Electric energy metering management system and method based on big data

Abstract

The invention relates to the technical field of electric energy metering management, in particular to an electric energy metering management system and method based on big data, and the method comprises the steps: analyzing the wiring deterioration degree of an electric meter based on the building wall state data of the installation position of the electric meter and the wiring state data of the electric meter; based on the metering parameter data and the wiring state data of the electricity meter, analyzing the metering performance abnormal degree of the electricity meter; according to the analysis result of the wiring deterioration degree and the analysis result of the metering performance abnormity degree of the electric meter, evaluating the wiring loosening risk of the electric meter; and according to the wiring loosening risk assessment result of the electric meter, electric meter wiring maintenance early warning is carried out on operation and maintenance personnel, so that the electric energy metering management efficiency is improved, and the electric energy metering management cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy metering management, and particularly to a big data-based electric energy metering management system and method. Background Art

[0002] With the development of the intelligentization of the power system and the energy Internet, the management of electric energy metering is gradually transforming from traditional mechanical metering to the digital and networked directions, becoming the core link to ensure power market transactions and optimize the economic operation of the power grid. At the same time, during the iterative update process of electric energy metering technology, its management still faces many challenges. On the one hand, the wide access of new power electronic devices and distributed energy sources will lead to a sharp increase in harmonic content in the power grid and complex load characteristics, making it difficult for traditional power frequency-based steady-state electric energy metering models to accurately obtain dynamic electric energy information. On the other hand, the physical reliability problems of electric energy metering devices during their life cycle are becoming increasingly prominent. For example, potential hazards such as loose wiring terminals and deteriorated contact resistance still exist for a long time, directly affecting the accuracy and stability of electric energy metering data. Therefore, when analyzing electric energy metering errors, not only the performance drift of internal components of the meter needs to be considered, but also in-depth analysis of systematic factors such as its external environment, installation process, and operation and maintenance level should be carried out simultaneously. Especially in densely populated urban areas, when large transportation vehicles such as subways frequently pass by the buildings where the meters are installed, the low-frequency vibration generated during their operation will resonate with the building structure, significantly amplifying the vibration amplitude of the wall. This continuous mechanical impact not only accelerates the loosening process of the wiring terminal screws but also exacerbates the oxidation and micro-deformation of the contact surface, becoming an important inducement for the deterioration of contact resistance.

[0003] However, when existing technologies perform electric energy metering management, they mainly focus on the optimization of electric energy metering parameters such as harmonic compensation, temperature drift correction, and load adaptive range switching. For example, in most existing electric energy metering error analysis models, it is defaulted that the wiring state is always reliable, ignoring the consideration of the time-varying characteristics of contact resistance caused by loose wiring. At the same time, for example, the mechanical vibration transmission path of the meter installation base caused by special working conditions such as building resonance caused by subway operation and its long-term impact on the connection stability of wiring terminals, existing technologies also lack systematic monitoring and analysis, making it difficult to timely identify and locate the problem of inaccurate electric energy metering caused by wiring deterioration in actual operation and maintenance. It often relies on manual on-site inspections, resulting in low efficiency and high cost of electric energy metering management.

[0004] To solve these problems, the present application designs a big data-based electric energy metering management system and method. Summary of the Invention

[0005] The purpose of the present invention is to provide a power metering management system and method based on big data, which analyzes the wiring deterioration degree and metering performance anomaly degree of an electric meter; thereby realizing the assessment of the wiring loosening risk of the electric meter; and further improving the power metering management efficiency and reducing the power metering management cost.

[0006] The present invention is implemented as follows: In a first aspect, the present invention provides a power metering management method based on big data, including the following steps: S1. Obtain the metering parameter data and wiring status data of the electric meter, and at the same time obtain the building wall status data of the installation location of the electric meter; S2. Analyze the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter; S3. Analyze the metering performance anomaly degree of the electric meter based on the metering parameter data and wiring status data of the electric meter; S4. Evaluate the wiring loosening risk of the electric meter according to the analysis results of the wiring deterioration degree and metering performance anomaly degree of the electric meter; S5. Give a warning to the operation and maintenance personnel for the wiring repair of the electric meter according to the evaluation result of the wiring loosening risk of the electric meter.

[0007] Preferably, on the basis of the above solution, in step S2, analyzing the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter specifically includes: S21. Extract the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter; S22. Analyze the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter to obtain the analysis result of the wiring deterioration degree of the electric meter.

[0008] Preferably, on the basis of the above solution, in step S22, analyzing the wiring deterioration degree of the electric meter specifically includes: S221. Analyze the vibration torque attenuation degree of the wiring based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter to obtain the analysis result of the vibration torque attenuation degree of the wiring; S222. Analyze the environmental corrosion degree of the wiring based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter to obtain the analysis result of the environmental corrosion degree of the wiring; S223. Based on the analysis results of the vibration torque attenuation degree of the wiring and the analysis results of the environmental corrosion degree, establish an analysis model for the vibration environment coupling effect, calculate the vibration environment coupling effect index, conduct a coupling analysis on the torque attenuation caused by vibration of the wiring and the corrosion of the wiring material caused by the environment, and obtain the vibration environment coupling analysis results; S224. Based on the analysis results of the vibration torque attenuation degree of the wiring, the analysis results of the environmental corrosion degree, and the vibration environment coupling analysis results, analyze the deterioration degree of the wiring of the electric meter to obtain the analysis results of the deterioration degree of the wiring of the electric meter.

[0009] On the basis of the above solutions, preferably, in step S3, based on the measurement parameter data and wiring state data of the electric meter, analyze the abnormal degree of the measurement performance of the electric meter, which specifically includes the following steps: S31. Extract the measurement parameter data and wiring state data of the electric meter; S32. Based on the measurement parameter data and wiring state data of the electric meter, analyze the abnormal degree of the measurement performance of the electric meter to obtain the analysis results of the abnormal degree of the measurement performance of the electric meter.

[0010] On the basis of the above solutions, preferably, in step S32, analyzing the abnormal degree of the measurement performance of the electric meter includes the following specific steps: S321. Based on the measurement parameter data and wiring state data of the electric meter, analyze the abnormal degree of harmonic coupling of the electric meter to obtain the analysis results of the abnormal degree of harmonic coupling of the electric meter; S322. Based on the measurement parameter data and wiring state data of the electric meter, analyze the abnormal degree of error coupling of the electric meter to obtain the analysis results of the abnormal degree of error coupling of the electric meter; S323. According to the analysis results of the abnormal degree of harmonic coupling of the electric meter and the analysis results of the abnormal degree of error coupling of the electric meter, analyze the abnormal degree of the measurement performance of the electric meter to obtain the analysis results of the abnormal degree of the measurement performance of the electric meter.

[0011] On the basis of the above solutions, preferably, in step S4, according to the analysis results of the deterioration degree of the wiring of the electric meter and the analysis results of the abnormal degree of the measurement performance, evaluate the risk of wiring looseness of the electric meter, including the following specific steps: S41. Obtain the analysis results of the deterioration degree of the wiring of the electric meter obtained by analysis, and at the same time obtain the analysis results of the abnormal degree of the measurement performance of the electric meter obtained by analysis; S42. According to the analysis results of the deterioration degree of the wiring of the electric meter and the analysis results of the abnormal degree of the measurement performance, evaluate the risk of wiring looseness of the electric meter to obtain the evaluation results of the risk of wiring looseness of the electric meter.

[0012] Preferably based on the above solution, in step S5, according to the wiring loosening risk assessment result of the electric meter, a maintenance warning for the wiring of the electric meter is given to the operation and maintenance personnel, specifically including: S51. Obtain the wiring loosening risk assessment result of the electric meter obtained by evaluation; S52. Preset a wiring loosening risk threshold. When the wiring loosening risk assessment result of the electric meter is greater than the wiring loosening risk threshold, a maintenance warning for the wiring of the electric meter is given to the operation and maintenance personnel.

[0013] In a second aspect, the present invention provides a power metering management system based on big data, including: A data acquisition module for acquiring the metering parameter data and wiring status data of the electric meter, and simultaneously acquiring the building wall status data of the installation location of the electric meter; A wiring deterioration degree analysis module for analyzing the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter; A metering performance anomaly degree analysis module for analyzing the metering performance anomaly degree of the electric meter based on the metering parameter data and wiring status data of the electric meter; A wiring loosening risk assessment module for assessing the wiring loosening risk of the electric meter according to the analysis results of the wiring deterioration degree and metering performance anomaly degree of the electric meter; An electric meter wiring maintenance warning module for giving a maintenance warning for the wiring of the electric meter to the operation and maintenance personnel according to the wiring loosening risk assessment result of the electric meter; A control module for controlling the operation of the data acquisition module, wiring deterioration degree analysis module, metering performance anomaly degree analysis module, wiring loosening risk assessment module, and electric meter wiring maintenance warning module.

[0014] In a third aspect, the present invention provides an electronic device, including: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory, and the processor executes the power metering management method based on big data by calling the computer program stored in the memory.

[0015] Compared with the prior art, the present invention has the following advantages and beneficial effects: Based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter, the present invention analyzes the wiring deterioration degree of the electric meter; based on the metering parameter data and wiring status data of the electric meter, it analyzes the metering performance anomaly degree of the electric meter; according to the analysis results of the wiring deterioration degree and metering performance anomaly degree of the electric meter, it assesses the wiring loosening risk of the electric meter; according to the wiring loosening risk assessment result of the electric meter, it gives a maintenance warning for the wiring of the electric meter to the operation and maintenance personnel, thereby improving the power metering management efficiency and reducing the power metering management cost. Description of the Drawings

[0016] Other features, objectives, and advantages of the present invention will become more apparent by reading the following detailed description of non - restrictive embodiments with reference to the accompanying drawings: Figure 1 It is a schematic diagram of the overall process of the power metering management method based on big data of the present invention; Figure 2 It is a schematic diagram of the structure of the power metering management system based on big data of the present invention; Figure 3 It is an analysis flowchart of each step of the power metering management method based on big data of the present invention. Detailed Embodiments

[0017] The technical solution of the present invention will be described in detail below with reference to the drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. Without conflict, the technical features in the embodiments of the present invention and the embodiments can be combined with each other.

[0018] Embodiment 1 As shown in Figure 1 、 Figure 3 , this embodiment provides a power metering management method based on big data, which specifically includes the following steps: S1. Obtain the metering parameter data and wiring status data of the electric meter, and at the same time obtain the building wall status data of the installation location of the electric meter; S2. Analyze the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter; S3. Analyze the abnormal degree of metering performance of the electric meter based on the metering parameter data and wiring status data of the electric meter; S4. Evaluate the wiring loosening risk of the electric meter according to the analysis results of the wiring deterioration degree and the abnormal degree of metering performance of the electric meter; S5. Give a warning to the operation and maintenance personnel for wiring repair of the electric meter according to the evaluation result of the wiring loosening risk of the electric meter.

[0019] As a preferred technical solution of the present invention, in step S2, analyzing the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter specifically includes: S21. Extract the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter; S22. Analyze the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter to obtain the analysis result of the wiring deterioration degree of the electric meter.

[0020] As a preferred technical solution of the present invention, in step S22, the analysis of the wiring deterioration degree of the electric meter specifically includes: S221. Based on the building wall state data of the electric meter installation position and the wiring state data of the electric meter, analyze the vibration torque attenuation degree of the wiring to obtain the analysis result of the vibration torque attenuation degree of the wiring. In buildings where large transportation vehicles such as subways frequently pass by, the low-frequency vibration generated by the operation of large transportation vehicles such as subways will resonate with the building structure, thereby amplifying the wall vibration amplitude at the electric meter installation position and further accelerating the relaxation process of the wiring terminal screws; therefore, in this step, the input of the cumulative energy under the vibration action is calculated by integration to quantify its attenuation effect on the pre-tightening force of the wiring screws; the attenuation amplitude of the pre-tightening force of the wiring screws caused by the wall vibration is quantified through the natural logarithmic function, so as to quantify the vibration torque attenuation degree of the wiring; the calculation formula for the vibration torque attenuation degree of the wiring is: , where Zn is the vibration torque attenuation degree of the wiring, Ln is the torque of the wiring screw in the wiring state data, Lo is the initial pre-tightening force of the wiring screw in the wiring state data, K is the damping coefficient of the wiring material in the wiring state data, t1 and t2 are respectively the start time and the end time of the wall vibration occurrence time interval at the electric meter installation position in the building wall state data, and a(t) is the wall vibration acceleration at the electric meter installation position at the t-th moment in the building wall state data; S222. Based on the building wall state data of the electric meter installation position and the wiring state data of the electric meter, analyze the environmental corrosion degree of the wiring to obtain the analysis result of the environmental corrosion degree of the wiring. In this step, the oxidation corrosion cumulative effect of the wiring material under the action of temperature and the interaction with the change of the contact resistance are quantified through the integral term, so as to realize the analysis of the environmental corrosion degree of the wiring. The calculation formula for the environmental corrosion degree of the wiring is: , where Hf is the environmental corrosion degree of the wiring, Ro is the initial contact resistance of the electric meter wiring in the wiring state data, Ea is the oxidation activation energy of the electric meter wiring material in the wiring state data, R is the gas constant, T(t) is the temperature at the electric meter installation position at the t-th moment in the building wall state data, is the temperature gradient at the electric meter installation position in the building wall state data; S223. Based on the analysis results of the vibration torque attenuation degree of the wiring and the environmental corrosion degree analysis results, establish a vibration environment coupling effect analysis model, calculate the vibration environment coupling effect index, conduct a coupling analysis on the torque attenuation caused by vibration of the wiring and the corrosion of the wiring material caused by the environment, and obtain the vibration environment coupling analysis result. In this embodiment, because the vibration of the building wall will cause the wiring to loosen and the wiring gap to increase, resulting in an accelerated oxidation corrosion rate of the wiring in the environment; at the same time. When the cross-section of the wiring is corroded due to environmental corrosion, it will reduce the rigidity of the wiring material, thereby weakening the anti-vibration performance of the wiring. Therefore, in this step, based on the Jahn-Teller effect theory, a two-way feedback model of vibration and corrosion is established, and the dynamic coupling strength between the vibration torque attenuation degree and the environmental corrosion degree is characterized by the weight coefficient and the derivative term; the calculation formula of the vibration environment coupling effect index is: ; where Ce is the vibration environment coupling effect index, are respectively the attenuation rate of the vibration torque attenuation degree changing with time and the catalytic rate of the environmental corrosion degree changing with temperature, is the weight factor; S224. According to the analysis results of the vibration torque attenuation degree of the wiring, the environmental corrosion degree analysis results, and the vibration environment coupling analysis results, analyze the deterioration degree of the wiring of the electric meter to obtain the analysis result of the deterioration degree of the wiring of the electric meter; in this step, the weight is dynamically adjusted by a fuzzy adaptive weight regulator to adaptively optimize the weight distribution corresponding to the vibration torque attenuation degree, environmental corrosion degree, and vibration environment coupling effect index of the wiring, so as to achieve the purpose of accurately quantifying the deterioration degree of the wiring; at the same time, in this embodiment, the fuzzy adaptive weight regulator is used to dynamically adjust the weight, which can also accurately reflect that during the use of the electric meter, the deterioration of the wiring is dominated by vibration torque attenuation or environmental corrosion or the deterioration dominated by the coupling of the two; the calculation formula of the wiring deterioration degree is: , where LH is the deterioration degree of the wiring of the electric meter, are respectively the vibration torque attenuation influence weight, environmental corrosion influence weight, and coupling effect influence weight; It should be noted that the above weight factor and influence weight are both dynamically adjusted using a fuzzy adaptive weight regulator; the specific adjustment process is as follows: Calculate the vibration intensity factor , where vmax is the critical acceleration that causes fatigue failure of the wiring material; Calculate the corrosion rate factor , where, is the corrosion rate of the environmental corrosion degree changing with time, and Fs is the threshold value of the wiring material corrosion rate that requires immediate maintenance; Calculate the vibration environment coupling strength factor , where max() is the maximum value function; Taking the calculated vibration intensity factor, corrosion rate factor, and vibration environment coupling strength factor as the inputs of the fuzzy adaptive weight regulator can directly reflect the real-time intensity of the vibration impact on the meter wiring, thus reflecting the instantaneous change of the vibration intensity, and can improve the sensitivity of the weight to the instantaneous change of the result after vibration torque attenuation; at the same time, the corrosion rate factor is directly related to the real-time development of the wiring corrosion process. If the environmental corrosion degree of S222 is used as the input of the fuzzy adaptive weight regulator, it only reflects the cumulative corrosion effect and lacks sensitivity to sudden corrosion events (such as a sudden increase in the concentration of corrosive gases). Therefore, in this embodiment, the corrosion rate factor is used as the input of the fuzzy adaptive weight regulator, thereby improving the sensitivity of the wiring deterioration degree calculation formula to sudden corrosion events; Through the fuzzy adaptive weight regulator for and perform dynamic adjustment; Exemplarily, when it is detected that the resonance caused by the vibration of large transportation vehicles such as subways in the building wall becomes larger or the corrosion rate suddenly increases, resulting in an increase in the vibration intensity factor or the corrosion rate factor, leading to an increase in the degree of vibration torque attenuation or the degree of environmental corrosion, the fuzzy adaptive weight regulator automatically reduces to avoid the vibration environment coupling effect index being dominated by a single factor. When it is found that the coupling effect between the torque attenuation caused by vibration of the wiring and the corrosion of the wiring material caused by the environment intensifies, then actively increase , then strengthen the contribution of the coupling effect to the wiring deterioration degree, making the vibration environment coupling effect index increase.

[0021] As a preferred technical solution of the present invention, in step S3, based on the metering parameter data and wiring state data of the meter, the abnormal degree of the metering performance of the meter is analyzed, which specifically includes the following steps: S31. Extract the metering parameter data and wiring state data of the meter; S32. Based on the metering parameter data and wiring state data of the meter, analyze the abnormal degree of the metering performance of the meter to obtain the analysis result of the abnormal degree of the metering performance of the meter.

[0022] As a preferred technical solution of the present invention, in step S32, the analysis of the abnormal degree of the metering performance of the meter includes the following specific steps: S321. Based on the metering parameter data and wiring state data of the meter, analyze the abnormal degree of harmonic coupling of the meter to obtain the analysis result of the abnormal degree of harmonic coupling of the meter. This step quantifies the abnormal degree of harmonic coupling of the meter by comparing the measured maximum total harmonic distortion rate with the specified total harmonic distortion rate limit value. The calculation formula for the abnormal degree of harmonic coupling of the meter is: , where Hd is the degree of harmonic coupling anomaly of the electricity meter, XBs is the total harmonic distortion rate limit in the metering parameter data, XBmax is the maximum total harmonic distortion rate of the electricity meter measured during the use of the currently installed wiring, Time is the usage duration of the currently installed wiring in the wiring status data, and txb is the total duration of harmonic occurrences in the metering parameter data during the use of the currently installed wiring; S322. Analyze the error coupling anomaly degree of the electricity meter based on the metering parameter data and wiring status data of the electricity meter to obtain the analysis result of the error coupling anomaly degree of the electricity meter. This step considers the ratio of the absolute error of the active power of the electricity meter to the rated active power, which can directly reflect the metering accuracy of the electricity meter. At the same time, the ratio of the usage duration of the currently installed wiring to the total usage duration of the electricity meter is introduced, which can further evaluate the long-term impact of the wiring status on the electricity meter error. The calculation formula for the error coupling anomaly degree of the electricity meter is: , where Wc is the error coupling anomaly degree of the electricity meter, P is the rated active power of the electricity meter in the metering parameter data, is the absolute error of the active power of the electricity meter measured during the use of the currently installed wiring in the metering parameter data, Time is the usage duration of the currently installed wiring in the wiring status data, and DT is the total usage duration of the electricity meter in the wiring status data; S323. Analyze the metering performance anomaly degree of the electricity meter according to the analysis results of the harmonic coupling anomaly degree and error coupling anomaly degree of the electricity meter to obtain the analysis result of the metering performance anomaly degree of the electricity meter. This step takes into account that the impacts of the harmonic coupling anomaly degree and error coupling anomaly degree of the electricity meter on the metering performance anomaly degree are different in different scenarios. Therefore, in this embodiment, the method of introducing weights is used to dynamically adjust the impacts of the two. The calculation formula for the metering performance anomaly degree of the electricity meter is: , where JL is the metering performance anomaly degree of the electricity meter, and b1 and b2 are the harmonic coupling anomaly impact weight and error coupling anomaly impact weight respectively.

[0023] As a preferred technical solution of the present invention, in step S4, the wiring loosening risk of the electricity meter is evaluated according to the analysis results of the wiring deterioration degree and metering performance anomaly degree of the electricity meter, including the following specific steps: S41. Obtain the analysis result of the wiring deterioration degree of the electricity meter obtained by analysis, and at the same time obtain the analysis result of the metering performance anomaly degree of the electricity meter obtained by analysis; S42. Based on the analysis results of the wiring deterioration degree of the electric meter and the analysis results of the abnormal degree of metering performance, evaluate the wiring loosening risk of the electric meter to obtain the evaluation result of the wiring loosening risk of the electric meter. This step takes into account that the wiring deterioration degree and the abnormal degree of metering performance of the electric meter under different scenarios and different metering requirements have different impacts on the wiring loosening risk. Therefore, in this embodiment, a method of introducing weights is used to dynamically adjust the impacts of the two. The evaluation formula for the wiring loosening risk of the electric meter is: , where SD is the wiring loosening risk of the electric meter, and c1 and c2 are the influence weights of the wiring deterioration degree and the influence weight of the abnormal metering performance respectively.

[0024] As a preferred technical solution of the present invention, in step S5, according to the evaluation result of the wiring loosening risk of the electric meter, a wiring repair warning is given to the operation and maintenance personnel, which specifically includes: S51. Obtain the evaluation result of the wiring loosening risk of the evaluated electric meter; S52. Preset a wiring loosening risk threshold. When the evaluation result of the wiring loosening risk of the electric meter is greater than the wiring loosening risk threshold, a wiring repair warning is given to the operation and maintenance personnel. Among them, the acquisition method of the set parameters (such as weights and thresholds) in this embodiment is obtained through experiments by those skilled in the art. The specific experimental method is: obtain the metering parameter data and wiring status data of multiple historical electric meters, and at the same time obtain the building wall status data of the installation location of the corresponding electric meters; substitute the metering parameter data, wiring status data and the corresponding building wall status data into each step of this embodiment to obtain the evaluation results of the wiring loosening risks of multiple historical electric meters; obtain the judgment results of whether there is wiring loosening in multiple historical electric meters, and import the evaluation results of the wiring loosening risks of multiple historical electric meters obtained by substituting into each step of this embodiment and the judgment results of whether the corresponding electric meters have wiring loosening into the fitting software, and output the values of the set parameters (such as weights and thresholds) that meet the highest wiring loosening risk judgment accuracy rate.

[0025] Embodiment 2 As Figure 2 shown, this embodiment provides a power metering management system based on big data, including: A data acquisition module for acquiring the metering parameter data and wiring status data of the electric meter, and at the same time acquiring the building wall status data of the installation location of the electric meter; A wiring deterioration degree analysis module for analyzing the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter; A metering performance abnormal degree analysis module for analyzing the abnormal degree of the metering performance of the electric meter based on the metering parameter data and wiring status data of the electric meter; The wiring loosening risk assessment module is used to assess the wiring loosening risk of the electric meter according to the analysis results of the wiring deterioration degree and the abnormal degree of metering performance of the electric meter; The electric meter wiring maintenance warning module is used to give a wiring maintenance warning to the operation and maintenance personnel according to the assessment result of the wiring loosening risk of the electric meter; The control module is used to control the operation of the data acquisition module, the wiring deterioration degree analysis module, the metering performance abnormal degree analysis module, the wiring loosening risk assessment module, and the electric meter wiring maintenance warning module.

[0026] For the steps of each parameter and each unit module in the above-mentioned big data-based electric energy metering management system of the present invention to realize corresponding functions, reference can be made to the parameters and steps in the embodiments of the big data-based electric energy metering management method in the above text, which will not be elaborated here.

[0027] Embodiment 3 An electronic device according to an embodiment of the present invention includes: a processor and a memory. Among them, a computer program that can be called by the processor is stored in the memory, and the processor executes the big data-based electric energy metering management method by calling the computer program stored in the memory. It should be noted that: all computer programs of the big data-based electric energy metering management method are implemented using the C language. Among them, the data acquisition module, the wiring deterioration degree analysis module, the metering performance abnormal degree analysis module, the wiring loosening risk assessment module, the electric meter wiring maintenance warning module, and the control module are all controlled by a remote server.

[0028] In the description of this specification, the description with reference to terms such as "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0029] The above-disclosed preferred embodiments of the present invention are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of this specification. These embodiments are selected and specifically described in this specification in order to better explain the principles and practical applications of the present invention, so that those skilled in the art in the technical field can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A method for power metering management based on big data, characterized in that Including the following steps: S1. Obtain the metering parameter data and wiring status data of the electric meter, and at the same time obtain the building wall status data of the installation location of the electric meter; S2. Analyze the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter; S3. Analyze the abnormal degree of metering performance of the electric meter based on the metering parameter data and wiring status data of the electric meter; S4. Evaluate the wiring loosening risk of the electric meter according to the analysis results of the wiring deterioration degree and the abnormal degree of metering performance of the electric meter; S5. Give a warning to the operation and maintenance personnel for the wiring repair of the electric meter according to the evaluation result of the wiring loosening risk of the electric meter.

2. The power metering management method based on big data according to claim 1, characterized in that In step S2, analyzing the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter specifically includes: S21. Extract the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter; S22. Analyze the wiring deterioration degree of the electric meter based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter to obtain the analysis result of the wiring deterioration degree of the electric meter.

3. The power metering management method based on big data according to claim 2, wherein In step S22, analyzing the wiring deterioration degree of the electric meter specifically includes: S221. Analyze the vibration torque attenuation degree of the wiring based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter to obtain the analysis result of the vibration torque attenuation degree of the wiring; S222. Analyze the environmental corrosion degree of the wiring based on the building wall status data of the installation location of the electric meter and the wiring status data of the electric meter to obtain the analysis result of the environmental corrosion degree of the wiring; S223. According to the analysis results of the vibration torque attenuation degree and the environmental corrosion degree of the wiring, establish a vibration environment coupling effect analysis model, calculate the vibration environment coupling effect index, and conduct a coupling analysis on the torque attenuation caused by vibration and the corrosion of the wiring material caused by the environment of the wiring to obtain the vibration environment coupling analysis result; S224. Analyze the wiring deterioration degree of the electric meter according to the analysis results of the vibration torque attenuation degree and the environmental corrosion degree of the wiring and the vibration environment coupling analysis result to obtain the analysis result of the wiring deterioration degree of the electric meter.

4. The method for power metering management based on big data according to claim 3, wherein In step S3, analyzing the abnormal degree of metering performance of the electric meter based on the metering parameter data and wiring status data of the electric meter specifically includes the following steps: S31. Extract the metering parameter data and wiring status data of the electric meter; S32. Analyze the abnormal degree of metering performance of the electric meter based on the metering parameter data and wiring status data of the electric meter to obtain the analysis result of the abnormal degree of metering performance of the electric meter.

5. The power metering management method based on big data according to claim 4, characterized in that In step S32, analyzing the abnormal degree of metering performance of the electric meter includes the following specific steps: S321. Analyze the abnormal degree of harmonic coupling of the electric meter based on the metering parameter data and wiring status data of the electric meter to obtain the analysis result of the abnormal degree of harmonic coupling of the electric meter; S322. Analyze the abnormal degree of error coupling of the electric meter based on the metering parameter data and wiring status data of the electric meter to obtain the analysis result of the abnormal degree of error coupling of the electric meter; S323. Analyze the abnormal degree of the metering performance of the electricity meter based on the analysis results of the harmonic coupling abnormality degree and the error coupling abnormality degree of the electricity meter, and obtain the analysis result of the abnormal degree of the metering performance of the electricity meter.

6. The method for power metering management based on big data according to claim 5, characterized in that In step S4, based on the analysis result of the wiring deterioration degree and the analysis result of the abnormal degree of the metering performance of the electricity meter, evaluate the wiring loosening risk of the electricity meter, including the following specific steps: S41. Obtain the analysis result of the wiring deterioration degree of the electricity meter obtained by analysis, and at the same time obtain the analysis result of the abnormal degree of the metering performance of the electricity meter obtained by analysis; S42. Evaluate the wiring loosening risk of the electricity meter based on the analysis result of the wiring deterioration degree and the analysis result of the abnormal degree of the metering performance of the electricity meter, and obtain the evaluation result of the wiring loosening risk of the electricity meter.

7. The method for power metering management based on big data according to claim 6, wherein In step S5, based on the evaluation result of the wiring loosening risk of the electricity meter, give a warning to the maintenance personnel for the wiring repair of the electricity meter, specifically including: S51. Obtain the evaluation result of the wiring loosening risk of the electricity meter obtained by evaluation; S52. Preset a wiring loosening risk threshold. When the evaluation result of the wiring loosening risk of the electricity meter is greater than the wiring loosening risk threshold, give a warning to the maintenance personnel for the wiring repair of the electricity meter.

8. A power metering management system based on big data for implementing the power metering management method based on big data according to any one of claims 1-7, characterized in that, The system includes: A data acquisition module, which is used to acquire the metering parameter data and the wiring status data of the electricity meter, and at the same time acquire the building wall status data of the installation location of the electricity meter; A wiring deterioration degree analysis module, which is used to analyze the wiring deterioration degree of the electricity meter based on the building wall status data of the installation location of the electricity meter and the wiring status data of the electricity meter; A metering performance abnormal degree analysis module, which is used to analyze the abnormal degree of the metering performance of the electricity meter based on the metering parameter data and the wiring status data of the electricity meter; A wiring loosening risk evaluation module, which is used to evaluate the wiring loosening risk of the electricity meter according to the analysis result of the wiring deterioration degree and the analysis result of the abnormal degree of the metering performance of the electricity meter; An electricity meter wiring repair warning module, which is used to give a warning to the maintenance personnel for the wiring repair of the electricity meter according to the evaluation result of the wiring loosening risk of the electricity meter; A control module, which is used to control the operation of the data acquisition module, the wiring deterioration degree analysis module, the metering performance abnormal degree analysis module, the wiring loosening risk evaluation module, and the electricity meter wiring repair warning module.

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