A power supply digital management system based on the power system

Abstract

The present invention provides a power supply digital management system based on a power system. The system includes a display platform, a metering monitoring and analysis module, a customer analysis module, and a power supply station analysis module. The display platform is used for users to log in, uniformly authenticate user identities, and display the data analysis results from the metering monitoring and analysis module, the customer analysis module, and the power supply station analysis module, and at the same time display the to-do items from the metering monitoring and analysis module, the customer analysis module, and the power supply station analysis module. The metering monitoring and analysis module is used to realize off-line analysis of metering terminals, analysis of abnormal metering data, analysis of unsuccessful meter reading, and line loss analysis according to metering information. The customer analysis module is used to realize customer label classification and customer demand analysis according to customer information. The power supply station analysis module is used to realize analysis of power supply station index values and ranking according to the business system data of each power supply station.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply management, and particularly to a power supply digital management system based on a power system. Background Art

[0002] With the continuous growth of the power supply demand in various industries of society and the continuous growth of the power grid scale, there are problems in the current power supply system such as low efficiency of various power supply service data, serious information island phenomenon, a large variety of reports, low data visualization level, and incomplete problem analysis, making it difficult to achieve the standardized construction and digital transformation of power supply stations. Summary of the Invention

[0003] The purpose of the present invention is to provide a power supply digital management system based on a power system to solve the problems raised in the above background art.

[0004] The present invention is realized through the following technical solutions: A power supply digital management system based on a power system, the system includes a display platform, a metering monitoring and analysis module, a customer analysis module, and a power supply station analysis module. The display platform is used for users to log in, uniformly authenticate user identities, and display the data analysis results from the metering monitoring and analysis module, the customer analysis module, and the power supply station analysis module, and at the same time display the to-do items from the metering monitoring and analysis module, the customer analysis module, and the power supply station analysis module;

[0005] The metering monitoring and analysis module is used to realize metering terminal offline analysis, metering abnormal data analysis, unsuccessful meter reading analysis, and line loss analysis according to metering information;

[0006] The customer analysis module is used to realize customer label classification and customer demand analysis according to customer information;

[0007] The power supply station analysis module is used to realize power supply station index value analysis and ranking according to the business system data of each power supply station.

[0008] Optionally, the metering monitoring and analysis module includes a metering terminal offline analysis unit, a metering abnormal data analysis unit, an unsuccessful meter reading analysis unit, and a line loss analysis unit.

[0009] The metering terminal offline analysis unit is used to analyze and count the total number of devices of the offline terminals and output a list of offline terminals;

[0010] The unsuccessful meter reading analysis unit is used to analyze and count the total number of customers with unsuccessful meter reading and output a list of customers with unsuccessful meter reading. According to the list of customers with unsuccessful meter reading, an unsuccessful meter reading card is established, and the unsuccessful meter reading card is associated with the line name and the customer manager;

[0011] The metering anomaly data analysis unit is used to analyze the voltage and current data of newly installed metering devices, and statistically display the metering anomaly data, which includes reverse power, loss of current, and loss of voltage data. Based on the metering anomaly data, a metering anomaly card associated with the newly installed metering device is established;

[0012] The line loss analysis unit is used to collect metering line loss analysis data, analyze the power consumption fluctuation of specific users, obtain the power consumption fluctuation curve of specific users, and at the same time analyze the real-time line loss trend of the line associated with specific users, obtain the line trend curve, perform fitting analysis on the power consumption fluctuation curve of specific users and the line trend curve, select the curve with a high fitting degree with the line trend curve among the power consumption fluctuation curves of multiple specific users, and output a list of users with high fitting degrees.

[0013] Optionally, the customer analysis module includes a customer label classification unit and a customer demand analysis unit.

[0014] The customer label classification unit is used to classify customers into high-demand customers, high-risk customers, long-term power outage customers, and repeated power outage customers according to customer information and customer demand work orders;

[0015] The customer demand analysis unit selects customer demand work orders in different time periods, extracts keywords in the customer demand work orders, clusters the customer demand work orders according to the keywords, obtains multiple cluster results, sorts the cluster results based on the number of members in the cluster, and selects the cluster result with the largest number of members as the hot demand.

[0016] Optionally, classifying customers into high-demand customers, high-risk customers, long-term power outage customers, and repeated power outage customers according to customer information and customer demand work orders specifically includes:

[0017] Set a threshold for the number of customer demands to analyze whether the number of customer demands reaches or exceeds the threshold up to the current time, and output a high-demand customer label after evaluation;

[0018] Set thresholds for the amount of customer arrears and monthly power consumption value to analyze whether the amount of customer arrears reaches or exceeds the threshold up to the current time, and output a high-risk customer label after evaluation;

[0019] Set a threshold for the total power outage duration of customers to analyze whether the total power outage duration of customers reaches or exceeds the threshold up to the current time, and output a long-term power outage customer label after evaluation;

[0020] Set a threshold for the number of customer power outages to analyze whether the number of customer power outages reaches or exceeds the threshold up to the current time, and output a repeated power outage customer label after evaluation.

[0021] Optionally, the steps of extracting keywords from the customer demand work orders and clustering the customer demand work orders according to the keywords are specifically as follows:

[0022] Collect the text content in the demand work order through the text collector in the text mining engine; and perform word segmentation on the text content to obtain multiple phrases;

[0023] Calculate the occurrence frequency of each phrase in the text content, and select the phrase with the highest occurrence frequency as the keyword;

[0024] Use the keyword as the clustering center to cluster multiple customer demand work orders to obtain multiple cluster results. Based on the number of members in the cluster, sort the cluster results, and select the clustering result with the most members in the cluster as the hot demand.

[0025] Optionally, the power supply station analysis module includes an index value calculation unit and a sorting unit. The index value calculation unit is used to calculate multiple index values of each power supply station according to the business data of each power supply station;

[0026] The sorting unit is used to sort the specific index values of multiple power supply stations according to the numerical size to generate the ranking of power supply stations based on the specific index.

[0027] Optionally, the display platform is used for users to log in and uniformly authenticate the user identity, and specifically includes the following steps:

[0028] When the user logs in through the display platform for the first time, the user inputs the identity ID and the login password through the display platform, and the display platform sends an authentication message containing the identity ID and the timestamp information to the authentication server;

[0029] Establish an image library and a color library in the authentication server. There are multiple pictures with different colors in the image library, and there are multiple pictures containing only a single color in the color library;

[0030] Randomly select a picture from the image library as the first picture, and randomly select a picture from the color library as the second picture. Respectively extract and detect the color with the largest proportion in the first picture and the second picture, and calculate the Euclidean distance between the colors with the largest proportion in the first picture and the second picture;

[0031] Construct an authentication code with the identity ID, timestamp, Euclidean distance, and width and height data of the picture sent by the display platform. The identity ID and the authentication code are stored in the authentication server, and at the same time, the authentication server sends the authentication code back to the display platform;

[0032] When the user logs in to the display platform for non - first time, the display platform sends the identity ID and the authentication code to the authentication server for comparison. If the comparison is consistent, the user can log in through the display platform.

[0033] Optionally, it further includes a visualization module, which is used to form visualization images of the data analysis results of the metering monitoring and analysis module, the customer analysis module, and the power supply station analysis module, and display them through the display platform.

[0034] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0035] A power - supply digital management system based on a power system provided by the present invention comprehensively analyzes metering data, power - supply service data, and customer data, avoiding the phenomenon of information islands. At the same time, it realizes the overall analysis of power - supply service data, avoiding problems such as incomplete problem analysis. The present invention can comprehensively support the business process of the power supply station, control business risks, promote the efficient operation of business processes, continuously improve the service level of grass - roots power - supply units in production, enhance the work experience and efficiency of grass - roots units, and improve the reliability level of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only the preferred embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0037] Figure 1 It is a structural block diagram of a power - supply digital management system based on a power system provided by the present invention;

[0038] Figure 2 It is a structural block diagram of the metering monitoring and analysis module provided by the present invention;

[0039] Figure 3 It is a structural block diagram of the customer analysis module provided by the present invention;

[0040] Figure 4 It is a structural block diagram of the power supply station analysis module provided by the present invention.

[0041] In the figure, 1 is the display platform, 2 is the metering monitoring and analysis module, 201 is the metering terminal offline analysis unit, 202 is the metering abnormal data analysis unit, 203 is the unsuccessful meter - reading analysis unit, 204 is the line - loss analysis unit, 3 is the customer analysis module, 301 is the customer label classification unit, 302 is the customer demand analysis unit, 4 is the power supply station analysis module, 401 is the index value calculation unit, 402 is the sorting unit, and 5 is the visualization module. DETAILED DESCRIPTION OF THE INVENTION

[0042] In order to make the objectives, technical solutions and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments of the present invention. It should be understood that the present invention is not limited by the exemplary embodiments described herein. Based on the embodiments of the present invention described herein, all other embodiments obtained by those skilled in the art without creative efforts shall fall within the protection scope of the present invention.

[0043] In the following description, numerous specific details are given to provide a more thorough understanding of the present invention. However, it is obvious to those skilled in the art that the present invention may be implemented without one or more of these details. In other instances, in order to avoid confusion with the present invention, some well-known technical features are not described.

[0044] It should be understood that the present invention can be implemented in different forms and should not be construed as limited to the embodiments presented herein. On the contrary, providing these embodiments will make the disclosure thorough and complete, and will fully convey the scope of the present invention to those skilled in the art.

[0045] The purpose of the terms used herein is only to describe specific embodiments and is not a limitation of the present invention. When used herein, the singular forms "a", "an" and "the" are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms "comprising" and / or "including", when used in this specification, determine the presence of the described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups. When used herein, the term "and / or" includes any and all combinations of the related listed items.

[0046] To thoroughly understand the present invention, detailed structures will be presented in the following description to illustrate the technical solutions proposed by the present invention. The optional embodiments of the present invention are described in detail as follows. However, in addition to these detailed descriptions, the present invention may also have other implementation manners.

[0047] See Figures 1 to 4 , a power supply digital management system based on a power system. The system includes a display platform 1, a metering monitoring and analysis module 2, a customer analysis module 3, and a power supply station analysis module 4. The display platform 1 is used for users to log in, uniformly authenticate user identities, and display the data analysis results from the metering monitoring and analysis module 2, the customer analysis module 3, and the power supply station analysis module 4, and at the same time display the to-do items from the metering monitoring and analysis module 2, the customer analysis module 3, and the power supply station analysis module 4;

[0048] The metering monitoring and analysis module 2 is used to perform off-line analysis of metering terminals, analysis of abnormal metering data, analysis of unsuccessful meter reading, and line loss analysis based on metering information;

[0049] The customer analysis module 3 is used to classify customer tags and analyze customer demands according to customer information;

[0050] The power supply station analysis module 4 is used to analyze the index values of each power supply station and rank them according to the business system data of each power supply station.

[0051] Furthermore, for the metering monitoring and analysis module 2, it includes a metering terminal off-line analysis unit 201, a metering abnormal data analysis unit 202, an unsuccessful meter reading analysis unit 203, and a line loss analysis unit 204.

[0052] The metering terminal off-line analysis unit 201 is used to analyze and count the total number of devices of the off-line terminals and output a list of off-line terminals. The list information includes: line name, transformer name, number of customers with unsuccessful meter reading, customer manager, time of unsuccessful meter reading, proportion of unsuccessful meter reading, and off-line duration of customer terminals.

[0053] The unsuccessful meter reading analysis unit 203 is used to analyze and count the total number of customers with unsuccessful meter reading and output a list of customers with unsuccessful meter reading. According to the list of customers with unsuccessful meter reading, an unsuccessful meter reading card is established, and the unsuccessful meter reading card is associated with the line name and customer manager. Users can query the unsuccessful meter reading cards of the corresponding transformer by inputting the corresponding transformer name and substation area number, and can filter the corresponding unsuccessful meter reading cards by line name and customer manager for individual viewing.

[0054] The metering abnormal data analysis unit 202 is used to analyze the voltage and current data of newly installed metering devices and statistically display metering abnormal data. The metering abnormal data includes reverse power, loss of current, and loss of voltage data. Based on the metering abnormal data, a metering abnormal card associated with the newly installed metering device is established. By associating with the corresponding customers, the number of customers with reverse power, loss of current, and loss of voltage is output for card display, and the customer details list (substation name, transformer name, customer name, customer address) can be viewed by expanding. By jumping to the details, the trend chart of the metering abnormal data (reverse power, loss of current, loss of voltage, etc.) of the customer can be viewed.

[0055] The line loss analysis unit 204 is based on the metering system according to the substation area, and according to the current user permissions, it statistically analyzes the basic data with inconsistent file information and the basic data of abnormal three-phase meters (voltage abnormality, current abnormality, power abnormality, three-phase imbalance), and statistically analyzes the user situations with abnormal line losses.

[0056] Specifically, by analyzing the power consumption fluctuation of a specific user, a power consumption fluctuation curve of the specific user is obtained. At the same time, the real-time line loss trend of the line associated with the specific user is analyzed to obtain a line trend curve. The power consumption fluctuation curve of the specific user and the line trend curve are subjected to fitting analysis. Among the power consumption fluctuation curves of multiple specific users, the curve with a high fitting degree to the line trend curve is selected, and a list of users with a high fitting degree is output. The information included in the foregoing list is: line name, transformer name, customer name, and customer number.

[0057] Furthermore, the customer analysis module 3 includes a customer label classification unit 301 and a customer demand analysis unit 302.

[0058] The customer label classification unit 301 is used to classify customers into high-demand customers, high-risk customers, customers with long-term power outages, and customers with repeated power outages according to customer information and customer demand work orders.

[0059] The customer demand analysis unit 302 selects customer demand work orders in different time periods, extracts keywords in the customer demand work orders, and clusters the customer demand work orders according to the keywords to obtain multiple cluster results. Based on the number of members in the cluster, the cluster results are sorted, and the cluster result with the largest number of members is selected as the hot demand.

[0060] When the customer demand analysis unit 302 is working, the extraction of keywords in the customer demand work orders and the clustering of the customer demand work orders according to the keywords specifically include the following steps:

[0061] S1. Collect the text content in the demand work order through the text collector in the text mining engine; and perform word segmentation on the text content to obtain multiple phrases. In this embodiment, an HMM (Hidden Markov Model) word segmentation model with Chinese character word formation ability is used for word segmentation. HMM is a process in which a hidden Markov chain randomly generates an unobservable random sequence, and then each state generates an observed random sequence. Its main principle is to regard the input sentence and the word segmentation result as two sequences, the sentence as the observed sequence, and the word segmentation result as the state sequence. When the annotation of the state sequence is completed, the word segmentation result is obtained. The Viterbi algorithm of dynamic programming can be used during the annotation process to reduce the algorithm complexity.

[0062] S2. Calculate the occurrence frequency of each phrase in the text content, and select the phrase with the highest occurrence frequency as the keyword.

[0063] In step S2, after word segmentation is completed, there will be a large number of words that have no actual meaning but appear very frequently. These are called stop words, which are roughly divided into the following two categories: one category is words that are very widely used, such as "is", "in", "but", "that", etc.; the other category is words that appear frequently in the text but have no clear meaning for the text itself, but have a certain role in a complete sentence, such as the common words "de" (of), "qu" (go), etc. Therefore, it is also necessary to establish a common word list, eliminate the common words in the phrase, and the remaining phrases are the keywords of the text content.

[0064] S3. Using the keywords as the clustering centers, cluster multiple customer demand work orders to obtain multiple cluster results. For example, the keywords of several customer demand work orders are "power outage", and the keywords of several other customer demand work orders are "electricity price". Taking the keyword "power outage" as the clustering center, multiple customer demand work orders with the keyword "power outage" form a cluster result with the keyword "power outage". Similarly, multiple customer demand work orders with the keyword "electricity price" form a cluster result with the keyword "electricity price". Compare the number of members in the cluster result of the keyword "power outage" with the number of members in the cluster result of the keyword "electricity price", and based on the number of members in the cluster, sort the cluster results, and select the clustering result with the largest number of members in the cluster as the hot demand. If the number of members in the cluster result of the keyword "power outage" is greater than the number of members in the cluster result of the keyword "electricity price", then "power outage" is the hot demand of the customers.

[0065] Furthermore, according to the customer information and the customer's demand work orders, classify the customers into high-demand customers, high-risk customers, long-term power outage customers, and repeated power outage customers, specifically including:

[0066] Set a threshold for the number of customer demands, which is used to analyze whether the number of customer demands reaches or exceeds the threshold within the current time, and output the label of high-demand customers after evaluation;

[0067] Set thresholds for the customer's overdue payment amount and monthly electricity consumption value, which are used to analyze whether the customer's overdue payment amount reaches or exceeds the threshold within the current time, and output the label of high-risk customers after evaluation;

[0068] Set a threshold for the total power outage duration of the customer, which is used to analyze whether the total power outage duration of the customer reaches or exceeds the threshold within the current time, and output the label of long-term power outage customers after evaluation;

[0069] Set a threshold for the number of power outages of the customer, which is used to analyze whether the number of power outages of the customer reaches or exceeds the threshold within the current time, and output the label of repeated power outage customers after evaluation.

[0070] Furthermore, the power supply station analysis module 4 includes an index value calculation unit 401 and a sorting unit 402. The index value calculation unit 401 is used to calculate multiple index values of each power supply station according to the business data of each power supply station.

[0071] Among them, the index values include: production - related indicators: medium - voltage line failure rate, distribution transformer failure power outage rate, qualified rate of distribution network data quality, proportion of users with repeated power outages, online rate of distribution automation terminals, average customer power outage time (low - voltage), average user power outage time (medium - voltage), self - healing line coverage rate, actual power transfer rate during planned power outages, year - on - year decline rate of the number of medium - voltage users with power outages exceeding 12 hours, year - on - year decline rate of the number of users with power outage times reaching 3 or more times, year - on - year decline rate of the number of overloaded distribution transformers in peak load months, safety violation notifications (A, B, C, D);

[0072] Marketing - related indicators: electricity charge recovery rate, comprehensive line loss rate, abnormal line loss rate, lossy line loss rate, compliance rate of time used for optimizing the business environment - average time used for low - voltage business expansion (for small and micro enterprises) installation, compliance rate of time used for optimizing the business environment - proportion of low - voltage non - residential business expansion installation exceeding the specified time, power supply volume, electricity sales volume, automatic meter reading success rate, customer complaint rate, electricity charge error rate, electronic settlement rate, completion rate of electricity use inspection.

[0073] The sorting unit 402 is used to sort the specific index values of multiple power supply stations according to the numerical size, and generate the ranking of power supply stations based on the specific index.

[0074] For example, for production - related indicators, the results that the sorting unit 402 can obtain include: for the medium - voltage line failure rate, at the regulatory level, the ranking of the permanent fault times of the current 10kV lines of the municipal bureau can be viewed; at the enterprise management level, the ranking of the permanent fault times of the 10kV lines of the current power supply station can be viewed, and the equipment owner.

[0075] For the distribution transformer failure power outage rate, at the regulatory and enterprise management levels, the ranking of the current medium - voltage fault power outage household times can be viewed, belonging to the power supply station, and through the power supply station, the proportion chart of fault causes can be jumped to view.

[0076] For the qualified rate of distribution network data quality, at the power supply station level and enterprise management level, the ranking of power supply stations with a qualified rate less than 100% can be viewed; at the regulatory level, the ranking of the number of power supply stations with a qualified rate less than 100% in each regional bureau can be viewed.

[0077] For the proportion of users with repeated power outages, at the power supply station level, the number of medium - voltage users with repeated power outages can be viewed; at the enterprise management level, the ranking of the number of medium - voltage users with repeated power outages, the name of the power supply station, and the number of medium - voltage users with repeated power outages in the power supply station can be viewed; at the regulatory level, the ranking of the number of medium - voltage users with repeated power outages in each local municipal bureau, the name of the local municipal bureau, and the number of medium - voltage users with repeated power outages can be viewed.

[0078] For the online rate of distribution automation terminals, at the enterprise management level, the ranking of the terminal online rates of each district and county bureau (name of the district and county bureau, terminal online rate) can be viewed; at the regulatory level, the ranking of the terminal online rate of the municipal bureau (name of the municipal bureau, terminal online rate) can be viewed.

[0079] Safety violation notice (A, B, C, D): At the regulatory level of drilling down, the ranking of the number of safety violations in the municipal bureaus can be viewed, and it supports jumping to view the proportion chart of the number of various types of safety violations in the municipal bureaus through the number of violations; at the enterprise management level, the ranking of the number of safety violations in the power supply stations can be viewed, and it supports jumping to view the proportion chart of the number of various types of safety violations in each power supply station through the number of violations.

[0080] For marketing indicators: At the regulatory level of drilling down for the electricity fee recovery rate, the ranking of the total amount of outstanding fees of each municipal bureau as of the current year can be viewed; at the enterprise management level, the ranking of the total amount of outstanding fees of the power supply stations under the municipal bureau as of the current year can be viewed; the power supply station can view the ranking of the total amount of outstanding fees of the management areas of the customer managers as of the current year, and it supports jumping to the electricity fee visualization module 5 through the customer manager to view the detailed outstanding fee data.

[0081] For the comprehensive line loss rate: At the regulatory level of drilling down, the ranking of the loss electricity quantity of each municipal bureau in the current month and as of the current year can be viewed; at the enterprise management level, the ranking of the loss electricity quantity of each power supply station in the current month and as of the current year can be viewed.

[0082] For the line loss abnormality rate: At the regulatory level of drilling down, the ranking of the number of abnormal lines and abnormal areas in each municipal bureau in the current month can be viewed; at the enterprise management level, the ranking of the number of abnormal lines and abnormal areas in each power supply station in the current month can be viewed.

[0083] For the power supply quantity: At the regulatory level of drilling down, the ranking of the power supply quantity of each municipal bureau in the current month and the power supply quantity as of the current year can be viewed; at the enterprise management level, the ranking of the power supply quantity of each power supply station in the current month and the power supply quantity as of the current year can be viewed.

[0084] For the electricity sales quantity: At the regulatory level of drilling down, the ranking of the electricity sales quantity of each municipal bureau in the current month and the electricity sales quantity as of the current year can be viewed; at the enterprise management level, the ranking of the electricity sales quantity of each power supply station in the current month and the electricity sales quantity as of the current year can be viewed.

[0085] For the automatic meter reading success rate: At the regulatory level of drilling down, the ranking of the number of users with failed low-voltage meter readings in each municipal bureau in the current month can be viewed; at the enterprise management level, the ranking of the number of users with failed low-voltage meter readings in each power supply station in the current month can be viewed.

[0086] For the customer complaint rate: At the regulatory level of drilling down, the ranking of the number of 95598 complaint-type work orders of each municipal bureau in the current month and as of the current year can be viewed; at the enterprise management level, the ranking of the number of 95598 complaint-type work orders of each power supply station in the current month and as of the current year can be viewed.

[0087] Furthermore, the display platform 1 is used for users to log in and uniformly authenticate the user identities, and specifically includes the following steps:

[0088] S21. When the user first logs in through the display platform 1, the user inputs the identity ID and the login password through the display platform 1, and the display platform 1 sends an authentication message containing the identity ID and the timestamp information to the authentication server;

[0089] S22. Establish an image library and a color library in the authentication server. The image library contains multiple pictures of different colors, and the color library contains multiple pictures that only contain a single color.

[0090] S23. Randomly select a picture from the image library as the first picture, and randomly select a picture from the color library as the second picture. Extract and detect the color with the largest proportion in the first picture and the second picture respectively, and calculate the Euclidean distance between the colors with the largest proportion in the first picture and the second picture.

[0091] S24. Construct an authentication code with the identity ID, timestamp, Euclidean distance, and width and height data of the picture sent by the display platform 1. The identity ID and the authentication code are stored in the authentication server, and at the same time, the authentication server sends the authentication code back to the display platform 1.

[0092] S25. When the user logs in to the display platform 1 for non-first time, the display platform 1 sends the identity ID and the authentication code to the authentication server for comparison. If the comparison is consistent, the user can log in through the display platform 1.

[0093] Further, it further includes a visualization module 5. The visualization module 5 is used to form a visualization image of the data analysis results of the metering monitoring and analysis module 2, the customer analysis module 3, and the power supply station analysis module 4, and display it through the display platform 1.

[0094] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A power supply digital management system based on a power system, characterized in that, the system includes a display platform, a metering monitoring and analysis module, a customer analysis module, and a power supply station analysis module. The display platform is used for users to log in, uniformly authenticate user identities, and display the data analysis results from the metering monitoring and analysis module, the customer analysis module, and the power supply station analysis module, and at the same time display the to-do items from the metering monitoring and analysis module, the customer analysis module, and the power supply station analysis module; the metering monitoring and analysis module is used to achieve metering terminal offline analysis, metering abnormal data analysis, unsuccessful meter reading analysis, and line loss analysis according to metering information. The metering monitoring and analysis module includes a line loss analysis unit. The line loss analysis unit is used to collect metering line loss analysis data, analyze the electricity consumption fluctuation situation of a specific user, obtain the electricity consumption fluctuation curve of the specific user, and at the same time analyze the real-time line loss trend of the line associated with the specific user, obtain the line trend curve, perform fitting analysis on the electricity consumption fluctuation curve of the specific user and the line trend curve, select the curve with a high fitting degree with the line trend curve among the electricity consumption fluctuation curves of multiple specific users, and output a list of users with a high fitting degree; the customer analysis module is used to achieve customer label classification and customer demand analysis according to customer information and customer demand work orders. When implementing customer demand analysis, by extracting keywords in the customer demand work orders and clustering the customer demand work orders according to the keywords, the specific steps are as follows: collect the text content in the demand work order through the text collector in the text mining engine; and perform word segmentation processing on the text content to obtain multiple phrases; calculate the occurrence frequency of each phrase in the text content, and select the phrase with the highest occurrence frequency as the keyword; cluster multiple customer demand work orders with the keyword as the clustering center to obtain multiple cluster results, sort the cluster results based on the number of members in the cluster, and select the clustering result with the most members in the cluster as the hot demand; the power supply station analysis module is used to achieve power supply station index value analysis and ranking according to the business system data of each power supply station; the display platform is used for users to log in and uniformly authenticate user identities, and the specific steps are as follows: when a user first logs in through the display platform, the user inputs the identity ID and login password through the display platform, and the display platform sends an authentication message containing the identity ID and timestamp information to the authentication server; establish an image library and a color library in the authentication server. There are multiple pictures of different colors in the image library, and there are multiple pictures containing only a single color in the color library; randomly select a picture as the first picture in the image library, randomly select a picture as the second picture in the color library, respectively extract and detect the color with the largest proportion in the first picture and the second picture, and calculate the Euclidean distance between the colors with the largest proportion in the first picture and the second picture; Construct an authentication code with the identity ID, timestamp, Euclidean distance, and width and height data of the picture sent by the display platform. The identity ID and the authentication code are stored in the authentication server, and at the same time, the authentication server sends the authentication code back to the display platform; When the user logs in to the display platform for non-first time, the display platform sends the identity ID and the authentication code to the authentication server for comparison. If the comparison is consistent, the user can log in through the display platform.

2. A power system-based power supply digital management system according to claim 1, characterized in that, The metering monitoring and analysis module further includes a metering terminal offline analysis unit, a metering abnormal data analysis unit, and a meter reading unsuccessful analysis unit. The metering terminal offline analysis unit is used to analyze and count the total number of devices of the offline terminals and output a list of offline terminals; The meter reading unsuccessful analysis unit is used to analyze and count the total number of customers with unsuccessful meter reading, output a list of customers with unsuccessful meter reading, establish a meter reading unsuccessful card according to the list of customers with unsuccessful meter reading, and establish an associated relationship between the meter reading unsuccessful card and the line name and the customer manager; The metering abnormal data analysis unit is used to analyze the voltage and current data of newly installed metering devices, and count and display metering abnormal data. The metering abnormal data includes reverse power, loss of current, and loss of voltage data. Based on the metering abnormal data, a metering abnormal card associated with the newly installed metering device is established.

3. A power system-based power supply digital management system according to claim 2, characterized in that, The customer analysis module includes a customer label classification unit and a customer demand analysis unit. The customer label classification unit is used to classify customers into high-demand customers, high-risk customers, customers with long-term power outages, and customers with repeated power outages according to customer information and customer demand work orders; The customer demand analysis unit selects customer demand work orders in different time periods, extracts keywords in the customer demand work orders, clusters the customer demand work orders according to the keywords to obtain multiple cluster results, sorts the cluster results based on the number of members in the cluster, and selects the cluster result with the largest number of members in the cluster as the hot demand.

4. A power system-based power supply digital management system according to claim 3, characterized in that, Classifying customers into high-demand customers, high-risk customers, customers with long-term power outages, and customers with repeated power outages according to customer information and customer demand work orders specifically includes: Setting a customer demand frequency threshold for analyzing whether the customer's demand frequency reaches or exceeds the threshold up to the current time, and outputting a high-demand customer label after evaluation; Setting customer arrears amount and monthly power consumption value thresholds for analyzing whether the customer's arrears amount reaches or exceeds the threshold up to the current time, and outputting a high-risk customer label after evaluation; Setting a customer total power outage duration threshold for analyzing whether the customer's total power outage duration reaches or exceeds the threshold up to the current time, and outputting a long-term power outage customer label after evaluation; Setting a customer power outage frequency threshold for analyzing whether the customer's power outage frequency reaches or exceeds the threshold up to the current time, and outputting a repeated power outage customer label after evaluation.

5. A power supply digital management system based on a power system according to claim 4, characterized in that, the power supply station analysis module includes an index value calculation unit and a sorting unit. The index value calculation unit is used to calculate multiple index values of each power supply station according to the business data of each power supply station; the sorting unit is used to sort the specific index values of multiple power supply stations according to the numerical size, and generate a ranking of power supply stations based on the specific index.

6. A power supply digital management system based on a power system according to claim 1, characterized in that, it further includes a visualization module, and the visualization module is used to form visualization images of the data analysis results of the metering monitoring and analysis module, the customer analysis module and the power supply station analysis module, and display them through a display platform.

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