Intelligent management system for whole life cycle of power grid assets

Abstract

The application discloses a whole life cycle intelligent management system for power grid assets, relates to the technical field of power grid asset management, and comprises an asset data collection unit, a data processing unit, a management control unit and a historical data unit. The asset data collection unit collects asset information of a power grid, builds an asset management database in the collection process, centrally collects and stores the collected data, and performs identification processing in the collection and storage process. In the asset management process of the power grid, the asset data is updated in a regular and real-time manner, the accuracy of the asset data in use is ensured, after the asset data is updated, the management model and the management pre-control scheme are improved, and the actual situation in the implementation process is ensured.

Description

Technical Field

[0001] This invention relates to the field of power grid asset management technology, specifically to a smart management system for the entire lifecycle of power grid assets. Background Technology

[0002] Currently, power grid asset management involves the systematic and full-cycle planning, investment, construction, operation and maintenance, decommissioning and disposal of the core resources of power grid enterprises (including physical equipment, facilities and related data and technologies in all aspects of transmission, transformation, distribution and consumption). Existing asset management systems cannot accurately manage and control according to the management level, which leads to the failure to achieve the expected results in a short period of time, or even to solve the problems that arise. Furthermore, the inability to adjust, improve, and optimize management plans in real time during the management and control process results in deviations between the management and control plans and the actual situation, thus prolonging the processing time and increasing the processing costs. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent management system for the entire lifecycle of power grid assets, in order to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: a smart management system for the entire life cycle of power grid assets, comprising an asset data collection unit, a data processing unit, a management control unit, and a historical data unit; The asset data collection unit collects asset information of the power grid and builds an asset management database during the collection process. The collected data is centrally collected and stored, and identification processing is performed during the collection and storage process. The data processing unit receives data collected from the asset management database, analyzes and processes the data after receiving it, and periodically collects and updates the asset management data after the analysis is completed. The management control unit formulates a management model based on the analyzed data. Once the management model is formulated, an asset management plan is developed. After the plan is developed, problems arising during implementation are collected, and a historical database is established for centralized management. Historical data is analyzed periodically, and the asset data collection unit and data processing unit are dynamically adjusted after analysis.

[0005] Preferably, the asset data collection unit formulates a static basic data collection plan and a dynamic operation data collection plan when collecting data on power grid assets. The data collected by the static basic data collection plan and the dynamic operation data collection plan are centrally collected through the asset management database. The static basic data collection plan collects data on newly built and renovated project assets through automated collection technology, and collects data on existing assets through manual supplementary collection. After the data collection is completed, the static basic data is integrated and processed, and the data is standardized.

[0006] Preferably, the data processing unit includes a data classification module and a data update module. The data classification module classifies the data collected internally by the asset management database into static basic data, dynamic operation data, operation and maintenance data, full life cycle data, and environmental related data according to data categories. The classified data is then verified and cleaned, and the classified data is labeled. After the labeling is completed, the data is classified in chronological order.

[0007] Preferably, the data update module updates and adjusts the collected data by formulating a data update plan, and the data update plan includes manual collection and update and real-time collection and update, and the updated data is marked during the update process; The manual data collection and update process is divided into three levels: Level 1, Level 2, and Level 3, based on the type of data collected by the equipment. Level 1 is the most complex and involves manual data collection every 15 days. After collection, the data is analyzed and updated within the asset management database. Level 2 is of moderate difficulty and involves manual data collection every 10 days. After collection, the data is analyzed and updated within the asset management database. Level 3 is the easiest and involves manual data collection every 5 days. After collection, the data is analyzed and updated within the asset management database. In the event of abnormal or extreme weather conditions, the manual data collection time is shortened, and the shortened time is adjusted according to the degree of impact of the weather. The more severe the impact, the shorter the shortened time. When the impact is judged to be moderate or slight, the shortened time is adaptively adjusted.

[0008] Preferably, the management control unit includes a management model module, a management and control module, and a feedback adjustment module. The management model module builds a management model using virtual technology and big data technology, and performs comprehensive real-time monitoring and feedback on the equipment through the management model. The specific construction steps are as follows: (1) A data management platform is built based on the specific data collection of the hardware infrastructure, and the data management platform is associated with the asset management database. The data management platform is used for centralized storage, management and retrieval of power grid asset data, and real-time analysis and processing of real-time data is carried out through big data technology. (2) Formulate a full life cycle management application method for power grid assets, including functional modules such as asset management, operation monitoring, fault early warning, and maintenance management. Digitalize and visualize asset data, and be able to grasp the asset status in real time. Formulate operation and maintenance management plan, including operation and maintenance plan formulation, task allocation and progress tracking. (3) Formulate a pilot operation plan and conduct pilot operation in some regions or business scenarios. Before the pilot operation, set the operation objectives, scope, time and evaluation criteria. Collect user feedback in a centralized manner during the operation. After collection, analyze the data management platform to optimize and improve it. Analyze the effectiveness, feasibility and user acceptance of the data management platform. (4) After optimization and improvement, conduct pilot operation again. If the pilot operation is qualified, it needs to be adjusted, optimized and improved again until the pilot operation is qualified. Summarize and analyze the problems during implementation, expand the scope of pilot operation and conduct pilot operation again. After the expanded pilot operation is qualified, it is fully promoted. When fully promoting, the scope, time nodes and training content of the promotion are formulated. During the promotion, the promotion situation is investigated regularly.

[0009] Preferably, the management and control module formulates a management and pre-control scheme. During the implementation of the management and pre-control scheme, the management and pre-control scheme receives real-time monitoring data from the management model and manages and pre-controls power grid assets through the management and pre-control scheme. The management and pre-control scheme includes a first management scheme, a second management scheme, and a third management scheme. The first management scheme is equipped with a first pre-control scheme, the second management scheme is equipped with a second pre-control scheme, and the third management scheme is equipped with a third pre-control scheme.

[0010] Preferably, the feedback and adjustment module associates with the management and control database, analyzes the stored data after each management and control operation, and formulates a feedback and adjustment plan to adjust and optimize the management pre-control plan and the control and control processing plan through analysis. The feedback and adjustment plan includes a first processing optimization plan, a second processing optimization plan and a third processing optimization plan, wherein the first processing optimization plan optimizes and adjusts the first management plan, the second processing optimization plan optimizes and adjusts the second management plan, and the third processing optimization plan optimizes and adjusts the third management plan.

[0011] Preferably, the historical data unit collects the results after management. After collection, a historical database is built to analyze and classify the collected data, and a regular analysis and processing plan is formulated to regularly analyze the data in the historical database. During the analysis, a special team is used to conduct the analysis and classify the results into three levels: Level 1, Level 2, and Level 3. Level 1 is high risk, Level 2 is medium risk, and Level 3 is low risk. Within the regular analysis and processing plan, Level 1 optimization processing plan, Level 2 optimization processing plan, and Level 3 optimization processing plan are formulated.

[0012] Compared with the prior art, the beneficial effects of the present invention are: In the process of managing and controlling power grid assets, this invention can accurately and efficiently manage and control power grid assets by formulating management and control schemes of different levels. During the management and control process, the effectiveness and problems of management are analyzed, and the management and control schemes are automatically optimized after the analysis is completed. This ensures the stability and accuracy of the management and control schemes during implementation and avoids timeliness issues during implementation, which could lead to the failure to achieve the expected results. In the process of power grid asset management, this invention updates asset data regularly and in real time to ensure the accuracy of asset data when it is used. After the asset data is updated, the management model and management pre-control scheme are improved to ensure that they conform to the actual situation during implementation. Attached Figure Description

[0013] Figure 1 This is a system block diagram provided for an embodiment of the present invention. Detailed Implementation

[0014] 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.

[0015] Please see Figure 1 The present invention provides a technical solution: a smart management system for the entire life cycle of power grid assets, including an asset data collection unit, a data processing unit, a management control unit, and a historical data unit; The asset data collection unit collects asset information of the power grid and builds an asset management database during the collection process. The collected data is centrally collected and stored, and identification processing is performed during the collection and storage process. The data processing unit receives data collected from the asset management database, analyzes and processes the data after receiving it, and periodically collects and updates the asset management data after the analysis is completed. The management control unit formulates a management model based on the analyzed data. Once the management model is formulated, an asset management plan is developed. After the plan is developed, problems arising during implementation are collected, and a historical database is established for centralized management. Historical data is analyzed periodically, and the asset data collection unit and data processing unit are dynamically adjusted after analysis.

[0016] The asset data collection unit formulates a static basic data collection plan and a dynamic operation data collection plan when collecting data on power grid assets. The data collected by the static basic data collection plan and the dynamic operation data collection plan are centrally collected through the asset management database. The static basic data collection plan collects data on newly built and renovated project assets through automated collection technology, and collects data on existing assets through manual supplementary collection. After the data collection is completed, the static basic data is integrated and processed, and the data is standardized. The dynamic operation data collection scheme collects key parameters in real time by deploying dedicated sensors on different devices and by using mobile methods to collect data on different high-altitude devices. After the data collection is completed, data is collected throughout the entire life cycle, including collection, construction, operation and maintenance and disposal. Problems that arise during data collection are also collected. After the data collection is completed, problem solutions are developed, and the problem solutions are adjusted for both the static basic data collection scheme and the dynamic operation data collection scheme.

[0017] The data processing unit includes a data classification module and a data update module. The data classification module classifies the data collected inside the asset management database into categories such as static basic data, dynamic operation data, operation and maintenance data, full life cycle data, and environmental related data. The classified data is then verified and cleaned, and labeled. After the labeling is completed, the data is classified in chronological order. The static basic data includes asset ID, name, model specifications, manufacturer, manufacturing date, installation location, material, and rated parameters. The dynamic operating data includes voltage, current, power, temperature, humidity, vibration, insulation status, load rate, and fault alarm information. The maintenance and repair data includes maintenance records, defect information, test data, replaced parts, maintenance cycles, and maintenance personnel. The full lifecycle data includes purchase contracts, warehousing records, installation and acceptance reports, depreciation information, scrapping approvals, and disposal results. The environmental data includes the region's meteorological and geological conditions and surrounding obstacles.

[0018] The data update module updates and adjusts the collected data by formulating a data update plan, which includes manual data collection and real-time data collection and updates. During the update process, the updated data is marked. The manual data collection and update process is divided into three levels based on the type of data collected by the equipment: Level 1, Level 2, and Level 3. Level 1 is the most complex and involves manual data collection every 15 days. After collection, the data is analyzed and updated in the asset management database. Level 2 is of moderate difficulty and involves manual data collection every 10 days. After collection, the data is analyzed and updated in the asset management database. Level 3 is the easiest and involves manual data collection every 5 days. After collection, the data is analyzed and updated in the asset management database. In case of abnormal or extreme weather, the manual data collection time is shortened, and the shortened time is adjusted according to the degree of impact of the weather. The more severe the impact, the shorter the time. When the impact is judged to be moderate or slight, the shortened time is adaptively adjusted. The real-time data collection and update process involves three analysis and storage schemes based on equipment type. The first analysis and storage scheme stores and analyzes data that directly affects the safe and stable operation of the power grid, the assessment of new energy consumption, or the settlement of inter-provincial power transactions. After storage and analysis, the data within the asset management database is updated. The second analysis and storage scheme analyzes and stores data that may cause production line shutdowns, failures of important and emergency equipment, or data loss, and updates the data within the asset management database. The third analysis and storage scheme analyzes and stores data generated for internal energy consumption analysis or compliance self-inspection, and updates the data within the asset management database. When encountering man-made weather anomalies, equipment is manually inspected and calibrated.

[0019] The management and control unit includes a management model module, a management and control module, and a feedback adjustment module. The management model module builds a management model using virtual technology and big data technology, and performs comprehensive real-time monitoring and feedback on the equipment through the management model. The specific construction steps are as follows: (1) A data management platform is built based on the specific data collection of the hardware infrastructure, and the data management platform is associated with the asset management database. The data management platform is used for centralized storage, management and retrieval of power grid asset data, and real-time analysis and processing of real-time data is carried out through big data technology. (2) Formulate a full life cycle management application method for power grid assets, including functional modules such as asset management, operation monitoring, fault early warning, and maintenance management. Digitalize and visualize asset data, and be able to grasp the asset status in real time. Formulate operation and maintenance management plan, including operation and maintenance plan formulation, task allocation and progress tracking. (3) Formulate a pilot operation plan and conduct pilot operation in some regions or business scenarios. Before the pilot operation, set the operation objectives, scope, time and evaluation criteria. Collect user feedback in a centralized manner during the operation. After collection, analyze the data management platform to optimize and improve it. Analyze the effectiveness, feasibility and user acceptance of the data management platform. (4) After optimization and improvement, conduct pilot operation again. If the pilot operation is qualified, it needs to be adjusted, optimized and improved again until the pilot operation is qualified. Summarize and analyze the problems during implementation, expand the scope of pilot operation and conduct pilot operation again. After the expanded pilot operation is qualified, it is fully promoted. When fully promoting, the scope, time nodes and training content of the promotion are formulated. During the promotion, the promotion situation is investigated regularly.

[0020] The management and control module formulates a management and pre-control scheme. During the implementation of the management and pre-control scheme, the management model monitors time-varying data in real time and manages and pre-controls power grid assets through the management and pre-control scheme. The management and pre-control scheme includes a first management scheme, a second management scheme, and a third management scheme. The first management scheme is equipped with a first pre-control scheme, the second management scheme is equipped with a second pre-control scheme, and the third management scheme is equipped with a third pre-control scheme. Furthermore, the first management plan adjusts the control over equipment in a high-risk state and with serious problems, focusing on key core assets and important assets during comprehensive control. The first pre-control plan addresses the issues managed by the first management plan. The second management plan adjusts the control over equipment in a medium-risk state and with abnormal problems, focusing on general assets during comprehensive control. The second pre-control plan addresses the issues managed by the second management plan. The third management plan adjusts the control over equipment in a low-risk state and with sub-optimal condition, focusing on general assets and secondary assets during comprehensive control. The third pre-control plan addresses the issues managed by the third management plan. Furthermore, the first, second, and third pre-control schemes include real-time pre-control processing during the planning and design, procurement and construction, operation and maintenance, and decommissioning and scrapping stages. Data on problems and results generated during control and pre-control are collected and stored in a control database.

[0021] The feedback and adjustment module associates with the control database, analyzes the stored data after each control operation, and formulates feedback and adjustment plans to optimize the management pre-control plan and the control and processing plan based on the analysis. The feedback and adjustment plan includes a first processing optimization plan, a second processing optimization plan, and a third processing optimization plan. The first processing optimization plan optimizes and adjusts the first management plan, the second processing optimization plan optimizes and adjusts the second management plan, and the third processing optimization plan optimizes and adjusts the third management plan. The first processing optimization scheme has the largest processing range and the greatest optimization intensity, the second processing optimization scheme has a medium processing range and the greatest optimization intensity, and the third processing optimization scheme has a moderate processing range and the greatest optimization intensity.

[0022] The historical data unit collects the results after management. After collection, a historical database is built to analyze and classify the collected data. A regular analysis and processing plan is formulated to regularly analyze the data in the historical database. During the analysis, a special team is used to conduct the analysis and classify the results into three levels: Level 1, Level 2, and Level 3. Level 1 is high risk, Level 2 is medium risk, and Level 3 is low risk. Within the regular analysis and processing plan, optimization processing plans for Level 1, Level 2, and Level 3 are formulated. The Level 1 optimization solution optimizes risks at Level 1, primarily targeting critical and high-risk equipment. The Level 2 optimization solution optimizes risks at Level 2, primarily targeting general and medium-risk equipment. The Level 3 optimization solution optimizes risks at Level 3, primarily targeting non-critical and low-risk equipment. The optimization and adjustment process is monitored in real time, and the monitoring results are analyzed. Based on the analysis, adjustments and optimizations are made as soon as possible according to the actual situation. The data within the asset data collection unit and asset management database are adjusted according to the results of the optimization and processing based on the periodic analysis and processing plan.

[0023] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0024] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A smart management system for the entire lifecycle of power grid assets, characterized in that... It includes an asset data collection unit, a data processing unit, a management control unit, and a historical data unit; The asset data collection unit collects asset information of the power grid and builds an asset management database during the collection process. The collected data is centrally collected and stored, and identification processing is performed during the collection and storage process. The data processing unit receives data collected from the asset management database, analyzes and processes the data after receiving it, and periodically collects and updates the asset management data after the analysis is completed. The management control unit formulates a management model based on the analyzed data. Once the management model is formulated, an asset management plan is developed. After the plan is developed, problems arising during implementation are collected, and a historical database is established for centralized management. Historical data is analyzed periodically, and the asset data collection unit and data processing unit are dynamically adjusted after analysis.

2. The intelligent management system for the entire lifecycle of power grid assets according to claim 1, characterized in that: The asset data collection unit formulates a static basic data collection plan and a dynamic operation data collection plan when collecting data on power grid assets. The data collected by the static basic data collection plan and the dynamic operation data collection plan are centrally collected through the asset management database. The static basic data collection plan collects data on newly built and renovated project assets through automated collection technology, and collects data on existing assets through manual supplementary collection. After the data collection is completed, the static basic data is integrated and processed, and the data is standardized.

3. The intelligent management system for the entire lifecycle of power grid assets according to claim 2, characterized in that: The data processing unit includes a data classification module and a data update module. The data classification module classifies the data collected inside the asset management database into categories such as static basic data, dynamic operation data, operation and maintenance data, full life cycle data, and environmental related data. The classified data is then verified and cleaned, and labeled. After the labeling is completed, the data is classified in chronological order.

4. The intelligent management system for the entire lifecycle of power grid assets according to claim 3, characterized in that: The data update module updates and adjusts the collected data by formulating a data update plan, which includes manual data collection and real-time data collection and updates. During the update process, the updated data is marked. The manual data collection and update process is divided into three levels: Level 1, Level 2, and Level 3, based on the type of data collected by the equipment. Level 1 is the most complex and involves manual data collection every 15 days. After collection, the data is analyzed and updated within the asset management database. Level 2 is of moderate difficulty and involves manual data collection every 10 days. After collection, the data is analyzed and updated within the asset management database. Level 3 is the easiest and involves manual data collection every 5 days. After collection, the data is analyzed and updated within the asset management database. In the event of abnormal or extreme weather conditions, the manual data collection time is shortened, and the shortened time is adjusted according to the degree of impact of the weather. The more severe the impact, the shorter the shortened time. When the impact is judged to be moderate or slight, the shortened time is adaptively adjusted.

5. The intelligent management system for the entire lifecycle of power grid assets according to claim 4, characterized in that: The management and control unit includes a management model module, a management and control module, and a feedback adjustment module. The management model module builds a management model using virtual technology and big data technology, and performs comprehensive real-time monitoring and feedback on the equipment through the management model. The specific construction steps are as follows: (1) A data management platform is built based on the specific data collection of the hardware infrastructure, and the data management platform is associated with the asset management database. The data management platform is used for centralized storage, management and retrieval of power grid asset data, and real-time analysis and processing of real-time data is carried out through big data technology. (2) Formulate a full life cycle management application method for power grid assets, including functional modules such as asset management, operation monitoring, fault early warning, and maintenance management. Digitalize and visualize asset data, and be able to grasp the asset status in real time. Formulate operation and maintenance management plan, including operation and maintenance plan formulation, task allocation and progress tracking. (3) Formulate a pilot operation plan and conduct pilot operation in some regions or business scenarios. Before the pilot operation, set the operation objectives, scope, time and evaluation criteria. Collect user feedback in a centralized manner during the operation. After collection, analyze the data management platform to optimize and improve it. Analyze the effectiveness, feasibility and user acceptance of the data management platform. (4) After optimization and improvement, conduct pilot operation again. If the pilot operation is qualified, it needs to be adjusted, optimized and improved again until the pilot operation is qualified. Summarize and analyze the problems during implementation, expand the scope of pilot operation and conduct pilot operation again. After the expanded pilot operation is qualified, it is fully promoted. When fully promoting, the scope, time nodes and training content of the promotion are formulated. During the promotion, the promotion situation is investigated regularly.

6. The intelligent management system for the entire lifecycle of power grid assets according to claim 5, characterized in that: The management and control module formulates a management and pre-control scheme. During the implementation of the management and pre-control scheme, the management model monitors time-varying data in real time and manages and pre-controls power grid assets through the management and pre-control scheme. The management and pre-control scheme includes a first management scheme, a second management scheme, and a third management scheme. The first management scheme is equipped with a first pre-control scheme, the second management scheme is equipped with a second pre-control scheme, and the third management scheme is equipped with a third pre-control scheme.

7. The intelligent management system for the entire lifecycle of power grid assets according to claim 6, characterized in that: The feedback and adjustment module associates with the control database and analyzes the stored data after each control operation. Through analysis, it formulates feedback and adjustment schemes to adjust and optimize the management pre-control scheme and the control and processing scheme. The feedback and adjustment schemes include a first processing optimization scheme, a second processing optimization scheme, and a third processing optimization scheme. The first processing optimization scheme optimizes and adjusts the first management scheme, the second processing optimization scheme optimizes and adjusts the second management scheme, and the third processing optimization scheme optimizes and adjusts the third management scheme.

8. The intelligent management system for the entire lifecycle of power grid assets according to claim 7, characterized in that: The historical data unit collects the results after management. After collection, a historical database is built to analyze and classify the collected data. A regular analysis and processing plan is formulated to regularly analyze the data in the historical database. During the analysis, a special team is used to analyze the data and classify the results into three levels: Level 1, Level 2, and Level 3. Level 1 is high risk, Level 2 is medium risk, and Level 3 is low risk. Within the regular analysis and processing plan, optimization processing plans for Level 1, Level 2, and Level 3 are formulated.

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