White list problem grading management and control method

Abstract

The invention discloses a white list problem grading management and control treatment method, which comprises three aspects of intelligent grading management and control index library building, index abnormity intelligent identification grading management and control and work order intelligent grading management and control, and automatically completes real-time monitoring, rapid identification and grading processing of abnormal indexes and white list problems. According to the invention, through integration and induction of important indexes, precise monitoring of important indexes such as power failure of a transformer area, power failure of a line, low voltage, overload and three-phase imbalance can be realized; according to the invention, by establishing an online appeal management and control system, the problems that sensitive emergency appeals are not reported in time, the information is blocked, the workload is large and the like can be found in time, and closed-loop management such as single-line reporting, automatic circulation / upgrading, automatic filing and the like of appeal workers is realized; according to the invention, through comprehensive process standard management, the customer appeal grading control traceability is enhanced, the employee automatic assessment standard is perfected, basic level energization and burden reduction are assisted, the effects of taking points with faces and promoting all the faces are achieved, and the effect of jointly improving the power supply service is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system data management and mining and use, and specifically relates to a method for upgrading the control and management of whitelist problems. Background Art

[0002] With the continuous expansion of residents' electricity demand and the scale of the main grid, the workload of abnormal fault management of distribution transformers has also increased. In order to relieve the work pressure of employees and improve the quality and efficiency of power supply services, in the current information age, the development of power grids is gradually moving towards intelligence. The storage, management, processing and analysis of data have become an important part of the safe production and economic operation of the power grid. The efficiency, mobility and security of data play a vital role in the digitalization process of power grid enterprises.

[0003] The whitelist of a power supply company mainly refers to a list of customer groups with specific attributes or good reputation identified by the power supply company. From a reputation perspective, enterprises or residential users who pay their electricity bills on time and in full, have no arrears records, and comply with relevant power supply regulations may be included in the whitelist. For example, some large enterprises have maintained good payment habits for a long time and are at a high-quality level in the credit evaluation system of the power supply company, thus entering the whitelist. Considering the nature of electricity consumption, important livelihood guarantee units, such as hospitals, schools, fire departments, etc., will also be included in the whitelist because the services they provide are vital to social stability and public safety. This means that when the power supply is tight (such as tight power resources during the peak summer and winter power consumption periods) or when the power system fails and repairs and restores power supply, these customers on the whitelist will receive special treatment such as priority power supply.

[0004] However, at present, the important indicator data such as low voltage and heavy overload of power supply companies in most areas are still scattered in various systems. The business between systems is not interconnected, manual coordination is difficult, and there is a lack of refined indicator monitoring data. There is a lack of real-time collection, analysis and monitoring of sensitive emergency abnormal indicators of white-listed customers, and it is impossible to predict, analyze, warn and intervene in advance for important indicators, which leads to problems such as difficulty in locating the root cause of abnormal data, low efficiency in problem handling, and delayed fault repair time. Moreover, the current upgraded management and control is a tedious and complicated task. In daily work, staff need to travel back and forth between multiple systems to monitor the operation of various indicators in real time, and coordinate multiple departments for upgraded management and control, conduct summary analysis and upgraded processing, so as to ensure the timely elimination of abnormal situations, which leads to low quality and low efficiency of power supply services for white-listed customers. In order to solve the above problems, it is necessary to develop a white-list problem upgraded management and control governance method. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and to provide a method for upgrading the management and control of whitelist problems. By integrating and summarizing key indicators, accurate monitoring of important indicators such as power outages in substations, power outages in lines, low voltage, overload, and three-phase imbalance can be achieved. An online demand management and control system can be established to promptly discover problems such as untimely reporting of sensitive and urgent demands, information blockage, and heavy workload. Closed-loop management such as online submission of demand work orders, automatic transfer / upgrading, and automatic archiving can be achieved. Through comprehensive process-based standardized management, the ability to trace customer demand upgrade management and control can be enhanced, and the automated assessment standards for employees can be improved, helping the grassroots to empower and reduce their burdens, so as to achieve the effect of leading by example and promoting the whole, and jointly improve the quality and efficiency of power supply services.

[0006] The object of the present invention is achieved by: a method for upgrading the control and management of whitelist issues, comprising the following steps: (1) Building an intelligent upgrade control indicator library: Building an intelligent upgrade control indicator library based on business logic, historical data or key indicators, supporting customized upgrade control rules according to business needs, using the data analysis engine to perform correlation calculation and analysis on real-time indicator data and work order data, triggering upgrade reminder information, and ensuring that relevant responsible persons can receive message reminders in a timely manner and pay attention to and handle abnormal problems as soon as possible. Specifically, it includes the configuration of indicator upgrade control process and work order upgrade control process; (2) Intelligent identification of abnormal indicators and upgraded control: Real-time monitoring of power outages, line losses, data collection success rate, low voltage, overload, and three-phase imbalance data in the substation area, and setting reasonable abnormal thresholds for each monitoring indicator. When the monitoring data exceeds or falls below the threshold, the system automatically generates an upgrade notification and supports order transfer operations, realizing real-time monitoring of abnormal indicators, intelligent identification, and automatic upgrade of orders; (3) Intelligent escalation and control of work orders: Based on business rules and templates, an intelligent work order analysis system is built to automatically determine whether escalation is required based on the type, priority, and urgency of the work order. According to business specifications, a closed-loop management process of work order distribution, problem feedback, problem handling, completion archiving, and escalation reporting is implemented, thereby achieving escalation and control of whitelist issues.

[0007] Preferably, the configuration of the indicator upgrade control process is specifically as follows: building an indicator upgrade management system to achieve unified planning and management of indicators, supporting the upgrade configuration of adding, deleting, and editing indicators, supporting the use of event numerical attribute abnormality type, duration, deadline, statistical period, and total quantity as the standard for upgrade assessment, setting reasonable upgrade thresholds for each monitoring indicator, establishing an association with real-time indicator data through indicator upgrade configuration, and using the data analysis engine to analyze indicator data in real time. When the data exceeds the threshold, the system automatically triggers an upgrade reminder to notify the relevant responsible persons to pay attention to and handle the abnormal problems as soon as possible.

[0008] Preferably, it supports setting escalation control for eight types of indicators, including low voltage area, three-phase unbalanced area, overload area, area power outage, line power outage, daily high loss area, daily negative loss area and users with unsuccessful collection, including timeout escalation configuration and overtime escalation configuration, among which the timeout escalation configuration is as follows: (1) Upgrade control based on duration: Upgrade settings are made based on the duration of abnormal indicators. The duration range can be set, and the system will automatically escalate and report when the preset value is reached. (2) Control by deadline: Based on whether the abnormality of the indicator still exists at a certain time, the abnormality will be automatically upgraded and reported when it reaches the preset value; The super-level upgrade configuration is as follows: (1) Conditions: Some indicators involve time requirements, that is, reaching the time requirement will trigger the upgrade; (2) Data range: supports daily, monthly, and annual dimensions for summary statistics. It supports configuring the number of days for data summary by day, the number of months for data summary by month, and the number of years for data summary by year. (3) Abnormal situations: Supports summary statistics by day or by time.

[0009] Preferably, the work order escalation control process configuration is specifically as follows: building a work order escalation management system to achieve unified planning and management of work orders, supporting the addition, deletion, and editing of work order escalation configurations, supporting the use of event numerical attribute abnormal type, warning time, and timeout escalation time as escalation assessment standards, setting reasonable escalation thresholds for each type of monitoring work order, establishing an association with real-time work order data through work order escalation configurations, and using a data analysis engine to analyze work order data in real time. When the data exceeds the threshold, the system automatically triggers an escalation reminder to notify the relevant responsible person to pay attention to and handle abnormal problems as soon as possible, including problem feedback and problem handling, wherein the problem feedback is as follows: (1) Work order warning: Calculated based on the work order dispatch time, if the current time from the work order dispatch time is ≥ the warning threshold and is still in the feedback waiting state, the i State Grid warning message will be triggered to notify the order receiver; (2) Work order escalation: Calculated based on the work order dispatch time, if the current time from the work order dispatch time is ≥ the escalation threshold and it is still in the feedback waiting state, the i State Grid timeout escalation message will be triggered to notify the order taker and the escalator; The problem handling is aimed at the situation where the work order status is pending, as follows: (1) Work order warning: Calculated based on the estimated completion time of the work order, if the current time is less than or equal to the estimated completion time and the work order has not been processed, the iState Grid warning message will be triggered to notify the order taker; (2) Work order escalation: Calculated based on the estimated completion time of the work order, if the current time exceeds the estimated completion time ≥ the escalation threshold and the work order has not yet been processed, the iState Grid timeout escalation message will be triggered and notified to the order acceptor and the escalator.

[0010] Preferably, the intelligent identification and upgrading control of abnormal indicators is specifically as follows: establish an abnormal monitoring mechanism, monitor the processing process of seven important indicator data, including low voltage, overload, three-phase imbalance, power outage in the substation, power outage in the line, line loss in the substation, and collection success rate in real time through scheduled tasks. When the abnormal situation of the indicator reaches the upgrading threshold, the platform automatically triggers the upgrading task according to the indicator upgrading rules, and sends an upgrading notification to the target object, so as to realize real-time monitoring, intelligent identification and automatic upgrading of abnormal indicators, as follows: (1) Monitoring scope: Set up upgraded control for eight types of indicators, including low voltage areas, three-phase unbalanced areas, overloaded areas, area power outages, line power outages, daily high-loss areas, daily negative-loss areas, and users with unsuccessful data collection; (2) Main functions: confirmation of upgrade, notification of upgrade, and abnormal transfer of work orders.

[0011] Preferably, the intelligent escalation control of work orders is as follows: first, based on business rules and templates, an intelligent work order analysis system is constructed, and the work order execution status is monitored in real time through scheduled tasks. When the work order problem feedback and problem handling link processing time limit reaches the escalation threshold, the platform automatically triggers the escalation task according to the escalation rules, and sends an escalation notification to the target object, so as to realize real-time monitoring, intelligent identification and automatic escalation of timed work orders; secondly, the work order management module is configured, and business personnel perform full-process closed-loop management of work order one-click dispatch, problem feedback, problem handling, and completion archiving in combination with the escalation control work specifications.

[0012] Preferably, the configuration work order management module specifically includes the following contents: (1) Basic information of the work order: including the work order number, creation time, work order type, professional classification and urgency; (2) Problem description and details: Record key information in detail, including the problem encountered, phenomenon description, and fault occurrence time; (3) Processing records and results: record the processing process, processing personnel, processing time, and processing result information of the work order; (4) Process definition: Define the work order processing flow according to the actual business process, including five sections: creation, problem feedback, problem handling, review, and closure; (5) Automated and intelligent processing: Automatically allocate, process, and upgrade work orders based on business rules.

[0013] Preferably, data fusion and sharing technology is introduced into the intelligent identification and upgraded management of indicator anomalies and the intelligent upgraded management and control of work orders to achieve unified access, cleaning, integration, governance and cross-departmental sharing of multi-source data, as well as a hierarchical response mechanism and intelligent algorithm to realize the platform's automatic capture, improved anomaly identification and upgraded processing intelligence level.

[0014] Preferably, a visual dashboard is introduced into the program for intelligently identifying and upgrading the management and control of abnormal indicators and the program for intelligently upgrading the management and control of work orders, so as to intuitively display the monitoring information of key indicators and the monitoring information of work orders.

[0015] Preferably, data analysis and mining technology and statistical technology are introduced into the program for intelligent identification and upgrading of control of abnormal indicators and the program for intelligent upgrading of control of work orders to summarize and count abnormal situations and display them through a visual dashboard.

[0016] Due to the adoption of the above technical solution, the beneficial effects of the present invention are: (1) The present invention adopts the construction of intelligent upgrading and control index library, intelligent identification and upgrading of index abnormalities, and intelligent upgrading and control of work orders. By integrating and summarizing key indicators, it realizes accurate monitoring of important indicators such as power outages in substations, power outages in lines, low voltage, overload, and three-phase imbalance. By building an online demand management system, it timely discovers problems such as untimely reporting of sensitive and urgent demands, information blockage, and heavy workload, and realizes closed-loop management such as online submission, automatic transfer / upgrading, and automatic archiving of demand work orders. It also comprehensively standardizes and manages processes, enhances the traceability of customer demand upgrading and control, and improves the automated assessment standards for employees. It solves the existing problems of difficult work supervision, control, statistical analysis, and employee assessment, helps empower and reduce the burden on the grassroots, and achieves the effect of leading by example and promoting the whole, so as to jointly improve the quality and efficiency of power supply services. (2) The present invention facilitates business personnel to discover problems early, and quickly query and eliminate them through real-time monitoring, rapid identification and upgraded processing of abnormal indicators and whitelist issues, thereby solving the problems of difficult manual collaboration and low efficiency in the existing whitelist problem management process. At the same time, it reduces the difficulty of manual intervention, improves the problem response speed and problem solving efficiency, and ensures business continuity and security.

[0017] (3) The present invention significantly shortens the time to discover problems and improves response speed through real-time monitoring and intelligent early warning mechanisms. The present invention simplifies the processing flow and improves processing efficiency and quality through automated processing and upgraded response mechanisms. The present invention achieves comprehensive monitoring of key indicators by expanding the monitoring scope, reduces the omission of potential problems, and effectively enhances the monitoring capability of whitelist problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of the method of the present invention.

[0019] Figure 2 It is the program development business architecture diagram of the present invention.

[0020] Figure 3 It is the program development business relationship diagram of the present invention.

[0021] Figure 4 is a program development data architecture diagram of the present invention, Figure 5 It is a technical architecture diagram of program development of the present invention. DETAILED DESCRIPTION

[0022] The technical solution of the present invention is further specifically described below through embodiments and in conjunction with the accompanying drawings.

[0023] like Figure 1 As shown, the present invention provides a method for upgrading the control and management of whitelist issues, and the method includes the following three aspects: (1) Building an intelligent upgrade control indicator library: Building an intelligent upgrade control indicator library based on business logic, historical data or key indicators, supporting customized upgrade control rules according to business needs, using the data analysis engine to perform correlation calculation and analysis on real-time indicator data and work order data, triggering upgrade reminder information, and ensuring that relevant responsible persons can receive message reminders in a timely manner and pay attention to and handle abnormal problems as soon as possible. Specifically, it includes the configuration of indicator upgrade control process and work order upgrade control process; (2) Intelligent identification of abnormal indicators and upgraded control: Real-time monitoring of power outages, line losses, data collection success rate, low voltage, overload, and three-phase imbalance data in the substation area, and setting reasonable abnormal thresholds for each monitoring indicator. When the monitoring data exceeds or falls below the threshold, the system automatically generates an upgrade notification and supports order transfer operations, realizing real-time monitoring of abnormal indicators, intelligent identification, and automatic upgrade of orders; (3) Intelligent escalation and control of work orders: Based on business rules and templates, an intelligent work order analysis system is built to automatically determine whether escalation is required based on the type, priority, and urgency of the work order. According to business specifications, a closed-loop management process of work order distribution, problem feedback, problem handling, completion archiving, and escalation reporting is implemented, thereby achieving escalation and control of whitelist issues.

[0024] The configuration of the indicator upgrade control process is specifically as follows: building an indicator upgrade management system to achieve unified planning and management of indicators, supporting the upgrade configuration of adding, deleting, and editing indicators, supporting the use of event numerical attribute abnormal type, duration, deadline, statistical cycle, and total number as the standard for upgrade assessment, setting reasonable upgrade thresholds for each monitoring indicator, establishing an association with real-time indicator data through indicator upgrade configuration, and using the data analysis engine to analyze indicator data in real time. When the data exceeds the threshold, the system automatically triggers an upgrade reminder to notify the relevant responsible persons to pay attention to and handle the abnormal problems as soon as possible.

[0025] The present invention supports setting up upgraded control for eight types of indicators, including low voltage substations, three-phase unbalanced substations, overloaded substations, substation power outages, line power outages, daily high loss substations, daily negative loss substations and users with unsuccessful collection, including timeout upgraded configuration and over-time upgraded configuration.

[0026] The timeout upgrade configuration is as follows: (1) Control by duration: Set the escalation level according to the duration of abnormal indicators. It supports setting the duration range. When the preset value is reached, the escalation level will be automatically reported (for example, 0<A<1, the escalation value is a certain position or a certain person); (2) Control by escalation based on deadline: Based on whether the abnormality still exists at a certain time, the report will be automatically escalated when it reaches the preset value (for example, if the abnormality still exists at 15:00 on the same day, the report will be escalated to a certain position or person).

[0027] The super-level upgrade configuration is as follows: (1) Conditions: Some indicators involve duration requirements, that is, reaching the duration will trigger an upgrade (for example, if the duration is ≥ 1 hour and it occurs once in a month, the upgrade will occur); (2) Data range: supports daily, monthly, and annual dimensions for summary statistics. It supports configuring the number of days for data summary by day, the number of months for data summary by month, and the number of years for data summary by year. (3) Abnormal situations: Supports summary statistics by day or by time.

[0028] Example: It occurred once in the current year, 3 days in the current month, and 2 consecutive days in the past 2 days.

[0029] The specific configuration of the work order escalation control process is as follows: building a work order escalation management system to achieve unified planning and management of work orders, supporting the addition, deletion, and editing of work order escalation configurations, supporting the use of event numerical attributes such as abnormal type, warning time, and timeout escalation time as standards for escalation assessment, setting reasonable escalation thresholds for each type of monitoring work order, establishing an association with real-time work order data through work order escalation configurations, and using the data analysis engine to analyze work order data in real time. When the data exceeds the threshold, the system automatically triggers an escalation reminder to notify the relevant responsible persons to pay attention to and handle abnormal problems as soon as possible, including problem feedback and problem handling.

[0030] The feedback is as follows: (1) Work order warning: calculated based on the work order dispatch time, if the current time from the work order dispatch time is ≥ the warning threshold and is still in the waiting feedback state, the i State Grid warning message notification will be triggered to the order receiver (if there is no feedback within 1 day after the dispatch, an early warning notification will be issued); (2) Work order escalation: Calculated based on the work order dispatch time, if the current time from the work order dispatch time is ≥ the escalation threshold and is still in the feedback-pending state, the i-State Grid timeout escalation message will be triggered to notify the order receiver and the escalator (for example, if there is no feedback within 3 days after the dispatch, an overtime escalation notification will be issued).

[0031] The problem handling is aimed at the situation where the work order status is pending, as follows: (1) Work order warning: Calculated based on the estimated completion time of the work order, if the current time is less than or equal to the warning threshold and the work order has not been processed, the i-State Grid warning message will be triggered to notify the order taker (e.g., if the time is 1 day away from the [estimated completion time], an early warning notification will be sent); (2) Work order escalation: Calculated based on the estimated completion time of the work order, if the current time exceeds the estimated completion time ≥ the escalation threshold and the work order has not yet been processed, the iState Grid timeout escalation message will be triggered to notify the order taker and the escalator (for example, if the estimated completion time exceeds 3 days, an overtime escalation notification will be issued).

[0032] The specific steps of intelligent identification and upgrading of abnormal indicators are as follows: establish an abnormal monitoring mechanism, monitor the processing of seven important indicator data, including low voltage, overload, three-phase imbalance, power outage in the substation, power outage in the line, line loss in the substation, and collection success rate, in real time through scheduled tasks. When the abnormal situation of the indicator reaches the upgrading threshold, the platform automatically triggers the upgrading task according to the indicator upgrading rules, and sends an upgrading notification to the target object, so as to realize real-time monitoring, intelligent identification and automatic upgrading of abnormal indicators. The details are as follows: (1) Monitoring scope: Set up upgraded control for eight types of indicators, including low voltage areas, three-phase unbalanced areas, overloaded areas, area power outages, line power outages, daily high-loss areas, daily negative-loss areas, and users with unsuccessful data collection; (2) Main functions: confirmation of upgrade, notification of upgrade, and abnormal transfer of work orders.

[0033] The intelligent escalation control of work orders is as follows: first, based on business rules and templates, an intelligent work order analysis system is built, and the execution and processing of work orders are monitored in real time through scheduled tasks. When the processing time limit of work order problem feedback and problem handling reaches the escalation threshold, the platform automatically triggers the escalation task according to the escalation rules and sends an escalation notification to the target object, realizing real-time monitoring, intelligent identification and automatic escalation of timed work orders; secondly, a work order management module is configured to facilitate business personnel to perform full-process closed-loop management of work order one-click distribution, problem feedback, problem handling, completion and archiving in combination with the escalation control work specifications, thereby improving the timeliness and standardization of work order management.

[0034] Configuring the work order management module specifically includes the following contents: (1) Basic information of the work order: including the work order number, creation time, work order type, professional classification and urgency, etc.; (2) Problem description and details: Record in detail the problem encountered, phenomenon description, fault occurrence time and other key information; (3) Processing records and results: record the processing process of the work order, the person who processed it, the processing time, the processing results and other information; (4) Process definition: Define the work order processing flow according to the actual business process, including five sections: creation, problem feedback, problem handling, review, and closure; (5) Automated and intelligent processing: Automatically allocate, process, and upgrade work orders based on business rules.

[0035] Since the upgraded indicator data are scattered in multiple systems and there is a lack of unified data management, business personnel need to frequently log into multiple systems for inspection, processing and analysis, which increases the workload and reduces work efficiency and data quality. Therefore, the present invention introduces data fusion and sharing technology to achieve unified access, cleaning, integration, governance and cross-departmental sharing of multi-source data, solve problems such as diverse data sources, low query efficiency and poor data quality, and achieve comprehensive monitoring of key indicators.

[0036] Due to the lack of a unified data display platform, it is difficult to conduct in-depth analysis and mining of data, which limits the value of data. Therefore, the present invention introduces intelligent algorithms to improve the intelligence level of anomaly identification and upgraded processing, and solve the problems of incomplete coverage of upgraded management and control and insufficient data utilization.

[0037] Due to the involvement of multiple parties, problems such as delayed information update, imperfect processing, inadequate monitoring, and poor sharing often occur in the problem handling process, seriously affecting the quality of business management and control and collaborative efficiency. Therefore, the present invention establishes a cross-departmental collaborative work platform to achieve rapid sharing and transmission of work orders and upgraded information, reduce the difficulty of manual collaboration, and improve processing efficiency.

[0038] Different levels of escalation rules are set according to the severity of the problem, and a graded response mechanism is introduced to monitor abnormal behavior of the platform in real time. The platform automatically captures and analyzes the abnormal behavior of indicator objects. Combined with thresholds and rules, once an abnormality occurs, the early warning mechanism is immediately triggered, which automatically triggers the escalation process and notifies business personnel to complete the abnormality and defect elimination in a timely manner.

[0039] It provides a visual dashboard function, using data analysis and mining technology to intuitively display key data in the form of charts, graphs, etc., to help business personnel quickly mine the value of data and provide support for decision-making. The main displayed data includes: key indicator information and work order information.

[0040] (1) Key indicator monitoring: Monitoring of substations: low voltage, three-phase imbalance, overload, substation power outage, high load loss, and 400V comprehensive line loss; Monitoring line category: line power outage; Monitoring user category: collection failure rate, low voltage.

[0041] (2) Work order monitoring: Statistics of various work orders, various fault levels, and various processing links.

[0042] Utilizing data analysis and mining technology, through intuitive charts, we deeply analyze the processing status of work orders in different dimensions, as well as abnormal summary statistics of indicators such as low-voltage substations, three-phase unbalanced substations, overloaded substations, substation power outages, daily high-loss substations, and daily negative-loss substations, so that business personnel can accurately and efficiently grasp the overall information of work orders and indicators.

[0043] (1) Work order analysis: supports work order statistics by work order status, work order node, work order level, professional classification, indicator type, and upgrade status; (2) Abnormal area statistics: Supports statistics on the number of abnormal indicators by unit, area, and time.

[0044] In summary, the present invention is based on the research on upgraded control and management of whitelist problems. By integrating data such as power outages in substations, line losses in substations, collection success rate, low voltage, overload, and three-phase imbalance, it can realize abnormal perception and monitoring of indicators, accurately control the progress of on-site emergency repairs, and conduct real-time command and dispatch, thereby promoting the level of digital and refined office management.

[0045] The following are the program development design principles of the present invention.

[0046] 1. The following six principles should be followed when designing the system architecture: (1) Principle of unity: System construction is an integral part of the information construction of State Grid Corporation of China and should always be coordinated with the overall planning of the information project of State Grid Corporation of China. The construction of the system should follow the idea of ​​overall planning, unified design and step-by-step implementation, and adhere to the four principles of "unified leadership, unified planning, unified standards and unified organization and implementation" during the implementation process; (2) Standardization principle: meet the requirements of the unified data model (SG-CIM), the system is developed based on the original system and based on the company's existing development platform, and the technical solution follows the existing system architecture. The system should support Internet Protocol Version 6 (IPv6) on the basis of supporting Internet Protocol Version 4 (IPv4). At the same time, the system provides a standard data exchange format and an open data structure to ensure support for data integration applications with other systems; (3) Principle of practicality and advancement: The construction of the system must adhere to the principle of practicality. On the premise of ensuring practicality and reliability, the subject uses mature technology and appropriately adopts new technologies such as intelligent analysis for design and customization. It is necessary to properly handle the relationship between the advancement and practicality of information technology. We should neither be conservative and stick to the old ways nor be greedy for perfection, over-emphasizing the advancement of technology while ignoring maturity and stability. This ensures a high starting point for system construction and extends the life cycle of the entire system; (4) Scalability principle: By adopting a flexible architecture, the system functions can be expanded to meet the ever-expanding application needs. Scalability is reflected in the scalability of application functions, deployment methods, data models, and services, ensuring a smooth upgrade of the expansion process and avoiding duplicate investment; (5) Openness principle: The system should adopt an open technology platform and software architecture to ensure that the system can be easily integrated with other applications. The openness principle of the system is the basis for interconnection between the system and other systems. It enables the platform to have good expansion and interoperability capabilities for easy maintenance and management; (6) Security principle: All application functions and services provided by the system require user authentication to ensure the security of the services. Anonymous access and invocation of related functions and services are not allowed. For the horizontal domain boundaries of the information external network, in accordance with the relevant requirements of the company, the existing boundary security protection equipment of each unit shall be used, and security policies such as access control, intrusion detection, logging and auditing shall be configured to achieve boundary isolation and security protection. Deploy information security network isolation devices to achieve strong logical isolation and realize the mutual transmission of system control instructions and images between the management information area and the Internet area.

[0047] 2. Overall structural design: The overall structure meets the requirements of the State Grid power grid architecture and the company's unified data model (SG-CIM). System development complies with the five major architectural design principles of business architecture, application architecture, data architecture, technical architecture, and security architecture.

[0048] 3. Overall technical route: system construction, using the vue framework on the front end, springCloud, springBoot, springMVC architecture on the back end, and using RDS cloud database.

[0049] 4. The overall technical solution is as follows: (1) If Figure 2 As shown, the business architecture is as follows: The upgraded work order manager can be developed based on the i State Grid platform, mainly providing functions such as comprehensive indicator dashboards and work order centers. The data is stored in the whitelist customer demand upgraded control closed-loop governance micro-application database of the information intranet resource library, and the i State Grid platform provides a unified access portal. Access the information extranet server service from the i State Grid mobile client through the secure interactive platform, and then access the information intranet database through a strong isolation device to ensure data transmission security. The software system users are designated personnel of the regional power supply company.

[0050] (2) If Figure 3 As shown, the business relationship is: with upgraded control and governance as the theme, it supports key indicator monitoring, closed-loop management of work orders, upgraded control, statistical analysis and other functions.

[0051] (3) If Figure 4 As shown in the figure, the data architecture is as follows: The closed-loop governance micro-application system for upgrading whitelist customer demands enters business data through the management background, generates business data through other functional modules, and stores it in the information intranet database. When using each functional module, the staff will display it on the i State Grid mobile and PC interfaces.

[0052] (4) If Figure 5 As shown, the technical architecture is: complying with the technical architecture of the State Grid and provincial electric power companies.

[0053] (5) The security architecture is: Based on the "Implementation Guidance on Information Security Level Protection Construction" and the "General Plan for Security Protection of State Grid Corporation's Informatization Project", the degree of damage after the damage is analyzed according to the business information security protection level analysis and system service security protection level analysis. The data content of this invention does not contain sensitive information and meets the information security requirements of the provincial company.

[0054] In summary, the present invention adopts a multi-layer architecture system, uses the mature Spring Cloud microservice architecture as the development architecture, and the services run in different processes. The services interact through a lightweight communication mechanism, and the services can be independently deployed through automated deployment. In the technical architecture, the services are independent of each other.

[0055] (1) Improve development efficiency: The development model of front-end and back-end separation can divide the application development according to the skills of developers, develop in parallel, and improve the overall development efficiency. The division of labor is clearer. The front-end only focuses on the front-end affairs, and the back-end only cares about the back-end work. The development of both can be carried out at the same time. When the back-end does not have time to provide an interface, the front-end can first hard-code the data or call a local JSON file. There is no need to bother the back-end to add pages and modify routes, and development is more flexible.

[0056] (2) Flexible deployment, independent expansion, and strong portability: Using a microservice architecture, different service modules are designed as different microservices. The application of each microservice is more modular and easy to deploy. Higher scalability is based on the independence of services, and the coupling between services is reduced. Both in terms of function and architecture, more flexible expansion can be carried out without affecting other services. It can also be deployed across multiple servers and infrastructures to fully meet business needs.

[0057] In general, during the actual use of the present invention, by deploying the upgraded work order manager micro-application in the iState Grid mobile portal, a complete online demand management and control system including online submission, automatic circulation, early warning and upgrading, automatic archiving, etc. can be realized, online closed-loop management of demand work orders can be achieved, and the ability to upgrade work orders and trace work orders online can be enhanced, solving problems such as difficulty in work supervision, management, statistical analysis, and employee assessment, comprehensively improving the company's digital capability level, and helping to empower and reduce the burden on the grassroots.

[0058] 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, those skilled in the art should understand that the specific implementation modes of the present invention can still be modified or replaced by equivalents, and any modification or equivalent replacement that does 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 upgrading the control and management of whitelist issues, characterized in that: The steps include: (1) Building an intelligent upgrade control indicator library: Building an intelligent upgrade control indicator library based on business logic, historical data or key indicators, supporting customized upgrade control rules according to business needs, using the data analysis engine to perform correlation calculation and analysis on real-time indicator data and work order data, triggering upgrade reminder information, and ensuring that relevant responsible persons can receive message reminders in a timely manner and pay attention to and handle abnormal problems as soon as possible. Specifically, it includes the configuration of indicator upgrade control process and work order upgrade control process; (2) Intelligent identification of abnormal indicators and upgraded control: Real-time monitoring of power outages, line losses, data collection success rate, low voltage, overload, and three-phase imbalance data in the substation area, and setting reasonable abnormal thresholds for each monitoring indicator. When the monitoring data exceeds or falls below the threshold, the system automatically generates an upgrade notification and supports order transfer operations, realizing real-time monitoring of abnormal indicators, intelligent identification, and automatic upgrade of orders; (3) Intelligent escalation and control of work orders: Based on business rules and templates, an intelligent work order analysis system is built to automatically determine whether escalation is required based on the type, priority, and urgency of the work order. According to business specifications, a closed-loop management process of work order distribution, problem feedback, problem handling, completion archiving, and escalation reporting is implemented, thereby achieving escalation and control of whitelist issues.

2. The method for upgrading the whitelist problem control and management according to claim 1 is characterized in that: The configuration of the indicator upgrade control process is specifically as follows: building an indicator upgrade management system to achieve unified planning and management of indicators, supporting the upgrade configuration of adding, deleting, and editing indicators, supporting the use of event numerical attribute abnormal type, duration, deadline, statistical cycle, and total number as the standard for upgrade assessment, setting a reasonable upgrade threshold for each monitoring indicator, establishing an association with real-time indicator data through indicator upgrade configuration, and using the data analysis engine to analyze indicator data in real time. When the data exceeds the threshold, the system automatically triggers an upgrade reminder to notify the relevant responsible persons to pay attention to and handle the abnormal problems as soon as possible.

3. The method for upgrading the whitelist problem control and management according to claim 2 is characterized in that: Supports the setting of upgrade control for eight types of indicators, including low voltage area, three-phase unbalanced area, overload area, area power outage, line power outage, daily high loss area, daily negative loss area and users with unsuccessful data collection, including overtime upgrade configuration and overtime upgrade configuration. The overtime upgrade configuration is as follows: (1) Upgrade control based on duration: Upgrade settings are made based on the duration of abnormal indicators. The duration range can be set, and the system will automatically escalate and report when the preset value is reached. (2) Control by deadline: Based on whether the abnormality of the indicator still exists at a certain time, the abnormality will be automatically upgraded and reported when it reaches the preset value; The super-level upgrade configuration is as follows: (1) Conditions: Some indicators involve time requirements, that is, reaching the time requirement will trigger the upgrade; (2) Data range: supports daily, monthly, and annual dimensions for summary statistics. It supports configuring the number of days for data summary by day, the number of months for data summary by month, and the number of years for data summary by year. (3) Abnormal situations: Supports summary statistics by day or by time.

4. The method for upgrading the whitelist problem control and management according to claim 2 is characterized in that: The work order escalation control process configuration is specifically as follows: building a work order escalation management system to achieve unified planning and management of work orders, supporting the addition, deletion, and editing of work order escalation configurations, supporting the use of event numerical attribute abnormal type, warning time, and timeout escalation time as escalation assessment standards, setting reasonable escalation thresholds for each type of monitoring work order, establishing an association with real-time work order data through work order escalation configurations, and using the data analysis engine to analyze work order data in real time. When the data exceeds the threshold, the system automatically triggers an escalation reminder to notify the relevant responsible person to pay attention to and handle the abnormal problem as soon as possible, including problem feedback and problem handling, where the problem feedback is as follows: (1) Work order warning: Calculated based on the work order dispatch time, if the current time from the work order dispatch time is ≥ the warning threshold and is still in the feedback waiting state, the i State Grid warning message will be triggered to notify the order receiver; (2) Work order escalation: Calculated based on the work order dispatch time, if the current time from the work order dispatch time is ≥ the escalation threshold and it is still in the feedback waiting state, the i State Grid timeout escalation message will be triggered to notify the order taker and the escalator; The problem handling is aimed at the situation where the work order status is pending, as follows: (1) Work order warning: Calculated based on the estimated completion time of the work order, if the current time is less than or equal to the estimated completion time and the work order has not been processed, the i State Grid warning message will be triggered and notified to the order receiver; (2) Work order escalation: Calculated based on the estimated completion time of the work order, if the current time exceeds the estimated completion time ≥ the escalation threshold and the work order has not yet been processed, the iState Grid timeout escalation message will be triggered and notified to the order acceptor and the escalator.

5. The method for upgrading the whitelist problem control and management according to claim 1 is characterized in that: The intelligent identification and upgrading of abnormal indicators is specifically as follows: establish an abnormal monitoring mechanism, monitor the processing of seven important indicator data, including low voltage, overload, three-phase imbalance, power outage in the substation, power outage in the line, line loss in the substation, and collection success rate, in real time through scheduled tasks. When the abnormal situation of the indicator reaches the upgrading threshold, the platform automatically triggers the upgrading task according to the indicator upgrading rules, and sends an upgrading notification to the target object, so as to realize real-time monitoring, intelligent identification and automatic upgrading of abnormal indicators, as follows: (1) Monitoring scope: Set up upgraded control for eight types of indicators, including low voltage areas, three-phase unbalanced areas, overloaded areas, area power outages, line power outages, daily high-loss areas, daily negative-loss areas, and users with unsuccessful data collection; (2) Main functions: confirmation of upgrade, notification of upgrade, and abnormal transfer of work orders.

6. The method for upgrading the whitelist problem control and management according to claim 1 is characterized in that: The intelligent escalation control of work orders is as follows: first, based on business rules and templates, an intelligent work order analysis system is built, and the execution and processing of work orders are monitored in real time through scheduled tasks. When the processing time limit of work order problem feedback and problem handling reaches the escalation threshold, the platform automatically triggers the escalation task according to the escalation rules and sends an escalation notification to the target object, thereby realizing real-time monitoring, intelligent identification and automatic escalation of timed work orders; secondly, the work order management module is configured, and business personnel perform full-process closed-loop management of work order one-click distribution, problem feedback, problem handling, and completion and archiving in combination with the escalation control work specifications.

7. The method for upgrading the whitelist problem control and management according to claim 1 is characterized in that: The configuration work order management module specifically includes the following contents: (1) Basic information of the work order: including the work order number, creation time, work order type, professional classification and urgency; (2) Problem description and details: Record key information in detail, including the problem encountered, phenomenon description, and fault occurrence time; (3) Processing records and results: record the processing process, processing personnel, processing time, and processing result information of the work order; (4) Process definition: Define the work order processing flow according to the actual business process, including five sections: creation, problem feedback, problem handling, review, and closure; (5) Automated and intelligent processing: Automatically allocate, process, and upgrade work orders based on business rules.

8. The method for upgrading the whitelist problem control and management according to claim 1 is characterized by: In the intelligent identification and upgraded management of indicator anomalies and the intelligent upgraded management and control of work orders, data fusion and sharing technology is introduced to achieve unified access, cleaning, integration, governance and cross-departmental sharing of multi-source data, as well as hierarchical response mechanisms and intelligent algorithms to achieve the platform's automatic capture, improved anomaly identification and upgraded processing intelligence level.

9. The method for upgrading the whitelist problem control and management according to claim 1 is characterized by: In the program of intelligent identification and upgrading of control over abnormal indicators and the program of intelligent upgrading of control over work orders, a visual dashboard is introduced to intuitively display key indicator monitoring information and work order monitoring information.

10. The method for upgrading the whitelist problem control and management according to claim 9 is characterized in that: In the program for intelligently identifying and upgrading the management of abnormal indicators and the program for intelligently upgrading the management of work orders, data analysis and mining technology as well as statistical technology are introduced to summarize and count abnormal situations and display them through a visual dashboard.

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