WO2022110558A1 - Smart electricity meter malfunction early warning method and device - Google Patents
Smart electricity meter malfunction early warning method and device Download PDFInfo
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- WO2022110558A1 WO2022110558A1 PCT/CN2021/077142 CN2021077142W WO2022110558A1 WO 2022110558 A1 WO2022110558 A1 WO 2022110558A1 CN 2021077142 W CN2021077142 W CN 2021077142W WO 2022110558 A1 WO2022110558 A1 WO 2022110558A1
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- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
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- the invention relates to the technical field of monitoring of smart electric energy meters, in particular to a method and device for early warning of intelligent electric energy meters.
- the electric energy meter may fail at any time during the long-term use.
- the method of rotating the electric energy meter is usually adopted at present, that is, the sampling inspection is carried out regularly during the use process, and the electric energy meter usage reaches a certain level. After the expiration date, it will be replaced regardless of the actual status. In fact, a large number of expired electric energy meters may still be qualified, and the use of expiration rotation will cause a lot of waste, which is not conducive to energy conservation and environmental protection.
- one solution is to compare the electric energy meter with a high-accuracy standard device at regular intervals, to obtain the electric energy meter error, and determine whether the electric energy meter needs to be replaced by the error.
- this kind of scheme still needs to rely on manual operation, which is not only inefficient and has a large workload, but also it is difficult to find the problem of the electric energy meter in time when the electric energy meter is faulty, and it cannot cover the full capacity of the electric energy meter.
- the technical problem to be solved by the present invention is: aiming at the technical problems existing in the prior art, the present invention provides a fault warning method for a smart electric energy meter with a simple implementation method, a high degree of intelligence, a high degree of complexity, low implementation cost and high precision, and the device.
- the technical scheme proposed by the present invention is:
- a fault early warning method for a smart electric energy meter comprising the steps of:
- the meter operation error analysis model is constructed according to the law of energy conservation and the relationship between the power supply of the total meter in the station area, the actual power consumption of each sub-meter, the fixed loss of the station area, and the sum of line losses in the station area. Obtained, wherein the actual power consumption of each sub-meter is calculated according to the measurement value of each sub-meter and the operation error.
- the operation error analysis model of the electric meter is specifically:
- y(i) is the power supply of the total meter in the i-th cycle
- ⁇ j is the electricity consumption of the j-th sub-meter
- e j is the relative operating error of the j-th sub-meter
- e 0 is the station area Fixed loss
- e y is the line loss rate in the station area
- P is the number of smart meters in the station area.
- step of solving in the step S2 includes:
- ⁇ 0 is the average fixed loss of the M metering periods in the station area
- ⁇ y is the weighted average line of the M metering periods in the station area Loss rate
- ⁇ j is the estimated relative error weighted average of the jth sub-meter in M measurement periods
- the weighted least squares recursive method is specifically used to solve the solving relationship.
- LL(i) is the line loss of the station area in the i-th cycle
- ⁇ j (i) is the metered value of the j-th sub-table in the i-th cycle
- ⁇ k (i) is the i-th sub-table in the k-th sub-table.
- Period measurement value e j is the measurement error of the jth sub-meter
- ⁇ jk is the line loss coefficient
- U j is the voltage of the line at the jth sub-meter
- U k is the voltage of the line at the k-th sub-meter
- P is the number of smart meters in the station area.
- the step S1 also includes a model training step, and the model training step includes: using the historical data of the power supply of the total meter in the station area and the actual power consumption of each sub-meter to train the operation error analysis model of the electric meter, To determine each parameter in the operating error analysis model of the electric meter.
- step S3 if it is determined that the operating error of the target electric energy meter exceeds a preset threshold, an abnormal event correlation analysis is performed to confirm that it is an abnormal electric energy meter. Further judgment is made, if it is judged that it belongs to a new or abnormal station area or the proportion of electricity is less than the preset threshold, it is judged as an observation table to prompt continuous observation, otherwise it is judged as a normal table.
- a fault warning device for a smart electric energy meter comprising:
- the error solving module is used to obtain the measurement values of the target station master meter and each sub-meter in real time, obtain the real-time power supply of the station area total meter and the actual power consumption of each sub-meter, and input them into the meter operation error analysis model for solving. , to obtain the operating error of each sub-meter.
- the analysis model for the operation error of the electric meter is to construct the relationship between the power supply of the total meter in the station area, the actual power consumption of each sub-meter and the fixed loss of the station area, the line loss of the station area, and the measurement error of each sub-meter. The relational model is obtained;
- the fault early warning module is used to obtain the operating error of each sub-meter in real time or regularly for judgment, and if the operating error exceeds a preset value, it controls to send out fault early warning information.
- a fault warning device for a smart electric energy meter comprising a processor and a memory, the memory is used to store a computer program, the processor is used to execute the computer program, and the processor is used to execute the computer program to execute the above method Smart energy meter fault warning device.
- the present invention utilizes the law of energy conservation to conduct online analysis on the running error of the electric energy meter by modeling the unit area of the electric energy meter. Analysis, can remotely monitor the operating error status of the electric energy meter, monitor in real time and discover the electric energy meter with faults and abnormalities in time, and can also accurately locate the electric energy meters with faults and abnormalities, which is convenient for timely detection of faults and abnormal electric energy meters. replace.
- the present invention further, by using the measurement value, voltage and power factor of each sub-meter in multiple cycles, can more accurately characterize the composition of the line loss, build a more accurate line loss model, and further improve the operating error. online monitoring accuracy.
- FIG. 1 is a schematic diagram of the implementation flow of the method and device for early warning of a smart electric energy meter fault in this embodiment.
- Figure 2 is a schematic diagram of the composition principle of the electricity meter in the Taiwan area.
- FIG. 3 is a schematic diagram of the principle of Kirchhoff's law.
- FIG. 4 is a schematic diagram of a diagnostic flow chart of an abnormal electric meter in this embodiment.
- the steps of the smart electric energy meter fault early warning method in this embodiment include:
- the power supply of the total meter, the power consumption of each user meter, the line loss and other fixed losses are inevitable connections supported by physical laws, that is, they conform to the law of energy conservation.
- the user power supply is based on the station area
- a station area is an area where a transformer supplies power
- a transformer usually corresponds to a station area main station M 0
- a station area general table corresponds to multiple sub-user tables M 1 ⁇ Mn
- the power supply of the total meter in the station area is composed of the actual power consumption of each sub-meter, the fixed loss in the station area, the line loss in the station area, and the measurement error of each sub-meter.
- each electric energy meter The characteristics of each electric energy meter are hidden in the overall relationship of the station area. If the electric energy consumption characteristics of each electric energy meter are irrelevant and change continuously in different time periods, by comprehensively analyzing the characteristics in multiple time periods, it is possible to find out the characteristics of each electric energy meter. characteristics of an electric energy meter.
- the above-mentioned law of energy conservation is used to conduct online analysis of the operating error of the electric energy meter by modeling the unit area. Analysis, can remotely monitor the operating error status of the electric energy meter, monitor in real time and discover the electric energy meter with faults and abnormalities in time, and can also accurately locate the electric energy meters with faults and abnormalities, which is convenient for timely detection of faults and abnormal electric energy meters. replace.
- the power supply of the total meter in the station area the actual power consumption of each sub-meter + the fixed loss of the station area + the line loss
- the actual power consumption of each sub-meter the sum of the actual power consumption of each sub-meter * (1-relative error), namely:
- y is the power supply of the total meter in the station area
- ⁇ j is the sub-meter power consumption of the j-th sub-meter (metering point j)
- e j is the relative operating error of the j-th sub-meter (metering point j)
- e 0 is the fixed loss in the station area
- LL is the line loss in the station area
- P is the number of smart meters in the station area.
- the line loss in the station area can be expressed as:
- e y is the line loss rate of the station area.
- y(i) is the power supply of the total meter of the station area in the ith cycle
- e y is the line loss rate of the station area.
- the operation error analysis model of the electric meter is constructed. After obtaining the real-time power supply of the total meter in the station area and the actual power consumption of each sub-meter, the operating error of each sub-meter can be determined by the model, and then the operation error of each sub-meter can be determined. Realize online error analysis.
- the metering error should maintain a constant linear relationship with the metering value through the (0,0) point (that is, there is no zero point error), so that it can be assumed that the relative error weighted average of M metering periods at the beginning of different metering periods The value remains unchanged, and the line loss rate in the station area and other fixed losses in the station area are random within a certain range, and it can be assumed that the weighted average or average value of M metering periods remains unchanged.
- step S2 of this embodiment includes:
- Step S21 Take the metering value data of M cycles of the total table of the station area and each sub-table to carry out a weighted average, and obtain the solving relational formula as:
- ⁇ 0 is the average fixed loss of the M metering periods in the station area
- ⁇ y is the weighted average line loss rate of the M metering periods in the station area
- ⁇ j is the weighted average of the estimated relative running errors of the M metering cycles of the metering point j.
- LL(i) is the line loss of the station area in the i-th cycle
- ⁇ j (i) is the metered value of the j-th sub-table in the i-th cycle
- ⁇ k (i) is the i-th sub-table in the k-th sub-table.
- Period measurement value e j is the measurement error of the jth sub-meter
- ⁇ jk is the line loss coefficient
- U j is the voltage of the line at the jth sub-meter
- U k is the voltage of the line at the k-th sub-meter
- P is the number of smart meters in the station area.
- T is the measurement time period
- R is the resistance value, that is, the line loss coefficient is proportional to the sum of the resistance value and inversely proportional to the measurement time period.
- the measurement value, voltage and power factor of each sub-meter in multiple cycles, according to the above formula (5) can more accurately characterize the composition of the line loss, build a more accurate line loss model, and further improve the operating error. Online monitoring accuracy.
- the above line loss model can accurately evaluate users with a measurement value above 0.1Ib, but for users with a measurement value below 0.1Ib, due to the influence of the quantization error of the total meter, it cannot be accurately evaluated. Users with a large number of users have a great contribution to the line loss, which will lead to inaccurate estimation of the line loss in the station area and distortion of the calculation result in the station area.
- the accuracy of the user line loss analysis below the metering value of 0.1Ib can be further ensured.
- Step S1 of this embodiment also includes a model training step, and the model training step includes: using the historical data of the power supply of the total meter in the station area and the actual power consumption of each sub-meter to train the meter operation error analysis model to determine the operation of the meter The parameters in the error analysis model. Specifically, through system simulation, model training without labeled data can be realized, and appropriate model parameters of the station area can be automatically adapted.
- step S3 of this embodiment if it is determined that the operating error of the target electric energy meter exceeds a preset threshold, an abnormal event correlation analysis is performed to confirm that it is an abnormal electric energy meter, and if it is confirmed to be an abnormal electric energy meter, control to issue a fault Early warning information, otherwise further judgment is made. If it is judged that it belongs to a new or abnormal station or the proportion of electricity is less than the preset threshold, it will be judged as an observation table to indicate that continuous observation is required, otherwise it will be judged as a normal table. Monitor its operating error status to ensure that the online normal operation table is qualified table.
- the goodness of fit R 2 is further used to measure the fitting degree of the regression curve to the observed value.
- the maximum value of R 2 is 1, and the closer the value is to 1, the better the fitting degree.
- the goodness of fit R2 is:
- a i is the real value
- F is the calculated value
- the line loss fitting difference dYerr the smaller the amplitude standard deviation, the better the fitting
- the smaller the mean the better the fitting.
- the error solving module is used to obtain the measurement values of the target station master meter and each sub-meter in real time, obtain the real-time power supply of the station area total meter and the actual power consumption of each sub-meter, and input them into the meter operation error analysis model for solving. , to obtain the operating error of each sub-meter.
- the analysis model for the operation error of the electric meter is to construct the relationship between the power supply of the total meter in the station area, the actual power consumption of each sub-meter and the fixed loss of the station area, the line loss of the station area, and the measurement error of each sub-meter. The relational model is obtained;
- the fault early warning module is used to obtain the operating error of each sub-meter in real time or regularly for judgment, and if the operating error exceeds a preset value, it controls to send out fault early warning information.
- the smart electric energy meter fault early warning device in this embodiment corresponds to the above-mentioned smart electric energy meter fault early warning method, which will not be repeated here.
- the smart electric energy meter fault warning device of the present invention may further include a processor and a memory, where the memory is used for storing a computer program, and the processor is used for executing the computer program, wherein the processor is used for The computer program is executed to execute the above-mentioned method for early warning of a fault of a smart electric energy meter.
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Abstract
Description
本发明涉及智能电表监测技术领域，尤其涉及一种智能电能表故障预警方法及装置。The invention relates to the technical field of monitoring of smart electric energy meters, in particular to a method and device for early warning of intelligent electric energy meters.
电能表在长期的使用过程中随时可能发生故障而失效，为确保电能表计量数据的可靠性，目前通常是采用到期轮换电表的方式，即在使用过程中定时进行抽检，电能表使用达到一定年限后无论实际状态如何均进行更换。而实际上大量到期的电能表仍然可能是合格的，该类采用到期轮换的方式会造成大量的浪费，不利于节能环保。The electric energy meter may fail at any time during the long-term use. In order to ensure the reliability of the measurement data of the electric energy meter, the method of rotating the electric energy meter is usually adopted at present, that is, the sampling inspection is carried out regularly during the use process, and the electric energy meter usage reaches a certain level. After the expiration date, it will be replaced regardless of the actual status. In fact, a large number of expired electric energy meters may still be qualified, and the use of expiration rotation will cause a lot of waste, which is not conducive to energy conservation and environmental protection.
为解决上述问题，一种解决方案即是人工定时将电能表与高准确度等级的标准器进行比较，得到电能表误差，由该误差确定电能表是否需要更换。但是该类方案仍然需要依赖人工操作，不仅效率较低、工作量大，且难以及时在电能表存在故障时发现电能表的问题，也无法覆盖全量电能表。而若考虑采用在线分析的方式来获取电能表的运行误差，由于不同电能表的运行状况会存在差异，不同电能表的用电特性都不相关，且不同时段内是不断变化的，就难以以单个电能表为单位建模实现在线分析。In order to solve the above problem, one solution is to compare the electric energy meter with a high-accuracy standard device at regular intervals, to obtain the electric energy meter error, and determine whether the electric energy meter needs to be replaced by the error. However, this kind of scheme still needs to rely on manual operation, which is not only inefficient and has a large workload, but also it is difficult to find the problem of the electric energy meter in time when the electric energy meter is faulty, and it cannot cover the full capacity of the electric energy meter. However, if the online analysis method is considered to obtain the operating error of the electric energy meter, because the operating conditions of different electric energy meters will be different, the power consumption characteristics of different electric energy meters are not related, and they are constantly changing in different time periods, it is difficult to use A single energy meter is modeled as a unit for online analysis.
【发明内容】[Content of the invention]
本发明要解决的技术问题就在于：针对现有技术存在的技术问题，本发明提供一种实现方法简单、智能化程度高、复杂度以及实现成本低且精度高的智能电能表故障预警方法及装置。The technical problem to be solved by the present invention is: aiming at the technical problems existing in the prior art, the present invention provides a fault warning method for a smart electric energy meter with a simple implementation method, a high degree of intelligence, a high degree of complexity, low implementation cost and high precision, and the device.
为解决上述技术问题，本发明提出的技术方案为：In order to solve the above-mentioned technical problems, the technical scheme proposed by the present invention is:
一种智能电能表故障预警方法，步骤包括：A fault early warning method for a smart electric energy meter, comprising the steps of:
S1.构建台区总表供电量、各分表实际用电量与台区固定损耗、台区线路损耗以及各分表计量误差之间的关系模型，得到电表运行误差分析模型；S1. Build a relationship model between the power supply of the total meter in the station area, the actual power consumption of each sub-meter and the fixed loss in the station area, the line loss in the station area, and the measurement error of each sub-meter, and obtain an analysis model for the operation error of the electric meter;
S2.实时获取指定时长内多个周期的目标台区总表以及各分表的计量值，得到实时的台区总表供电量、各分表实际用电量，并输入至所述电表运行误差分析模型中进行求解，得到各分表的运行误差；S2. Real-time acquisition of the total meter of the target station area and the measurement values of each sub-meter for multiple cycles within a specified period of time, to obtain the real-time power supply of the station area total meter and the actual power consumption of each sub-meter, and input them into the operation error of the electric meter Solve in the analysis model to get the running error of each sub-table;
S3.实时或定时获取各分表的所述运行误差进行判断，若所述运行误差超过预设值则控制发出故障预警信息。S3. Acquire the running error of each sub-meter in real time or regularly for judgment, and if the running error exceeds a preset value, control to issue a fault warning message.
进一步的：所述电表运行误差分析模型具体根据能量守恒定律，按照所述台区总表供 电量为各分表实际用电量与所述台区固定损耗、台区线路损耗之和的关系构建得到，其中所述各分表实际用电量根据各分表的计量值以及运行误差计算得到。Further: the meter operation error analysis model is constructed according to the law of energy conservation and the relationship between the power supply of the total meter in the station area, the actual power consumption of each sub-meter, the fixed loss of the station area, and the sum of line losses in the station area. Obtained, wherein the actual power consumption of each sub-meter is calculated according to the measurement value of each sub-meter and the operation error.
进一步的，所述电表运行误差分析模型具体为：Further, the operation error analysis model of the electric meter is specifically:
其中，y(i)为第i个周期的台区总表供电量，φ j为第j个分表的用电量，e j为第j个分表的相对运行误差，e 0为台区固定损耗，e y为台区线路损耗率，P为台区内智能表的数量。 Among them, y(i) is the power supply of the total meter in the i-th cycle, φ j is the electricity consumption of the j-th sub-meter, e j is the relative operating error of the j-th sub-meter, and e 0 is the station area Fixed loss, e y is the line loss rate in the station area, P is the number of smart meters in the station area.
进一步的，所述步骤S2中进行求解的步骤包括：Further, the step of solving in the step S2 includes:
S21.取台区总表、各分表的M个周期的计量值数据进行加权平均，得到求解关系为：S21. Take the measurement value data of M cycles of the total table of the station area and each sub-meter to perform a weighted average, and obtain the solution relationship as follows:
其中，
S22.将所述台区总表、各分表指定时长内的计量值输入至所述求解关系式中，得到各个分表的运行误差以及台区固定损耗、台区线损率。S22. Input the metering value of the total meter of the station area and each sub-meter within the specified time period into the solving relationship to obtain the running error of each sub-meter, the fixed loss of the station area, and the line loss rate of the station area.
进一步的，所述步骤S32中具体使用加权最小二乘法递归方法求解所述求解关系式。Further, in the step S32, the weighted least squares recursive method is specifically used to solve the solving relationship.
进一步的，所述电表运行误差分析模型中台区线路损耗按照下式计算得到：Further, the line loss in the platform area in the meter operation error analysis model is calculated according to the following formula:
其中，LL(i)为第i个周期的台区线路损耗，φ
j(i)为第j个分表第i个周期的计量值，φ
k(i)为第k个分表第i个周期的计量值，e
j为第j个分表的计量误差，β
jk为线损系数，U
j为第j个分表处线路的电压，U
k为第k个分表处线路的电压，
进一步的，所述步骤S1中还包括模型训练步骤，所述模型训练步骤包括：使用台区 总表供电量、各分表实际用电量的历史数据对所述电表运行误差分析模型进行训练，以确定所述电表运行误差分析模型中各参数。Further, the step S1 also includes a model training step, and the model training step includes: using the historical data of the power supply of the total meter in the station area and the actual power consumption of each sub-meter to train the operation error analysis model of the electric meter, To determine each parameter in the operating error analysis model of the electric meter.
进一步的，所述步骤S3中若判断到目标电能表的所述运行误差超过预设阈值，进行异常事件关联分析以确认为异常电能表，若确认为异常电能表，控制发出故障预警信息，否则进一步进行判断，若判断到属于新建或异常台区或电量占比小于预设阈值，则判定为观察表以提示需持续观测，否则判定为正常表。Further, in the step S3, if it is determined that the operating error of the target electric energy meter exceeds a preset threshold, an abnormal event correlation analysis is performed to confirm that it is an abnormal electric energy meter. Further judgment is made, if it is judged that it belongs to a new or abnormal station area or the proportion of electricity is less than the preset threshold, it is judged as an observation table to prompt continuous observation, otherwise it is judged as a normal table.
一种智能电能表故障预警装置，包括：A fault warning device for a smart electric energy meter, comprising:
误差求解模块，用于实时获取目标台区总表以及各分表的计量值，得到实时的台区总表供电量、各分表实际用电量，并输入至电表运行误差分析模型中进行求解，得到各分表的运行误差，所述电表运行误差分析模型通过构建台区总表供电量、各分表实际用电量与台区固定损耗、台区线路损耗以及各分表计量误差之间的关系模型得到；The error solving module is used to obtain the measurement values of the target station master meter and each sub-meter in real time, obtain the real-time power supply of the station area total meter and the actual power consumption of each sub-meter, and input them into the meter operation error analysis model for solving. , to obtain the operating error of each sub-meter. The analysis model for the operation error of the electric meter is to construct the relationship between the power supply of the total meter in the station area, the actual power consumption of each sub-meter and the fixed loss of the station area, the line loss of the station area, and the measurement error of each sub-meter. The relational model is obtained;
故障预警模块，用于实时或定时获取各分表的所述运行误差进行判断，若所述运行误差超过预设值则控制发出故障预警信息。The fault early warning module is used to obtain the operating error of each sub-meter in real time or regularly for judgment, and if the operating error exceeds a preset value, it controls to send out fault early warning information.
一种智能电能表故障预警装置，包括处理器以及存储器，所述存储器用于存储计算机程序，所述处理器用于执行所述计算机程序，所述处理器用于执行所述计算机程序，以执行上述方法智能电能表故障预警装置。A fault warning device for a smart electric energy meter, comprising a processor and a memory, the memory is used to store a computer program, the processor is used to execute the computer program, and the processor is used to execute the computer program to execute the above method Smart energy meter fault warning device.
与现有技术相比，本发明的优点在于：Compared with the prior art, the advantages of the present invention are:
1、本发明利用能量守恒定律，以台区为单位建模对电能表的运行误差进行在线分析，通过构建电表运行误差分析模型，使用该电表运行误差分析模型对多个周期内实时计量值进行分析，可以对电能表的运行误差状态进行远程监测，实时监控并及时发现存在故障、异常的电能表，同时还能够准确定位到存在故障、异常的电能表，便于及时进行故障、异常电能表的更换。1. The present invention utilizes the law of energy conservation to conduct online analysis on the running error of the electric energy meter by modeling the unit area of the electric energy meter. Analysis, can remotely monitor the operating error status of the electric energy meter, monitor in real time and discover the electric energy meter with faults and abnormalities in time, and can also accurately locate the electric energy meters with faults and abnormalities, which is convenient for timely detection of faults and abnormal electric energy meters. replace.
2、本发明进一步，通过使用多个周期中各分表的计量值、电压以及功率因子，可以更为精确的表征线损的构成，构建得到更为精确的线损模型，进而进一步提高运行误差的在线监测精度。2. The present invention further, by using the measurement value, voltage and power factor of each sub-meter in multiple cycles, can more accurately characterize the composition of the line loss, build a more accurate line loss model, and further improve the operating error. online monitoring accuracy.
图1是本实施例智能电能表故障预警方法及装置的实现流程示意图。FIG. 1 is a schematic diagram of the implementation flow of the method and device for early warning of a smart electric energy meter fault in this embodiment.
图2是台区内电表构成原理示意图。Figure 2 is a schematic diagram of the composition principle of the electricity meter in the Taiwan area.
图3是基尔霍夫定律的原理示意图。Figure 3 is a schematic diagram of the principle of Kirchhoff's law.
图4是本实施例中异常电表诊断流程示意图。FIG. 4 is a schematic diagram of a diagnostic flow chart of an abnormal electric meter in this embodiment.
以下结合说明书附图和具体优选的实施例对本发明作进一步描述，但并不因此而限制本发明的保护范围。The present invention will be further described below with reference to the accompanying drawings and specific preferred embodiments, but the protection scope of the present invention is not limited thereby.
如图1所示，本实施例智能电能表故障预警方法的步骤包括：As shown in FIG. 1 , the steps of the smart electric energy meter fault early warning method in this embodiment include:
S1.构建台区总表供电量、各分表实际用电量与台区固定损耗、台区线路损耗以及各分表计量误差之间的关系模型，得到电表运行误差分析模型；S1. Build a relationship model between the power supply of the total meter in the station area, the actual power consumption of each sub-meter and the fixed loss in the station area, the line loss in the station area, and the measurement error of each sub-meter, and obtain an analysis model for the operation error of the electric meter;
S2.实时获取指定时长内多个周期的目标台区总表以及各分表的计量值，得到实时的台区总表供电量、各分表实际用电量，并输入至所述电表运行误差分析模型中进行求解，得到各分表的运行误差；S2. Real-time acquisition of the total meter of the target station area and the measurement values of each sub-meter for multiple cycles within a specified period of time, to obtain the real-time power supply of the station area total meter and the actual power consumption of each sub-meter, and input them into the operation error of the electric meter Solve in the analysis model to get the running error of each sub-table;
S3.实时或定时获取各分表的所述运行误差进行判断，若运行误差超过预设值则控制发出故障预警信息，以提示需进行更换或故障处理。S3. Obtain the running error of each sub-meter in real time or regularly for judgment, and if the running error exceeds a preset value, control to issue a fault warning message to prompt replacement or fault treatment.
在某个台区下，总表的供电量、各用户表的用电量、线路损耗和其他固定损耗是有物理规律支撑的必然联系的，即符合能量守恒定律。如图2所示，用户供电是以台区为单位，一个台区是一个变压器供电的区域，一个变压器通常对应一个台区总台M 0，一个台区总表下对应多个分用户表M 1～M n，台区总表供电量即为由各分表实际用电量与台区固定损耗、台区线路损耗以及各分表计量误差构成。每个电能表的特征即隐藏在台区的整体关系中，若每只电能表的用电特性都不相关，且不同时段内不断变化，通过综合分析多个时段内的特性，可以查找出每个电能表的特征。 In a certain station area, the power supply of the total meter, the power consumption of each user meter, the line loss and other fixed losses are inevitable connections supported by physical laws, that is, they conform to the law of energy conservation. As shown in Figure 2, the user power supply is based on the station area, a station area is an area where a transformer supplies power, a transformer usually corresponds to a station area main station M 0 , and a station area general table corresponds to multiple sub-user tables M 1 ~ Mn , the power supply of the total meter in the station area is composed of the actual power consumption of each sub-meter, the fixed loss in the station area, the line loss in the station area, and the measurement error of each sub-meter. The characteristics of each electric energy meter are hidden in the overall relationship of the station area. If the electric energy consumption characteristics of each electric energy meter are irrelevant and change continuously in different time periods, by comprehensively analyzing the characteristics in multiple time periods, it is possible to find out the characteristics of each electric energy meter. characteristics of an electric energy meter.
本实施例利用上述能量守恒定律，以台区为单位建模对电能表的运行误差进行在线分析，通过构建电表运行误差分析模型，使用该电表运行误差分析模型对多个周期内实时计量值进行分析，可以对电能表的运行误差状态进行远程监测，实时监控并及时发现存在故障、异常的电能表，同时还能够准确定位到存在故障、异常的电能表，便于及时进行故障、异常电能表的更换。In this embodiment, the above-mentioned law of energy conservation is used to conduct online analysis of the operating error of the electric energy meter by modeling the unit area. Analysis, can remotely monitor the operating error status of the electric energy meter, monitor in real time and discover the electric energy meter with faults and abnormalities in time, and can also accurately locate the electric energy meters with faults and abnormalities, which is convenient for timely detection of faults and abnormal electric energy meters. replace.
由于按照能量守恒定律有：Since according to the law of conservation of energy:
台区总表供电量＝各分表实际用电量+台区固定损耗+线路损耗The power supply of the total meter in the station area = the actual power consumption of each sub-meter + the fixed loss of the station area + the line loss
其中，各分表实际用电量＝各分表实际用电量*(1-相对误差)之和，即有：Among them, the actual power consumption of each sub-meter = the sum of the actual power consumption of each sub-meter * (1-relative error), namely:
其中，y为台区总表供电量，φ j为第j个分表(计量点j)的分表用电量，e j为第j个分表(计量点j)的相对运行误差，e 0为台区的固定损耗，LL为台区线路损耗，P为台区内智能表的数量。 Among them, y is the power supply of the total meter in the station area, φ j is the sub-meter power consumption of the j-th sub-meter (metering point j), e j is the relative operating error of the j-th sub-meter (metering point j), e 0 is the fixed loss in the station area, LL is the line loss in the station area, and P is the number of smart meters in the station area.
台区线路损耗可表示为：The line loss in the station area can be expressed as:
LL＝y(i)e y (2) LL=y(i)e y (2)
其中，e y为台区线路损耗率。 Among them, e y is the line loss rate of the station area.
则有：Then there are:
其中，y(i)为第i个周期台区总表供电量，e y为台区线路损耗率。 Among them, y(i) is the power supply of the total meter of the station area in the ith cycle, and e y is the line loss rate of the station area.
由上式(3)即构建得到电表运行误差分析模型，由该模型在获取实时台区总表供电量、各分表实际用电量后经过求解即可确定出各分表的运行误差，进而实现在线误差分析。From the above formula (3), the operation error analysis model of the electric meter is constructed. After obtaining the real-time power supply of the total meter in the station area and the actual power consumption of each sub-meter, the operating error of each sub-meter can be determined by the model, and then the operation error of each sub-meter can be determined. Realize online error analysis.
在电能计量正常的情况下，计量误差应当与计量值保持恒定过(0,0)点的线性关系(即没有零点误差)，从而可假设不同计量周期开始的M个计量周期的相对误差加权平均值保持不变，且台区线路损耗率和台区其他固定损耗在一定范围内随机性较大，可以假设M个计量周期的加权平均值或平均值保持不变。In the case of normal electric energy metering, the metering error should maintain a constant linear relationship with the metering value through the (0,0) point (that is, there is no zero point error), so that it can be assumed that the relative error weighted average of M metering periods at the beginning of different metering periods The value remains unchanged, and the line loss rate in the station area and other fixed losses in the station area are random within a certain range, and it can be assumed that the weighted average or average value of M metering periods remains unchanged.
本实施例步骤S2中进行求解的步骤包括：The step of solving in step S2 of this embodiment includes:
步骤S21.取台区总表、各分表的M个周期的计量值数据进行加权平均，得到求解关系式为：Step S21. Take the metering value data of M cycles of the total table of the station area and each sub-table to carry out a weighted average, and obtain the solving relational formula as:
其中，
S22.将台区总表、各分表指定时长内的计量值输入至所述求解关系式中，得到各个分表的运行误差以及台区固定损耗、台区线损率。S22. Input the metering value of the total meter of the station area and each sub-meter within the specified time period into the solving relationship to obtain the running error of each sub-meter, the fixed loss of the station area, and the line loss rate of the station area.
本实施例通过采用如上述式(4)的模型，综合多个周期的数据进行分析，可构建得到更为贴近实际工况的线损模型，进而进一步提高运行误差在线监测的精度。In this embodiment, by adopting the model of the above formula (4) and synthesizing the data of multiple cycles for analysis, a line loss model that is closer to the actual working condition can be constructed, thereby further improving the accuracy of the online monitoring of the running error.
进一步的，本实施例考虑构建更精确的线损模型，具体如下所示：Further, this embodiment considers building a more accurate line loss model, which is as follows:
其中，LL(i)为第i个周期的台区线路损耗，φ
j(i)为第j个分表第i个周期的计量值，φ
k(i)为第k个分表第i个周期的计量值，e
j为第j个分表的计量误差，β
jk为线损系数，U
j为第j个分表处线路的电压，U
k为第k个分表处线路的电压，
上述式(5)中具体
如图3所示，按照基尔霍夫定律，在节点U 0处，电流为各支路电流的总和，由于日线损＝瞬时线损之和，瞬时即为时间颗粒度足够小，在该时间段内，用户负载无变化，且台区线损跟电流平方与线路长度的乘积成正比，通常电流大3.3倍，线损贡献即高一个数量。本实施例通过只考虑大用电用户及长线路用户的线损贡献，同时考虑在用电时间段内，用电量类似、用电习惯类似，则对线损的贡献也类似的特性，使用多个周期中各分表的计量值、电压以及功率因子，按照上式(5)，可以更为精确的表征线损的构成，构建得到更为精确的线损模型，进而进一步提高运行误差的在线监测精度。 As shown in Figure 3, according to Kirchhoff's law, at the node U 0 , the current is the sum of the currents of all branches. Since the daily line loss = the sum of the instantaneous line losses, the instant is the time granularity is small enough. During the time period, the user's load does not change, and the line loss in the station area is proportional to the product of the square of the current and the line length. Usually, the current is 3.3 times larger, and the line loss contribution is one amount higher. In this embodiment, by only considering the line loss contribution of large power users and long-line users, and considering the characteristics of similar power consumption and similar power consumption habits during the power consumption time period, the contribution to the line loss is also similar. The measurement value, voltage and power factor of each sub-meter in multiple cycles, according to the above formula (5), can more accurately characterize the composition of the line loss, build a more accurate line loss model, and further improve the operating error. Online monitoring accuracy.
上述线损模型，能够对于0.1Ib计量值以上的用户准确评价，但是对于0.1Ib计量值以下的用户，由于总表量化误差的影响，无法准确评价，如果这部分用户里有负超差很大的用户，对线损贡献很大，会导致台区线损估计不准，台区计算结果失真。本实施例进一步通过自动提取用电量变化的特征时段，并提取日冻结电量信息中与计量点误差相关的特征，再求解模型，可以进一步确保0.1Ib计量值以下的用户线损分析的精度。The above line loss model can accurately evaluate users with a measurement value above 0.1Ib, but for users with a measurement value below 0.1Ib, due to the influence of the quantization error of the total meter, it cannot be accurately evaluated. users with a large number of users have a great contribution to the line loss, which will lead to inaccurate estimation of the line loss in the station area and distortion of the calculation result in the station area. In this embodiment, by automatically extracting the characteristic period of power consumption change, and extracting the features related to metering point errors in the daily frozen power information, and then solving the model, the accuracy of the user line loss analysis below the metering value of 0.1Ib can be further ensured.
本实施例步骤S1中还包括模型训练步骤，模型训练步骤包括：使用台区总表供电量、各分表实际用电量的历史数据对所述电表运行误差分析模型进行训练，以确定电表运行误差分析模型中各参数。具体可通过系统仿真，实现无标注数据的模型训练，自动适配出合适的台区模型参数。Step S1 of this embodiment also includes a model training step, and the model training step includes: using the historical data of the power supply of the total meter in the station area and the actual power consumption of each sub-meter to train the meter operation error analysis model to determine the operation of the meter The parameters in the error analysis model. Specifically, through system simulation, model training without labeled data can be realized, and appropriate model parameters of the station area can be automatically adapted.
如图4所示，本实施例步骤S3中若判断到目标电能表的所述运行误差超过预设阈值，进行异常事件关联分析以确认为异常电能表，若确认为异常电能表，控制发出故障预警信息，否则进一步进行判断，若判断到属于新建或异常台区或电量占比小于预设阈值，则判定为观察表以提示需持续观测，否则判定为正常表，对于观察表后续则需要不断监测其运行误差状态，确保在线运行正常表都是合格表。As shown in FIG. 4 , in step S3 of this embodiment, if it is determined that the operating error of the target electric energy meter exceeds a preset threshold, an abnormal event correlation analysis is performed to confirm that it is an abnormal electric energy meter, and if it is confirmed to be an abnormal electric energy meter, control to issue a fault Early warning information, otherwise further judgment is made. If it is judged that it belongs to a new or abnormal station or the proportion of electricity is less than the preset threshold, it will be judged as an observation table to indicate that continuous observation is required, otherwise it will be judged as a normal table. Monitor its operating error status to ensure that the online normal operation table is qualified table.
本实施例进一步使用拟合优度R 2用于度量回归曲线对观测值的拟合程度，R 2最大值为1，值越接近1拟合程度越好，对统计线损进行拟合，拟合优度R 2为： In this embodiment, the goodness of fit R 2 is further used to measure the fitting degree of the regression curve to the observed value. The maximum value of R 2 is 1, and the closer the value is to 1, the better the fitting degree. The goodness of fit R2 is:
以及使用运行误差计算结果与预期结果的MAE值(Mean Absolute Error)：And the MAE value (Mean Absolute Error) between the calculated result and the expected result using the running error:
其中，A i为真实值，F为计算值，线损拟合差值dYerr，幅度标准偏差越小拟合越好，均值越小拟合越好。 Among them, A i is the real value, F is the calculated value, the line loss fitting difference dYerr, the smaller the amplitude standard deviation, the better the fitting, and the smaller the mean, the better the fitting.
本实施例智能电能表故障预警装置包括：The fault warning device of the smart electric energy meter in this embodiment includes:
误差求解模块，用于实时获取目标台区总表以及各分表的计量值，得到实时的台区总表供电量、各分表实际用电量，并输入至电表运行误差分析模型中进行求解，得到各分表的运行误差，所述电表运行误差分析模型通过构建台区总表供电量、各分表实际用电量与台区固定损耗、台区线路损耗以及各分表计量误差之间的关系模型得到；The error solving module is used to obtain the measurement values of the target station master meter and each sub-meter in real time, obtain the real-time power supply of the station area total meter and the actual power consumption of each sub-meter, and input them into the meter operation error analysis model for solving. , to obtain the operating error of each sub-meter. The analysis model for the operation error of the electric meter is to construct the relationship between the power supply of the total meter in the station area, the actual power consumption of each sub-meter and the fixed loss of the station area, the line loss of the station area, and the measurement error of each sub-meter. The relational model is obtained;
故障预警模块，用于实时或定时获取各分表的所述运行误差进行判断，若所述运行误差超过预设值则控制发出故障预警信息。The fault early warning module is used to obtain the operating error of each sub-meter in real time or regularly for judgment, and if the operating error exceeds a preset value, it controls to send out fault early warning information.
本实施例智能电能表故障预警装置与上述智能电能表故障预警方法对应，在此不再一一赘述。The smart electric energy meter fault early warning device in this embodiment corresponds to the above-mentioned smart electric energy meter fault early warning method, which will not be repeated here.
在另一实施例中，本发明智能电能表故障预警装置还可以为：包括处理器以及存储器，存储器用于存储计算机程序，处理器用于执行所述计算机程序，其特征在于，所述处理器用于执行所述计算机程序，以执行如上述智能电能表故障预警方法。In another embodiment, the smart electric energy meter fault warning device of the present invention may further include a processor and a memory, where the memory is used for storing a computer program, and the processor is used for executing the computer program, wherein the processor is used for The computer program is executed to execute the above-mentioned method for early warning of a fault of a smart electric energy meter.
上述只是本发明的较佳实施例，并非对本发明作任何形式上的限制。虽然本发明已以较佳实施例揭露如上，然而并非用以限定本发明。因此，凡是未脱离本发明技术方案的内容，依据本发明技术实质对以上实施例所做的任何简单修改、等同变化及修饰，均应落在本发明技术方案保护的范围内。The above are only preferred embodiments of the present invention, and do not limit the present invention in any form. Although the present invention has been disclosed above with preferred embodiments, it is not intended to limit the present invention. Therefore, any simple modifications, equivalent changes and modifications made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solutions of the present invention should fall within the protection scope of the technical solutions of the present invention.
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