boxes and access points have front side faults).

[0073] Part of the basic principles of the application are supplemented as follows:

[0074] First, the principle of voltage transient: ;

[0075] In the formula: This refers to the low-voltage side voltage of the distribution transformer. The voltage measured by the user's meter; The current used by the user; The resistance between the low-voltage side of the distribution transformer and the user's meter.

[0076] when When smaller, ;

[0077] when When the resistance is large (i.e., there is a large contact resistance before the user's meter). Will be more Much smaller, it is represented on the user voltage curve as a sudden drop in voltage caused by an increase in current.

[0078] Second, the judgment of voltage sag events based on the principle of voltage sag:

[0079] 1. At the time of the user's lowest voltage on a single day, if the voltage difference between the user and the transformer area is greater than 7V, identify the users that meet this condition.

[0080] 2. Determining the instantaneous descent point:

[0081] 1) At the low point, the minimum three-phase voltage in the transformer area minus the user voltage is greater than 5V;

[0082] 2) The pressure drop between the two points is greater than 5;

[0083] 3) The current (primary value) at the low point is >0.1A;

[0084] 4) (Low point current - High point current) / High point current > 100% && (Low point current - High point current) > 20% of the average of the five maximum currents within a week;

[0085] 3. For single-phase users, voltage difference * current < 2000; for three-phase users, < 4000.

[0086] Exclusion criteria:

[0087] If the total meter voltage is less than 198V at the moment of the instantaneous drop, the instantaneous drop event is excluded.

[0088] Data with a voltage greater than 420 is considered bad data, and sudden drop events are discarded.

[0089] If the current at the previous point is negative, the instantaneous drop event is eliminated.

[0090] Third, the recovery process incorporates additional instantaneous event culling calculations:

[0091] Current recovery cleaning: record the current when the user's certain transient event voltage transient drops to low voltage, if the current basically disappears in 4 measurement points after the transient (the current at the beginning of the transient is less than 20% of the low voltage current, and the voltage has not recovered to the high point-voltage difference*0.5-1V), the transient event is excluded.

[0092] In the case of poor quality of transformer area topology data, the present application uses the transformer user measurement data and access point data in power data, historical risk data, analyzes the voltage fluctuation characteristics of users in low load period and transformers in high load period, combines the fluctuation of group users in the transformer area and the user access point identification data, and the current and voltage fluctuation of three-phase users, to distinguish the end users and the users with defects before the meter, and locate the group defect position. On the one hand, the pre-meters joint oxidation, cable bulge emergency defects and non-emergency defects corresponding to the line parameters such as long power supply radius and thin wire diameter are distinguished, so that the power supply can effectively arrange the plan and improve the efficiency of on-site inspection and defect elimination. On the other hand, the problems of the upper nodes of group users such as distribution box and wire clamp are identified, and such defects with large influence are more effectively handled. The preventive maintenance based on this improves the power supply reliability and user power consumption satisfaction.

[0093] It is worth mentioning that the transformer and other technical features involved in the present patent application should be regarded as prior art. The specific structure, working principle and possible control method and spatial arrangement method of these technical features can be selected conventionally in the art, and should not be regarded as the invention point of the present patent. The present patent will not be further expanded and detailed.

[0094] For those skilled in the art, the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced equivalently. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A high resistance problem classification and location method based on voltage fluctuation and historical analysis, characterized in that, The method comprises the following steps: Step S1: selecting high-resistance users identified by voltage sag; Step S2: judging whether the high-resistance user is an end user by at least one of the following methods: Step S2.1: calculating the average voltage difference between the user and the transformer during the low-load period of the user and the high-load period of the transformer, and judging whether it is an end user according to the comparison result of the average voltage difference and the first threshold value; Step S2.2: for three-phase users in the high-resistance user, calculating the average value of each phase resistance corresponding to the voltage sag and the resistance difference coefficient, and judging whether it is an end user according to the comparison results of the average value and the second threshold value, and the resistance difference coefficient and the third threshold value; Step S2.3: based on the resistance array corresponding to the voltage sag event in a certain period, calculating the resistance fluctuation rate, and judging whether it is an end user according to the comparison results of the resistance fluctuation rate and the fourth threshold value, and the range of the resistance average value; Step S2.4: according to the difference between the historical risk value and the current risk value of the user calculated by the analytic hierarchy process, and combining the user repair or maintenance record to judge whether it is an end user; Step S2.5: judging whether it is an end user according to the comparison result of the line pole number of the access point and the sixth threshold value by using regular expression or semantic recognition of the access point description based on RAG enhancement; Step S3: for high-resistance users determined as non-end users, analyzing the voltage waveform fitting and access point ID information of the users and the users in the same area to identify group defects; The identification of group defects in step S3 is specifically implemented as: Step S3.1: for non-end high-resistance users, obtaining a set T of all voltage sag event times within a week, and marking users in the same area with the same user as the same drop users if the voltage difference between the high point and the low point of the user at time T is within a preset value; Step S3.2: marking non-end high-resistance users in the same area belonging to the same access point and having a risk value greater than a seventh threshold value as the same access point users, and marking non-end high-resistance users in the same area belonging to the same meter box and having a risk value greater than the seventh threshold value as the same meter box users; Step S3.3: grouping the same drop users, the same access point users and the same meter box users, respectively calculating the voltage average and the current total value of the users in the group, when the current total value of the two measuring points before and after the grouped set increases by more than the eighth threshold value of the average value of the maximum five points in a certain range of the grouped current total value and the voltage average of the users in the group decreases by more than a threshold value, it is judged as a grouping voltage sag event, and if the voltage sag event is determined as high risk by the analytic hierarchy process, the front side of the grouped users is a group fault, and the fault position is the common nearest topology node of the user set, and the fault position is found by sequentially searching the meter box-access point-low voltage tap-low voltage branch four levels and using the accurate data of the meter account to topologically search upwards.

2. The method of claim 1, wherein, The calculation of the average voltage difference in step S2.1 is specifically implemented as: Step S2.1.1: obtaining a list of time points less than the maximum current preset value in the high-resistance user load measuring point, and eliminating the measuring points with total distributed photovoltaic power greater than a threshold value in the area distribution; Step S2.1.2: Obtain the substation three-phase current and the maximum N measuring points in the measuring point list, and calculate the difference between the user voltage Uu and the substation total table voltage Ut of each measuring point, and take the average value to obtain the average voltage difference Udif; Step S2.1.3: If it is a single-phase user, the above average value is directly used; if it is a three-phase user, the three-phase average value is obtained after separate calculation; when the average voltage difference Udif is greater than the first threshold value, it is determined to be an end user.

3. The method of claim 2, wherein, Step S2.2 is implemented as: The resistance corresponding to the voltage transient of each phase of the three-phase user is , the average value of Ra, Rb, Rc in a certain time range is calculated; When non-end user is determined; When the resistance gap coefficient is calculated wherein: If Cr is greater than the third threshold value, it is determined to be an oxidation fault and an end user; if Cr is less than the third threshold value, it is determined to be a simple end user.

4. The method of claim 3, wherein, Step S2.3 is implemented as: The resistance array Ar is a set of resistances corresponding to a plurality of voltage transient events in a certain period, and after removing the first preset records in Ar, the standard deviation Sa and the resistance fluctuation rate are calculated ; When Br is less than the fourth threshold value and the resistance average value of Ar is between the preset range, it is determined to be an end user.

5. The method of claim 4, wherein, Step S2.4 is implemented as: Take the data of the month close to the electricity consumption M years ago as the comparison object; The historical risk value is calculated by the analytic hierarchy process algorithm; If the difference between the current risk value and the risk value corresponding to the month close to the electricity consumption M years ago is less than the fifth threshold value, and there is no repair or maintenance record in the past M years, it is determined to be an end user; otherwise, it is determined to be a table front fault user.

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