Metering equipment enterprise operation state monitoring method and system based on electric power data

Abstract

The invention provides a metering equipment enterprise operation state monitoring method and system based on electric power data. The method comprises the following steps: acquiring power consumption data of a metering equipment enterprise; based on the power consumption data, extracting power consumption characteristics of the metering equipment enterprise; constructing a power utilization model of the metering equipment enterprise according to the power utilization characteristics, and calculating power utilization state data of the metering equipment enterprise through the power utilization model; and monitoring and evaluating the operation state of the metering equipment enterprise based on the operation data and the power utilization state data of the metering equipment enterprise. Accurate portraying and real-time monitoring analysis of metering equipment manufacturing enterprises are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing and analysis in the electric power industry, and in particular to a method and system for monitoring the operation status of a metering equipment enterprise based on electric power data. Background Art

[0002] According to the "China Metrology Industry Status Analysis and Development Prospects Report" released by China Economic Intelligence, the supply and demand structural contradictions in my country's metrology instrument industry are prominent. Domestic products are mainly concentrated in the middle and low-end, with a high degree of product homogeneity and fierce competition among enterprises. On the other hand, some high-end metrology instruments still need to be imported, with a large growth rate. At present, the big data of power energy metering data has the problems of "difficulty in acquisition", "difficulty in analysis" and "difficulty in application". Summary of the invention

[0003] In view of the above technical problems, the present invention provides a method for monitoring the operation status of a metering equipment enterprise based on power data, comprising:

[0004] Obtain electricity consumption data from metering equipment companies;

[0005] Based on the electricity consumption data, extracting the electricity consumption characteristics of the metering equipment enterprise;

[0006] According to the electricity consumption characteristics, construct an electricity consumption model of the metering equipment enterprise, and calculate the electricity consumption status data of the metering equipment enterprise through the electricity consumption model;

[0007] Based on the operating data and electricity usage status data of the metering equipment enterprise, the operating status of the metering equipment enterprise is monitored and evaluated.

[0008] Furthermore, the electricity consumption data of the metering equipment enterprises include:

[0009] The electricity consumption of the metering equipment enterprise, enterprise credit code, enterprise address, enterprise type, and statistical date.

[0010] Furthermore, after the step of obtaining the electricity consumption data of the metering equipment enterprise, it also includes:

[0011] Preprocessing the electricity consumption data of the metering equipment enterprise includes:

[0012] Remove irrelevant content from electricity consumption data according to the statistical scope;

[0013] Check and correct the abnormal data in the electricity consumption data, and treat the electricity consumption data that cannot be checked as missing values;

[0014] Missing values ​​were checked and supplemented, and data that could not be supplemented were interpolated or eliminated;

[0015] Clean the electricity consumption data, remove duplicate and redundant data, and ensure the uniqueness of the data

[0016] Furthermore, based on the electricity consumption data, the electricity consumption characteristics of the metering equipment enterprise are extracted, including:

[0017] Based on the electricity consumption data of the metering equipment enterprise, the electricity consumption characteristics of the metering equipment enterprise, the number of users, business expansion capacity, electricity charges, installed capacity and electricity consumption indicators are extracted.

[0018] Furthermore, the electricity consumption status data of the metering equipment enterprise is calculated by using the electricity consumption model, including:

[0019] The daily electricity consumption fluctuation rate is calculated as follows:

[0020]

[0021] Judgment rules: A month-on-month decrease of more than 10% for three consecutive months is considered abnormal;

[0022] The rate of change of electricity consumption trend is calculated as follows:

[0023]

[0024] Judgment rules: A significant deviation of 10% from the historical average for two consecutive weeks is considered abnormal;

[0025] The abnormal frequency of electricity consumption is calculated as follows:

[0026] Abnormal power consumption frequency = the number of times the daily power consumption is zero in a month

[0027] Judgment rules: Abnormal frequency exceeding 5 times / month is considered abnormal.

[0028] The month-on-month change rate of electricity consumption is calculated as follows:

[0029]

[0030] Judgment rules: A year-on-year decline for three consecutive months, or a year-on-year growth rate decline of 50%, is considered abnormal;

[0031] The year-on-year growth rate of electricity consumption is calculated as follows:

[0032]

[0033] Judgment rules: A year-on-year decline for three consecutive months, or a 50% drop in the year-on-year growth rate, is considered abnormal.

[0034] Furthermore, based on the operating data and electricity usage status data of the metering equipment enterprise, the operating status of the metering equipment enterprise is monitored and evaluated, including:

[0035] Collecting the operating data of the measuring equipment enterprises;

[0036] Conduct a correlation analysis between the electricity consumption index and the operating data of the metering equipment enterprise. If the electricity consumption index shows a significant positive or negative correlation with the operating income and net profit operating indicators, it means that the index reflects the changes in the production and operation status of the enterprise;

[0037] Establish a regression model between electricity consumption indicators and operating data. Quantify the impact of each indicator on operating indicators;

[0038] For electricity consumption indicators that do not match operating data, analyze their production and operation problems.

[0039] The present invention provides a system for monitoring the operation status of a metering device enterprise based on power data, comprising:

[0040] The electricity consumption data acquisition module is used to obtain the electricity consumption data of the metering equipment enterprise;

[0041] An electricity consumption feature extraction module, used to extract the electricity consumption features of the metering equipment enterprise based on the electricity consumption data;

[0042] A power consumption status data calculation module, used to construct a power consumption model of the metering equipment enterprise according to the power consumption characteristics, and calculate the power consumption status data of the metering equipment enterprise through the power consumption model;

[0043] The monitoring and evaluation module is used to monitor and evaluate the operating status of the metering equipment enterprise based on the operating data and power consumption status data of the metering equipment enterprise.

[0044] Furthermore, the electricity consumption data of the metering equipment enterprises include:

[0045] The electricity consumption of the metering equipment enterprise, enterprise credit code, enterprise address, enterprise type, and statistical date.

[0046] Furthermore, it also includes:

[0047] The preprocessing module is used to preprocess the electricity consumption data of the metering equipment enterprise, specifically including:

[0048] Remove irrelevant content from electricity consumption data according to the statistical scope;

[0049] Check and correct the abnormal data in the electricity consumption data, and treat the electricity consumption data that cannot be checked as missing values;

[0050] Missing values ​​were checked and supplemented, and data that could not be supplemented were interpolated or eliminated;

[0051] Clean the electricity consumption data, remove duplicate and redundant data, and ensure the uniqueness of the data

[0052] Furthermore, the electricity consumption characteristics of the metering equipment enterprise include:

[0053] The electricity consumption characteristics of the metering equipment enterprise, including electricity consumption, number of users, business expansion capacity, electricity charges, installed capacity and electricity consumption indicators.

[0054] The present invention provides a method and system for monitoring the operating status of a metering equipment enterprise based on electric power data. By establishing a portrait of the metering equipment manufacturing enterprise, the basic situation of the metering equipment manufacturing enterprise can be accurately understood. By establishing an enterprise status monitoring model system, the operating status of the metering equipment manufacturing enterprise can be monitored in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 It is a flow chart of a method for monitoring the operation status of a metering device enterprise based on power data provided by an embodiment of the present invention;

[0056] Figure 2 is the correlation between the month-on-month growth rate of electricity consumption and operating income involved in the embodiment of the present invention;

[0057] Figure 3 is the correlation between the year-on-year growth rate of electricity consumption and operating income involved in the embodiment of the present invention;

[0058] Figure 4 is the main operating income of a certain measuring equipment manufacturing enterprise involved in the embodiment of the present invention;

[0059] Figure 5 It is a structural schematic diagram of a metering equipment enterprise operation status monitoring system based on power data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0060] Many specific details are set forth in the following description to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of the present invention, so the present invention is not limited to the specific implementation disclosed below.

[0061] Figure 1 The present invention provides a flow chart of a method for monitoring the operation status of a metering device enterprise based on power data, which mainly includes: data processing, data model construction and model effect evaluation. The method includes the following steps:

[0062] Step S101, obtaining electricity consumption data of a metering equipment enterprise.

[0063] Data source: State Grid Electricity Consumption Collection 2.0 System.

[0064] Data fields: including electricity consumption, enterprise credit code, enterprise address, enterprise type, statistical date and other fields.

[0065] Data volume: Since the electricity consumption collection system has comprehensive data coverage and fine data granularity, the data volume is usually in the billions.

[0066] Then the electricity consumption data of the metering equipment enterprises are checked and preprocessed, including:

[0067] Data missing rate statistics: statistics on data missing rate by different dimensions such as region, enterprise type, date, etc.

[0068] Data uniqueness statistics: count the amount of data in each dimension field, check whether the data is unique, and avoid data duplication.

[0069] Abnormal data statistics: check the historical values ​​of electricity consumption and other data in different dimensions for the same period and the previous period, and count the enterprise data with large fluctuations.

[0070] Data consistency check: Check the data level of internal electricity consumption data with the external electricity consumption data released by the National Energy Administration to ensure the consistency of data levels of different calibers.

[0071] Step S102: extracting the electricity consumption characteristics of the metering equipment enterprise based on the electricity consumption data.

[0072] Based on the electricity consumption data of the metering equipment enterprises, the electricity consumption characteristics of the metering equipment enterprises, such as the electricity consumption, number of users, business expansion capacity, electricity charges, installed capacity and electricity consumption indicators, are extracted. The constructed features are analyzed by feature importance, correlation and other methods to select the electricity consumption indicators as the important features of the model.

[0073] Step S103: constructing a power consumption model of the metering equipment enterprise according to the power consumption characteristics, and calculating the power consumption status data of the metering equipment enterprise through the power consumption model.

[0074] Model selection is done according to the following principles:

[0075] Relevance: The selected indicator should directly or indirectly reflect the electricity consumption pattern of the enterprise.

[0076] Representativeness: The selected indicators can cover the electricity consumption characteristics in different time periods.

[0077] Stability: The selected indicators should have a certain stability under normal circumstances.

[0078] Sensitivity: The selected indicator is sensitive to changes in abnormal states.

[0079] Interpretability: The selected metrics are easy to understand and interpret for subsequent analysis.

[0080] Calculating the power consumption status data of the metering equipment enterprise through the power consumption model includes:

[0081] The daily electricity consumption fluctuation rate is calculated as follows:

[0082]

[0083] Judgment rules: A month-on-month decrease of more than 10% for three consecutive months is considered abnormal;

[0084] The rate of change of electricity consumption trend is calculated as follows:

[0085]

[0086] Judgment rules: A significant deviation of 10% from the historical average for two consecutive weeks is considered abnormal;

[0087] The abnormal frequency of electricity consumption is calculated as follows:

[0088] Abnormal power consumption frequency = the number of times the daily power consumption is zero in a month

[0089] Judgment rules: Abnormal frequency exceeding 5 times / month is considered abnormal.

[0090] The month-on-month change rate of electricity consumption is calculated as follows:

[0091]

[0092] Judgment rules: A year-on-year decline for three consecutive months, or a year-on-year growth rate decline of 50%, is considered abnormal;

[0093] The year-on-year growth rate of electricity consumption is calculated as follows:

[0094]

[0095] Judgment rules: A year-on-year decline for three consecutive months, or a 50% drop in the year-on-year growth rate, is considered abnormal.

[0096] Step S104: monitoring and evaluating the operating status of the metering equipment enterprise based on the operating data and power usage status data of the metering equipment enterprise.

[0097] Collecting the operating data of the measuring equipment enterprises;

[0098] Conduct a correlation analysis between the electricity consumption index and the operating data of the metering equipment enterprise. If the electricity consumption index shows a significant positive or negative correlation with the operating income and net profit operating indicators, it means that the index reflects the changes in the production and operation status of the enterprise;

[0099] Establish a regression model between electricity consumption indicators and operating data. Quantify the impact of each indicator on operating indicators;

[0100] For electricity consumption indicators that do not match operating data, analyze their production and operation problems.

[0101] The specific model evaluation process is as follows:

[0102] 1) Select representative listed companies in the industry.

[0103] 2) Collect operating data of listed companies

[0104] Including financial statement data (operating income, net profit, etc.), production and operation data (output, product prices, etc.), etc. The time span can be selected as 3-5 years.

[0105] 3) Correlation between analytical indicators and operating data

[0106] The calculated power consumption index values ​​are analyzed for correlation with the operating data of listed companies. If certain power consumption indicators show a significant positive or negative correlation with operating indicators such as operating income and net profit, it means that the indicator reflects the changes in the production and operation status of the enterprise.

[0107] 4) Explanatory power of test indicators

[0108] Establish a regression model between electricity consumption indicators and operating data. Quantify the impact of each indicator on operating indicators.

[0109] 5) Analyze abnormal situations

[0110] Pay attention to abnormal power consumption indicators that do not match the operating data, and conduct in-depth analysis of the possible production and operation problems behind them. Further verify the accuracy of model diagnosis through interviews with management and field research.

[0111] In the first quarter of 2024, the power consumption behavior indicator data of a listed company that produces metering equipment was abnormal. The specific indicator data is shown in Table 1. After checking the operating income data of the company, it was verified that the main operating income in the first quarter of 2024 declined compared with the previous month and the same period last year, as follows Figure 4 .

[0112] Table 1: Electricity consumption indicators of a certain enterprise

[0113]

[0114] According to the model evaluation, the month-on-month growth rate of electricity consumption and the year-on-year growth rate of electricity consumption are positively correlated with operating income. Figure 2 and Figure 3The correlation coefficients are 0.65 and 0.61 respectively, which shows that the indicators of the model of the present invention can reflect the production and operation status of the enterprise.

[0115] Based on the same inventive concept, the present invention also provides a metering equipment enterprise operation status monitoring system 500 based on power data, such as Figure 5 As shown, including:

[0116] The power consumption data acquisition module 510 is used to acquire the power consumption data of the metering equipment enterprise;

[0117] The power consumption feature extraction module 520 is used to extract the power consumption features of the metering equipment enterprise based on the power consumption data;

[0118] The power consumption status data calculation module 530 is used to construct a power consumption model of the metering equipment enterprise according to the power consumption characteristics, and calculate the power consumption status data of the metering equipment enterprise through the power consumption model;

[0119] The monitoring and evaluation module 540 is used to monitor and evaluate the operating status of the metering equipment enterprise based on the operating data and power consumption status data of the metering equipment enterprise.

[0120] Furthermore, the electricity consumption data of the metering equipment enterprises include:

[0121] The electricity consumption of the metering equipment enterprise, enterprise credit code, enterprise address, enterprise type, and statistical date.

[0122] Furthermore, it also includes:

[0123] The preprocessing module is used to preprocess the electricity consumption data of the metering equipment enterprise, specifically including:

[0124] Remove irrelevant content from electricity consumption data according to the statistical scope;

[0125] Check and correct the abnormal data in the electricity consumption data, and treat the electricity consumption data that cannot be checked as missing values;

[0126] Missing values ​​were checked and supplemented, and data that could not be supplemented were interpolated or eliminated;

[0127] Clean the electricity consumption data, remove duplicate and redundant data, and ensure the uniqueness of the data

[0128] Furthermore, the electricity consumption characteristics of the metering equipment enterprise include:

[0129] The electricity consumption characteristics of the metering equipment enterprise, including electricity consumption, number of users, business expansion capacity, electricity charges, installed capacity and electricity consumption indicators.

[0130] The present invention provides a method and system for monitoring the operating status of a metering equipment enterprise based on electric power data. By establishing a portrait of the metering equipment manufacturing enterprise, the basic situation of the metering equipment manufacturing enterprise can be accurately understood. By establishing an enterprise status monitoring model system, the operating status of the metering equipment manufacturing enterprise can be monitored in real time.

[0131] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0132] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0133] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0134] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0135] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalents that do not depart from the spirit and scope of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A method for monitoring the operation status of a metering equipment enterprise based on power data, characterized in that: include: Obtain electricity consumption data from metering equipment companies; Based on the electricity consumption data, extracting the electricity consumption characteristics of the metering equipment enterprise; According to the electricity consumption characteristics, construct an electricity consumption model of the metering equipment enterprise, and calculate the electricity consumption status data of the metering equipment enterprise through the electricity consumption model; Based on the operating data and electricity usage status data of the metering equipment enterprise, the operating status of the metering equipment enterprise is monitored and evaluated.

2. The method according to claim 1, characterized in that Metering equipment company electricity consumption data, including: The electricity consumption of the metering equipment enterprise, enterprise credit code, enterprise address, enterprise type, and statistical date.

3. The method according to claim 1, characterized in that: After the step of obtaining the electricity consumption data of the metering equipment enterprise, it also includes: Preprocessing the electricity consumption data of the metering equipment enterprise includes: Remove irrelevant content from electricity consumption data according to the statistical scope; Check and correct the abnormal data in the electricity consumption data, and treat the electricity consumption data that cannot be checked as missing values; Missing values ​​were checked and supplemented, and data that could not be supplemented were interpolated or eliminated; Clean the electricity consumption data, remove duplicate and redundant data, and ensure the uniqueness of the data.

4. The method according to claim 1, characterized in that Based on the electricity consumption data, extracting the electricity consumption characteristics of the metering equipment enterprise includes: Based on the electricity consumption data of the metering equipment enterprise, the electricity consumption characteristics of the metering equipment enterprise, the number of users, business expansion capacity, electricity charges, installed capacity and electricity consumption indicators are extracted.

5. The method according to claim 1, characterized in that Calculating the power consumption status data of the metering equipment enterprise through the power consumption model includes: The daily electricity consumption fluctuation rate is calculated as follows: Judgment rules: A month-on-month decrease of more than 10% for three consecutive months is considered abnormal; The rate of change of electricity consumption trend is calculated as follows: Judgment rules: A significant deviation of 10% from the historical average for two consecutive weeks is considered abnormal; The abnormal frequency of electricity consumption is calculated as follows: Abnormal power consumption frequency = the number of times the daily power consumption is zero in a month Judgment rules: Abnormal frequency exceeding 5 times / month is considered abnormal. The month-on-month change rate of electricity consumption is calculated as follows: Judgment rules: A year-on-year decline for three consecutive months, or a year-on-year growth rate decline of 50%, is considered abnormal; The year-on-year growth rate of electricity consumption is calculated as follows: Judgment rules: A year-on-year decline for three consecutive months, or a 50% drop in the year-on-year growth rate, is considered abnormal.

6. The method according to claim 1, characterized in that Based on the operating data and electricity usage status data of the metering equipment enterprise, the operating status of the metering equipment enterprise is monitored and evaluated, including: Collecting the operating data of the measuring equipment enterprises; Conduct a correlation analysis between the electricity consumption index and the operating data of the metering equipment enterprise. If the electricity consumption index shows a significant positive or negative correlation with the operating income and net profit operating indicators, it means that the index reflects the changes in the production and operation status of the enterprise; Establish a regression model between electricity consumption indicators and operating data. Quantify the impact of each indicator on operating indicators; For electricity consumption indicators that do not match operating data, analyze their production and operation problems.

7. A system for monitoring the operation status of a metering equipment enterprise based on power data, characterized in that: include: The electricity consumption data acquisition module is used to obtain the electricity consumption data of the metering equipment enterprise; An electricity consumption feature extraction module, used to extract the electricity consumption features of the metering equipment enterprise based on the electricity consumption data; A power consumption status data calculation module, used to construct a power consumption model of the metering equipment enterprise according to the power consumption characteristics, and calculate the power consumption status data of the metering equipment enterprise through the power consumption model; The monitoring and evaluation module is used to monitor and evaluate the operating status of the metering equipment enterprise based on the operating data and power consumption status data of the metering equipment enterprise.

8. The system according to claim 7, characterized in that Metering equipment company electricity consumption data, including: The electricity consumption of the metering equipment enterprise, enterprise credit code, enterprise address, enterprise type, and statistical date.

9. The system according to claim 7, characterized in that Also includes: The preprocessing module is used to preprocess the electricity consumption data of the metering equipment enterprise, specifically including: Remove irrelevant content from electricity consumption data according to the statistical scope; Check and correct the abnormal data in the electricity consumption data, and treat the electricity consumption data that cannot be checked as missing values; Missing values ​​were checked and supplemented, and data that could not be supplemented were interpolated or eliminated; Clean the electricity consumption data, remove duplicate and redundant data, and ensure the uniqueness of the data.

10. The system according to claim 7, characterized in that The electricity consumption characteristics of the metering equipment enterprise include: The electricity consumption characteristics of the metering equipment enterprise, including electricity consumption, number of users, business expansion capacity, electricity charges, installed capacity and electricity consumption indicators.

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