CN115940429A - Data acquisition and line loss analysis method based on broadband carrier - Google Patents
Data acquisition and line loss analysis method based on broadband carrier Download PDFInfo
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Abstract
The invention discloses a data acquisition and line loss analysis method based on broadband carrier waves, which comprises the following steps: an AI module is embedded into a main node module CCO to construct a distribution room AI management unit, and edge calculation is sunk into a concentrator carrier communication module; performing multivariate data synchronous acquisition on the electric quantity, power and load of each station equipment in the low-voltage station area by utilizing the clock synchronism of broadband carrier communication; establishing communication with a broadband carrier channel by utilizing an AI module, acquiring accurate small data required by AI calculation, and establishing a data analysis model; based on the data analysis, a power supply network topological relation of a transformer area, accurate line loss analysis of the transformer area and power utilization abnormity diagnosis of the transformer area are established; the analysis result is sent to the concentrator through the carrier communication module and is pushed to the master station for display; the invention can realize accurate monitoring and positioning of line loss of each node in the transformer area, improves the positioning speed of abnormal diagnosis, electricity stealing and metering equipment abnormality of the household meter, reduces manual troubleshooting and improves the detection efficiency.
Description
Technical Field
The invention relates to the technical field of power data monitoring, in particular to a data acquisition and line loss analysis method based on broadband carrier waves.
Background
At the present stage, power enterprises have already established power consumer power consumption information acquisition systems to acquire power consumption conditions of all distribution areas. The system accumulates a large amount of power grid data and provides a new method and thought for loss reduction management. However, currently, due to the fact that the number of the transformer areas is large, the base number is large, any meter abnormality affects line loss, the transformer areas are complex in wiring, in-situ in disorder and the like, transformer area line loss data obtained through the prior art are huge and complex, the data quality is still not high, on the other hand, the cause of loss is complex, and a traditional method which only depends on the line loss rate as a decision basis cannot efficiently find out equipment with problems.
At present, the line loss in the power system is mainly monitored by a monitoring terminal deployed at a distribution transformer of a distribution area, and the line loss of each node of the distribution area cannot be accurately monitored and positioned, so that when an abnormal condition occurs at a certain node in the distribution area, the abnormal condition cannot be timely discovered and maintained, and the power supply reliability is reduced; in addition, in the existing power consumption information acquisition system, all power consumption nodes in the distribution room are generally required to be analyzed at the cloud server according to large-scale historical data, and then the comprehensive line loss analysis result of the line is estimated. However, the conventional line loss analysis and evaluation are usually completed in background data centers such as a cloud server, and the cloud server needs to perform comprehensive analysis and processing on mass data when a settlement period is reached, so that the management method has the defects of complex data processing process and delayed monitoring.
Therefore, it is necessary to reduce the manual troubleshooting amount, and to reduce the labor cost while improving the detection efficiency.
Disclosure of Invention
Aiming at the defects in the background technology, the invention provides a data acquisition and line loss analysis method based on broadband carrier waves, which solves the problems that the existing line loss monitoring can not realize the monitoring and positioning of the line loss of each node in a distribution area, so that when an abnormal condition occurs at a certain node in the distribution area, the abnormal condition can not be found and maintained in time, the power supply reliability is reduced, and the manual troubleshooting amount is large; in addition, in the existing power consumption information acquisition system, all power consumption nodes in a distribution room are generally required to be analyzed at a cloud server according to large-scale historical data, so that the comprehensive line loss analysis result of a line is estimated, and the data processing process is complicated.
The technical scheme adopted by the invention for solving the technical problems is as follows: a data acquisition and line loss analysis method based on broadband carriers comprises the following steps: an AI module is embedded into a main node module CCO to construct a distribution room AI management unit, and edge calculation is sunk into a concentrator carrier communication module;
performing multi-data synchronous acquisition on the electric quantity, power and load of each station device in the low-voltage distribution area by utilizing the clock synchronism of broadband carrier communication;
establishing communication with a broadband carrier channel by utilizing an AI module, acquiring accurate small data required by AI calculation, and establishing a data analysis model;
based on the data analysis, a power supply network topological relation of a transformer area, accurate line loss analysis of the transformer area and power utilization abnormity diagnosis of the transformer area are established;
and the analysis result is sent to the concentrator through the carrier communication module and is pushed to a master station for display.
Preferably, the method for synchronously acquiring the metadata of the electric quantity, the power and the load of the equipment at each station of the low-voltage transformer area includes the following steps:
step 1, establishing a broadband carrier communication network for real-time communication in a low-voltage distribution area;
step 2, synchronizing all the devices in the broadband carrier communication network to a common clock NTB;
step 3, the main station starts the AI management unit of the area and initiates a synchronous data acquisition command to the STA equipment in the carrier communication network in a broadcasting mode, the STA equipment calculates the acquisition time after receiving the acquisition command, and starts the acquisition when the time reaches a set value;
after receiving an acquisition command started by a master station, a district AI management unit acquires a current NTB time T1, calculates an NTB value T2 after 900 seconds according to the T1 value, sends the T2 to a whole network STA device in a broadcasting mode, acquires the current NTB time T1 and the acquisition time T2 after the STA device receives a carrier synchronization broadcasting message of the district AI management unit, and acquires data after calculating a waiting time T3;
wherein: t3= T2-T1;
the STA equipment is connected to the end of the electric energy meter and used for collecting voltage, current and power factor data information of the user electric energy meter and storing the data information in a storage module of the STA equipment in a curve data form.
Preferably, the step 2 specifically includes:
the main node module CCO maintains a 32-bit timer NTB _ CCO for the whole power line carrier communication network;
all STA equipment in the broadband carrier communication network must synchronize to a common clock NTB, and all STA equipment maintains a 32-bit timer NTB _ STA locally;
wherein, the frequency and absolute value of the timer NTB _ STA are synchronized with the timer NTB _ CCO of the master node module CCO.
Preferably, the step 3 includes the following steps:
31 After the STA equipment receives the acquisition starting command, the system enters a 96-point acquisition flow, starts first acquisition according to NTB (time delay of network shared clock) delay, and calculates NTB time value T after 900 seconds after the system clears historical cache data;
32 When the timer is up, the timer is started first, then data 1 is acquired, and meanwhile, the system acquires an acquired data list according to an actual ammeter protocol;
33 Receiving the response of the data 1, or collecting the data 2 to the data N in sequence after the retransmission is overtime;
34 ) if the timer T is up, repeating the above step 33), otherwise, executing step 35);
35 Receives the data reading command, finishes the timer after sampling 96 points, packages the data according to the protocol format and sends the data to the concentrator carrier communication module.
Preferably, the STA device is a carrier module at the electric energy meter end.
Preferably, the main node module CCO selects a standard broadband carrier concentrator module.
Preferably, the building of the power supply network topology relationship of the power grid area includes:
controlling the clock error of each STA device within 20us to ensure the synchronism of sampling;
performing cluster analysis on voltage data among different meter boxes to distinguish the different meter boxes;
analyzing the current user address information of the acquisition master station by using an AI algorithm, and improving the identification speed of the topology identification of the distribution room;
checking the user address according to the station area topology identification result, and improving the accuracy of topology identification;
and obtaining an abnormal branch identification result with low correlation between the voltage variation trend of the transformer area and the variation trends of other branches of the transformer area according to the topology analysis and calculation result of the transformer area.
Preferably, the accurate line loss analysis of the transformer area comprises monthly line loss analysis, daily statistical line loss analysis and power line loss analysis;
the monthly line loss analysis is used for identifying and carrying out split-phase statistics on 24-point electricity meter freezing electricity quantity at the end of a day, NTB synchronous electricity quantity and phase, and calculating end-of-day electricity quantity and synchronous clock correction line loss split-phase statistics;
the daily statistical line loss is used for calculating 96 NTB synchronous electric quantity and electric meter hourly frozen electric quantity every day, and acquiring a 96-point synchronous sampling curve and split-phase statistics;
and the power line loss analysis is used for calculating NTB synchronous acquisition power and power factors, calculating power line loss, ensuring clock synchronous power sampling, reducing line loss generated by errors of metering equipment, analyzing instantaneous power of the transformer area and analyzing line loss fluctuation rules of the transformer area.
Preferably, the power utilization abnormity diagnosis of the transformer area comprises a line loss intelligent diagnosis system running on a system platform, and the intelligent diagnosis system comprises clock abnormity diagnosis, electricity stealing analysis, user variation common diagnosis and metering abnormity distribution statistics;
the clock abnormity diagnosis is used for providing quantitative analysis for line loss statistics, daily data acquisition and expense settlement;
the electricity stealing analysis is used for carrying out quantitative analysis on the zero line current abnormity of the electric meter and the live line current abnormity, positioning the abnormal time period of current metering and facilitating manual investigation and analysis;
specifically, a platform area diagnosis database is established by collecting an ammeter data curve and records of uncapping, state words and events, a diagnosis parameter model is trained through an AI algorithm, and the current abnormal metering condition is comprehensively analyzed;
the frequent diagnosis of the household variation is used for carrying out secondary confirmation on the household variation relationship, analyzing and judging the wrong distribution area, the current distribution area and the unknown electric meter;
and the measurement abnormal distribution statistics is used for analyzing and monitoring the abnormal state of the ammeter, clock deviation, wrong wiring, ammeter events and voltage and current states.
Compared with the prior art, the invention has the beneficial effects that: a data acquisition and line loss analysis method based on broadband carrier, through increasing AI arithmetic element to carry on the edge calculation in the host node module CCO, realize AI administrative unit and monitor the carrier channel by oneself, can carry on the data acquisition while the channel is idle, will not produce the influence to the original business; in addition, topology operation is mainly realized in the AI unit, interaction with the master station is avoided frequently, an uplink channel of the concentrator is avoided being occupied frequently, and meanwhile, on the basis of realizing a platform area topology identification technology, a platform area line loss intelligent diagnosis and analysis function is realized;
the distribution room AI management unit carries out abnormality diagnosis, electricity stealing analysis and metering abnormality positioning on the household meter by utilizing high-frequency HPLC (high performance liquid chromatography) high-frequency acquisition characteristics and carrying out comprehensive analysis on electric energy meter data acquisition, user side power supply monitoring, HPLC (high performance liquid chromatography) characteristic data and the like at regular time;
the method has the advantages that a high-precision electrical synchronization curve, event records such as uncovering and status words are collected through a carrier technology, a platform area diagnosis database is established, a diagnosis parameter model is trained through an AI algorithm, the current abnormal metering situation is comprehensively analyzed in combination with the electricity utilization characteristic similarity of peripheral electric meters, and the coverage of various wiring types is realized.
Drawings
Fig. 1 is a schematic flow chart of a data acquisition and line loss analysis method based on broadband carrier according to the present invention;
fig. 2 is a data acquisition flow chart of the broadband carrier-based data acquisition and line loss analysis method thereof according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the present invention provides a technical solution: a data acquisition and line loss analysis method based on broadband carriers comprises the following steps: an AI module is embedded into the main node module CCO to construct a platform area AI management unit, and the edge calculation is sunk into the concentrator carrier communication module; specifically, the AI module establishes communication with a broadband carrier technology channel through an independent UART port, and the storage of the STA carrier module at the electric energy meter end of each station realizes an extension protocol through software upgrading, so that the reading and the transmission of extension data (voltage, current and power factors) are realized. The AI module transmits a copying command to the main node module CCO through a carrier communication protocol command, and then calculates the acquired data through the AI module, so that no new equipment is needed on site, and the improvement cost is saved. The low-voltage area does not need additional equipment, and high-precision data synchronous acquisition and algorithm analysis can be realized through a standard HPLC meter module (software is additionally provided with a synchronous acquisition interface); wherein, the main node module CCO selects a standard broadband carrier concentrator module.
Performing multivariate data synchronous acquisition on the electric quantity, power and load of each station equipment in the low-voltage station area by utilizing the clock synchronism of broadband carrier communication; each station device is a plurality of electric energy meters distributed in a low-voltage distribution area.
Establishing communication with a broadband carrier channel by utilizing an AI module, acquiring accurate small data required by AI calculation, and establishing a data analysis model;
based on the data analysis, a power supply network topological relation of a transformer area, accurate line loss analysis of the transformer area and power utilization abnormity diagnosis are established;
the analysis result is sent to the concentrator through the carrier communication module to the main website of propelling movement demonstrates, this embodiment also can carry out encryption data transmission through bluetooth interface and mobile operation terminal.
The method for synchronously acquiring the multi-element data of the electric quantity, the power and the load of the equipment of each station in the low-voltage transformer area comprises the following steps:
step 1, establishing a broadband carrier communication network for real-time communication in a low-voltage distribution area;
step 2, synchronizing all devices in the broadband carrier communication network to a common clock NTB;
the step 2 specifically comprises the following steps:
the main node module CCO maintains a 32-bit timer NTB _ CCO for the whole power line carrier communication network;
all STA equipment in the broadband carrier communication network must synchronize to a common clock NTB, and all STA equipment maintains a 32-bit timer NTB _ STA locally;
the frequency and the absolute value of the timer NTB _ STA are synchronous with the timer NTB _ CCO of the main node module CCO;
in the embodiment, the STA equipment is an STA carrier module at the electric energy meter end, and the crystal clock frequency of the STA carrier module is within +/-25 ppm of the crystal clock frequency of the CCO of the main node module; the main node module CCO adopts terminal body time as reference time, all STA carrier modules in the whole power line carrier communication network are synchronous with the main node module CCO, and the synchronous error is less than 50us; the master node module CCO has to maintain a 32-bit timer as Network Time Base (NTB), its clock is provided by the 25MIz clock of the master node module CCO, NTB is sent by the "beacon timestamp" in the master node module CCO central beacon, and synchronization of NTB is done by receiving the master node module CCO central beacon.
Step 3, the main station starts the AI management unit of the area and initiates a synchronous data acquisition command to the STA equipment in the carrier communication network in a broadcasting mode, the STA equipment calculates the acquisition time after receiving the acquisition command, and starts the acquisition when the time reaches a set value;
after receiving an acquisition command started by a master station, a station area AI management unit acquires a current NTB time T1, calculates an NTB value T2 after 900 seconds according to the T1 value, sends the T2 to a whole network STA device in a broadcasting mode, acquires the current NTB time T1 and an acquisition time T2 after the STA device receives a carrier synchronization broadcast message of the station area AI management unit, and performs data acquisition after calculating a waiting time T3;
wherein: t3= T2-T1;
the STA equipment is an STA carrier module connected to the electric energy meter end and used for collecting data information such as voltage, current and power factors of a user electric energy meter and storing the data information in a storage module of the STA equipment in a curve data form, and the station area AI management unit can directly acquire historical curve data from the STA carrier module of the electric energy meter end, so that the curve data synchronism and integrity are effectively improved, and reliable data support is provided for subsequent line loss analysis.
Referring to fig. 2, the step 3 includes the following steps:
31 After the STA equipment receives the acquisition starting command, the system enters a 96-point acquisition process, starts first acquisition according to NTB delay of a clock shared by the network, and calculates an NTB time value T after 900 seconds after the system clears historical cache data;
32 When the timer is up, the timer is started first, then data 1 is acquired, and meanwhile, the system acquires an acquired data list according to an actual ammeter protocol;
33 Receiving the response of the data 1, or collecting the data 2 to the data N in sequence after the retransmission is overtime;
34 ) if the timer T is up, repeating the above step 33), otherwise, executing step 35);
35 Receives the read data command, finishes the timer after sampling 96 points, packages the data according to the protocol format and sends the data to the concentrator carrier communication module.
Data acquisition and operation flow description:
(1) The STA carrier module collects 96-point real-time electricity utilization data of the user electric energy meter every day, the data comprises information such as voltage, current and power factor, the collection interval is 15 minutes, the load curve data in 3 days are stored by the carrier communication unit at the same time by considering the memory size and channel conditions of the existing carrier module, then the data in the earliest day are removed, and the data storage space in the current day is vacated;
(2) Synchronous data acquisition is started by a master station, a station area AI management unit broadcasts an acquisition command for multiple times in the whole network after receiving the acquisition command, an electric energy meter terminal STA carrier module calculates acquisition time after receiving the acquisition command, and the acquisition is started after the time is up; after receiving a synchronous acquisition command started by a master station, a distribution room AI management unit acquires a current NTB moment T1, calculates an NTB value T2 after 15 minutes (900 seconds) according to the T1 value, sends the T2 to a whole network STA carrier module in a broadcasting mode, continuously sends 10 broadcasts at intervals of 3 seconds for ensuring the effectiveness of the broadcasts, and recalculates the T2 before each broadcast for ensuring the accuracy of a clock;
(3) The STA carrier module receives an HPLC synchronous broadcast acquisition message of the station area AI management unit, acquires the current NTB time T1 and the acquisition time T2, calculates the waiting time T3= T2-T1, and starts to acquire data after waiting for T3.
The method for constructing the power supply network topological relation of the platform area comprises the following steps:
controlling the clock error of each STA device within 20us to ensure the synchronism of sampling;
performing cluster analysis on voltage data among different meter boxes to distinguish the different meter boxes; in this embodiment, a K-means clustering algorithm (K-means) is adopted, and a basic idea is that, for a given sample set, the sample set is divided into K clusters according to the distance between samples, so that points in the clusters are connected as close as possible, and the distance between the clusters is as large as possible, and a division scheme of the K clusters is searched through iteration, so that a loss function corresponding to a clustering result is minimum.
Because all the ammeter share same section electric wire on same table case, consequently the pressure drop from the summary table to these house tables is approximate equal, because electric wire length is different under the different table casees, the electric current on the electric wire is also different, under the circumstances that has the load, there is the difference in the pressure drop of summary table to between the different table casees, consequently, voltage is approximate equal under same table case, and voltage difference is great between the different table casees, then can be through carrying out cluster analysis to voltage data between the different table casees, thereby reach the purpose of distinguishing the table case.
Analyzing the existing user address information of the acquisition master station by using an AI algorithm, and improving the identification speed of the station area topology identification;
checking the user address according to the station area topology identification result, and improving the accuracy of topology identification;
according to the station area topology analysis and calculation result, the abnormal branch identification result with lower correlation between the station area voltage variation trend and other branch variation trends in the station area is obtained, a necessary analysis result is provided for common knowledge of the household variation in the line loss of the station area, and the investigation efficiency of the household variation common management in the line loss management is improved.
According to the calculation result of the distribution room topology analysis, whether the voltage value of the distribution room electric energy meter is abnormal or not can be detected, the abnormal electric meter with the same voltage variation trend of the household meter under the same branch and the voltage value deviating from the abnormal electric meter with the excessively high or excessively low branch is identified, the misjudgment phenomenon of undervoltage abnormality in the metering abnormality caused by unbalanced three-phase power supply or excessively low power supply voltage is effectively eliminated, the abnormal electric meter is effectively identified, and the accuracy of the metering abnormality judgment is improved.
The accurate line loss analysis of the transformer area comprises monthly line loss analysis, daily statistical line loss analysis and power line loss analysis;
the monthly line loss analysis is used for identifying and carrying out split-phase statistics on 24-point electricity meter freezing electricity quantity at the end of a day, NTB synchronous electricity quantity and phase, and calculating end-of-day electricity quantity and synchronous clock correction line loss split-phase statistics;
the daily statistical line loss is used for calculating 96 NTB synchronous electric quantity and electric meter hour frozen electric quantity every day, and acquiring a 96-point synchronous sampling curve and split-phase statistics;
and the power line loss analysis is used for calculating NTB synchronous acquisition power and power factors, calculating power line loss, ensuring clock synchronous power sampling, reducing line loss generated by errors of metering equipment, analyzing instantaneous power of the transformer area and analyzing line loss fluctuation rules of the transformer area.
According to the method, the high-line-loss time period is analyzed more accurately by adopting the two-dimensional synchronous analysis of the electric quantity line loss and the power line loss of power supply and sale, the basis is provided for line loss abnormal positioning, the curve of 96-point daily line loss of the whole-network ammeter is realized, and the higher-density monitoring curve is realized.
The station area power utilization abnormity diagnosis comprises a line loss intelligent diagnosis system running on a system platform, wherein the intelligent diagnosis system comprises clock abnormity diagnosis, electricity stealing analysis, household variation frequent diagnosis and metering abnormity distribution statistics;
the clock abnormity diagnosis is used for providing quantitative analysis for line loss statistics, daily data acquisition and expense settlement;
the electricity stealing analysis is used for carrying out quantitative analysis on the zero line current abnormity of the electric meter and the live line current abnormity, positioning the abnormal time period of current metering and facilitating manual investigation and analysis;
specifically, a platform area diagnosis database is established by collecting an ammeter data curve and records of uncapping, state words and events, a diagnosis parameter model is trained through an AI algorithm, and the current abnormal metering condition is comprehensively analyzed;
the frequent diagnosis of the household variation is used for carrying out secondary confirmation on the household variation relationship, analyzing and judging the wrong distribution area, the current distribution area and the unknown electric meter;
and the measurement abnormal distribution statistics is used for analyzing and monitoring the abnormal state of the ammeter, clock deviation, wrong wiring, ammeter events and voltage and current states.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. A data acquisition and line loss analysis method based on broadband carrier is characterized in that: the method comprises the following steps:
an AI module is embedded into a main node module CCO to construct a distribution room AI management unit, and edge calculation is sunk into a concentrator carrier communication module;
performing multivariate data synchronous acquisition on the electric quantity, power and load of each station equipment in the low-voltage station area by utilizing the clock synchronism of broadband carrier communication;
establishing communication with a broadband carrier channel by utilizing an AI module, acquiring accurate small data required by AI calculation, and establishing a data analysis model;
based on the data analysis, a power supply network topological relation of a transformer area, accurate line loss analysis of the transformer area and power utilization abnormity diagnosis of the transformer area are established;
and the analysis result is sent to the concentrator through the carrier communication module and is pushed to the master station for display.
2. The method according to claim 1, wherein the method comprises the following steps: the method for synchronously acquiring the multi-element data of the electric quantity, the power and the load of the equipment of each station in the low-voltage transformer area comprises the following steps:
step 1, establishing a broadband carrier communication network for real-time communication in a low-voltage distribution room;
step 2, synchronizing all devices in the broadband carrier communication network to a common clock NTB;
step 3, the main station starts the AI management unit of the area and initiates a synchronous data acquisition command to the STA equipment in the carrier communication network in a broadcasting mode, the STA equipment calculates the acquisition time after receiving the acquisition command, and starts the acquisition when the time reaches a set value;
after receiving an acquisition command started by a master station, a station area AI management unit acquires a current NTB time T1, calculates an NTB value T2 after 900 seconds according to the T1 value, sends the T2 to a whole network STA device in a broadcasting mode, acquires the current NTB time T1 and an acquisition time T2 after the STA device receives a carrier synchronization broadcast message of the station area AI management unit, and performs data acquisition after calculating a waiting time T3;
wherein: t3= T2-T1;
the STA equipment is connected to the end of the electric energy meter and used for collecting voltage, current and power factor data information of the user electric energy meter and storing the data information in a storage module of the STA equipment in a curve data form.
3. The method for data acquisition and line loss analysis based on broadband carriers of claim 2, wherein the method comprises the following steps: the step 2 specifically comprises:
the main node module CCO maintains a 32-bit timer NTB _ CCO for the whole power line carrier communication network;
all STA equipment in the broadband carrier communication network must synchronize to a common clock NTB, and all STA equipment maintains a 32-bit timer NTB _ STA locally;
wherein, the frequency and absolute value of the timer NTB _ STA are synchronized with the timer NTB _ CCO of the master node module CCO.
4. The method according to claim 2, wherein the method comprises the following steps: the step 3 comprises the following steps:
31 After the STA equipment receives the acquisition starting command, the system enters a 96-point acquisition process, starts first acquisition according to NTB delay of a clock shared by the network, and calculates an NTB time value T after 900 seconds after the system clears historical cache data;
32 When the timer is up, the timer is started first, then data 1 is acquired, and meanwhile, the system acquires an acquired data list according to an actual ammeter protocol;
33 Receiving the data 1 response, or collecting data 2 to data N in sequence after the retransmission is overtime;
34 ) if the T timer is up, the above step 33) is executed repeatedly, otherwise, step 35) is executed;
35 Receives the data reading command, finishes the timer after sampling 96 points, packages the data according to the protocol format and sends the data to the concentrator carrier communication module.
5. The method for data acquisition and line loss analysis based on wideband carrier as claimed in any of claims 2-4, wherein: and the STA equipment is a carrier module at the electric energy meter end.
6. The method for data acquisition and line loss analysis based on broadband carriers of claim 1, wherein the method comprises the following steps: and the main node module CCO selects a standard broadband carrier concentrator module.
7. The method according to claim 1, wherein the method comprises the following steps: the building of the power supply network topological relation of the platform area comprises the following steps:
controlling the clock error of each STA device within 20us to ensure the synchronism of sampling;
performing cluster analysis on voltage data among different meter boxes to distinguish the different meter boxes;
analyzing the existing user address information of the acquisition master station by using an AI algorithm, and improving the identification speed of the station area topology identification;
checking the user address according to the station area topology identification result, and improving the accuracy of topology identification;
and obtaining an abnormal branch identification result with low correlation between the voltage variation trend of the transformer area and the variation trends of other branches of the transformer area according to the topology analysis and calculation result of the transformer area.
8. The method for data acquisition and line loss analysis based on broadband carriers of claim 1, wherein the method comprises the following steps: the accurate line loss analysis of the transformer area comprises monthly line loss analysis, daily statistical line loss analysis and power line loss analysis;
the monthly line loss analysis is used for identifying and carrying out split-phase statistics on 24-point electricity meter freezing electricity quantity at the end of a day, NTB synchronous electricity quantity and phase, and calculating end-of-day electricity quantity and synchronous clock correction line loss split-phase statistics;
the daily statistical line loss is used for calculating 96 NTB synchronous electric quantity and electric meter hour frozen electric quantity every day, and acquiring a 96-point synchronous sampling curve and split-phase statistics;
and the power line loss analysis is used for calculating NTB synchronous acquisition power and power factors, calculating power line loss, ensuring clock synchronous power sampling, reducing line loss generated by errors of metering equipment, analyzing instantaneous power of the transformer area and analyzing line loss fluctuation rules of the transformer area.
9. The method according to claim 1, wherein the method comprises the following steps: the station area power utilization abnormity diagnosis comprises a line loss intelligent diagnosis system running on a system platform, wherein the intelligent diagnosis system comprises clock abnormity diagnosis, electricity stealing analysis, household variation frequent diagnosis and metering abnormity distribution statistics;
the clock abnormity diagnosis is used for providing quantitative analysis for line loss statistics, daily data acquisition and expense settlement;
the electricity stealing analysis is used for carrying out quantitative analysis on the zero line current abnormity of the electric meter and the live line current abnormity, positioning the abnormal time period of current metering and facilitating manual investigation and analysis;
specifically, a platform area diagnosis database is established by collecting an ammeter data curve and records of uncapping, state words and events, a diagnosis parameter model is trained through an AI algorithm, and the current abnormal metering condition is comprehensively analyzed;
the frequent diagnosis of the household variation is used for carrying out secondary confirmation on the household variation relationship, analyzing and judging the wrong distribution area, the current distribution area and the unknown electric meter;
and the measurement abnormal distribution statistics is used for analyzing and monitoring the abnormal state of the ammeter, clock deviation, wrong wiring, ammeter events and voltage and current states.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116582603A (en) * | 2023-07-13 | 2023-08-11 | 北京前景无忧电子科技股份有限公司 | Low-voltage station clock level data acquisition method based on HPLC+HRF communication |
| CN117638881A (en) * | 2023-11-20 | 2024-03-01 | 国网江苏省电力有限公司南京供电分公司 | Method for analyzing line loss reason based on edge calculation in HPLC (high Performance liquid chromatography) platform area |
| CN118627695A (en) * | 2024-08-13 | 2024-09-10 | 江苏电力信息技术有限公司 | Power data optimization method and system based on time sequence mask |
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2023
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116582603A (en) * | 2023-07-13 | 2023-08-11 | 北京前景无忧电子科技股份有限公司 | Low-voltage station clock level data acquisition method based on HPLC+HRF communication |
| CN116582603B (en) * | 2023-07-13 | 2023-09-22 | 北京前景无忧电子科技股份有限公司 | Low-voltage station clock level data acquisition method based on HPLC+HRF communication |
| CN117638881A (en) * | 2023-11-20 | 2024-03-01 | 国网江苏省电力有限公司南京供电分公司 | Method for analyzing line loss reason based on edge calculation in HPLC (high Performance liquid chromatography) platform area |
| CN118627695A (en) * | 2024-08-13 | 2024-09-10 | 江苏电力信息技术有限公司 | Power data optimization method and system based on time sequence mask |
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