CN111525697B - Medium and low voltage power distribution network electricity larceny prevention method and system based on current monitoring and line topology analysis - Google Patents
Medium and low voltage power distribution network electricity larceny prevention method and system based on current monitoring and line topology analysis Download PDFInfo
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- H—ELECTRICITY
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- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
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Abstract
The invention discloses a method and a system for preventing electricity stealing of a medium and low voltage distribution network based on current monitoring and circuit topology analysis, which can meet the application of electricity stealing prevention of the medium and low voltage distribution network. The method has great improvement on the conditions that the conventional power distribution network electricity larceny prevention detection and measurement is difficult, the resolution ratio is low, the accuracy rate is low, the manufacturing cost is high, the large-scale application is difficult, and the like.
Description
Technical Field
The invention relates to the fields of electrical engineering, instrument science and technology and signal processing, relates to the technical direction of high voltage, and particularly relates to a method and a system for preventing electricity stealing of a medium and low voltage power distribution network based on current monitoring and line topology analysis.
Background
The electricity stealing behavior not only directly affects the economic profit of the power company, but also can damage power supply equipment with high price, affect normal network operation, even cause large-area power failure due to illegal operation, cause fire disasters, cause huge economic loss and harm to personal safety.
The existing electricity stealing method mainly comprises an electricity meter electricity stealing method and a shared wire connection method, wherein the electricity stealing method mainly aims at an electric energy meter monitoring terminal, and an electricity thief changes the normal connection of a current loop of the electric energy meter or directly changes the proportion and the polarity of a mutual inductor in a specific mode so as to change the normal phase relation of voltage, current or the two in an electric energy meter coil and achieve the purpose of reducing the electric quantity of the electric energy meter; the latter uses electricity by connecting branch line on the power supply line or directly crossing the electric energy meter to achieve the purpose of electricity stealing. But whatever electricity stealing mode is shown in the electricity quantity of the user or the electricity quantity of the regional line loss.
Aiming at the electricity stealing modes, in addition to hardware electricity stealing prevention measures such as a prying-resistant lead seal and a special metering box, an electricity stealing prevention method based on electricity meter data analysis is developed at home and abroad, and electricity consumption state parameters of a user, including voltage, current, power, electric quantity and the like, are monitored in real time as electricity stealing criteria by analyzing data acquired by an electricity consumption information acquisition system. The method mainly comprises the following steps: the method comprises a power stealing prevention method based on a K-means algorithm, a power stealing prevention method based on a large data structured model for power utilization information acquisition, and a power stealing prevention method for analyzing abnormal event parameters. Has good effect in practical application.
The above methods have drawbacks. Firstly, for potential electricity stealing users, the judgment accuracy is poor, which is mainly caused by the fact that electricity consumption data cannot be updated in time and the algorithm does not have a self-learning function. On the one hand, the reduction of user output and the updating of technology can reduce the power demand and reduce the power consumption. On the other hand, when the user increases the electricity consumption, the electricity consumption increases, and at this time, if electricity stealing behavior occurs, the electricity consumption does not necessarily exceed the previously recorded electricity consumption. In addition, the line loss factors are many, and a large error exists only through threshold judgment; secondly, the electricity stealing amount and the electricity stealing time are difficult to judge, and when a plurality of users exist, the small electricity stealing amount of the community is difficult to discover due to the accuracy problem of the electricity meter, untimely meter reading, meter reading omission and the like. Finally, positioning, timing and checking are difficult, a main line of the power distribution network steals power, and the current transformer is sparsely installed due to large current, so that the current transformer is difficult to accurately identify at present. In addition, as the area of the power grid is larger and larger, the structure is more and more complex, and the requirements on the coverage area, the cost and the like of the measuring equipment are higher and higher. Meanwhile, mass and centralized data also cause great burden to a communication network and a data processing system.
Therefore, the novel small-size low-cost current monitoring system is adopted, high-density installation is realized on the power distribution network, the electricity stealing prevention system with accurate and real-time monitoring is developed, reliable electricity stealing prevention monitoring data are obtained, and the method is very important for improving the accuracy of judging whether electricity stealing behaviors exist and preventing and reducing loss caused by the electricity stealing behaviors.
Disclosure of Invention
The invention aims to provide an electricity larceny prevention system which is suitable for engineering practice and can meet the precision requirement of online real-time current monitoring and the accurate positioning requirement of electricity larceny prevention.
In order to achieve the above-mentioned summary of the invention, the present invention provides the following technical solutions.
The system is composed of a plurality of current monitoring systems and a data processing system, wherein each current monitoring system comprises an alternating current measuring front end, a signal conditioning circuit, a signal acquisition circuit, a microprocessor, a communication circuit and an online electricity-taking circuit; wherein,
the alternating current measurement front end is used for measuring the current on the trunk line and the branch line; the signal conditioning circuit is used for conditioning the signal from the alternating current measuring front end into a signal which can be identified by the signal acquisition circuit; the signal acquisition circuit converts the signal sent by the signal conditioning circuit from analog quantity to digital quantity and transmits the digital quantity to the microprocessor; after receiving the signal, the microprocessor compares the measured current with a set current threshold value, judges the running state of the line, stores abnormal data and the time of the abnormal condition, and realizes the monitoring and recording of electricity stealing behavior; the communication line is used for networking and data transmission with the data processing system; the online power-taking circuit is used for taking power from a line for the use of the whole current monitoring system; when the system is used, a group of current monitoring systems are installed at two ends of a branch point of a transformer area to monitor line current, and once suspected electricity stealing behavior occurs, whether electricity stealing occurs or not is accurately judged according to the quantity relation among the currents measured at the front ends of the alternating current measurement in the group and the circuit topological structure, electricity stealing data is recorded, and an electricity stealing position is obtained.
The invention has the further improvement that the current monitoring system is divided into a trunk current monitoring system arranged at a trunk monitoring point of the T-connection and a branch current monitoring system arranged at a branch monitoring point of the T-connection, the trunk current monitoring system and the branch current monitoring system respectively monitor the current on the trunk line and the branch line, and a current monitoring system is arranged on each monitoring point and each line in parallel; a current monitoring group is formed by a trunk current monitoring system and a branch current monitoring system which are positioned on two sides of the branch point.
The invention has the further improvement that the trunk current monitoring system and the branch current monitoring system are only different on a communication circuit, wherein the communication circuit of the branch current monitoring system comprises a power line carrier communication circuit and an infrared communication circuit, the power line carrier communication circuit is used for the communication between different current monitoring systems on the same power line, and the communication comprises the communication between the branch current monitoring system and the communication between the branch current monitoring system and the trunk current monitoring system; the infrared communication circuit is used for communication between current monitoring systems on different power lines at the same monitoring point; the main current monitoring system comprises a power line carrier communication circuit and an infrared communication circuit, and also comprises a remote wireless communication or optical communication circuit which is used for communicating with a data processing system.
The invention has the further improvement that the alternating current measurement front end has good linearity in the measurement range, the conversion of line voltage and measurement voltage is convenient, and the problem of magnetic saturation does not exist; the actual effective resolution of the signal acquisition circuit is not lower than 12 bits, and the sampling frequency is not lower than 1kHz; and the microprocessor receives the multi-channel data uploaded by the alternating current measurement front end and the communication circuit and judges whether the power stealing behavior of the power transmission line exists according to the data of each channel.
The current monitoring system is further improved in that the current monitoring system is suitable for outdoor overhead lines or underground cables, so that the current monitoring system has at least IP 64-level waterproof and dustproof functions as a whole, the total weight of the system is lower than 1 kilogram, and the current monitoring system has anti-electromagnetic interference and lightning protection functions.
In a further improvement of the present invention, the data processing system comprises data processing software, a communication network and a data storage server; wherein,
the data processing software is based on an artificial neural network and is used for processing and analyzing the electricity utilization data of the user; the communication network is used for carrying out data transmission with the intelligent ammeter of the user and each trunk current monitoring system; and the data storage server is used for storing user electricity utilization data, including historical electricity utilization data uploaded by the intelligent electric meter and electricity utilization data transmitted by the main current monitoring system.
The method for preventing electricity stealing of the medium and low voltage distribution network based on current monitoring and line topology analysis is based on the electricity stealing prevention system of the medium and low voltage distribution network based on the current monitoring and the line topology analysis, and the processing and the analysis of the electricity data of the user are carried out according to the following modes:
after the electricity consumption data of the user is input, analyzing historical electricity consumption information of the user by using a K-means algorithm, and extracting electricity consumption characteristics of the user, including electricity consumption and electricity consumption change rate; on the basis, a prediction model formed on the basis of a random forest and a deep belief network is used for selecting different influence factors for different types of users and key users to predict the electricity consumption of the middle-long term and the long term, such as the monthly, the quarterly and the year; finally, according to the electricity utilization characteristics of different users, a characteristic threshold value for predicting the electricity utilization amount is given; in addition, for the users without electricity stealing behavior, the data processing system can update and correct the characteristic threshold value of the predicted electricity consumption according to the electricity consumption data uploaded by the intelligent ammeter.
The invention is further improved in that the electricity larceny prevention monitoring and positioning are carried out as follows:
when the line normally runs, the data processing system analyzes and processes the data uploaded by the intelligent ammeter, and performs feature extraction on the electricity utilization data according to the daily cycle and the annual cycle, so that the interference of normal and periodic electricity utilization data changes on system judgment is avoided;
when electricity stealing behavior occurs, the current monitoring system firstly carries out in-group preliminary judgment: based on a characteristic threshold value of power consumption data provided by a data processing system, a current monitoring system can judge abnormal power consumption data, when the abnormal data are monitored, a branch line current monitoring system firstly judges whether the abnormal data are suspected power consumption data according to the change condition and the duration of the abnormal data, if the abnormal data are detected, the branch line current monitoring system judges a suspected power consumption generation section and a suspected power consumption mode according to the measurement data of each branch line current measuring system through group communication, and sends the suspected power consumption generation section and the suspected power consumption mode to the data processing system for further confirmation; the mains current monitoring system uploads the sensed data to the data processing system at five minute intervals each.
The invention is further improved in that the judgment of whether the electricity stealing behavior exists or not and the classification of the electricity stealing behavior are carried out as follows:
1) For the single-phase power distribution line, when the single-phase power distribution line normally works, the following relationship exists between the current value monitored by the main line measuring unit and the current value monitored by the branch line measuring unit:
i M ≈-i′ M (3)
wherein n represents the number of branches, i M And i' M The current values, Δ i, on the live and neutral lines of the mains, respectively M And delta i' M The allowable error between the current value measured value on the main line live wire and the zero line and the branch current measured value is determined by the accuracy grade of the current transformer; under the normal operation condition, the two are same in size and opposite in direction, and are measured by a trunk line measuring unit; i.e. i j And i' j Respectively representing the current values of the live wire and the zero line on the ith branch, and measuring by each branch measuring unit;
2) When it suddenly appears:
i M ＞-i′ M
and the time lasts for more than 3 seconds, the current value is continuously stable, and the situation that live wire pulling electricity stealing happens on the trunk line is indicated;
if so:
i M ≈-i′ M
and the time lasts for more than 3 seconds, the current value is continuously stable, and the situation that double-wire pulling wire electricity stealing happens to the trunk line is indicated;
the sum of the current data of a plurality of lines and the current data of the branch is unequal, and the current data is in a state of sudden change from top to bottom, so that the problem of electric leakage is suspected to exist;
3) When electricity stealing of the electric meter occurs, the current value of each line still meets the mathematical relations of the formulas (1), (2) and (3), and the data processing system compares the data recorded by the intelligent electric meter, the predicted electricity consumption and the electricity consumption data converted by the current monitoring system; if the electricity consumption data recorded by the intelligent ammeter is lower than the characteristic threshold value of the predicted electricity consumption and the measuring unit does not monitor the situation, the situation indicates that electricity stealing behavior possibly exists; if the electricity consumption data recorded by the intelligent ammeter is within the characteristic threshold value of the predicted electricity consumption, but the electricity consumption data monitored by the current monitoring system exceeds the predicted electricity consumption, electricity stealing behavior or electricity leakage problem is suspected to exist; and if the electricity utilization data recorded by the intelligent electricity meter is consistent with the current monitoring system but exceeds or is lower than the historical electricity utilization data, writing the new data into the database, and performing neural network analysis on the new data by the data processing system.
The invention has at least the following beneficial technical effects:
in the electricity larceny prevention application, the online integrated system is adopted, and can be directly installed on a line to be monitored, so that the monitoring of two electricity larceny modes, namely pull wire electricity larceny and electricity meter electricity larceny, can be realized; the real-time monitoring of the power consumption of the user can be realized, the sampling precision is high, and the accuracy of data is ensured; the anti-theft monitoring system is low in manufacturing cost and simple and convenient to install, can be applied to medium and low voltage distribution networks in a large scale, and ensures the coverage area and the resolution of the anti-theft monitoring network; meanwhile, the invention provides an electricity larceny prevention method based on line topology analysis and neural network-based prediction model analysis by combining the current monitoring system provided by the invention, which comprises the following steps: through the circuit topology analysis, the false alarm caused by factors such as electric leakage and the like is reduced, and meanwhile, the circuit topology analysis method also has certain monitoring capability on newly added equipment; a prediction model is established based on a neural network, and the actual power consumption is compared with the predicted power consumption, so that false alarm caused by factors such as equipment change, season and time change is avoided, the judgment is accurate, and the positioning error is small; the method also has certain learning ability, realizes automatic monitoring by updating data, and reduces the cost of manual maintenance.
Drawings
FIG. 1 is a schematic structural diagram of a measurement unit;
FIG. 2 is a schematic view of the installation and operation principle of the measurement unit;
fig. 3 is a flow chart of the system for preventing electricity theft.
Detailed Description
The invention will be further illustrated and discussed in connection with the figures and examples.
The invention provides a method and a system for preventing electricity stealing of a medium and low voltage power distribution network based on current monitoring and line topology analysis. The schematic structural diagram of the measuring system formed by the method and the connection mode of the measuring system in a power distribution network line are shown in fig. 1 and fig. 3, and the measuring unit comprises a current measuring front end, a signal conditioning circuit, a signal acquisition circuit, a microprocessor, a communication circuit, an online electric energy acquisition circuit and the like.
Specifically, the system for preventing electricity stealing of the medium and low voltage power distribution network based on current monitoring and line topology analysis is composed of a plurality of current monitoring systems and a data processing system, wherein each current monitoring system comprises an alternating current measuring front end, a signal conditioning circuit, a signal acquisition circuit, a microprocessor, a communication circuit and an online electricity taking circuit; the alternating current measurement front end is used for measuring the current on a trunk line and a branch line; the signal conditioning circuit is used for conditioning the signal from the alternating current measuring front end into a signal which can be identified by the signal acquisition circuit; the signal acquisition circuit converts the signal sent by the signal conditioning circuit from analog quantity to digital quantity and transmits the digital quantity to the microprocessor; after receiving the signal, the microprocessor compares the measured current with a set current threshold value, judges the running state of the line, stores abnormal data and the time of the abnormal condition, and realizes the monitoring and recording of electricity stealing behavior; the communication line is used for networking and data transmission with the data processing system; the online power taking circuit is used for taking power from a line to be used by the whole current monitoring system; when the system is used, a group of current monitoring systems are installed at two ends of a branch point of a transformer area to monitor line current, and once suspected electricity stealing behavior occurs, whether electricity stealing occurs or not is accurately judged according to the quantity relation among the currents measured at the front ends of the alternating current measurement in the group and the circuit topological structure, electricity stealing data is recorded, and an electricity stealing position is obtained.
The current monitoring system comprises a trunk current monitoring system arranged at a trunk monitoring point of a T-connection wire and a branch current monitoring system arranged at a branch monitoring point of the T-connection wire, the trunk current monitoring system and the branch current monitoring system respectively monitor currents on a trunk wire and a branch wire, and a current monitoring system is arranged on each monitoring point and each wire in parallel; a current monitoring group is formed by a trunk current monitoring system and a branch current monitoring system which are positioned on two sides of the branch point.
The trunk current monitoring system and the branch current monitoring system are only different in communication circuit, wherein the communication circuit of the branch current monitoring system comprises a power line carrier communication circuit and an infrared communication circuit, the power line carrier communication circuit is used for communication between different current monitoring systems on the same power line, and the communication between the branch current monitoring system and between the branch current monitoring system and the trunk current monitoring system are included; the infrared communication circuit is used for communication between current monitoring systems on different power lines at the same monitoring point; the main current monitoring system comprises a power line carrier communication circuit and an infrared communication circuit, and also comprises a remote wireless communication or optical communication circuit which is used for communicating with a data processing system.
The front end of the alternating current measurement has good linearity in a measurement range, so that the conversion of line voltage and measurement voltage is convenient, and the problem of magnetic saturation does not exist; the actual effective resolution of the signal acquisition circuit is not lower than 12 bits, and the sampling frequency is not lower than 1kHz; and the microprocessor receives the multi-channel data uploaded by the alternating current measurement front end and the communication circuit and judges whether the power stealing behavior of the power transmission line exists according to the data of each channel.
The current monitoring system is suitable for outdoor overhead lines or underground cables, so that the whole current monitoring system has at least IP 64-level waterproof and dustproof functions, the total weight of the system is lower than 1 kilogram, and the current monitoring system has certain anti-electromagnetic interference and lightning protection functions.
The data processing system comprises data processing software, a communication network and a data storage server; the data processing software is based on an artificial neural network and is used for processing and analyzing the power utilization data of the user; the communication network is used for carrying out data transmission with the intelligent ammeter of the user and each trunk current monitoring system; and the data storage server is used for storing user electricity utilization data, including historical electricity utilization data uploaded by the intelligent electric meter and electricity utilization data transmitted by the main current monitoring system.
The signal conditioning circuit shown in fig. 1 includes a plurality of modules that are capable of performing signal conditioning from the current measurement front end. The actual effective resolution of the signal acquisition circuit is not less than 12 bits. The corresponding microprocessor can receive the data synchronously sampled by the acquisition unit, calculate the actual current data and preliminarily judge whether the electricity stealing abnormality exists; the communication circuit comprises an infrared communication device for communication among lines, a power carrier communication circuit for communication on the same line and a wireless or wired communication circuit which is used for communication with a data center on the trunk line measuring unit, wherein the part can be a GPRS communication circuit, an optical fiber communication circuit and the like. The microprocessor can transmit real-time measurement data to the data processing system through the communication circuit; the microprocessor can be a singlechip, a DSP, an FPGA or other embedded systems and the like. The online electricity taking circuit takes electricity through induction and supplies power to the whole measuring circuit.
The installation schematic diagram of the measuring units is shown in fig. 2, for single-phase electricity, the measuring units are parallelly laid in pairs to ensure the accuracy of infrared communication between lines, because the distribution transformer has blocking performance on power carrier signals, the installation range of the same group is limited only in the same power supply station area, and the trunk line measuring unit and the branch line measuring unit are respectively installed on two sides of a branch point to ensure the effectiveness of communication when the electricity load is high. The installation distance d between the two measurement units on the same line is required to be less than or equal to 100m, and the installation mode of the three-phase power is similar to that of the single-phase power, and is not described again.
Because the power utilization load changes periodically, when the data processing system analyzes the power utilization data uploaded by the intelligent electric meter, the power utilization characteristic threshold value is analyzed according to the month, the season and the year, corresponding time intervals are set based on the power utilization characteristic threshold value, and predicted power utilization characteristic threshold values at different times are transmitted to the main line measuring unit. Meanwhile, the uploaded data are updated, sorted, new power utilization characteristics of the users are extracted, prediction results are updated in time, and the like, so that the accuracy of the system is guaranteed.
The invention provides a medium and low voltage distribution network electricity larceny prevention method based on current monitoring and line topology analysis, wherein the processing and analysis of user electricity utilization data are carried out according to the following modes:
after the electricity consumption data of the user is input, analyzing historical electricity consumption information of the user by using a K-means algorithm, and extracting electricity consumption characteristics of the user, including electricity consumption and electricity consumption change rate; on the basis, a prediction model formed on the basis of a random forest and a deep belief network is used for selecting different influence factors for different types of users and key users to predict the electricity consumption of the middle-long term and the long term, such as the monthly, the quarterly and the year; finally, according to the electricity utilization characteristics of different users, a characteristic threshold value for predicting the electricity utilization amount is given; in addition, for the users without electricity stealing behavior, the data processing system can update and correct the characteristic threshold value of the predicted electricity consumption according to the electricity consumption data uploaded by the intelligent electricity meter.
The electricity larceny prevention monitoring and positioning are carried out according to the following modes:
when the line normally runs, the data processing system analyzes and processes data uploaded by the intelligent ammeter, and performs feature extraction on electricity utilization data according to daily cycle and annual cycle, so that interference on system judgment caused by normal and periodic electricity utilization data changes is avoided;
when electricity stealing behavior occurs, the current monitoring system firstly carries out in-group preliminary judgment: based on the characteristic threshold of the electricity consumption data provided by the data processing system, the current monitoring system can judge abnormal electricity consumption data, when the abnormal data are monitored, the branch current monitoring system firstly judges whether the abnormal data are suspected electricity stealing data according to the change condition and the duration of the abnormal data, if so, the trunk current monitoring system judges a suspected electricity stealing occurrence section and a suspected electricity stealing mode according to the measurement data of each branch current measuring system through group communication and sends the suspected electricity stealing occurrence section and the suspected electricity stealing mode to the data processing system for further confirmation; the mains current monitoring system uploads the sensed data to the data processing system at five minute intervals each.
The judgment of whether the electricity stealing behavior exists or not and the classification of the electricity stealing behavior are carried out according to the following modes:
1) For a single-phase power distribution line, when the single-phase power distribution line normally works, the following relation exists between the current value monitored by the main line measuring unit and the current value monitored by the branch line measuring unit:
i M ≈-i′ M (3)
wherein n represents the number of branches, i M And i' M The current values, Δ i, on the live and neutral mains lines, respectively M And delta i' M The allowable error between the current value measured value on the main line live wire and the zero line and the branch current measured value is determined by the accuracy grade of the current transformer; under the normal operation condition, the two are same in size and opposite in direction, and are measured by a trunk line measuring unit; i.e. i j And i' j Respectively representing the current values of the live wire and the zero line on the ith branch circuit, and measuring by each branch circuit measuring unit;
2) When it suddenly appears:
i M ＞-i′ M
and lasting for more than 3 seconds, the current value is continuously stable, which indicates that live wire pulling electricity stealing occurs on the trunk line;
if so:
i M ≈-i′ M
and lasting for more than 3 seconds, the current value is continuously stable, which indicates that the trunk line has double-wire pull wire electricity stealing;
the sum of the current data of a plurality of lines and the current data of the branch is unequal, and the current data is in a state of sudden change from top to bottom, so that the problem of electric leakage is suspected to exist;
3) When electricity stealing of the electric meter occurs, the current value of each line still meets the mathematical relations of the formulas (1), (2) and (3), and the data processing system compares the data recorded by the intelligent electric meter, the predicted electricity consumption and the electricity consumption data converted by the current monitoring system; if the electricity consumption data recorded by the intelligent ammeter is lower than the characteristic threshold value of the predicted electricity consumption and the measuring unit does not monitor the situation, the situation indicates that electricity stealing behavior possibly exists; if the electricity consumption data recorded by the intelligent ammeter is within the characteristic threshold value of the predicted electricity consumption, but the electricity consumption data monitored by the current monitoring system exceeds the predicted electricity consumption, electricity stealing behavior or electricity leakage problem is suspected to exist; and if the electricity utilization data recorded by the intelligent electricity meter is consistent with the current monitoring system but exceeds or is lower than the historical electricity utilization data, writing the new data into the database, and performing neural network analysis on the new data by the data processing system.
The embodiment is as follows:
this embodiment will briefly explain the implementation process in conjunction with the schematic structure of the measuring unit of fig. 1, the schematic structure of the device for preventing electric theft of magnetic field cancellation of fig. 2, and the schematic diagram of the system for preventing electric theft of fig. 3.
Supposing that the voltage grade of a medium and low voltage distribution network where the measuring device is located is less than or equal to 10kV, and the highest current is in the hundred ampere grade, magnetic rings with different wire diameters are selected according to different transmission line specifications and current grades to form a large current detection front end, and the required measuring accuracy grade is 0.2 grade.
The method comprises the steps of firstly, obtaining historical electricity utilization data through a database, extracting characteristic values of the historical electricity utilization data of a user through a data processing program, and obtaining a threshold value and a change rule of the historical electricity utilization data.
According to different current grades, measuring devices with different specifications are respectively installed at main lines and branch lines of the power distribution network, and current on the lines is monitored in real time. Under the condition of normal operation, according to the line topology relation, the current of the wire has the following relation:
i A ＝i a +i b
i A′ ＝i a′ +i b′
i A ＝-i A′
at this time, the trunk line measuring unit communicates with the data processing system once at regular intervals, and only current change data and duration are uploaded, so that the amount of uploaded data is reduced, and the load of the data processing system is reduced.
If the current data is abnormal, for example: i.e. i A ＞i a +i b ,i A′ ＝i a′ +i b′ (ii) a Indicating that the live wire leaks electricity or the live wire is pulled to steal electricity between the monitoring points 1 and 3. At the moment, the main line measuring unit starts timing and further analyzes current data, if the data are stable and continuous, electricity stealing behavior is suspected to exist, and the main line measuring unit uploads the recorded data to a data processing system for further processing; if the data is continuous but fluctuates up and down, the leakage is suspected to exist, and the measuring unit is uploaded to the data processing system for processing.
In addition, when the current of the wire meets the mathematical relation of normal operation, the data processing system finds the following abnormal conditions by comparing the data recorded by the intelligent electric meter, the predicted electricity consumption and the electricity consumption data converted by the measuring unit:
1) If the electricity consumption data recorded by the intelligent ammeter is lower than the characteristic threshold value of the predicted electricity consumption and the measuring unit does not monitor the situation, the electricity stealing behavior is indicated;
2) The electricity consumption data recorded by the intelligent ammeter is within the characteristic threshold value of the predicted electricity consumption, but the electricity consumption data monitored by the measuring unit exceeds the characteristic threshold value of the predicted electricity consumption, so that electricity stealing behavior or electricity leakage problem is suspected to exist;
3) And if the electricity consumption data recorded by the intelligent ammeter is consistent with the measuring unit but exceeds or is lower than the characteristic threshold value of the predicted electricity consumption, writing the new data into the database, and analyzing the new data by the data processing system.
After receiving the abnormal data, the data processing system interacts with other monitoring systems to further determine whether the data processing system is in a power stealing behavior or other faults, so that the resolution accuracy of the system is improved. And a basis is provided for the on-site screening and punishment of the power staff afterwards.
The foregoing is a further detailed description of the invention in connection with specific embodiments thereof. It should be noted that the embodiments of the present invention are not limited to the above, and that those skilled in the art can make several deductions and extensions without departing from the spirit of the present invention, but should be construed as the scope of protection defined by the appended claims.
Claims (2)
1. The method is characterized in that the method is based on a medium-low voltage distribution network electricity stealing prevention system of current monitoring and line topology analysis, the system is composed of a plurality of current monitoring systems and a data processing system, and each current monitoring system comprises an alternating current measuring front end, a signal conditioning circuit, a signal acquisition circuit, a microprocessor, a communication circuit and an online electricity taking circuit; the alternating current measurement front end is used for measuring the current on a main line and a branch line; the signal conditioning circuit is used for conditioning the signal from the alternating current measurement front end into a signal which can be identified by the signal acquisition circuit; the signal acquisition circuit converts the signal sent by the signal conditioning circuit from analog quantity to digital quantity and transmits the digital quantity to the microprocessor; after receiving the signal, the microprocessor compares the measured current with a set current threshold value, judges the running state of the line, stores abnormal data and the time when an abnormal condition occurs, and realizes the monitoring and recording of electricity stealing behavior; the communication line is used for networking and data transmission with the data processing system; the online power taking circuit is used for taking power from a line to be used by the whole current monitoring system; when the system is used, a group of current monitoring systems are installed at two ends of a branch point of a distribution room to monitor line current, and once suspected electricity stealing behavior occurs, whether electricity stealing occurs or not is accurately judged according to the quantity relation between currents measured at the front ends of the alternating current measurement in the group and a circuit topological structure, electricity stealing data is recorded, and an electricity stealing position is obtained; the current monitoring system is divided into a trunk current monitoring system arranged at a trunk monitoring point of the T-connection and a branch current monitoring system arranged at a branch monitoring point of the T-connection;
the data processing system comprises data processing software, a communication network and a data storage server; the data processing software is based on an artificial neural network and is used for processing and analyzing the electricity utilization data of the user; the communication network is used for carrying out data transmission with the intelligent ammeter of the user and each main current monitoring system; the data storage server is used for storing user electricity consumption data which comprise historical electricity consumption data uploaded by the intelligent ammeter and electricity consumption data transmitted by the main current monitoring system;
the processing and analysis of the user electricity consumption data are carried out as follows:
after the electricity consumption data of the user is input, analyzing historical electricity consumption information of the user by using a K-means algorithm, and extracting electricity consumption characteristics of the user, including electricity consumption and electricity consumption change rate; on the basis, a prediction model formed on the basis of a random forest and a deep belief network is used for selecting different influence factors for different types of users and key users to predict the electricity consumption of the middle and long periods of the month, the quarter and the year; finally, according to the electricity utilization characteristics of different users, a characteristic threshold value for predicting the electricity utilization amount is given; in addition, for users without electricity stealing behaviors, the data processing system can update and correct the characteristic threshold value of the predicted electricity consumption according to the electricity consumption data uploaded by the intelligent ammeter;
the judgment of whether the electricity stealing behavior exists or not and the classification of the electricity stealing behavior are carried out according to the following modes:
1) For a single-phase power distribution line, when the single-phase power distribution line normally works, the following relationship exists between the current value monitored by the main line current monitoring system and the current value monitored by the branch line current monitoring system:
i M ≈-i′ M (3)
wherein n represents the number of branches, i M And i' M The current values, Δ i, on the live and neutral mains lines, respectively M And delta i' M The allowable error between the current value measured value on the main line live wire and the zero line and the branch current measured value is determined by the accuracy grade of the current transformer; under the normal operation condition, the two are same in size and opposite in direction, and are measured by a main current monitoring system; i.e. i j And i' j Respectively representing the current values of the live wire and the zero line on the ith branch circuit, and measuring by each branch circuit current monitoring system;
2) When it suddenly appears:
i M >-i′ M
and lasting for more than 3 seconds, the current value is continuously stable, which indicates that live wire pulling electricity stealing occurs on the trunk line;
if so:
i M ≈-i′ M
and the time lasts for more than 3 seconds, the current value is continuously stable, and the situation that double-wire pulling wire electricity stealing happens to the trunk line is indicated;
the sum of the current data of a plurality of lines and the current data of the branch is unequal, and the current data is in a state of sudden change from top to bottom, so that the problem of electric leakage is suspected to exist;
3) When electricity stealing of the electric meter occurs, the current value of each line still meets the mathematical relations of the formulas (1), (2) and (3), and the data processing system compares the data recorded by the intelligent electric meter, the predicted electricity consumption and the electricity consumption data converted by the current monitoring system; if the electricity consumption data recorded by the intelligent ammeter is lower than the characteristic threshold value of the predicted electricity consumption and the current monitoring system does not monitor the situation, the situation indicates that electricity stealing behavior possibly exists; if the electricity consumption data recorded by the intelligent ammeter is within the characteristic threshold value of the predicted electricity consumption, but the electricity consumption data monitored by the current monitoring system exceeds the predicted electricity consumption, electricity stealing behavior or electricity leakage problem is suspected to exist; and if the electricity utilization data recorded by the intelligent electricity meter is consistent with the current monitoring system but exceeds or is lower than the historical electricity utilization data, writing the new data into the database, and performing neural network analysis on the new data by the data processing system.
2. The electricity larceny prevention method for the medium and low voltage power distribution network based on the current monitoring and the line topology analysis as claimed in claim 1, wherein the electricity larceny prevention monitoring and positioning are performed as follows:
when the line normally runs, the data processing system analyzes and processes the data uploaded by the intelligent ammeter, and performs feature extraction on the electricity utilization data according to the daily cycle and the annual cycle, so that the interference of normal and periodic electricity utilization data changes on system judgment is avoided;
when the electricity stealing behavior happens, the current monitoring system firstly carries out the preliminary judgment in the group: based on the characteristic threshold of the power consumption data provided by the data processing system, the current monitoring system can judge abnormal power consumption data, when the abnormal data are monitored, the branch current monitoring system firstly judges whether the abnormal data are suspected power stealing data according to the change condition and the duration of the abnormal data, if so, the trunk current monitoring system judges a suspected power stealing occurrence section and a suspected power stealing mode according to the measurement data of each branch current monitoring system through group communication and sends the suspected power stealing occurrence section and the suspected power stealing mode to the data processing system for further confirmation; the mains current monitoring system uploads the sensed data to the data processing system at five minute intervals each.
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| CN112162136A (en) * | 2020-09-14 | 2021-01-01 | 佰聆数据股份有限公司 | Electricity larceny prevention method and system applied to power distribution network fusion terminal |
| CN112213687B (en) * | 2020-10-10 | 2023-05-16 | 国网四川省电力公司电力科学研究院 | Gateway electric energy meter data anomaly detection method and system based on pseudo-anomaly point identification |
| CN113361608A (en) * | 2021-06-08 | 2021-09-07 | 太原科技大学 | Hidden electricity stealing detection method based on transverse pair bit sum and neural network |
| CN114217124B (en) * | 2021-11-09 | 2024-05-03 | 河南九域腾龙信息工程有限公司 | Fusion terminal with loop inspection function |
| CN113933556B (en) * | 2021-12-17 | 2022-04-08 | 广东电网有限责任公司东莞供电局 | Method and device for detecting electricity stealing behavior, computer equipment and storage medium |
| CN116187825B (en) * | 2023-01-03 | 2024-03-29 | 北京智芯微电子科技有限公司 | Safety electricity utilization detection method and system |
| CN116908533B (en) * | 2023-09-14 | 2023-12-08 | 安徽融兆智能有限公司 | Power consumer electricity consumption information acquisition equipment with metering function |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101216503A (en) * | 2008-01-02 | 2008-07-09 | 武汉国测科技股份有限公司 | Hierarchical type electricity anti-theft system and method |
| CN105092917A (en) * | 2015-07-20 | 2015-11-25 | 河南行知专利服务有限公司 | Electricity theft prevention system |
| CN106093704A (en) * | 2016-06-15 | 2016-11-09 | 国网江苏省电力公司电力科学研究院 | The monitoring of a kind of electrical network stealing user and localization method and system |
| CN106612014A (en) * | 2016-12-29 | 2017-05-03 | 国网浙江余姚市供电公司 | Distribution network anti-electric-larceny monitoring device and distribution network anti-electric-larceny monitoring system |
| CN109615004A (en) * | 2018-12-07 | 2019-04-12 | 江苏瑞中数据股份有限公司 | A kind of anti-electricity-theft method for early warning of multisource data fusion |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN2560148Y (en) * | 2002-03-22 | 2003-07-09 | 李世学 | Electric intelligent protecting & long controlling system |
| JP4588373B2 (en) * | 2004-06-30 | 2010-12-01 | 京セラミタ株式会社 | Power supply, power authentication system |
| CN101179206A (en) * | 2007-09-12 | 2008-05-14 | 刘爱民 | Low-voltage electric network remote monitoring and service network |
| CN101839926A (en) * | 2010-04-20 | 2010-09-22 | 江西电力职业技术学院 | Single-phase three-in electric energy meter for resisting technical electricity larceny |
| MY154570A (en) * | 2010-07-13 | 2015-06-30 | Univ Sains Malaysia | A power metering system and a method of displaying reading derived from the same |
| WO2014019055A1 (en) * | 2012-07-31 | 2014-02-06 | British Columbia Hydro And Power Authority | Method for identifying a system anomaly in a power distribution system |
| CN204514989U (en) * | 2015-04-24 | 2015-07-29 | 国家电网公司 | A kind of anti-electricity-theft warning ammeter box |
| CN109753989A (en) * | 2018-11-18 | 2019-05-14 | 韩霞 | Power consumer electricity stealing analysis method based on big data and machine learning |
-
2020
- 2020-05-09 CN CN202010387452.5A patent/CN111525697B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101216503A (en) * | 2008-01-02 | 2008-07-09 | 武汉国测科技股份有限公司 | Hierarchical type electricity anti-theft system and method |
| CN105092917A (en) * | 2015-07-20 | 2015-11-25 | 河南行知专利服务有限公司 | Electricity theft prevention system |
| CN106093704A (en) * | 2016-06-15 | 2016-11-09 | 国网江苏省电力公司电力科学研究院 | The monitoring of a kind of electrical network stealing user and localization method and system |
| CN106612014A (en) * | 2016-12-29 | 2017-05-03 | 国网浙江余姚市供电公司 | Distribution network anti-electric-larceny monitoring device and distribution network anti-electric-larceny monitoring system |
| CN109615004A (en) * | 2018-12-07 | 2019-04-12 | 江苏瑞中数据股份有限公司 | A kind of anti-electricity-theft method for early warning of multisource data fusion |
Non-Patent Citations (2)
| Title |
|---|
| On-line Condition Monitoring System of Medium-Voltage Switchgear;Zongqian Shi et al.;《IEEE》;20030219;第2290-2294页 * |
| 应用AMI数据的低压配电网精确线损分析;赵磊等;《电网技术》;20151105;第39卷(第11期);第3189-3194页 * |
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