An electric power copy and check lean and intensive information management system

Abstract

This invention discloses a lean and intensive information management system for electricity meter reading and billing, comprising an automated data acquisition module, a blockchain technology application module, a real-time data processing and analysis module, an intensive management module, a system management and maintenance module, and an intelligent optimization scheduling module. The system employs automated data acquisition technology to replace traditional manual on-site meter reading. Through smart meters and remote communication technology, it achieves automatic data collection and real-time transmission of electricity consumption, significantly improving operational efficiency and reducing error rates. It meets the requirements of high concurrency and low latency meter reading. An edge computing gateway is deployed at the data acquisition end to perform preliminary data processing and analysis, reducing the burden on the central server and improving the overall system response speed. It integrates core processes such as meter reading, billing, and billing onto a unified platform, achieving intensive management of business processes.

Description

Technical Field

[0001] This invention relates to the field of information management technology, specifically to a lean and intensive information management system for electricity meter reading and verification. Background Technology

[0002] The technological background of the lean and intensive information management system for electricity meter reading and billing stems from the systemic pain points faced by traditional electricity marketing management models during their digital transformation. Traditional management models suffer from three major structural defects: First, the data collection process heavily relies on manual on-site meter reading, resulting in low efficiency and high error rates. Typical problems include missed readings and incorrect readings, leading to data distortion and high labor costs. Second, business processes suffer from severe fragmentation, with core processes such as meter reading, accounting, and billing operating in multiple independent systems, creating data silos and hindering cross-departmental collaboration and workflow obstruction. Finally, the inherent lag in traditional manual data collection leads to insufficient data timeliness, making it difficult to support the refined operational needs of modern electricity marketing, such as real-time dynamic pricing mechanisms and accurate load forecasting. These inherent defects collectively constitute the core driving force behind the transformation of electricity meter reading and billing systems towards intelligence and intensification. Summary of the Invention

[0003] The purpose of this invention is to provide a lean and intensive information management system for electricity meter reading and verification, so as to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a lean and intensive information management system for electricity meter reading and verification, comprising an automated data acquisition module, wherein the automated data acquisition module is connected to a real-time data processing and analysis module, the real-time data processing and analysis module is connected to an intensive management module, and the intensive management module is connected to an intelligent optimization scheduling module.

[0005] As a further technical solution of the present invention, the automated data acquisition module includes an intelligent data access module, a multi-type compatibility module, a remote communication module, a data verification module, a data cleaning module, an abnormal data identification module, an abnormal data marking module, and an edge computing gateway module.

[0006] As a further technical solution of the present invention, the real-time data processing and analysis module includes a data receiving and storage module, a real-time data processing module, a load forecasting and analysis module, a data visualization module, a report generation module, and a data analysis and mining module.

[0007] As a further technical solution of the present invention, the integrated management module includes a meter reading management module, an accounting management module, a billing management module, a process collaboration module, and a monitoring module.

[0008] As a further technical solution of the present invention, the intelligent optimization scheduling module includes a load optimization scheduling module, a distributed energy management module, and a demand-side response management module.

[0009] As a further technical solution of the present invention, the data analysis and mining module includes an algorithm integration module, a prediction model module, and an anomaly detection and early warning module.

[0010] As a further technical solution of the present invention, the automated data acquisition module is connected to a blockchain technology application module, and the real-time data processing and analysis module and the centralized management module are both connected to the blockchain technology application module.

[0011] As a further technical solution of the present invention, the blockchain technology application module includes a data security module, a distributed ledger module, and a decentralized transaction module.

[0012] As a further technical solution of the present invention, the centralized management module is connected to a system management and maintenance module.

[0013] As a further technical solution of the present invention, the system management and maintenance module includes a user rights management module, a log and audit module, a system configuration module and a system maintenance module.

[0014] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention designs a lean and intensive information management system for electricity meter reading and billing. The system adopts automated data acquisition technology to replace the traditional manual on-site meter reading method. Through smart meters and remote communication technology, it realizes automatic collection and real-time transmission of electricity consumption, significantly improving work efficiency and reducing error rate, meeting the requirements of high concurrency and low latency meter reading. An edge computing gateway is deployed at the data acquisition end to realize preliminary data processing and analysis, reducing the burden on the central server and improving the overall system response speed. It integrates core links such as meter reading, accounting, and billing on a unified platform to realize intensive management of business processes. Through information sharing and process collaboration, it breaks the data silo effect, improves cross-departmental collaboration efficiency, has real-time data acquisition and processing capabilities, adopts time-series databases and Spark stream computing technology to support real-time analysis of massive electricity consumption data, and can provide timely and accurate data support, which is conducive to refined operation strategies such as accurate load forecasting. Furthermore, it introduces an LSTM neural network anomaly detection algorithm to improve the accuracy of abnormal behavior identification. Attached Figure Description

[0015] Figure 1 This is a system structure diagram of the present invention;

[0016] Figure 2 This is a module architecture diagram of the automated data acquisition module of the present invention;

[0017] Figure 3 This is a module architecture diagram of the blockchain technology application module of the present invention;

[0018] Figure 4 This is a module architecture diagram of the real-time data processing and analysis module of the present invention;

[0019] Figure 5 This is a module architecture diagram of the data analysis and mining module of the present invention;

[0020] Figure 6 This is a module architecture diagram of the centralized management module of the present invention;

[0021] Figure 7 This is a module architecture diagram of the system management and maintenance module of the present invention;

[0022] Figure 8 This is a module architecture diagram of the intelligent optimization scheduling module of the present invention;

[0023] Figure 9 This is a system flowchart of the present invention.

[0024] In the diagram: 1. Automated Data Acquisition Module; 11. Intelligent Data Access Module; 12. Multi-Type Compatibility Module; 13. Remote Communication Module; 14. Data Verification Module; 15. Data Cleaning Module; 16. Abnormal Data Identification Module; 17. Abnormal Data Marking Module; 18. Edge Computing Gateway Module; 2. Blockchain Technology Application Module; 21. Data Security Module; 22. Distributed Ledger Module; 23. Decentralized Transaction Module; 3. Real-time Data Processing and Analysis Module; 31. Data Receiving and Storage Module; 32. Real-time Data Processing Module; 33. Load Forecasting and Analysis Module; 34. Data Visualization Module; 35. Reports The system includes the following modules: Generation Module; Data Analysis and Mining Module; Algorithm Integration Module; Predictive Model Module; Anomaly Detection and Early Warning Module; Centralized Management Module; Meter Reading Management Module; Accounting Management Module; Billing Management Module; Process Collaboration Module; Monitoring Module; System Management and Maintenance Module; User Access Management Module; Log and Audit Module; System Configuration Module; System Maintenance Module; Intelligent Optimized Scheduling Module; Load Optimized Scheduling Module; Distributed Energy Management Module; Demand-Side Response Management Module. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Please see the appendix Figure 1 - Appendix Figure 9This invention provides an embodiment of a lean and intensive information management system for electricity meter reading and verification, comprising an automated data acquisition module 1, a real-time data processing and analysis module 3 connected to the automated data acquisition module 1, an intensive management module 4 connected to the real-time data processing and analysis module 3, and an intelligent optimization scheduling module 6 connected to the intensive management module 4; the automated data acquisition module 1 includes an intelligent data access module 11, a multi-type compatible module 12, a remote communication module 13, a data verification module 14, a data cleaning module 15, an abnormal data identification module 16, an abnormal data marking module 17, and an edge computing gateway module 18. It connects to various smart meters through the intelligent data access module 11, utilizing multiple... The compatibility module 12 ensures that data from different brands and models of electricity meters can be collected. The remote communication module 13 is responsible for transmitting the collected data to the system in real time. The data verification module 14 and the data cleaning module 15 perform preliminary verification and cleaning of the data to ensure its accuracy and integrity. The abnormal data identification module 16 and the abnormal data marking module 17 are responsible for identifying and marking abnormal data for subsequent processing. The real-time data processing and analysis module 3 includes a data receiving and storage module 31, a real-time data processing module 32, a load forecasting and analysis module 33, a data visualization module 34, a report generation module 35, and a data analysis and mining module 36. The data receiving and storage module 31 receives and stores data, while the real-time data processing module 32 utilizes... The system utilizes time-series databases and Spark streaming computing technology to perform real-time analysis of massive amounts of electricity data. The load forecasting analysis module 33 uses predictive models to forecast future loads based on historical and real-time data. The data visualization module 34 displays the analysis results intuitively in the form of charts and curves, facilitating user understanding and decision-making. The report generation module 35 generates various statistical reports according to user needs. The centralized management module 4 includes a meter reading management module 41, an accounting management module 42, a billing management module 43, a process collaboration module 44, and a monitoring module 45. The meter reading management module 41 is responsible for confirming and verifying meter reading data; the accounting management module 42 calculates electricity charges based on meter reading data and electricity pricing policies; and the billing management module 43 is responsible for managing electricity charges. The system includes a collection and accounting management module 44, which breaks down data silos and improves cross-departmental collaboration efficiency through information sharing and process collaboration. The monitoring module 45 monitors and provides early warnings for the entire business process in real time to ensure the compliance and security of business operations. The intelligent optimization scheduling module 6 includes a load optimization scheduling module 61, a distributed energy management module 62, and a demand-side response management module 63. The load optimization scheduling module 61 achieves load balance and optimization by adjusting the power grid operation mode. The distributed energy management module 62 manages and schedules distributed energy in a unified manner to improve energy utilization efficiency. The demand-side response management module 63 guides users to participate in power grid peak shaving and valley filling through incentive measures to improve the flexibility and reliability of the power grid.The data analysis and mining module 36 includes an algorithm integration module 361, a prediction model module 362, and an anomaly detection and early warning module 363; the automated data acquisition module 1 is connected to the blockchain technology application module 2, and the real-time data processing and analysis module 3 and the centralized management module 4 are also connected to the blockchain technology application module 2; the blockchain technology application module 2 includes a data security module 21, a distributed ledger module 22, and a decentralized transaction module 23. The data security module 21 ensures the security and immutability of the data, and the distributed ledger module 22 achieves data transparency. To ensure automation and traceability, the decentralized trading module 23 supports the automation and intelligentization of electricity trading; the centralized management module 4 is connected to the system management and maintenance module 5; the system management and maintenance module 5 includes a user access management module 51, a log and audit module 52, a system configuration module 53, and a system maintenance module 54. The user access management module 51 is responsible for user authentication and access control; the log and audit module 52 records system operation logs and audit information to ensure the compliance and traceability of system operations; and the system maintenance module 54 is responsible for the daily maintenance and fault handling of the system.

[0027] Working Principle: When using this invention for lean and intensive information management of electricity meter reading and verification, the system is first initialized through the system configuration module 53 in the system management and maintenance module 5, including system parameter settings, user roles and permission allocation, etc., to ensure that the system can operate according to preset rules and requirements. After the system starts, the automated data acquisition module 1 starts working, connecting various smart meters through the intelligent data access module 11. The multi-type compatibility module 12 ensures that data from meters of different brands and models can be collected. The remote communication module 13 is responsible for transmitting the collected data to the system in real time. The data verification module 14 and the data cleaning module 15 perform preliminary verification and cleaning of the data to ensure the accuracy and integrity of the data. The abnormal data identification module 16 and the abnormal data marking module 17 are responsible for identifying and marking abnormal data for subsequent processing. The automated data acquisition module 1 significantly improves work efficiency, reduces the error rate, and meets the requirements of high concurrency and low latency meter reading. At the same time, the edge computing gateway module 18 performs preliminary processing and analysis at the data acquisition end, reducing the burden on the central server and improving the overall system response speed. The collected data is further processed by the real-time data processing and analysis module 3. The data processing module 31 receives and stores the data. The real-time data processing module 32 uses time-series databases and Spark streaming technology to analyze massive amounts of electricity consumption data in real time. The load forecasting and analysis module 33 uses a prediction model based on historical and real-time data to predict future loads. The LSTM algorithm, a special type of recurrent neural network (RNN), effectively handles long-term dependencies in time-series data. Through deep learning of historical electricity consumption data, it captures periodicity, trends, and randomness, thus achieving relatively accurate predictions of future loads. The data visualization module 34 displays the analysis results intuitively in the form of charts and curves, facilitating user understanding and decision-making. The report generation module 35 generates various statistical reports according to user needs. The data analysis and mining module 36, through the algorithm integration module 361, the prediction model module 362, and the anomaly detection and early warning module 363, deeply mines the value of the data. The anomaly detection and early warning module 363 introduces an isolation forest algorithm. The Forest algorithm, based on ensemble learning, constructs an isolation tree by randomly selecting features and feature split values ​​to isolate data. Outliers, due to their significant differences from normal data distribution, are typically isolated with fewer splits. By calculating the path length of a data point within the isolation tree, it's possible to determine whether a data point is an anomaly. This supports refined operational strategies such as accurate load forecasting, enabling the system to provide timely and accurate data support.This system facilitates the implementation of refined operational strategies such as dynamic electricity pricing mechanisms and accurate load forecasting, improving operational efficiency and economic benefits. Based on real-time data processing and analysis, the centralized management module 4 integrates core processes such as meter reading, accounting, and billing onto a unified platform. The meter reading management module 41 is responsible for confirming and verifying meter reading data; the accounting management module 42 calculates electricity charges based on meter reading data and electricity pricing policies; the billing management module 43 is responsible for collecting electricity charges and managing accounts; the process collaboration module 44 breaks down data silos and improves cross-departmental collaboration efficiency through information sharing and process collaboration; and the monitoring module 45 provides real-time monitoring and early warning for the entire business process, ensuring the compliance and security of business operations. Through centralized management, business flow is realized... The standardization and normalization of processes improve work efficiency and accuracy, reduce operating costs, and enhance cross-departmental collaboration efficiency and overall competitiveness through information sharing and process coordination. Based on real-time data processing and analysis results and the need for intensive management, the intelligent optimization scheduling module 6 performs load optimization scheduling, distributed energy management, and demand-side response management. The load optimization scheduling module 61 adjusts the power grid operation mode to achieve load balance and optimization. The distributed energy management module 62 manages and schedules distributed energy in a unified manner to improve energy utilization efficiency. The demand-side response management module 63 guides users to participate in power grid peak shaving and valley filling through incentive measures, improving the flexibility and reliability of the power grid. Intelligent optimization scheduling improves the power grid's... The system improves operational efficiency and stability, reduces operating costs, and promotes the consumption of renewable energy and sustainable energy development through distributed energy management and demand-side response management. Blockchain technology is applied in key components of the system (module 2). Data security module 21 employs asymmetric encryption algorithms to ensure data security and immutability. The asymmetric encryption algorithm uses two different keys, a public key and a private key, for encryption and decryption. The data sender uses the receiver's public key to encrypt the data, and only the receiver can decrypt the data using the corresponding private key, thus ensuring data security during transmission and storage. Distributed ledger module 22 enables data transparency and traceability, while decentralized transaction module 23 supports electricity trading. The automation and intelligence of the system, along with the application of blockchain technology, improves data security and credibility, reduces transaction costs and risks, and enhances transparency and fairness through distributed ledgers and decentralized transactions. During system operation, the user access management module 51 is responsible for user authentication and access control, the log and audit module 52 records system operation logs and audit information to ensure the compliance and traceability of system operations, and the system maintenance module 54 is responsible for daily system maintenance and fault handling. In summary, this lean and intensive information management system for electricity meter reading and verification works collaboratively through the collaborative efforts of multiple modules, including automated data acquisition, real-time data processing and analysis, intensive management, intelligent optimized scheduling, blockchain technology application, and system management and maintenance.This has enabled intelligent, centralized, and refined management of electricity meter reading and billing operations, improving work efficiency and accuracy while reducing operating costs and risks.

[0028] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A lean and intensive information management system for electricity meter reading and verification, comprising an automated data acquisition module (1), characterized in that: The automated data acquisition module (1) is connected to a real-time data processing and analysis module (3), the real-time data processing and analysis module (3) is connected to an intensive management module (4), and the intensive management module (4) is connected to an intelligent optimization scheduling module (6).

2. The lean and intensive information management system for electricity meter reading and verification according to claim 1, characterized in that: The automated data acquisition module (1) includes an intelligent data access module (11), a multi-type compatibility module (12), a remote communication module (13), a data verification module (14), a data cleaning module (15), an abnormal data identification module (16), an abnormal data marking module (17), and an edge computing gateway module (18).

3. The lean and intensive information management system for electricity meter reading and verification according to claim 1, characterized in that: The real-time data processing and analysis module (3) includes a data receiving and storage module (31), a real-time data processing module (32), a load forecasting and analysis module (33), a data visualization module (34), a report generation module (35), and a data analysis and mining module (36).

4. The lean and intensive information management system for electricity meter reading and verification according to claim 1, characterized in that: The centralized management module (4) includes a meter reading management module (41), an accounting management module (42), a billing management module (43), a process collaboration module (44), and a monitoring module (45).

5. The lean and intensive information management system for electricity meter reading and verification according to claim 1, characterized in that: The intelligent optimization scheduling module (6) includes a load optimization scheduling module (61), a distributed energy management module (62), and a demand-side response management module (63).

6. The lean and intensive information management system for electricity meter reading and verification according to claim 1, characterized in that: The data analysis and mining module (36) includes an algorithm integration module (361), a prediction model module (362), and an anomaly detection and early warning module (363).

7. The lean and intensive information management system for electricity meter reading and verification according to claim 1, characterized in that: The automated data acquisition module (1) is connected to the blockchain technology application module (2), and the real-time data processing and analysis module (3) and the centralized management module (4) are both connected to the blockchain technology application module (2).

8. The lean and intensive information management system for electricity meter reading and verification according to claim 7, characterized in that: The blockchain technology application module (2) includes a data security module (21), a distributed ledger module (22), and a decentralized transaction module (23).

9. The lean and intensive information management system for electricity meter reading and verification according to claim 1, characterized in that: The centralized management module (4) is connected to the system management and maintenance module (5).

10. A lean and intensive information management system for electricity meter reading and verification according to claim 9, characterized in that: The system management and maintenance module (5) includes a user rights management module (51), a log and audit module (52), a system configuration module (53), and a system maintenance module (54).

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