CN-121613236-B - Intelligent debugging method and device for power concentrator

CN121613236BCN 121613236 BCN121613236 BCN 121613236BCN-121613236-B

Abstract

The invention relates to the field of concentrator debugging, and particularly discloses an intelligent power concentrator debugging method and device. The method comprises the steps of building a dynamic composite test scene based on rated working conditions and overlapping a plurality of disturbance factors, dividing working condition fragments, generating test signals, inputting the test signals to a programmable power supply and a load simulator, starting precision and power consumption tests, obtaining a measurement error sequence of basic electric parameters read by a concentrator under each working condition fragment, evaluating precision grades based on the sequence, simultaneously obtaining a power consumption curve of a typical task executed by the concentrator and comparing the power consumption curve with a standard power consumption base line, identifying whether energy consumption is abnormal according to energy consumption characteristic deviation, judging whether the concentrator is qualified according to precision grades and energy consumption abnormality identification results, and marking unqualified working conditions and types. The invention can comprehensively and intelligently evaluate the measurement precision and the power consumption characteristic of the power concentrator under the complex working condition, and improves the authenticity, accuracy and efficiency of debugging.

Inventors

TIAN ZHENCHAO
ZHANG XINLI
REN XUGUANG
SUN LIANGLIANG
Lv Yanquan
XUE QINGPENG
SUN HAO
LIU JUN
CHEN PEIDONG
MU PENGJU

Assignees

山东梅格彤天电气有限公司

Dates

Publication Date: 20260505
Application Date: 20260127

Claims (8)

1. An intelligent debugging method for a power concentrator is characterized by comprising the following steps: Sequentially superposing a plurality of different disturbance factors on the test standard according to a set time window by taking a rated working condition as the test standard, constructing a dynamic composite test scene, and dividing each working condition segment in the test scene; identifying a time point corresponding to each working condition switching in the dynamic composite test scene, and dividing the whole test process into a plurality of continuous working condition fragments by taking the time point as a dividing node; Generating a test signal corresponding to the test scene, and inputting the test signal into a programmable power supply and a load simulator through test software to start precision test and power consumption test; acquiring a plurality of groups of original sampling values of basic electric parameters read by a concentrator under each working condition segment, comparing the values with a true value to obtain a measurement error sequence, and evaluating the precision grade based on the measurement error sequence; the method for evaluating the precision level comprises the following steps: d1, extracting a measurement error allowable range of each basic electric parameter from a preset database; D2, respectively comparing a plurality of measurement error values of each basic electric parameter in each working condition segment with corresponding measurement error allowable ranges, counting the number of the measurement error values exceeding the allowable ranges in each electric parameter, and calculating the ratio of the number to the total number of the measurement error values of the corresponding electric parameters to obtain the measurement out-of-tolerance ratio of the electric parameters; d3, judging whether the current working condition segment meets any one of the following conditions: (1) The measurement out-of-tolerance ratio of any electrical parameter is larger than a preset ratio threshold; (2) The whole measurement error sequence with any electric parameter has monotonically increasing trend; if yes, judging that the precision grade corresponding to the working condition segment is a preset appointed precision grade, and skipping a subsequent grading step; if not, executing the step D4; D4, based on the measurement error sequence of each electric parameter under each working condition segment, generating measurement error distribution of each electric parameter, and determining measurement precision scores corresponding to each electric parameter according to a mapping relation between preset measurement error distribution and measurement precision scores; calculating the average value of the measurement precision scores corresponding to the electric parameters, and taking the calculation result as the comprehensive measurement precision score of the working condition segment; Determining the precision grade corresponding to the working condition segment according to the comprehensive measurement precision scoring range corresponding to the preset different precision grades; D5, counting the precision grade corresponding to each working condition segment; acquiring a power consumption curve of a concentrator for executing a typical task under each working condition segment, comparing the power consumption curve with a preset standard power consumption base line, and identifying whether the energy consumption is abnormal or not according to the deviation degree of the power consumption curve and the standard power consumption base line on the energy consumption characteristics; And judging whether the concentrator is qualified or not according to the precision grade assessment result and the energy consumption abnormality identification result under each working condition segment, and marking unqualified working conditions and types.
2. The intelligent debugging method of the power concentrator of claim 1, wherein the method for constructing the dynamic composite test scene comprises the following steps: defining operation parameters under rated working conditions; Selecting a plurality of disturbance factors from a preset power grid disturbance factor library, and configuring attribute information of each disturbance factor; Determining the superposition sequence of disturbance factors, and setting a time window for superposition between two adjacent disturbance factors, wherein only one disturbance factor is applied to each superposition; The rated working condition is taken as a test standard, after a first set period of time is set for stable operation under the rated working condition, a first disturbance factor is overlapped, and a second disturbance factor is continuously overlapped after the time window is reached, and overlapping is carried out according to the sequence until all disturbance factors are overlapped; And after the last disturbance factor is overlapped and the second set time duration is continued, recovering to the rated working condition, thereby completing the construction of the dynamic composite test scene.
3. The intelligent debugging method of the power concentrator of claim 1, wherein the acquisition method of the measurement error sequence comprises the following steps: setting a plurality of sampling time points under each working condition segment respectively; Acquiring a plurality of groups of original sampling values of basic electric parameters read from a communication interface of the concentrator under each working condition segment, and constructing an actually measured electric parameter data set corresponding to each working condition segment, wherein the basic electric parameters comprise voltage, current, power, electric energy and frequency; Synchronously acquiring a plurality of groups of real values of corresponding basic electric parameters output by the programmable power supply and the load simulator, and constructing a real electric parameter data set corresponding to each working condition segment; and comparing the actually measured electric parameter data set with the actual electric parameter data set point by point under each working condition segment, counting a plurality of measurement error values of each basic electric parameter in each working condition segment, and sequencing according to sampling time to form a measurement error sequence of each electric parameter under each working condition segment.
4. The intelligent debugging method of the power concentrator of claim 1, wherein the method for generating the measurement error distribution comprises the following steps: uniformly dividing the allowable range of the measurement error of the electric parameter into a plurality of intervals; Counting the number of measurement errors falling into each interval according to the measurement error sequence of the electric parameter to obtain the measurement error frequency corresponding to each interval; and drawing a histogram based on the frequency, and generating a measurement error distribution of the electric parameter.
5. The intelligent debugging method for the power concentrator of claim 1, wherein the method for identifying whether the energy consumption is abnormal comprises the following steps: Acquiring a curve of the change of the electric power of the concentrator with time when executing each typical task under each working condition segment by a high-precision power analyzer connected in series in a power supply loop of the concentrator, so as to obtain a corresponding power consumption curve; based on the power consumption curve, extracting actual energy consumption characteristics, wherein the energy consumption characteristics comprise steady-state power consumption average value, transient power consumption peak value and power consumption fluctuation frequency; Extracting corresponding energy consumption characteristics from preset standard power consumption baselines corresponding to typical tasks to serve as standard energy consumption characteristics; Comparing the actual energy consumption characteristics of the concentrator for executing each typical task under each working condition segment with the standard energy consumption characteristics, and calculating the deviation degree of the energy consumption characteristics; if the deviation degree of the energy consumption characteristics when executing a typical task under a certain working condition segment is larger than a set deviation degree threshold, judging that the energy consumption of the working condition segment is abnormal, otherwise, judging that the energy consumption is normal; and summarizing the energy consumption abnormality recognition results of all the working condition fragments.
6. The intelligent debugging method of the power concentrator of claim 5, wherein the method for calculating the deviation of the energy consumption characteristic comprises the following steps: acquiring actual values of various energy consumption characteristics and corresponding standard values thereof when a typical task is executed, calculating the difference value between each actual value and the corresponding standard value, and obtaining the single deviation degree of various energy consumption characteristics based on the ratio of the difference value to the standard value; and carrying out linear weighted fusion analysis on each single deviation according to the preset weight of each energy consumption characteristic to obtain the comprehensive energy consumption characteristic deviation.
7. The intelligent debugging method of the power concentrator of claim 1, wherein the method for judging whether the concentrator is qualified comprises the following steps: If the precision level of the concentrator under all working condition segments is not lower than the preset expected precision level and the energy consumption of the concentrator under all working condition segments is identified as normal, judging that the concentrator is qualified, otherwise, judging that the concentrator is unqualified.
8. An intelligent debugging device of a power concentrator, which is characterized by comprising: The scene building module sequentially superimposes a plurality of different disturbance factors on the test standard according to a set time window by taking a rated working condition as a test standard, builds a dynamic composite test scene and divides each working condition segment in the test scene; the signal application module generates a test signal corresponding to the test scene, and inputs the test signal into the programmable power supply and the load simulator through test software so as to start precision test and power consumption test; The precision analysis module is used for acquiring a plurality of groups of original sampling values of basic electric parameters read by the concentrator under each working condition segment, comparing the original sampling values with a true value to obtain a measurement error sequence, and evaluating the precision grade based on the measurement error sequence; the method for evaluating the precision level comprises the following steps: d1, extracting a measurement error allowable range of each basic electric parameter from a preset database; D2, respectively comparing a plurality of measurement error values of each basic electric parameter in each working condition segment with corresponding measurement error allowable ranges, counting the number of the measurement error values exceeding the allowable ranges in each electric parameter, and calculating the ratio of the number to the total number of the measurement error values of the corresponding electric parameters to obtain the measurement out-of-tolerance ratio of the electric parameters; d3, judging whether the current working condition segment meets any one of the following conditions: (1) The measurement out-of-tolerance ratio of any electrical parameter is larger than a preset ratio threshold; (2) The whole measurement error sequence with any electric parameter has monotonically increasing trend; if yes, judging that the precision grade corresponding to the working condition segment is a preset appointed precision grade, and skipping a subsequent grading step; if not, executing the step D4; D4, based on the measurement error sequence of each electric parameter under each working condition segment, generating measurement error distribution of each electric parameter, and determining measurement precision scores corresponding to each electric parameter according to a mapping relation between preset measurement error distribution and measurement precision scores; calculating the average value of the measurement precision scores corresponding to the electric parameters, and taking the calculation result as the comprehensive measurement precision score of the working condition segment; Determining the precision grade corresponding to the working condition segment according to the comprehensive measurement precision scoring range corresponding to the preset different precision grades; D5, counting the precision grade corresponding to each working condition segment; the energy consumption analysis module is used for acquiring a power consumption curve of the concentrator for executing typical tasks under each working condition segment, comparing the power consumption curve with a preset standard power consumption base line, and identifying whether the energy consumption is abnormal or not according to the deviation degree of the power consumption curve and the standard power consumption base line on the energy consumption characteristics; And the comprehensive judging module is used for judging whether the concentrator is qualified or not and marking unqualified working conditions and types according to the precision grade evaluation result and the energy consumption abnormality recognition result under each working condition segment.

Description

Intelligent debugging method and device for power concentrator Technical Field The invention relates to the field of concentrator debugging, in particular to an intelligent power concentrator debugging method and device. Background Along with the continuous promotion of smart power grids construction, the electric power concentrator is used as a key intermediate device for connecting the electric energy meter and the main station system, and plays important roles of data acquisition, communication forwarding, protocol conversion and the like. The stability and measurement accuracy of the electrical performance directly influence the accuracy of electric energy metering, line loss analysis and load regulation. Therefore, the comprehensive and reliable performance test of the power concentrator before delivery and in daily operation and maintenance is of great significance. At present, the detection of the power concentrator is mainly focused on the aspects of communication function, protocol consistency, basic electric energy metering precision and the like, and a static and discrete test method is generally adopted, for example, point-to-point precision verification is carried out on voltage and current under rated conditions. However, the method has the obvious defects that (1) static spot inspection and test scene coverage are insufficient, the actual power grid has complex working conditions such as power factor fluctuation, harmonic pollution, load transient and the like, and the traditional test method is difficult to simulate the dynamic conditions, so that the measurement performance of the concentrator in the actual environment cannot be comprehensively estimated. (2) The electrical performance evaluation dimension is single, the existing detection is focused on the measurement precision of the electrical parameters, and the power consumption characteristics of the concentrator in different working modes are ignored. The power consumption characteristic is an important index reflecting the stability of the internal circuit of the equipment, the quality of the components and the potential defects, and a systematic testing and evaluating means is lacking at present. (3) The method has the advantages that the judgment rule is simple, the intelligent degree is low, the abnormal judgment is dependent on manual setting of a fixed threshold, if the error exceeds +/-0.5%, the failure is unqualified, the intermittent abnormality, transient power consumption peak and other complex fault forms cannot be identified in the method, the intelligent judgment mechanism based on multi-feature fusion is lacking, the missed judgment and the misjudgment are easy to occur, and the debugging efficiency and the product reliability are affected. Disclosure of Invention In view of this, in order to solve the problems set forth in the background art, an intelligent debugging method and device for a power concentrator are provided. The invention solves the technical problems by adopting the technical scheme that the invention provides an intelligent debugging method of an electric power concentrator, which comprises the following steps of S1, taking a rated working condition as a test reference, sequentially superposing a plurality of different disturbance factors on the test reference according to a set time window, constructing a dynamic composite test scene, and dividing each working condition segment in the test scene. S2, generating a test signal corresponding to the test scene, and inputting the test signal into the programmable power supply and the load simulator through test software to start precision test and power consumption test. S3, acquiring a plurality of groups of original sampling values of basic electric parameters read by the concentrator under each working condition segment, comparing the values with the true values to obtain a measurement error sequence, and evaluating the precision grade based on the measurement error sequence. S4, acquiring a power consumption curve of the concentrator for executing typical tasks under each working condition segment, comparing the power consumption curve with a preset standard power consumption base line, and identifying whether the energy consumption is abnormal or not according to the deviation degree of the power consumption curve and the standard power consumption base line on the energy consumption characteristics. S5, judging whether the concentrator is qualified or not and marking unqualified working conditions and types according to the precision grade assessment result and the energy consumption abnormality identification result under each working condition segment, wherein the types are at least one of precision out of tolerance and energy consumption abnormality. The intelligent debugging device of the power concentrator comprises a scene building module, wherein the scene building module takes rated working conditions as test benchmarks, sequentially superim