A method for identifying and handling the causes of line loss in a transformer area

Abstract

The present invention discloses a method for identifying and processing the causes of line loss in a substation, including step S1: obtaining corresponding data of each relevant system, and obtaining the line loss rate deviation value of the substation; step S2: analyzing and judging the line loss rate deviation value, if the line loss rate deviation value is greater than the upper threshold, entering the high loss cause judgment module; if the line loss rate deviation value is less than the lower threshold, entering the negative loss cause judgment module. The present invention discloses a method for identifying and processing the causes of line loss in a substation, by collecting the substation line loss data, the corresponding relationship data between the substation and the user, the user power consumption measurement data, and the substation topology data in the power data center, and performing step-by-step analysis through a set of algorithms, and finally locating the causes of line loss.

Description

Technical Field

[0001] The present invention belongs to the technical field of line loss in a transformer area, and specifically relates to a method for identifying and processing the cause of line loss in a transformer area based on ledger topology and measurement data characteristics. Background Art

[0002] The line loss of the substation is the difference and ratio between the power supply shown in the substation's gateway table and the power consumption of all users under its jurisdiction. Generally, the difference between the actual line loss of the substation in the power consumption information collection system and the theoretical line loss (the difference between the resistance voltage drop loss through the line) is used as the basis for abnormal judgment. When the difference is too large, it is divided into high line loss and negative line loss. Since there are many reasons for line loss problems, such as household transformer relationship, collection abnormality, meter damage, user overcapacity, wiring error, high resistance of the connection point, power supply radius, user power theft, etc., and the number of substations and users is huge, front-line power employees cannot use the existing system to quickly and accurately locate them. They often need to integrate a large number of substation ledgers and user load data scattered in different system pages every day, and spend several hours of system comparison to locate some problem users. It also requires professional knowledge and experience support, which is not convenient for timely processing. Long-term existence will affect power safety, power supply stability, power supply economy and fair electricity fee recovery. A set of convenient algorithms is urgently needed to identify and facilitate targeted verification by on-site operators. Summary of the invention

[0003] The main purpose of the present invention is to provide a method for identifying and processing the cause of line loss in a substation, by collecting the substation line loss data, the correspondence data between the substation and the user, the user's electricity consumption measurement data, and the substation topology data in the power data center, and performing step-by-step analysis through a set of algorithms to ultimately locate the cause of the line loss.

[0004] To achieve the above objectives, the present invention provides a method for identifying and processing line loss causes in a transformer area, comprising the following steps:

[0005] Step S1: Obtain corresponding data of each relevant system and obtain the line loss rate deviation value of the substation;

[0006] Step S2: Analyze and judge the line loss rate deviation value. If the line loss rate deviation value is greater than the upper threshold (preferably 2%), enter the high loss cause judgment module; if the line loss rate deviation value is less than the lower threshold (preferably -0.5%), enter the negative loss cause judgment module.

[0007] As a further preferred technical solution of the above technical solution, in step S1, the corresponding data includes:

[0008] Obtain the actual daily line loss data and theoretical line loss data of the power consumption information collection system, including the corresponding data of line loss rate, line loss quantity, normal line loss date and problem line loss date;

[0009] The power consumption information collection system obtains the corresponding data including the power supply and power load data of the total meter of the substation (96 points per day) and the missing data, the power consumption and power load data of the users under the jurisdiction of the substation (96 points per day) and the power generation load data of the user's photovoltaic power generation (96 points per day);

[0010] The data obtained from the marketing system include the corresponding relationship data between the substation and the users under its jurisdiction, the user's new installation data, the change process data, the (95598) work order data, the user's photovoltaic ledger data, the meter replacement record data, and the corresponding data between the meter rated capacity and the substation transformer rated capacity;

[0011] Obtain the topology and ledger data of the substation in the PMS3.0 system, including the topological relationship between users and low-voltage trunk lines and low-voltage branch lines, and obtain the low-voltage line length, wire diameter, line model and corresponding unit length impedance data.

[0012] As a further preferred technical solution of the above technical solution, in step S1, the line loss rate deviation value = actual line loss rate - theoretical line loss rate.

[0013] As a further preferred technical solution of the above technical solution, the high loss cause judgment module is specifically implemented as follows:

[0014] Condition 1: Compare the user list Z (collected within 15 days) under the jurisdiction of the area on normal line loss days with the user list G under the jurisdiction of high line loss days, and locate the difference user list C1 = ZZ∩G (users who have moved out of the area);

[0015] Define the (most recent) normal line loss daily line loss electricity DLN and the abnormal line loss daily line loss electricity DLA, and calculate the sudden increase line loss electricity DLT = DLA-DLN;

[0016] Through the user power data on the high line loss day, traverse the daily power consumption of a single user or a combination of multiple users in the difference user list C1. When the user power is greater than DLT*0.7 (the sudden increase in line loss power) and less than DLT*1.1, list the single user or multiple user combination list X1 that meets the requirements, and sort them from large to small according to power consumption, and prompt the user change relationship error;

[0017] Condition 2: When condition 1 is empty, confirm whether there is a situation where the user's collected electricity is missing on the high line loss day in the substation area and the estimated electricity is used to calculate the line loss. If so, locate the abnormal user and prompt the meter collection missing error;

[0018] When the lists of condition 1 and condition 2 are both empty, multi-dimensional analysis and calculation of conditions 3-9 are performed as follows:

[0019] Condition 3: Identification of meter replacement wiring errors: Traverse the list of users with meter replacement records within the preset time (15 days) under the jurisdiction of the high-line loss daily area, confirm whether their total power or ABC single-phase power is negative. If so, locate the user and the negative phase, and prompt that the meter replacement wiring is wrong, and suggest checking the meter wiring;

[0020] Condition 4: Photovoltaic metering error identification: traverse the list of newly installed photovoltaic users within the preset time (15 days) under the jurisdiction of the high-line loss daily area, confirm the user's self-generated and self-used daily grid-connected electricity S1, photovoltaic power meter daily electricity F1, confirm the user's electricity consumption Y1=S1+F1, if Y1<0, the user's electricity consumption is negative, locate the user, and prompt that the photovoltaic user's metering error is caused by the wiring error of the newly installed photovoltaic meter, and it is recommended to check the photovoltaic user meter wiring;

[0021] Condition 5: Overcapacity identification: traverse the load data F (96 measurement points per day) of users in the high-line loss daily area, compare with the rated capacity E of the user meter, when F>E*1.2, locate the user, and calculate the overcapacity integral value through the measurement points where F>E*1.2 among the daily (96) measurement points In the case of multiple users exceeding capacity, the users are sorted from large to small by C', and the users are located. It is prompted that the meter range is exceeded, resulting in an error in the calculation of the user's electricity consumption. It is recommended to replace the meter, and the appropriate model of the replacement meter is provided through the maximum daily load Fmax. When the user is a three-phase user, the load is calculated separately according to each load of ABC, and the phase overcapacity threshold is the rated capacity E / 3;

[0022] Condition 6: Identification of users with sudden electricity consumption reduction: Calculate the average daily electricity consumption AVEDL for the preset time (10 days) before the abnormal line loss of the user. If it is a three-phase user, calculate the average electricity consumption of each phase, A, B, and C phases respectively, and compare it with the electricity consumption GSRDL1 on the day with high line loss. Locate the list of users with sudden electricity consumption reduction of (AVEDL-GSRDL1) / AVEDL<=30%, increase the inspection priority of users with 1.5*DLT>(AVEDL-GSRDL1)>0.5*DLT, and provide feedback on the list of users with sudden electricity consumption reduction and the difference in phases. It will prompt that the meter (phase difference) is faulty or the user is stealing electricity. It is recommended to confirm whether the user has stolen electricity or to inspect the meter and replace the problematic meter.

[0023] Condition 7: Identification of high resistance of meter connector: Identification needs to meet four conditions at the same time: 1. The user switches between low voltage (less than 198V) and normal voltage (220V~230V) more than the preset number of times (3 times) within a day; 2. Identify the correlation between the voltage and current of the meter through the correlation coefficient function corr() (python). If the correlation coefficient value is less than the preset value (-0.9, negative correlation); 3. The user's voltage drops suddenly with the increase of current and exceeds the preset value (20V); 4. The user's maximum current is less than the preset current value (1A). If these four conditions are met at the same time, the user is prompted that the meter connector has high resistance, and it is recommended to remake the meter inlet and outlet connectors to prevent the connector from being damaged and the meter from being burned due to long-term heating;

[0024] Condition 8: Meter abnormality identification: Identify the loss of current, loss of voltage, and extreme three-phase imbalance of user meters in the high-line loss area on days with high line losses. Loss of current means that the maximum daily current of the user on a normal line loss day is greater than the rated current*0.05, and the maximum current of the user on a high line loss day is less than the rated current*0.05; loss of voltage means that the voltage of the user is normal on a normal line loss day, and the voltage of one or more phases of the user is continuously less than the rated voltage*0.8 for a preset number (4) or more measuring points on a high line loss day; extreme three-phase imbalance means that the three-phase is balanced on a normal line loss day, and the three-phase balance degree of a preset number (4) or more measuring points is continuously less than 0.3 on a high line loss day (where the three-phase balance degree = (max (three-phase current) - min (three-phase current)) / max (three-phase current)); if one of the loss of current, loss of voltage, and extreme three-phase imbalance is met, the user will be included in the list of abnormal meter users, indicating that the meter is damaged, and it is recommended to replace the problematic meter;

[0025] Condition 9: Line parameter problem: Use the substation topology and line parameters to identify whether the user's power supply radius is greater than the preset distance (200m) and whether the line diameter meets the minimum conductor diameter design standard. If yes, locate the user and suggest the user to switch to a nearby substation or replace the conductor.

[0026] As a further preferred technical solution of the above technical solution, the damage cause judgment module is specifically implemented as follows:

[0027] Condition 1: Compare the user list Z (collected within 15 days) of the normal line loss day in the area with the user list F2 of the negative line loss day, and locate the difference user list C2 = ZZ∩F2 (users migrated into the area);

[0028] Define the most recent normal line loss daily line loss electricity DLN and abnormal line loss daily line loss electricity DLA, and calculate the sudden line loss electricity DLT = DLA-DLN;

[0029] Through the user power data on the negative line loss day, traverse the daily power consumption of a single user or a combination of multiple users in the difference user list C2. When the user power is greater than DLT*0.7 (sudden power reduction due to line loss) and less than DLT*1.3, list the single user or multiple user combination list X2 that meets the requirement, and sort them from large to small according to power consumption, and prompt the user change relationship error;

[0030] Condition 2: When condition 1 is empty, confirm whether there is a situation where the user's collected electricity is missing on the negative line loss day in the substation area and the estimated electricity is used to calculate the line loss. If so, locate the abnormal user and prompt the meter collection missing error;

[0031] When the lists of condition 1 and condition 2 are both empty, multi-dimensional analysis and calculation of conditions 3-4 are performed as follows:

[0032] Condition 3: Photovoltaic metering error identification: traverse the list of users who installed photovoltaic power in the preset time (15th) under the jurisdiction of the high-loss area, confirm the daily power consumption S2 of the user's self-generated and self-used grid meter, and the daily power consumption F2 of the photovoltaic power meter, and confirm that the user's power consumption Y2=S2+F2. If Y2<0, the user's power consumption is negative, then locate the user, and prompt that the photovoltaic user's metering error is caused by the wiring error of the new photovoltaic installation, and it is recommended to check the photovoltaic user's meter wiring;

[0033] Condition 4: Identification of users with sudden increase in electricity consumption: Calculate the average daily electricity consumption AVEDL within the preset time (10 days) before the abnormal line loss of the user. If it is a three-phase user, calculate the average electricity consumption of each phase, ABC, and compare it with the electricity consumption GSRDL2 on the negative loss day. Locate the list of users with sudden increase in electricity consumption (GSRDL2-AVEDL) / AVEDL>=30%, increase the inspection priority of users with 1.5*DLT>(GSRDL2-AVEDL)>0.5*DLT, and provide feedback on the list of users with sudden increase in electricity consumption and their phases. It will prompt that the metering equipment is faulty or the household-transformer relationship is wrong. On-site verification is recommended. If there is a problem with the meter, replace the problematic meter. If there is an error in the household-transformer relationship, change the ledger.

[0034] As a further preferred technical solution of the above technical solution, the negative line loss cause judgment module is specifically implemented as follows: based on the extraction of the list of problematic users in high line loss and negative line loss areas, the data owner is informed to process:

[0035] The list of problematic users in high line loss and negative line loss areas extracted by the above algorithm. If the user also has a (95598) work order, the processing priority is increased;

[0036] The user list is linked to the data owner of the problem through the meter reader accountant field in the substation, and the list of problematic users, the cause of the problem and the solution are notified by SMS, making it convenient for front-line personnel to accurately solve line loss problems.

[0037] The beneficial effects of the present invention are:

[0038] Based on the data middle platform, through multi-dimensional algorithms based on substation line loss data, correspondence data between substations and users, user electricity consumption measurement data, and substation topology data, without the need for new hardware equipment, it can identify household-transformer relationships, collection anomalies, meter damage, user overcapacity, wiring errors, high resistance at connection points, power supply radius, and user electricity theft problems, and provide solutions to facilitate front-line personnel to accurately solve line loss problems, improve electricity safety, power supply stability, power supply economy, and the fairness of electricity fee recovery. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0040] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations. The basic principles of the present invention defined in the following description can be applied to other embodiments, variations, improvements, equivalents, and other technical solutions that do not deviate from the spirit and scope of the present invention.

[0041] In the preferred embodiment of the present invention, those skilled in the art should note that the substation, electricity consumption information collection system, marketing system, PMS3.0 system, etc. involved in the present invention can be regarded as prior art.

[0042] Preferred embodiments.

[0043] The present invention discloses a method for identifying and processing the causes of line loss in a transformer area, comprising the following steps:

[0044] Step S1: Obtain corresponding data of each relevant system and obtain the line loss rate deviation value of the substation;

[0045] Step S2: Analyze and judge the line loss rate deviation value. If the line loss rate deviation value is greater than the upper threshold (preferably 2%), enter the high loss cause judgment module; if the line loss rate deviation value is less than the lower threshold (preferably -0.5%), enter the negative loss cause judgment module.

[0046] Specifically, in step S1, the corresponding data includes:

[0047] Obtain the actual daily line loss data and theoretical line loss data of the power consumption information collection system, including the corresponding data of line loss rate, line loss quantity, normal line loss date and problem line loss date;

[0048] The power consumption information collection system obtains the corresponding data including the power supply and power load data of the total meter of the substation (96 points per day) and the missing data, the power consumption and power load data of the users under the jurisdiction of the substation (96 points per day) and the power generation load data of the user's photovoltaic power generation (96 points per day);

[0049] The data obtained from the marketing system include the corresponding relationship data between the substation and the users under its jurisdiction, the user's new installation data, the change process data, the (95598) work order data, the user's photovoltaic ledger data, the meter replacement record data, and the corresponding data between the meter rated capacity and the substation transformer rated capacity;

[0050] Obtain the topology and ledger data of the substation in the PMS3.0 system, including the topological relationship between users and low-voltage trunk lines and low-voltage branch lines, and obtain the low-voltage line length, wire diameter, line model and corresponding unit length impedance data.

[0051] More specifically, in step S1, line loss rate deviation value = actual line loss rate - theoretical line loss rate, where:

[0052] The actual line loss rate is calculated based on the power supply of the total meter at the substation and the power consumption of the user meter;

[0053] Actual line loss rate = (power supply - power consumption of subordinate users) / power supply calculation;

[0054] The theoretical line loss rate is the theoretical line loss obtained by calculating the voltage difference between the voltage of the total meter at the substation and the voltage of the user meter and the theoretical impedance loss;

[0055] The marketing system provides the relationship between the transformers in the substation and the users;

[0056] The electrical information collection system provides actual line loss rate and theoretical line loss rate.

[0057] Furthermore, the high loss cause judgment module is specifically implemented as follows:

[0058] Condition 1: Compare the user list Z (collected within 15 days) under the jurisdiction of the area on normal line loss days with the user list G under the jurisdiction of high line loss days, and locate the difference user list C1 = ZZ∩G (users who have moved out of the area);

[0059] Define the (most recent) normal line loss daily line loss electricity DLN and the abnormal line loss daily line loss electricity DLA, and calculate the sudden increase line loss electricity DLT = DLA-DLN;

[0060] Through the user power data on the high line loss day, traverse the daily power consumption of a single user or a combination of multiple users in the difference user list C1. When the user power is greater than DLT*0.7 (the sudden increase in line loss power) and less than DLT*1.1, list the single user or multiple user combination list X1 that meets the requirements, and sort them from large to small according to power consumption, and prompt the user change relationship error;

[0061] Condition 2: When condition 1 is empty, confirm whether there is a situation where the user's collected electricity is missing on the high line loss day in the substation area and the estimated electricity is used to calculate the line loss. If so, locate the abnormal user and prompt the meter collection missing error;

[0062] When the lists of condition 1 and condition 2 are both empty, multi-dimensional analysis and calculation of conditions 3-9 are performed as follows:

[0063] Condition 3: Identification of meter replacement wiring errors: Traverse the list of users with meter replacement records within the preset time (15 days) under the jurisdiction of the high-line loss daily area, confirm whether their total power or ABC single-phase power is negative. If so, locate the user and the negative phase, and prompt that the meter replacement wiring is wrong, and suggest checking the meter wiring;

[0064] Condition 4: Photovoltaic metering error identification: traverse the list of newly installed photovoltaic users within the preset time (15 days) under the jurisdiction of the high-line loss daily area, confirm the user's self-generated and self-used daily grid-connected electricity S1, photovoltaic power meter daily electricity F1, confirm the user's electricity consumption Y1=S1+F1, if Y1<0, the user's electricity consumption is negative, locate the user, and prompt that the photovoltaic user's metering error is caused by the connection error of the newly installed photovoltaic meter, and it is recommended to check the photovoltaic user meter connection;

[0065] Condition 5: Overcapacity identification: Traverse the load data F (96 measurement points per day) of users in the high-line loss daily area, compare with the rated capacity E of the user meter, when F>E*1.2 (1.2 is a preset value, which can be adjusted according to demand), locate the user, and calculate the overcapacity integral value through the measurement points where F>E*1.2 among the daily (96) measurement points In the case of multiple users exceeding capacity, the users are sorted from large to small by C', and the users are located. It is prompted that the meter range is exceeded, resulting in an error in the calculation of the user's electricity consumption. It is recommended to replace the meter, and the appropriate model of the replacement meter is provided through the maximum daily load Fmax. When the user is a three-phase user, the load is calculated separately according to each load of ABC, and the phase overcapacity threshold is the rated capacity E / 3;

[0066] Condition 6: Identification of users with sudden electricity consumption reduction: Calculate the average daily electricity consumption AVEDL for the preset time (10 days) before the abnormal line loss of the user. If it is a three-phase user, calculate the average electricity consumption of each phase, A, B, and C phases respectively, and compare it with the electricity consumption GSRDL1 on the day with high line loss. Locate the list of users with sudden electricity consumption reduction of (AVEDL-GSRDL1) / AVEDL<=30%, increase the inspection priority of users with 1.5*DLT>(AVEDL-GSRDL1)>0.5*DLT, and provide feedback on the list of users with sudden electricity consumption reduction and the difference in phases. It will prompt that the meter (phase difference) is faulty or the user is stealing electricity. It is recommended to confirm whether the user has stolen electricity or to inspect the meter and replace the problematic meter.

[0067] Condition 7: Identification of high resistance of meter connector: Identification needs to meet four conditions at the same time: 1. The user switches between low voltage (less than 198V) and normal voltage (220V~230V) more than the preset number of times (3 times) within a day; 2. Identify the correlation between the voltage and current of the meter through the correlation coefficient function corr() (python). If the correlation coefficient value is less than the preset value (-0.9, negative correlation); 3. The user's voltage drops suddenly with the increase of current and exceeds the preset value (20V); 4. The user's maximum current is less than the preset current value (1A). If these four conditions are met at the same time, the user is prompted that the meter connector has high resistance, and it is recommended to remake the meter inlet and outlet connectors to prevent the connector from being damaged and the meter from being burned due to long-term heating;

[0068] Condition 8: Meter abnormality identification: Identify the loss of current, loss of voltage, and extreme three-phase imbalance of user meters in the high-line loss area on days with high line losses. Loss of current means that the maximum daily current of the user on a normal line loss day is greater than the rated current*0.05, and the maximum current of the user on a high line loss day is less than the rated current*0.05; loss of voltage means that the voltage of the user is normal on a normal line loss day, and the voltage of one or more phases of the user is continuously less than the rated voltage*0.8 for a preset number (4) or more measuring points on a high line loss day; extreme three-phase imbalance means that the three-phase is balanced on a normal line loss day, and the three-phase balance degree of a preset number (4) or more measuring points is continuously less than 0.3 on a high line loss day (where the three-phase balance degree = (max (three-phase current) - min (three-phase current)) / max (three-phase current)); if one of the loss of current, loss of voltage, and extreme three-phase imbalance is met, the user will be included in the list of abnormal meter users, indicating that the meter is damaged, and it is recommended to replace the problematic meter;

[0069] Condition 9: Line parameter problem: Use the substation topology and line parameters to identify whether the user's power supply radius is greater than the preset distance (200m) and whether the line diameter meets the minimum conductor diameter design standard. If yes, locate the user and suggest the user to switch to a nearby substation or replace the conductor.

[0070] Furthermore, the damage cause judgment module is specifically implemented as follows:

[0071] Condition 1: Compare the user list Z (collected within 15 days) of the normal line loss day in the area with the user list F2 of the negative line loss day, and locate the difference user list C2 = ZZ∩F2 (users migrated into the area);

[0072] Define the most recent normal line loss daily line loss electricity DLN and abnormal line loss daily line loss electricity DLA, and calculate the sudden line loss electricity DLT = DLA-DLN;

[0073] Through the user power data on the negative line loss day, traverse the daily power consumption of a single user or a combination of multiple users in the difference user list C2. When the user power is greater than DLT*0.7 (sudden power reduction due to line loss) and less than DLT*1.3, list the single user or multiple user combination list X2 that meets the requirement, and sort them from large to small according to power consumption, and prompt the user change relationship error;

[0074] Condition 2: When condition 1 is empty, confirm whether there is a situation where the user's collected electricity is missing on the negative line loss day in the substation area and the estimated electricity is used to calculate the line loss. If so, locate the abnormal user and prompt the meter collection missing error;

[0075] When the lists of condition 1 and condition 2 are both empty, multi-dimensional analysis and calculation of conditions 3-4 are performed as follows:

[0076] Condition 3: Photovoltaic metering error identification: traverse the list of users who installed photovoltaic power in the preset time (15th) under the jurisdiction of the high-loss area, confirm the daily power consumption S2 of the user's self-generated and self-used grid meter, and the daily power consumption F2 of the photovoltaic power meter, and confirm that the user's power consumption Y2=S2+F2. If Y2<0, the user's power consumption is negative, then locate the user, and prompt that the photovoltaic user's metering error is caused by the wiring error of the new photovoltaic installation, and it is recommended to check the photovoltaic user's meter wiring;

[0077] Condition 4: Identification of users with sudden increase in electricity consumption: Calculate the average daily electricity consumption AVEDL within the preset time (10 days) before the abnormal line loss of the user. If it is a three-phase user, calculate the average electricity consumption of each phase, ABC, and compare it with the electricity consumption GSRDL2 on the negative loss day. Locate the list of users with sudden increase in electricity consumption (GSRDL2-AVEDL) / AVEDL>=30%, increase the inspection priority of users with 1.5*DLT>(GSRDL2-AVEDL)>0.5*DLT, and provide feedback on the list of users with sudden increase in electricity consumption and their phases. It will prompt that the metering equipment is faulty or the household-transformer relationship is wrong. On-site verification is recommended. If there is a problem with the meter, replace the problematic meter. If there is an error in the household-transformer relationship, change the ledger.

[0078] Preferably, based on the extraction of the list of problematic users in high line loss and negative line loss areas, the data owner is informed to handle:

[0079] The list of problematic users in high line loss and negative line loss areas extracted by the above algorithm. If the user also has a (95598) work order, the processing priority is increased;

[0080] The user list is linked to the data owner of the problem through the meter reader accountant field in the substation, and the list of problematic users, the cause of the problem and the solution are notified by SMS, making it convenient for front-line personnel to accurately solve line loss problems.

[0081] It is worth mentioning that among the multiple numbers involved in the present invention, such as 1.5*DLT, 0.5*DLT, etc., 1.5 and 0.5 are not the only fixed numbers, but are just preferred numbers, which can be adjusted according to actual needs.

[0082] It is worth mentioning that the technical features such as the substation, electricity consumption information collection system, marketing system, PMS3.0 system involved in the patent application of this invention should be regarded as the prior art. The specific structure, working principle and possible control method and spatial layout method of these technical features can be selected according to the conventional selection in the field, and should not be regarded as the inventive point of the patent of this invention. The patent of this invention will not be further elaborated.

[0083] For those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for identifying and processing the causes of line loss in a transformer area, characterized in that: The following steps are involved: Step S1: Obtain corresponding data of each relevant system and obtain the line loss rate deviation value of the substation; Step S2: Analyze and judge the line loss rate deviation value. If the line loss rate deviation value is greater than the upper limit threshold, enter the high loss cause judgment module; if the line loss rate deviation value is less than the lower limit threshold, enter the negative loss cause judgment module.

2. A method for identifying and processing line loss causes in a transformer area according to claim 1, characterized in that: In step S1, the corresponding data includes: Obtain the actual daily line loss data and theoretical line loss data of the power consumption information collection system, including the corresponding data of line loss rate, line loss quantity, normal line loss date and problem line loss date; Obtain the corresponding data of the power consumption information collection system, including the power supply and power supply load data of the total meter at the substation, as well as the collection missing information, the power consumption and power load data of the users under the substation, and the photovoltaic power generation load data of the users; Obtain the corresponding data of the marketing system, including the corresponding data between the substation and the users under its jurisdiction, the user's new installation data, the change process data, the work order data, the user's photovoltaic ledger data, the meter replacement record data, the corresponding data of the meter rated capacity and the substation transformer rated capacity; Obtain the topology and ledger data of the substation in the PMS3.0 system, including the topological relationship between users and low-voltage trunk lines and low-voltage branch lines, and obtain the low-voltage line length, wire diameter, line model and corresponding unit length impedance data.

3. A method for identifying and processing line loss causes in a transformer area according to claim 2, characterized in that: In step S1, line loss rate deviation value=actual line loss rate-theoretical line loss rate.

4. A method for identifying and processing line loss causes in a transformer area according to claim 3, characterized in that: The high loss cause judgment module is specifically implemented as follows: Condition 1: Compare the user list Z under the normal line loss day of the station area with the user list G under the high line loss day, and locate the difference user list C1 = ZZ∩G; Define the daily line loss electricity DLN of normal line loss and the daily line loss electricity DLA of abnormal line loss, and calculate the sudden increase line loss electricity DLT = DLA-DLN; Through the user power consumption data on the high line loss day, traverse the daily power consumption of a single user or a combination of multiple users in the difference user list C1. When the user power consumption is greater than DLT*0.7 and less than DLT*1.1, list the single user or multiple user combination list X1 that meets the requirements, and sort them from large to small according to power consumption, and prompt the user-to-user relationship error; Condition 2: When condition 1 is empty, confirm whether there is a situation where the user's collected electricity is missing on the high line loss day in the substation area and the estimated electricity is used to calculate the line loss. If so, locate the abnormal user and prompt the meter collection missing error; When the lists of condition 1 and condition 2 are both empty, multi-dimensional analysis and calculation of conditions 3-9 are performed as follows: Condition 3: Identification of meter replacement wiring errors: Traverse the list of users with meter replacement records within the preset time under the jurisdiction of the high-line loss daily area, confirm whether their total power or ABC single-phase power is negative, and if so, locate the user and the negative phase, and prompt that the meter replacement wiring is wrong, and suggest checking the meter wiring; Condition 4: Photovoltaic metering error identification: traverse the list of newly installed photovoltaic users within the preset time under the jurisdiction of the high-line loss daily area, confirm the daily electricity consumption of the user's self-generated and self-used grid-connected meter S1, the daily electricity consumption of the photovoltaic power meter F1, confirm the user's electricity consumption Y1=S1+F1, if Y1<0, the user's electricity consumption is negative, locate the user, and prompt that the photovoltaic user's metering error is caused by the wiring error of the newly installed photovoltaic meter, and it is recommended to check the photovoltaic user's meter wiring; Condition 5: Overcapacity identification: traverse the load data F of users in the high-line loss daily area, compare it with the rated capacity E of the user meter, and when F>E*1.2, locate the user and calculate the overcapacity integral value through the daily measurement points where F>E*1.2 In the case of multiple users exceeding capacity, the users are sorted from large to small by C', and the users are located. It is prompted that the meter range is exceeded, resulting in an error in the calculation of the user's electricity consumption. It is recommended to replace the meter, and the appropriate model of the replacement meter is provided through the maximum daily load Fmax. When the user is a three-phase user, the load is calculated separately according to each load of ABC, and the phase overcapacity threshold is the rated capacity E / 3; Condition 6: Identification of users with sudden power reduction: Calculate the average daily power consumption AVEDL of the user in the preset time before the abnormal line loss. If it is a three-phase user, calculate the average power consumption of each phase for each ABC phase, and compare it with the power consumption GSRDL1 on the day with high line loss. Locate the list of users with sudden power reduction of (AVEDL-GSRDL1) / AVEDL<=30%, increase the inspection priority of users with 1.5*DLT>(AVEDL-GSRDL1)>0.5*DLT, feedback the list of users with sudden power reduction and their phases, prompt the meter metering equipment failure or the user stealing electricity, and suggest to confirm whether the user has stolen electricity or to detect the meter and replace the problematic meter; Condition 7: Identification of high resistance of meter connector: Identification requires the simultaneous satisfaction of four conditions:

1. The user switches between low voltage and normal voltage more than a preset number of times per day; 2 is to identify the correlation between the voltage and current of the meter through the correlation coefficient function corr(). If the correlation coefficient value is less than the preset value; 3 is that the user's voltage drops suddenly with the increase of current and exceeds the preset value; 4 is that the user's maximum current is less than the preset current value. If all four conditions are met at the same time, it will prompt the user that the meter connector has high resistance and it is recommended to remake the meter inlet and outlet connectors to prevent connector loss and meter burning caused by long-term heating; Condition 8: Meter abnormality identification: Identify the loss of current, loss of voltage, and extreme three-phase imbalance of user meters in the high-line loss area on days with high line losses. Loss of current means that the user's maximum daily current on a normal line loss day is greater than the rated current*0.05, and the user's maximum current on a high line loss day is less than the rated current*0.05; loss of voltage means that the user's voltage is normal on a normal line loss day, and the voltage of one or more phases of the user is continuously less than the rated voltage*0.8 for a preset number of measuring points or more on a high line loss day; extreme three-phase imbalance means that the user's three-phase is balanced on a normal line loss day, and the three-phase balance degree is continuously less than 0.3 for a preset number of measuring points or more on a high line loss day; if any of the loss of current, loss of voltage, and extreme three-phase imbalance is met, the user will be included in the list of abnormal meter users, indicating that the meter is damaged, and it is recommended to replace the problematic meter; Condition 9: Line parameter problem: Use the substation topology and line parameters to identify whether the user's power supply radius is greater than the preset distance and whether the line diameter meets the minimum conductor diameter design standard. If so, locate the user and suggest the user to switch to a nearby substation or replace the conductor.

5. A method for identifying and processing line loss causes in a transformer area according to claim 4, characterized in that: The specific implementation of the damage cause judgment module is as follows: Condition 1: Compare the user list Z under the normal line loss day of the station area with the user list F2 under the negative line loss day, and locate the difference user list C2 = ZZ∩F2; Define the most recent normal line loss daily line loss electricity DLN and abnormal line loss daily line loss electricity DLA, and calculate the sudden line loss electricity DLT = DLA-DLN; Through the user power consumption data on the negative line loss day, traverse the daily power consumption of a single user or a combination of multiple users in the difference user list C2. When the user power consumption is greater than DLT*0.7 and less than DLT*1.3, list the single user or multiple user combination list X2 that meets the requirements, and sort them from large to small according to power consumption, and prompt the user-to-user relationship error; Condition 2: When condition 1 is empty, confirm whether there is a situation where the user's collected electricity is missing on the negative line loss day in the substation area and the estimated electricity is used to calculate the line loss. If so, locate the abnormal user and prompt the meter collection missing error; When the lists of condition 1 and condition 2 are both empty, multi-dimensional analysis and calculation of conditions 3-4 are performed as follows: Condition 3: Photovoltaic metering error identification: traverse the list of users who have newly installed photovoltaic power at the preset time in the high-loss area, confirm the user's self-generated and self-used daily grid-connected electricity S2, photovoltaic power meter daily electricity F2, confirm the user's electricity consumption Y2=S2+F2, if Y2<0, the user's electricity consumption is negative, then locate the user, and prompt that the photovoltaic user's metering error is caused by the wiring error of the newly installed photovoltaic meter, and it is recommended to check the photovoltaic user meter wiring; Condition 4: Identification of users with sudden increase in electricity consumption: Calculate the average daily electricity consumption AVEDL within the preset time before the abnormal line loss of the user. If it is a three-phase user, calculate the average electricity consumption of each phase, A, B, and C phases respectively, and compare it with the electricity consumption GSRDL2 on the negative loss day, locate the list of users with sudden increase in electricity consumption (GSRDL2-AVEDL) / AVEDL>=30%, increase the inspection priority of users with 1.5*DLT>(GSRDL2-AVEDL)>0.5*DLT, and provide feedback on the list of users with sudden increase in electricity consumption and their phases, prompting that the metering equipment is faulty or the household-transformer relationship is incorrect, and recommend on-site verification. If there is a problem with the meter, replace the problematic meter; if there is an error in the household-transformer relationship, change the ledger.

6. A method for identifying and processing line loss causes in a transformer area according to claim 5, characterized in that: Based on the list of problematic users in high line loss and negative line loss areas, inform the data owner to handle: The list of problematic users in high line loss and negative line loss areas extracted by the above algorithm, if the user has a work order at the same time, the processing priority will be increased; The user list is linked to the data owner of the problem through the meter reader accountant field in the substation, and the list of problematic users, the cause of the problem and the solution are notified by SMS, making it convenient for front-line personnel to accurately solve line loss problems.

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