Abnormal power equipment positioning method and device, equipment and medium

Abstract

The invention discloses an abnormal power equipment positioning method, an abnormal power equipment positioning device, abnormal power equipment positioning equipment and a medium. Determining to-be-selected abnormal power equipment in the abnormal area and line loss rate abnormal data and power consumption behavior abnormal data corresponding to each to-be-selected abnormal power equipment; based on the line loss rate abnormal data and the power consumption behavior abnormal data, determining a correlation coefficient between a line loss abnormal parameter corresponding to each abnormal power device to be selected and an abnormal power consumption parameter; and comparing the correlation coefficient corresponding to each abnormal power device to be selected with a preset coefficient threshold, and determining a target abnormal power device in the abnormal region based on a comparison result. Through the technical scheme of the embodiment of the invention, accurate and automatic positioning of the abnormal power equipment is realized, so that the labor cost is reduced, the positioning efficiency and accuracy of abnormal positioning are improved, and the safety and stability of power grid operation are effectively ensured.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, device, equipment and medium for locating abnormal power equipment. Background Art

[0002] With the development of the power industry, the positioning of abnormal power equipment has important practical significance as a key factor that can directly affect the economic interests of power companies and the normal operation of power systems.

[0003] At present, abnormal power equipment is usually located by manual inspection. However, the traditional abnormal power equipment location method has high labor costs, cannot locate abnormalities in time, and has low efficiency and accuracy in locating abnormal equipment, thus failing to effectively ensure the safety and stability of power grid operation. Summary of the invention

[0004] The present invention provides a method, device, equipment and medium for locating abnormal power equipment to achieve accurate and automatic positioning of abnormal power equipment, thereby reducing labor costs, and can promptly discover abnormal power equipment, improve the positioning efficiency and accuracy of abnormal positioning, and thus effectively ensure the safety and stability of power grid operation.

[0005] In a first aspect, an embodiment of the present invention provides a method for locating abnormal power equipment, comprising:

[0006] Based on the power equipment operation data corresponding to each power equipment in the abnormal area, determining the abnormal power equipment to be selected in the abnormal area and the abnormal line loss rate data and the abnormal power consumption behavior data corresponding to each abnormal power equipment to be selected;

[0007] Based on the abnormal line loss rate data and the abnormal power consumption behavior data, determining a correlation coefficient between an abnormal line loss parameter and an abnormal power consumption parameter corresponding to each abnormal power device to be selected;

[0008] The correlation coefficient corresponding to each abnormal power device to be selected is compared with a preset coefficient threshold, and the target abnormal power device in the abnormal area is determined based on the comparison result.

[0009] In a second aspect, an embodiment of the present invention further provides a device for locating abnormal power equipment, comprising:

[0010] An abnormal data determination module, used to determine the abnormal power equipment to be selected in the abnormal area and the abnormal line loss rate data and the abnormal power consumption behavior data corresponding to each of the abnormal power equipment to be selected in the abnormal area based on the power equipment operation data corresponding to each of the power equipment in the abnormal area;

[0011] A correlation coefficient determination module, used to determine the correlation coefficient between the abnormal line loss parameter and the abnormal power consumption parameter corresponding to each abnormal power device to be selected based on the abnormal line loss rate data and the abnormal power consumption behavior data;

[0012] The abnormality positioning module is used to compare the correlation coefficient corresponding to each candidate abnormal power device with a preset coefficient threshold, and determine the target abnormal power device in the abnormal area based on the comparison result.

[0013] In a third aspect, an embodiment of the present invention further provides an electronic device, characterized in that the electronic device comprises: at least one processor; and

[0014] a memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the abnormal power equipment locating method provided by any embodiment of the present invention.

[0016] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to execute the abnormal power equipment locating method provided by any embodiment of the present invention when executing.

[0017] The technical solution of the embodiment of the present invention provides data support for subsequent processing by determining the abnormal line loss rate data and abnormal power consumption behavior data corresponding to the selected abnormal power equipment in the abnormal area and each selected abnormal power equipment based on the power equipment operation data corresponding to each power equipment in the abnormal area. Based on the abnormal line loss rate data and the abnormal power consumption behavior data, the correlation coefficient between the abnormal line loss parameters and the abnormal power consumption parameters corresponding to each selected abnormal power equipment is determined, which can quantitatively describe the degree of correlation between the abnormal line loss rate and the abnormal power consumption behavior, and provide a scientific basis for abnormal positioning. By comparing the correlation coefficient corresponding to each selected abnormal power equipment with the preset coefficient threshold, and determining the target abnormal power equipment in the abnormal area based on the comparison result, the standardization and normalization of abnormal positioning can be achieved. By comprehensively considering the abnormal line loss rate data and the abnormal power consumption behavior data, as well as the correlation coefficient between them, the abnormal power equipment can be automatically located more accurately, the scope of troubleshooting can be quickly narrowed, and unnecessary manpower, material resources and time investment can be reduced. At the same time, through accurate positioning information, operation and maintenance personnel can find the source of the fault more quickly and repair it, thereby improving the efficiency of fault handling. It can quickly narrow the scope of troubleshooting, reduce unnecessary manpower, material resources and time investment. At the same time, through accurate positioning information, operation and maintenance personnel can find the source of the fault more quickly and repair it, thereby improving the efficiency of fault handling.

[0018] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 is a flow chart of a method for locating abnormal power equipment provided according to Embodiment 1 of the present invention;

[0021] Figure 2 is a flow chart of a method for locating abnormal power equipment provided according to Embodiment 2 of the present invention;

[0022] Figure 3 is a structural schematic diagram of an abnormal power equipment locating device provided according to Embodiment 3 of the present invention;

[0023] Figure 4It is a structural schematic diagram of an electronic device for implementing the abnormal power equipment locating method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "target", "current", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] Embodiment 1

[0027] Figure 1 A flowchart of a method for locating abnormal power equipment is provided for the first embodiment of the present invention. This embodiment is applicable to the situation of locating abnormal power equipment. Figure 1 As shown, the method can be performed by an abnormal power equipment locating device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. Figure 1 As shown, the method specifically comprises the following steps:

[0028] S110. Based on the power equipment operation data corresponding to each power equipment in the abnormal area, determine the abnormal power equipment to be selected in the abnormal area and the abnormal line loss rate data and the abnormal power consumption behavior data corresponding to each of the abnormal power equipment to be selected.

[0029] Among them, the abnormal area may refer to an area where abnormal conditions (such as abnormally high line loss rate, abnormal power consumption behavior, etc.) occur in the power system. Power equipment may refer to equipment used to produce, transform, transmit, distribute and consume electric energy, including two major categories: power generation equipment and power supply equipment. For example, power equipment may be equipment such as electric energy meters and voltmeters. Power equipment operation data may refer to various data generated by power equipment during operation, including power, voltage, current, power factor, etc. These data can be collected by sensors, smart meters and other equipment, and used to analyze the operating status and performance of power equipment. The selected abnormal power equipment may refer to power equipment that may be abnormal in the abnormal area by preliminary analysis of the power equipment operation data. Line loss rate abnormal data may refer to data on abnormal power loss rate caused by various reasons during the transmission of electric energy by power equipment. Abnormal power consumption behavior data may refer to data on abnormal power consumption behavior caused by various reasons during the use of electric energy by users. For example, abnormal power consumption behavior data may refer to abnormal power consumption data of users.

[0030] Specifically, the power equipment operation data corresponding to each power equipment in the abnormal area is collected in real time or regularly from the monitoring system of the power system. The data can cover various key indicators of the power equipment, such as current, voltage, power factor, temperature, etc. The power equipment operation data corresponding to each power equipment is analyzed, and based on the analysis results, the power equipment that may have abnormalities is screened out as the abnormal power equipment to be selected. For each abnormal power equipment to be selected, its corresponding line loss rate abnormal data is extracted, and at the same time, its power consumption behavior abnormal data is extracted. By analyzing the operation data of the power equipment, combined with the line loss abnormal parameters and the power consumption behavior abnormal data, a sufficient data basis is provided for the subsequent positioning of abnormal power equipment.

[0031] Exemplarily, S110 may include: performing anomaly analysis based on the power equipment operation data corresponding to each power equipment in the abnormal area to determine the abnormal power equipment to be selected in the abnormal area; performing abnormal data screening on the power equipment operation data corresponding to the selected abnormal power equipment to determine the line loss rate abnormal data and power consumption behavior abnormal data associated with each abnormal power equipment to be selected.

[0032] Specifically, the operating status and data transmission of each power equipment are monitored regularly, and an abnormal analysis is performed based on the power equipment operating data corresponding to each power equipment in the abnormal area. The power equipment with abnormal data or communication interruption is used as the abnormal power equipment to be selected in the abnormal area. The operating data of each abnormal power equipment to be selected is deeply analyzed to screen out abnormal data related to line loss rate and power consumption behavior. Abnormal line loss rate data may include sudden changes in line loss rate, continuous high or low line loss rate, etc.; abnormal power consumption behavior data may include abnormal fluctuations in power consumption, abnormal changes in load curves, etc. The screened abnormal data is verified to ensure the authenticity and reliability of the data, and the verified abnormal data is organized into a structured format. The abnormal line loss rate data and abnormal power consumption behavior data associated with each abnormal power equipment to be selected are recorded, which helps to locate the fault point more accurately.

[0033] S120. Determine the correlation coefficient between the abnormal line loss parameter and the abnormal power consumption parameter corresponding to each abnormal power equipment to be selected based on the abnormal line loss rate data and the abnormal power consumption behavior data.

[0034] Among them, the abnormal line loss parameter may refer to an indicator used to measure the abnormal degree of power loss caused by various reasons (such as resistance loss, leakage, power theft, etc.) during the transmission of power by power lines. The abnormal power consumption parameter may refer to an indicator reflecting the abnormal degree of user power consumption behavior. These parameters are usually related to the user's power consumption habits, the use of equipment, and possible safety hazards. The correlation coefficient may refer to a statistical indicator used to quantify the closeness of the linear relationship between two variables.

[0035] Specifically, based on the abnormal line loss rate data and the abnormal power consumption behavior data, the abnormal line loss parameters and abnormal power consumption parameters corresponding to each power device are extracted. Providing these parameters should be able to reflect the abnormal state of the power equipment. For each abnormal power device to be selected, the correlation coefficient between them is calculated using the selected statistical method and the extracted abnormal line loss parameters and abnormal power consumption parameters. The correlation coefficient is a value between -1 and 1, which represents the linear relationship or hierarchical correlation between two variables. The larger the value, the stronger the correlation. By calculating the correlation coefficient, the degree of correlation between abnormal line loss and abnormal power consumption behavior can be quantified, so as to more accurately locate the abnormal power equipment.

[0036] Exemplarily, when the abnormal power equipment to be selected is an electric energy meter, the line loss abnormality parameter includes: at least one of the line loss power loss and the line loss abnormality rate. Among them, the line loss power loss can be the total amount of electric energy lost due to line loss within a certain period of time, which can be calculated by the product of line loss power and time. The abnormal increase in line loss power may indicate that there is a problem with the power line. The line loss abnormality rate can be the main indicator to measure the degree of power loss, indicating the percentage of electric energy lost in the power network to the power supply to the power network. When the line loss rate increases abnormally, it may mean that there is a fault in the power line or the transmission efficiency is reduced.

[0037] S130: Compare the correlation coefficient corresponding to each abnormal power device to be selected with a preset coefficient threshold, and determine the target abnormal power device in the abnormal area based on the comparison result.

[0038] The preset coefficient threshold may refer to a preset minimum value of a correlation coefficient corresponding to a target abnormal power device. The target abnormal power device may refer to a power device that is determined to have an abnormality or potential problem.

[0039] Specifically, a reasonable correlation coefficient threshold is set in advance according to the actual situation and operation and maintenance experience of the power system. The selection of the threshold should comprehensively consider factors such as the type of power equipment, operating conditions, and historical fault data. The correlation coefficient value of each candidate abnormal power equipment is compared with the preset coefficient threshold. According to the comparison results, the power equipment with a correlation coefficient exceeding the threshold is screened out as the target abnormal power equipment, so that the abnormal power equipment can be discovered and handled in time, which can ensure the stable operation and power supply reliability of the power system. The screened target abnormal power equipment can also be further verified and confirmed, such as on-site inspection, measurement, etc. Ensure the accuracy of the target abnormal power equipment to avoid false alarms or omissions.

[0040] Exemplarily, "determining the target abnormal power equipment in the abnormal area based on the comparison result" in S130 may include: if there is only one line loss abnormal parameter, then the selected abnormal power equipment whose correlation coefficient between the line loss abnormal parameter and the abnormal power consumption parameter is greater than a preset coefficient threshold is determined as the target abnormal power equipment in the abnormal area; if there are at least two line loss abnormal parameters, then the selected abnormal power equipment whose correlation coefficient between each line loss abnormal parameter and the abnormal power consumption parameter is greater than the preset coefficient threshold is determined as the target abnormal power equipment in the abnormal area.

[0041] Specifically, if there is only one line loss abnormal parameter, the calculated correlation coefficient is compared with the preset coefficient threshold. If the correlation coefficient between the line loss abnormal parameter and the abnormal power consumption parameter of a selected abnormal power device is greater than the preset coefficient threshold, the device is determined as the target abnormal power device; if there are at least two line loss abnormal parameters, for each line loss abnormal parameter, the correlation coefficient between it and the abnormal power consumption parameter of each selected abnormal power device is calculated respectively, and the correlation coefficient between each line loss abnormal parameter and the abnormal power consumption parameter is compared with the preset coefficient threshold. If the correlation coefficients between all line loss abnormal parameters and the abnormal power consumption parameters of a selected abnormal power device are greater than the preset coefficient threshold, the device is determined as the target abnormal power device. By calculating the correlation coefficient and setting the preset coefficient threshold, the selected abnormal power device that has a significant linear relationship with the line loss abnormal parameter can be more accurately identified, thereby avoiding misjudgment and missed judgment.

[0042] The technical solution of the embodiment of the present invention provides data support for subsequent processing by determining the abnormal line loss rate data and abnormal power consumption behavior data corresponding to the selected abnormal power equipment in the abnormal area and each selected abnormal power equipment based on the power equipment operation data corresponding to each power equipment in the abnormal area. Based on the abnormal line loss rate data and the abnormal power consumption behavior data, the correlation coefficient between the abnormal line loss parameters and the abnormal power consumption parameters corresponding to each selected abnormal power equipment is determined, which can quantitatively describe the degree of correlation between the abnormal line loss rate and the abnormal power consumption behavior, and provide a scientific basis for abnormal positioning. By comparing the correlation coefficient corresponding to each selected abnormal power equipment with the preset coefficient threshold, and determining the target abnormal power equipment in the abnormal area based on the comparison result, the standardization and normalization of abnormal positioning can be achieved. By comprehensively considering the abnormal line loss rate data and the abnormal power consumption behavior data, as well as the correlation coefficient between them, the abnormal power equipment can be automatically located more accurately, the scope of troubleshooting can be quickly narrowed, and unnecessary manpower, material resources and time investment can be reduced. At the same time, through accurate positioning information, operation and maintenance personnel can find the source of the fault more quickly and repair it, thereby improving the efficiency of fault handling. It can quickly narrow the scope of troubleshooting, reduce unnecessary manpower, material resources and time investment. At the same time, through accurate positioning information, operation and maintenance personnel can find the source of the fault more quickly and repair it, thereby improving the efficiency of fault handling.

[0043] Embodiment 2

[0044] Figure 2This is a flow chart of a method for locating abnormal power equipment provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment optimizes the step of "determining the correlation coefficient between the abnormal line loss parameter and the abnormal power consumption parameter corresponding to each selected abnormal power equipment based on the abnormal line loss rate data and the abnormal power consumption behavior data". The explanations of the terms that are the same or corresponding to the above embodiments are not repeated here.

[0045] See also Figure 2 Another abnormal power equipment locating method provided in this embodiment specifically includes the following steps:

[0046] S210. Based on the power equipment operation data corresponding to each power equipment in the abnormal area, determine the abnormal power equipment to be selected in the abnormal area and the abnormal line loss rate data and the abnormal power consumption behavior data corresponding to each of the abnormal power equipment to be selected.

[0047] S220: Based on the abnormal line loss rate data and the abnormal power consumption behavior data, determine at least one abnormal line loss parameter value and abnormal power consumption parameter value corresponding to each abnormal power equipment to be selected.

[0048] Among them, the abnormal line loss parameter value may refer to a quantitative indicator reflecting the abnormal degree of power loss caused by various reasons (such as resistance loss, equipment aging, improper maintenance, leakage, power theft, etc.) during the power transmission process of the power line. The abnormal power consumption parameter value may refer to a quantitative indicator reflecting the abnormal degree of the user's power consumption behavior. These parameter values ​​are usually related to the user's power consumption habits, the use status of the equipment, and possible safety hazards.

[0049] Specifically, the collected data is sorted to extract at least one abnormal line loss parameter value (such as line loss rate, line loss power, etc.) and abnormal power consumption parameter value (such as abnormal power consumption fluctuation value, abnormal load curve change value, etc.) corresponding to each device. The extracted data can also be verified to ensure the accuracy and completeness of the data. By collecting, sorting and using abnormal line loss rate data and abnormal power consumption behavior data, the information contained in these data can be fully utilized to improve data utilization.

[0050] Exemplarily, the calculation formula of the above line loss rate is as follows:

[0051]

[0052] The calculation formula for the above line loss is as follows:

[0053]

[0054] Among them, the line loss in the abnormal area is Y, the fixed loss in the substation is A, ε i Indicates the measurement error of power equipment, Indicates the user meter measurement value during the sampling time.

[0055] Exemplarily, S220 may include: performing data cleaning processing on abnormal line loss rate data and abnormal power consumption behavior data to obtain cleaned abnormal line loss rate data and abnormal power consumption behavior data; performing missing value and abnormal value completion processing on the cleaned abnormal line loss rate data and abnormal power consumption behavior data, and determining at least one abnormal line loss parameter value and abnormal power consumption parameter value corresponding to each power equipment based on the completed abnormal line loss rate data and abnormal power consumption behavior data.

[0056] Specifically, the abnormal data of line loss rate and abnormal data of power consumption behavior are cleaned, duplicate data is removed, and each data point is ensured to be unique to avoid repeated calculations; missing data points are filled by appropriate methods (such as interpolation, mean filling, nearest neighbor filling, etc.); outliers in the data (such as extremely high or low values) are identified and corrected, which may be caused by measurement errors, equipment failures or other reasons. On the basis of data cleaning, the missing values ​​that still exist are further filled. According to the distribution and trend of the data, appropriate interpolation methods (such as linear interpolation, polynomial interpolation, etc.) are selected for filling. For time series data, time series-based interpolation methods (such as moving average, exponential smoothing, etc.) can be considered. For the identified outliers, they are corrected or replaced according to their possible causes. If the outliers are caused by equipment failure, it may be necessary to communicate with the equipment maintenance team to obtain more accurate data. If the outliers are caused by measurement errors, appropriate methods can be used to correct them according to the context (such as replacing them with the average value of adjacent data points). According to the cleaned and completed data, the abnormal line loss parameter values ​​(such as line loss rate, line loss power, etc.) and abnormal power consumption parameter values ​​(such as abnormal power consumption fluctuation value, abnormal load curve change value, etc.) corresponding to each power equipment are extracted. By processing missing values ​​and abnormal values, these values ​​can be avoided from having a negative impact on the analysis results, thereby enhancing the reliability of the analysis results.

[0057] Exemplarily, Newton interpolation method can be used as a method to correct missing values, as shown below:

[0058] f(x)=f(x0)+f[x0,x1](x-x0)+f[x0,x1,x2](x-x0)(x-x1)+...

[0059] +f[x0,x1,...x n ](x-x0)...(xx n-1 )

[0060] Among them, f[x0,x1] is called the first-order mean difference about x0, x1, and so on to f[x0,x1,…x n ] is the nth-order mean difference with respect to the function f(x).

[0061] S230. Determine the correlation coefficient between each abnormal line loss parameter and abnormal power consumption parameter corresponding to each abnormal power equipment to be selected based on a preset statistical method, abnormal line loss parameter values, and abnormal power consumption parameter values.

[0062] The preset statistical method may refer to a preset method for calculating the correlation coefficient.

[0063] Specifically, for each abnormal power device to be selected, according to its corresponding abnormal line loss parameter value and abnormal power consumption parameter value, a preset statistical method is used to calculate the correlation coefficient between each abnormal line loss parameter and abnormal power consumption parameter. By calculating the correlation coefficient, the degree of linear relationship between the abnormal line loss parameter and the abnormal power consumption parameter can be quantified, thereby enhancing the accuracy of the analysis.

[0064] Exemplarily, S230 may include: performing a linear analysis on the abnormal line loss parameter and the abnormal power usage parameter based on the Pearson correlation coefficient, and determining a correlation coefficient between the abnormal line loss parameter and the abnormal power usage parameter corresponding to each abnormal power device to be selected.

[0065] Among them, the Pearson correlation coefficient can refer to a statistical indicator used to measure the strength and direction of the linear relationship between two continuous variables.

[0066] Specifically, for each abnormal power equipment to be selected, the Pearson correlation coefficient formula is used to calculate the correlation coefficient between each abnormal line loss parameter and the abnormal power consumption parameter. The value range of the correlation coefficient is between -1 and 1. When the correlation coefficient is close to 1, it indicates that there is a strong positive correlation between the two parameters; when the correlation coefficient is close to -1, it indicates that there is a strong negative correlation; when the correlation coefficient is close to 0, it indicates that there is no obvious linear relationship between the two parameters. By analyzing the correlation coefficient, it is easier to identify the abnormal line loss parameters related to abnormal power consumption behavior, thereby more accurately locating the abnormal causes of power equipment.

[0067] Exemplarily, the Pearson correlation coefficient formula is as follows:

[0068]

[0069] Among them, r represents the correlation coefficient, x and y represent the observed values ​​of the two parameters respectively. and Represent the mean values ​​of the two parameters respectively.

[0070] S240: Compare the correlation coefficient corresponding to each abnormal power device to be selected with a preset coefficient threshold, and determine the target abnormal power device in the abnormal area based on the comparison result.

[0071] The technical solution of the embodiment of the present invention can fully reflect the abnormal state of the power equipment by determining at least one abnormal line loss parameter value and abnormal power consumption parameter value corresponding to each candidate abnormal power equipment based on abnormal line loss rate data and abnormal power consumption behavior data. Based on the preset statistical method, abnormal line loss parameter value and abnormal power consumption parameter value, the correlation coefficient between each abnormal line loss parameter and abnormal power consumption parameter corresponding to each candidate abnormal power equipment is determined, which can provide direct information about the correlation between abnormal power equipment. By calculating the correlation coefficient, the degree of correlation between line loss anomaly and abnormal power consumption behavior can be quantified, so as to more accurately locate the abnormal power equipment, which helps to reduce false alarms and missed alarms and improve the accuracy and reliability of fault location.

[0072] Embodiment 3

[0073] Figure 3 This is a schematic diagram of the structure of an abnormal power equipment locating device provided in the third embodiment of the present invention. Figure 3 As shown, the device includes: an abnormal data determination module 310, a correlation coefficient determination module 320 and an abnormality positioning module 330.

[0074] The abnormal data determination module is used to determine the abnormal power equipment to be selected in the abnormal area and the abnormal line loss rate data and the abnormal power consumption behavior data corresponding to each abnormal power equipment to be selected in the abnormal area based on the power equipment operation data corresponding to each power equipment in the abnormal area;

[0075] A correlation coefficient determination module, used to determine the correlation coefficient between the abnormal line loss parameter and the abnormal power consumption parameter corresponding to each abnormal power device to be selected based on the abnormal line loss rate data and the abnormal power consumption behavior data;

[0076] The abnormality positioning module is used to compare the correlation coefficient corresponding to each candidate abnormal power device with a preset coefficient threshold, and determine the target abnormal power device in the abnormal area based on the comparison result.

[0077] The technical solution of this embodiment provides data support for subsequent processing by determining the abnormal line loss rate data and abnormal power consumption behavior data corresponding to the selected abnormal power equipment in the abnormal area and each selected abnormal power equipment based on the power equipment operation data corresponding to each power equipment in the abnormal area. Based on the abnormal line loss rate data and the abnormal power consumption behavior data, the correlation coefficient between the abnormal line loss parameters and the abnormal power consumption parameters corresponding to each selected abnormal power equipment is determined, which can quantitatively describe the degree of correlation between the abnormal line loss rate and the abnormal power consumption behavior, and provide a scientific basis for abnormal positioning. By comparing the correlation coefficient corresponding to each selected abnormal power equipment with the preset coefficient threshold, and determining the target abnormal power equipment in the abnormal area based on the comparison result, the standardization and normalization of abnormal positioning can be achieved. By comprehensively considering the abnormal line loss rate data and the abnormal power consumption behavior data, as well as the correlation coefficient between them, the abnormal power equipment can be automatically located more accurately, the scope of troubleshooting can be quickly narrowed, and unnecessary manpower, material resources and time investment can be reduced. At the same time, through accurate positioning information, operation and maintenance personnel can find the source of the fault more quickly and repair it, thereby improving the efficiency of fault handling. It can quickly narrow the scope of troubleshooting, reduce unnecessary manpower, material resources and time investment. At the same time, through accurate positioning information, operation and maintenance personnel can find the source of the fault more quickly and repair it, thereby improving the efficiency of fault handling.

[0078] Optionally, the abnormal data determination module 310 is specifically used to: perform abnormal analysis based on the power equipment operation data corresponding to each power equipment in the abnormal area, and determine the abnormal power equipment to be selected in the abnormal area; perform abnormal data screening on the power equipment operation data corresponding to the selected abnormal power equipment, and determine the line loss rate abnormal data and power consumption behavior abnormal data associated with each abnormal power equipment to be selected.

[0079] Optionally, the correlation coefficient determination module 320 includes:

[0080] an abnormal parameter determination unit, configured to determine at least one abnormal line loss parameter value and abnormal power consumption parameter value corresponding to each abnormal power device to be selected based on the abnormal line loss rate data and the abnormal power consumption behavior data;

[0081] The correlation coefficient determination unit is used to determine the correlation coefficient between each abnormal line loss parameter and abnormal power consumption parameter corresponding to each abnormal power equipment to be selected based on a preset statistical method, the abnormal line loss parameter value and the abnormal power consumption parameter value.

[0082] Optionally, the abnormal parameter determination unit is specifically used to: perform data cleaning processing on the abnormal line loss rate data and the abnormal power consumption behavior data to obtain the cleaned abnormal line loss rate data and abnormal power consumption behavior data; perform missing value and abnormal value completion processing on the cleaned abnormal line loss rate data and abnormal power consumption behavior data, and determine at least one abnormal line loss parameter value and abnormal power consumption parameter value corresponding to each power equipment based on the completed abnormal line loss rate data and abnormal power consumption behavior data.

[0083] Optionally, the correlation coefficient determination unit is specifically used to: perform linear analysis on the abnormal line loss parameter and the abnormal power consumption parameter based on the Pearson correlation coefficient, and determine the correlation coefficient between the abnormal line loss parameter and the abnormal power consumption parameter corresponding to each abnormal power equipment to be selected.

[0084] Optionally, the abnormality locating module 330 is specifically used to: if there is only one line loss abnormal parameter, then the selected abnormal power equipment whose correlation coefficient between the line loss abnormal parameter and the abnormal power consumption parameter is greater than a preset coefficient threshold is determined as the target abnormal power equipment in the abnormal area; if there are at least two line loss abnormal parameters, then the selected abnormal power equipment whose correlation coefficient between each line loss abnormal parameter and the abnormal power consumption parameter is greater than the preset coefficient threshold is determined as the target abnormal power equipment in the abnormal area.

[0085] Optionally, when the abnormal power equipment to be selected is an electric energy meter, the line loss abnormality parameter includes: at least one of: line loss power and line loss abnormality rate.

[0086] The abnormal power equipment locating device provided in the embodiment of the present invention can execute the abnormal power equipment locating method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0087] Figure 4 A schematic diagram of the structure of an electronic device 12 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as desktop computers, workstations, servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0088] like Figure 4As shown, the electronic device 12 is in the form of a general purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0089] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0090] The electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0091] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0092] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0093] The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), may communicate with one or more devices that enable a user to interact with the electronic device 12, and / or may communicate with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed via an input / output (I / O) interface 22. Furthermore, the electronic device 12 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 via a bus 18. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0094] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing the steps of a method for locating abnormal power equipment provided in the embodiment of the present invention, the method comprising:

[0095] Based on the power equipment operation data corresponding to each power equipment in the abnormal area, determining the abnormal power equipment to be selected in the abnormal area and the abnormal line loss rate data and the abnormal power consumption behavior data corresponding to each abnormal power equipment to be selected;

[0096] Based on the abnormal line loss rate data and the abnormal power consumption behavior data, determining a correlation coefficient between an abnormal line loss parameter and an abnormal power consumption parameter corresponding to each abnormal power device to be selected;

[0097] The correlation coefficient corresponding to each abnormal power device to be selected is compared with a preset coefficient threshold, and the target abnormal power device in the abnormal area is determined based on the comparison result.

[0098] Of course, those skilled in the art can understand that the processor can also implement the technical solution of the abnormal power equipment locating method provided by any embodiment of the present invention.

[0099] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the abnormal power equipment locating method steps provided in any embodiment of the present invention are implemented. The method includes:

[0100] Based on the power equipment operation data corresponding to each power equipment in the abnormal area, determining the abnormal power equipment to be selected in the abnormal area and the abnormal line loss rate data and the abnormal power consumption behavior data corresponding to each abnormal power equipment to be selected;

[0101] Based on the abnormal line loss rate data and the abnormal power consumption behavior data, determining a correlation coefficient between an abnormal line loss parameter and an abnormal power consumption parameter corresponding to each abnormal power device to be selected;

[0102] The correlation coefficient corresponding to each abnormal power device to be selected is compared with a preset coefficient threshold, and the target abnormal power device in the abnormal area is determined based on the comparison result.

[0103] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0104] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0105] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0106] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0107] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0108] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for locating abnormal power equipment, characterized in that: include: Based on the power equipment operation data corresponding to each power equipment in the abnormal area, determining the abnormal power equipment to be selected in the abnormal area and the abnormal line loss rate data and the abnormal power consumption behavior data corresponding to each abnormal power equipment to be selected; Based on the abnormal line loss rate data and the abnormal power consumption behavior data, determining a correlation coefficient between an abnormal line loss parameter and an abnormal power consumption parameter corresponding to each abnormal power device to be selected; The correlation coefficient corresponding to each abnormal power device to be selected is compared with a preset coefficient threshold, and the target abnormal power device in the abnormal area is determined based on the comparison result.

2. The method according to claim 1, characterized in that: The determining, based on the power equipment operation data corresponding to each power equipment in the abnormal area, of the abnormal power equipment to be selected in the abnormal area and the abnormal line loss rate data and the abnormal power consumption behavior data corresponding to each abnormal power equipment to be selected, comprises: Performing an abnormality analysis based on the power equipment operation data corresponding to each power equipment in the abnormal area, and determining the abnormal power equipment to be selected in the abnormal area; The power equipment operation data corresponding to the abnormal power equipment to be selected is screened for abnormal data, and the line loss rate abnormal data and power consumption behavior abnormal data associated with each abnormal power equipment to be selected are determined.

3. The method according to claim 1, characterized in that The determining, based on the abnormal line loss rate data and the abnormal power consumption behavior data, a correlation coefficient between the abnormal line loss parameter and the abnormal power consumption parameter corresponding to each abnormal power device to be selected, comprises: Based on the abnormal line loss rate data and the abnormal power consumption behavior data, determining at least one abnormal line loss parameter value and abnormal power consumption parameter value corresponding to each abnormal power device to be selected; Based on a preset statistical method, the abnormal line loss parameter value and the abnormal power consumption parameter value, a correlation coefficient between each abnormal line loss parameter and the abnormal power consumption parameter corresponding to each abnormal power equipment to be selected is determined.

4. The method according to claim 3, characterized in that The determining, based on the abnormal line loss rate data and the abnormal power consumption behavior data, at least one abnormal line loss parameter value and abnormal power consumption parameter value corresponding to each abnormal power device to be selected includes: Performing data cleaning on the abnormal line loss rate data and the abnormal power consumption behavior data to obtain cleaned abnormal line loss rate data and abnormal power consumption behavior data; The cleaned abnormal line loss rate data and abnormal power consumption behavior data are processed for missing values ​​and abnormal values, and based on the completed abnormal line loss rate data and abnormal power consumption behavior data, at least one abnormal line loss parameter value and abnormal power consumption parameter value corresponding to each power equipment is determined.

5. The method according to claim 3, characterized in that: The determining, based on a preset statistical method, the abnormal line loss parameter and the abnormal power consumption parameter, a correlation coefficient between the abnormal line loss parameter and the abnormal power consumption parameter corresponding to each abnormal power device to be selected, includes: A linear analysis is performed on the abnormal line loss parameter and the abnormal power consumption parameter based on the Pearson correlation coefficient to determine the correlation coefficient between the abnormal line loss parameter and the abnormal power consumption parameter corresponding to each abnormal power equipment to be selected.

6. The method according to claim 1, characterized in that The step of determining the target abnormal power equipment in the abnormal area based on the comparison result includes: If there is only one abnormal line loss parameter, the abnormal power equipment to be selected, whose correlation coefficient between the abnormal line loss parameter and the abnormal power consumption parameter is greater than a preset coefficient threshold, is determined as the target abnormal power equipment in the abnormal area; If there are at least two abnormal line loss parameters, the candidate abnormal power equipment whose correlation coefficient between each abnormal line loss parameter and the abnormal power consumption parameter is greater than a preset coefficient threshold is determined as the target abnormal power equipment in the abnormal area.

7. The method according to any one of claims 1 to 6, characterized in that: When the abnormal power equipment to be selected is an electric energy meter, the line loss abnormality parameter includes: at least one of line loss power and line loss abnormality rate.

8. An abnormal power equipment locating device, characterized in that: include: An abnormal data determination module, used to determine the abnormal power equipment to be selected in the abnormal area and the abnormal line loss rate data and the abnormal power consumption behavior data corresponding to each of the abnormal power equipment to be selected in the abnormal area based on the power equipment operation data corresponding to each of the power equipment in the abnormal area; A correlation coefficient determination module, used to determine the correlation coefficient between the abnormal line loss parameter and the abnormal power consumption parameter corresponding to each abnormal power device to be selected based on the abnormal line loss rate data and the abnormal power consumption behavior data; The abnormality positioning module is used to compare the correlation coefficient corresponding to each candidate abnormal power device with a preset coefficient threshold, and determine the target abnormal power device in the abnormal area based on the comparison result.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the abnormal power equipment locating method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the abnormal power equipment locating method according to any one of claims 1 to 7 when executed.

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