Power production management system based on cloud native

Abstract

The invention provides an electric power production management system based on cloud native, and the system comprises an application deployment module which is used for packaging an electric power production management application based on cloud native, and deploying the electric power production management application in a standardized container based on a packaging result; the management module is used for analyzing the collected real-time power production data based on a deployment result and scheduling power production based on an analysis result; and the monitoring module is used for carrying out full-life-cycle monitoring on power production based on the scheduling result and carrying out recording management on a full-life-cycle monitoring result. The method solves the problems of complex system operation environment deployment and long maintenance downtime, improves the efficiency of power production, carries out full-life-cycle monitoring on power production in the scheduling process, records and manages the full-life-cycle monitoring result, facilitates the effective understanding of the scheduling condition, and improves the efficiency of power production. And the power production management effect is greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a cloud-native based power production management system. Background Art

[0002] At present, with the continuous development of the power industry and the advancement of digital transformation, power production management is facing increasingly complex demands and challenges. In the current technical environment, cloud-native technology has emerged and demonstrated strong advantages. Cloud-native architecture can provide high flexibility, scalability, and reliability, enabling power production management systems to better adapt to dynamically changing business needs.

[0003] The power production process involves many links, such as power generation, transmission, transformation, and distribution. Each link generates a large amount of data. Traditional power production management systems have gradually shown their limitations in dealing with large-scale data processing, high concurrent access, rapid deployment, and elastic expansion.

[0004] In addition, the safe and stable operation of the power system is crucial, and real-time monitoring and early warning systems are needed to detect potential problems in a timely manner and take countermeasures;

[0005] Therefore, in order to overcome the above-mentioned defects, the present invention provides a cloud-native based power production management system. Summary of the invention

[0006] The present invention provides a cloud-native-based power production management system, which is used to package power production management applications and deploy them in standardized containers by adopting cloud-native technology, thereby facilitating the management and operation of power production, and also solving the problems of complex deployment of the system operating environment and long maintenance downtime. Secondly, the collected real-time power production data is analyzed according to the deployment results, and accurate and effective scheduling of power production is achieved according to the analysis results, thereby improving the efficiency of power production. Finally, the power production in the scheduling process is monitored throughout the life cycle, and the monitoring results of the entire life cycle are recorded and managed, which is convenient for timely response when there are abnormalities in the scheduling process, and also convenient for effective understanding of the scheduling situation, thereby greatly improving the power production management effect.

[0007] The present invention provides a cloud-native-based power production management system, comprising:

[0008] An application deployment module, which is used to package the power production management application based on cloud native, and deploy the power production management application in a standardized container based on the packaging result;

[0009] A management module, used to analyze the collected real-time power production data based on the deployment results, and to schedule power production based on the analysis results;

[0010] The monitoring module is used to monitor the entire life cycle of power production based on the dispatch results, and to record and manage the monitoring results of the entire life cycle.

[0011] Preferably, a cloud-native-based power production management system, application deployment module, includes:

[0012] An application acquisition unit, used to acquire an electric power production management application, extract attribute parameters of the electric power production management application based on a background terminal, and acquire container parameters of a standardized container;

[0013] An application packaging unit, used to determine a packaging strategy required for the power production management application based on the attribute parameters and the container parameters, and to package the power production management application into an application image file based on the packaging strategy;

[0014] The upload unit is used to upload the application image file to the standardized container.

[0015] Preferably, a cloud-native-based power production management system, application deployment module, includes:

[0016] An application processing unit, used to parse the packaging results, extract the application structure characteristics of the power production management application, and determine the split nodes of the power production management application based on the application structure characteristics and the business execution process of the power production management application;

[0017] An application splitting unit, used to split the power production management application into N microservices based on the splitting nodes, and allocate deployment resources to each microservice based on the splitting results;

[0018] The application deployment unit is used to perform distributed deployment of N microservices based on deployment resources, reserve extension and update interfaces for each microservice based on the distributed deployment results, and complete the deployment of the power production management application in the standardized container based on the reserved results.

[0019] Preferably, a cloud-native-based power production management system, an application deployment unit, includes:

[0020] A result acquisition subunit, used to acquire the deployment result and start the power production management application deployed in the standardized container based on the deployment result;

[0021] The state monitoring subunit is used to obtain the operation state parameters of the power production management application in real time based on the startup result, and analyze the operation state parameters based on the preset state evaluation index to obtain the state evaluation result;

[0022] The optimization subunit is used to determine the optimization direction and optimization parameters of the deployment results based on the operating status parameters when the status evaluation results do not meet the preset requirements, and optimize the deployment results based on the optimization direction and optimization parameters.

[0023] Preferably, a cloud-native-based power production management system, an application deployment unit, includes:

[0024] A link opening subunit is used to obtain the deployment result of the power production management application in the standardized container, and to open a real-time interactive link with the management terminal based on the deployment result;

[0025] Application Update subunit, used to:

[0026] Based on the real-time interactive link, the application update request and application update target issued by the management terminal are received, and the application update target is parsed to obtain the microservice to be updated;

[0027] Temporarily split and separate the deployment results of the microservice to be updated in the standardized container, and cache the upper-level processing data of the microservice to be updated based on the temporary split and separation results;

[0028] At the same time, based on the temporary split, the microservices to be updated are updated independently, and based on the update results, the microservices to be updated are deployed and reset in the standardized container;

[0029] The cached upper-level processing data is processed based on the deployment reset result.

[0030] Preferably, a cloud-native-based power production management system, the management module includes:

[0031] A data collection and preparation unit is used to obtain a spatial structure distribution diagram of a power production scene and extract distribution characteristics of each power device in the power production scene;

[0032] A parameter mapping unit, used to extract the business parameters of each power device, and map and annotate the business parameters of each power device in a spatial structure distribution diagram of a power production scene based on distribution characteristics;

[0033] A location determination unit, used to obtain a business layout diagram of the power production scenario based on the mapping and annotation results, and determine the data collection dimension based on the preset power production management requirements;

[0034] Data acquisition unit for:

[0035] Match the data collection dimensions with the business parameters of each power device, determine the key data collection points based on the matching results, and provide installation guidance for the target sensors based on the key data collection points;

[0036] Based on the installed target sensors, each power equipment is monitored in real time to obtain the corresponding real-time power production data.

[0037] Preferably, a cloud-native-based power production management system, the management module includes:

[0038] Data pre-processing unit, used for:

[0039] Performing clustering processing on the collected real-time power production data, and obtaining a multi-dimensional power data set corresponding to the real-time power production data based on the clustering processing;

[0040] Traverse each dimensional power data set, and determine the existing abnormal data based on the traversal results. At the same time, extract the sample representation of each dimensional power data set, and call the target strategy from the preset cleaning strategy library based on the sample representation to clean the abnormal data, so as to obtain a multi-dimensional standard power data set;

[0041] Data analysis unit for:

[0042] Determine the subordinate and limiting relationship between the multi-dimensional standard power data sets based on the power production and operation protocol, and assign a corresponding weight value to each dimensional standard power data set based on the subordinate and limiting relationship;

[0043] Input each dimensional standard power data set and the corresponding weight value into the power demand forecasting model, and analyze each dimensional standard power data set based on the input result to obtain the power label of the current time period;

[0044] Determine the demand fluctuation characteristics of the power grid in the current time period based on the power tags, and correct the demand fluctuation characteristics based on the weight values ​​corresponding to the standard power data set of each dimension to obtain the demand trend of the power grid in the next stage, and obtain the power load demand based on the demand trend;

[0045] Power production dispatching unit, used for:

[0046] Analyze the performance parameters of each device in the power grid to obtain the performance range of each device. At the same time, traverse the power grid to obtain the topological structure and power flow distribution of the power grid, and obtain the line transmission capacity of the power grid based on the topological structure and power flow distribution;

[0047] Based on the power load demand, the performance range of each device and the line transmission capacity of the power grid, a preliminary dispatching plan for power production is obtained, and a simulation operation is performed on the preliminary dispatching plan. Based on the simulation operation results, the preliminary dispatching plan is adjusted for loopholes to obtain the final dispatching plan;

[0048] Power production is dispatched and managed based on the final dispatch plan.

[0049] Preferably, a cloud-native-based power production management system, a power production dispatching unit, comprises:

[0050] The scheme acquisition subunit is used to obtain the preliminary dispatching scheme and build a virtual power production scenario in the computer based on the structural relationship between the power grid and each device;

[0051] Analog subunit for:

[0052] Adding the preliminary dispatching scheme in the background of the virtual power production scenario based on a computer, and simulating the dispatching of power production of the virtual power production scenario according to the preliminary dispatching scheme based on the adding result;

[0053] Determine the power production status of each production node based on the simulated scheduling, and determine the potential hidden danger factors and corresponding hidden danger representations under the preliminary scheduling plan based on the power production status;

[0054] The scheme adjustment subunit is used to make loophole adjustments to the preliminary scheduling scheme based on potential hidden danger factors and hidden danger representations to obtain the final scheduling scheme.

[0055] Preferably, a cloud-native-based power production management system, monitoring module, includes:

[0056] Monitoring unit for:

[0057] Obtain monitoring requirements for power production and determine monitoring dimensions and monitoring nodes based on the monitoring requirements;

[0058] Configure monitoring mechanisms based on monitoring dimensions and monitoring nodes, and conduct full life cycle monitoring of the dispatching process of power production based on the monitoring mechanisms;

[0059] A classification unit is used to obtain multi-dimensional dispatching parameters of power production and status parameters of each device based on the full life cycle monitoring results, and map and associate the status parameters of each device with the multi-dimensional dispatching parameters;

[0060] Recording unit for:

[0061] Construct a parameter record table and extract the timestamp corresponding to the full life cycle monitoring results;

[0062] Based on the timestamp and mapping association results, the status parameters and multi-dimensional scheduling parameters of each device are recorded and managed in the parameter recording table.

[0063] Preferably, a cloud-native-based power production management system, a recording unit, comprises:

[0064] A parameter analysis subunit is used to extract the state parameters of each device during the power production and dispatching process, and determine the state of each device based on the state parameters;

[0065] Safety monitoring subunit, used for:

[0066] Based on the time series, the state of each device is visualized in a visualization coordinate system, and the state change amplitude of each device is obtained based on the visualization;

[0067] Determine risk devices based on the state change amplitude and the reference amplitude interval, and reallocate monitoring resources of the monitoring mechanism based on the risk devices;

[0068] Based on the reallocation results, risk equipment is monitored and early warning management is carried out when a fault occurs.

[0069] Compared with the prior art, the present invention has the following beneficial effects:

[0070] By adopting cloud-native technology to package power production management applications and deploy them in standardized containers, it is easier to manage power production and solve the problems of complex deployment of the system operating environment and long maintenance downtime. Secondly, the collected real-time power production data is analyzed according to the deployment results, and accurate and effective scheduling of power production is achieved based on the analysis results, thereby improving the efficiency of power production. Finally, the power production in the scheduling process is monitored throughout the life cycle, and the monitoring results of the entire life cycle are recorded and managed, which facilitates timely response when there are abnormalities in the scheduling process, and also facilitates effective understanding of the scheduling situation, greatly improving the power production management effect.

[0071] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures specifically pointed out in this application document.

[0072] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0074] Figure 1 This is a structural diagram of a cloud-native-based power production management system in an embodiment of the present invention;

[0075] Figure 2 This is a structural diagram of an application deployment module in a cloud-native-based power production management system in an embodiment of the present invention;

[0076] Figure 3This is a structural diagram of a management module in a cloud-native based power production management system in an embodiment of the present invention. DETAILED DESCRIPTION

[0077] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0078] Embodiment 1:

[0079] This embodiment provides a cloud-native-based power production management system. Figure 1 As shown, including:

[0080] An application deployment module, which is used to package the power production management application based on cloud native, and deploy the power production management application in a standardized container based on the packaging result;

[0081] A management module, used to analyze the collected real-time power production data based on the deployment results, and to schedule power production based on the analysis results;

[0082] The monitoring module is used to monitor the entire life cycle of power production based on the dispatch results, and to record and manage the monitoring results of the entire life cycle.

[0083] In this embodiment, cloud native is a method and concept for building and running applications, emphasizing the use of the characteristics and advantages of cloud computing to design applications to be suitable for efficient operation and management in a cloud environment.

[0084] In this embodiment, the power production management application is known in advance and is used to analyze and schedule power production data.

[0085] In this embodiment, the standardized container is set in advance and is a space for carrying the power production management application, thereby facilitating effective management and operation and maintenance of the power production management application.

[0086] In this embodiment, the real-time power production data may be data such as power generation, power load, and power consumption.

[0087] In this embodiment, full life cycle monitoring refers to monitoring the power production scheduling of each device in the power grid and the operating status of each device, so as to facilitate effective understanding of the power production scheduling and the operating status of the equipment.

[0088] The working principle and beneficial effects of the above technical solution are: by adopting cloud native technology to package the power production management application and deploy it in a standardized container, it is convenient to manage and operate power production, and also solves the problems of complex deployment of the system operating environment and long maintenance downtime. Secondly, the collected real-time power production data is analyzed according to the deployment results, and accurate and effective scheduling of power production is achieved according to the analysis results, thereby improving the efficiency of power production. Finally, the power production in the scheduling process is monitored throughout the life cycle, and the monitoring results of the entire life cycle are recorded and managed, which is convenient for timely response when there are abnormalities in the scheduling process, and also convenient for effective understanding of the scheduling situation, which greatly improves the power production management effect.

[0089] Embodiment 2:

[0090] Based on Example 1, this embodiment provides a cloud-native-based power production management system, an application deployment module, including:

[0091] An application acquisition unit, used to acquire an electric power production management application, extract attribute parameters of the electric power production management application based on a background terminal, and acquire container parameters of a standardized container;

[0092] An application packaging unit, used to determine a packaging strategy required for the power production management application based on the attribute parameters and the container parameters, and to package the power production management application into an application image file based on the packaging strategy;

[0093] The upload unit is used to upload the application image file to the standardized container.

[0094] In this embodiment, the attribute parameters refer to the type of the power production management application and requirements such as operating conditions that need to be met during operation.

[0095] In this embodiment, the container parameters refer to the space size and structural distribution of the standardized container.

[0096] In this embodiment, the packaging strategy refers to the way of packaging power production management applications, etc.

[0097] In this embodiment, the application image file refers to the result obtained after packaging the power production management application according to the packaging strategy, and is a file that can be directly deployed in a standardized container.

[0098] The working principle and beneficial effects of the above technical solution are: by extracting the attribute parameters of the power production management application from the background terminal and determining the container parameters of the standardized container, the packaging strategy required for the power production management application is accurately and effectively determined according to the attribute parameters and container parameters. Finally, the power production management application is packaged into an application image file according to the packaging strategy, thereby facilitating the deployment of the power production management application in the standardized container and solving the problem of complex deployment of the system operating environment.

[0099] Embodiment 3:

[0100] Based on Example 1, this example provides a cloud-native-based power production management system, such as Figure 2 As shown, the application deployment module includes:

[0101] An application processing unit, used to parse the packaging results, extract the application structure characteristics of the power production management application, and determine the split nodes of the power production management application based on the application structure characteristics and the business execution process of the power production management application;

[0102] An application splitting unit, used to split the power production management application into N microservices based on the splitting nodes, and allocate deployment resources to each microservice based on the splitting results;

[0103] The application deployment unit is used to perform distributed deployment of N microservices based on deployment resources, reserve extension and update interfaces for each microservice based on the distributed deployment results, and complete the deployment of the power production management application in the standardized container based on the reserved results.

[0104] In this embodiment, the application structure feature refers to the components included in the power production management application and the association relationship or structural relationship between the components.

[0105] In this embodiment, the business execution process refers to the execution sequence between the corresponding steps when the power production management application is working.

[0106] In this embodiment, the split node refers to a specific location where the power production management application is split.

[0107] In this embodiment, microservices refer to splitting the power production management application into multiple branches according to split nodes, thereby facilitating the deployment of the power production management application.

[0108] In this embodiment, deployment resources refer to the database and operation level required when deploying microservices.

[0109] In this embodiment, the reserved extension and update interface refers to an interface reserved for each microservice after each microservice is successfully deployed, so as to facilitate the expansion and data update operations of the microservice.

[0110] The working principle and beneficial effects of the above technical solution are: by determining the application structure characteristics of the power production management application, the power production management application is split into N microservices according to the application structure characteristics, which provides convenience for application deployment. Secondly, deployment resources are allocated to each microservice to achieve effective deployment of each microservice according to the deployment resources. Finally, after the deployment is completed, an extension and update interface is reserved for each microservice, which facilitates the update and extension management of the microservice, ensuring the reliability and accuracy of the deployment of the power production management application.

[0111] Embodiment 4:

[0112] Based on Example 3, this embodiment provides a cloud-native-based power production management system, an application deployment unit, including:

[0113] A result acquisition subunit, used to acquire the deployment result and start the power production management application deployed in the standardized container based on the deployment result;

[0114] The state monitoring subunit is used to obtain the operation state parameters of the power production management application in real time based on the startup result, and analyze the operation state parameters based on the preset state evaluation index to obtain the state evaluation result;

[0115] The optimization subunit is used to determine the optimization direction and optimization parameters of the deployment results based on the operating status parameters when the status evaluation results do not meet the preset requirements, and optimize the deployment results based on the optimization direction and optimization parameters.

[0116] In this embodiment, the operating status parameter refers to the specific operating status of the power production management application in the standardized container.

[0117] In this embodiment, the preset status evaluation index is set in advance, and may be, for example, an index such as stability and work efficiency.

[0118] In this embodiment, the preset requirements are set in advance, that is, the minimum operating standards that the power production management application needs to achieve under the preset state evaluation indicators.

[0119] In this embodiment, the optimization direction and optimization parameter refer to the parameter type optimized for the deployment result and the specific value optimized for the parameter type when the status evaluation result does not meet the preset requirements.

[0120] The working principle and beneficial effects of the above technical solution are: by starting the power production management application after the deployment is completed, the operating status parameters of the power production management application are comprehensively and effectively acquired; secondly, the operating status parameters are analyzed according to the preset status evaluation indicators, so as to accurately and effectively determine the status evaluation results of the power production management application in the standardized container; finally, when the status evaluation results do not meet the preset requirements, the deployment results are optimized and adjusted, thereby ensuring the operational reliability of the power production management application and facilitating the effective management of power production.

[0121] Embodiment 5:

[0122] Based on Example 3, this embodiment provides a cloud-native-based power production management system, an application deployment unit, including:

[0123] A link opening subunit is used to obtain the deployment result of the power production management application in the standardized container, and to open a real-time interactive link with the management terminal based on the deployment result;

[0124] Application Update subunit, used to:

[0125] Based on the real-time interactive link, the application update request and application update target issued by the management terminal are received, and the application update target is parsed to obtain the microservice to be updated;

[0126] Temporarily split and separate the deployment results of the microservice to be updated in the standardized container, and cache the upper-level processing data of the microservice to be updated based on the temporary split and separation results;

[0127] At the same time, based on the temporary split, the microservices to be updated are updated independently, and based on the update results, the microservices to be updated are deployed and reset in the standardized container;

[0128] The cached upper-level processing data is processed based on the deployment reset result.

[0129] In this embodiment, the application update target refers to the specific content that the management terminal needs to update for the power production management application.

[0130] In this embodiment, the microservice to be updated refers to a microservice that needs to be updated, which is one or more of all microservices of the power production management application.

[0131] In this embodiment, temporary splitting and independence refers to temporarily disconnecting the connection relationship and work undertaking relationship between the microservice to be updated and other microservices, so as to update the microservice to be updated without affecting the work of other microservices.

[0132] In this embodiment, the upper-level processing data cache refers to temporary storage of processing data of the previous microservice of the microservice to be updated, so that the cached data can be processed in time after the microservice to be updated completes the update.

[0133] In this embodiment, deployment resetting refers to resetting the updated microservice to be updated in a standardized container, so as to facilitate the continued execution of corresponding management operations.

[0134] The working principle and beneficial effects of the above technical solution are: by opening a real-time interactive link between the standardized container and the management terminal according to the deployment results, it is convenient to effectively receive the application update request and application update target issued by the management terminal; secondly, the microservice to be updated is effectively determined according to the received application update target, and the microservice to be updated is temporarily split and separated, so that only the microservice to be updated is updated without affecting the normal operation of other microservices; at the same time, after the microservice to be updated is updated, it is deployed and reset in the standardized container to achieve convenient and fast update of the power production management application.

[0135] Embodiment 6:

[0136] Based on Example 1, this embodiment provides a cloud-native-based power production management system, and the management module includes:

[0137] A data collection and preparation unit is used to obtain a spatial structure distribution diagram of a power production scene and extract distribution characteristics of each power device in the power production scene;

[0138] A parameter mapping unit, used to extract the business parameters of each power device, and map and annotate the business parameters of each power device in a spatial structure distribution diagram of a power production scene based on distribution characteristics;

[0139] A location determination unit, used to obtain a business layout diagram of the power production scenario based on the mapping and annotation results, and determine the data collection dimension based on the preset power production management requirements;

[0140] Data acquisition unit for:

[0141] Match the data collection dimensions with the business parameters of each power device, determine the key data collection points based on the matching results, and provide installation guidance for the target sensors based on the key data collection points;

[0142] Based on the installed target sensors, each power equipment is monitored in real time to obtain the corresponding real-time power production data.

[0143] In this embodiment, the spatial structure distribution diagram refers to the spatial situation corresponding to the power production scene, including the location distribution of power equipment and the spatial size of the power production scene.

[0144] In this embodiment, the distribution feature refers to the location distribution of each power device in the power production scenario.

[0145] In this embodiment, the service parameter refers to the working type corresponding to each power equipment, etc.

[0146] In this embodiment, mapping and labeling refers to labeling the business parameters of each power equipment at the power equipment in the spatial structure distribution diagram of the power production scenario, so as to facilitate the intuitive determination of the specific situation of each power equipment through the spatial structure distribution diagram, wherein the business layout diagram is the result of mapping and labeling, including the location of the power equipment and the corresponding business parameters.

[0147] In this embodiment, the preset power production management requirements are known in advance.

[0148] In this embodiment, the data collection dimension refers to the type of data that needs to be collected.

[0149] In this embodiment, the key data collection point refers to a specific location where the power equipment can be effectively monitored when the power equipment is monitored in real time.

[0150] In this embodiment, the target sensor refers to a plurality of different types of sensors that can monitor the operating conditions of the electric power equipment.

[0151] The working principle and beneficial effects of the above technical solution are: by analyzing the spatial structure distribution map of the power production scene, the distribution characteristics of each power equipment can be accurately and effectively determined. At the same time, the business parameters of each power equipment are obtained, and the business parameters and power equipment are associated in the spatial structure distribution map according to the distribution characteristics. Secondly, the data collection dimensions of the power equipment are locked according to the business layout map obtained by the association, thereby locking the key data collection points according to the data collection dimensions. Finally, the target sensor is installed according to the data collection point. Finally, real-time monitoring of the power equipment is achieved through the target sensor, thereby achieving accurate and effective acquisition of real-time power production data, ensuring the real-time and reliability of the real-time power production data.

[0152] Embodiment 7:

[0153] Based on Example 1, this example provides a cloud-native-based power production management system, such as Figure 3 As shown, the management module includes:

[0154] Data pre-processing unit, used for:

[0155] Performing clustering processing on the collected real-time power production data, and obtaining a multi-dimensional power data set corresponding to the real-time power production data based on the clustering processing;

[0156] Traverse each dimensional power data set, and determine the existing abnormal data based on the traversal results. At the same time, extract the sample representation of each dimensional power data set, and call the target strategy from the preset cleaning strategy library based on the sample representation to clean the abnormal data, so as to obtain a multi-dimensional standard power data set;

[0157] Data analysis unit for:

[0158] Determine the subordinate and limiting relationship between the multi-dimensional standard power data sets based on the power production and operation protocol, and assign a corresponding weight value to each dimensional standard power data set based on the subordinate and limiting relationship;

[0159] Input each dimensional standard power data set and the corresponding weight value into the power demand forecasting model, and analyze each dimensional standard power data set based on the input result to obtain the power label of the current time period;

[0160] Determine the demand fluctuation characteristics of the power grid in the current time period based on the power tags, and correct the demand fluctuation characteristics based on the weight values ​​corresponding to the standard power data set of each dimension to obtain the demand trend of the power grid in the next stage, and obtain the power load demand based on the demand trend;

[0161] Power production dispatching unit, used for:

[0162] Analyze the performance parameters of each device in the power grid to obtain the performance range of each device. At the same time, traverse the power grid to obtain the topological structure and power flow distribution of the power grid, and obtain the line transmission capacity of the power grid based on the topological structure and power flow distribution;

[0163] Based on the power load demand, the performance range of each device and the line transmission capacity of the power grid, a preliminary dispatching plan for power production is obtained, and a simulation operation is performed on the preliminary dispatching plan. Based on the simulation operation results, the preliminary dispatching plan is adjusted for loopholes to obtain the final dispatching plan;

[0164] Power production is dispatched and managed based on the final dispatch plan.

[0165] In this embodiment, the multi-dimensional power data set refers to different types of power data obtained after clustering (classifying) the real-time power production data.

[0166] In this embodiment, abnormal data refers to data with abnormal values ​​or distorted values ​​in each dimensional power data set.

[0167] In this embodiment, the sample representation refers to the data format of each dimensional power data set and the corresponding specific type, etc.

[0168] In this embodiment, the preset cleaning strategy library is known in advance, and a variety of different data cleaning strategies are stored internally, wherein the target strategy refers to a strategy suitable for cleaning the current dimension power data set.

[0169] In this embodiment, the multi-dimensional standard power data set refers to the result obtained by cleaning the abnormal data in each dimensional power data set by using the invoked target strategy.

[0170] In this embodiment, the power production operation protocol refers to the execution standards that the power equipment needs to follow when producing electricity.

[0171] In this embodiment, the subordinate restriction relationship refers to the association relationship or collaborative relationship between the multi-dimensional standard power data sets.

[0172] In this embodiment, allocating a corresponding weight value to each dimensional standard power data set based on the subordinate restriction relationship refers to allocating a weight value according to the importance of each dimensional standard power data set in the overall operation process.

[0173] In this embodiment, the power label refers to the power production, power usage, and power usage time distribution in the current time period.

[0174] In this embodiment, the demand fluctuation characteristic refers to the change in the power demand in the power grid during the current time period.

[0175] In this embodiment, the performance parameter refers to the amount of electric energy produced by each device per unit time, etc., wherein the performance range is the energy output range finally obtained.

[0176] In this embodiment, power flow distribution refers to the flow direction of electric energy generated by each device in the power grid.

[0177] The working principle and beneficial effects of the above technical solution are: by preprocessing the real-time power production data, the accuracy and reliability of the final power production data are ensured; secondly, the preprocessed multi-dimensional standard power data set is analyzed to accurately and effectively determine the power load demand of the power grid at different stages, so as to facilitate the determination of the corresponding scheduling plan according to the power load demand; finally, the performance parameters of each device in the power grid are analyzed to determine the performance range of each device. At the same time, the topological structure and flow distribution of the power grid are analyzed to lock the line transmission capacity of the power grid, and finally a preliminary scheduling plan for power production is obtained according to the power load demand, the performance range of each device and the line transmission capacity of the power grid, and the preliminary scheduling plan is simulated and adjusted to achieve accurate and reliable formulation of the final scheduling plan, thereby ensuring the effectiveness and reliability of scheduling and management of power production.

[0178] Embodiment 8:

[0179] Based on Example 7, this embodiment provides a cloud-native-based power production management system, a power production scheduling unit, including:

[0180] The scheme acquisition subunit is used to obtain the preliminary dispatching scheme and build a virtual power production scenario in the computer based on the structural relationship between the power grid and each device;

[0181] Analog subunit for:

[0182] Adding the preliminary dispatching scheme in the background of the virtual power production scenario based on a computer, and simulating the dispatching of power production of the virtual power production scenario according to the preliminary dispatching scheme based on the adding result;

[0183] Determine the power production status of each production node based on the simulated scheduling, and determine the potential hidden danger factors and corresponding hidden danger representations under the preliminary scheduling plan based on the power production status;

[0184] The scheme adjustment subunit is used to make loophole adjustments to the preliminary scheduling scheme based on potential hidden danger factors and hidden danger representations to obtain the final scheduling scheme.

[0185] In this embodiment, the virtual power production scenario refers to a simulation model of a power grid and various devices constructed in a computer.

[0186] In this embodiment, the power production status refers to the actual situation of power production by each production node under the influence of the scheduling scheme, wherein the production node refers to each power equipment.

[0187] In this embodiment, the hidden danger representation refers to the fault phenomenon caused by potential hidden danger factors.

[0188] The working principle and beneficial effects of the above technical solution are: by constructing a virtual power production scenario in a computer and simulating the preliminary scheduling, at the same time, monitoring and analyzing the power production status of each production node during the simulation scheduling process, timely and accurate determination of existing potential hidden danger factors and corresponding hidden danger representations is achieved, thereby achieving vulnerability adjustments to the preliminary scheduling plan based on the potential hidden danger factors and the corresponding hidden danger representations, thereby ensuring the reliability of the final scheduling plan.

[0189] Embodiment 9:

[0190] Based on Example 1, this embodiment provides a cloud-native-based power production management system, a monitoring module, including:

[0191] Monitoring unit for:

[0192] Obtain monitoring requirements for power production and determine monitoring dimensions and monitoring nodes based on the monitoring requirements;

[0193] Configure monitoring mechanisms based on monitoring dimensions and monitoring nodes, and conduct full life cycle monitoring of the dispatching process of power production based on the monitoring mechanisms;

[0194] A classification unit is used to obtain multi-dimensional dispatching parameters of power production and status parameters of each device based on the full life cycle monitoring results, and map and associate the status parameters of each device with the multi-dimensional dispatching parameters;

[0195] Recording unit for:

[0196] Construct a parameter record table and extract the timestamp corresponding to the full life cycle monitoring results;

[0197] Based on the timestamp and mapping association results, the status parameters and multi-dimensional scheduling parameters of each device are recorded and managed in the parameter recording table.

[0198] In this embodiment, the monitoring requirements refer to the rigor and dimensions of monitoring of power production, etc., wherein the monitoring dimensions are the types of monitoring required.

[0199] In this embodiment, the monitoring node refers to a specific location where power production needs to be monitored.

[0200] In this embodiment, the full life cycle monitoring refers to comprehensive monitoring of the dispatching process of power production, that is, process monitoring from the beginning to the end.

[0201] In this embodiment, the multi-dimensional scheduling parameters refer to the specific circumstances corresponding to the scheduling of electric energy and resources during the power production process.

[0202] The working principle and beneficial effects of the above technical solution are: by constructing a monitoring mechanism, the full life cycle monitoring of the dispatching process of power production is realized through the monitoring mechanism, so as to accurately and effectively determine the multi-dimensional dispatching parameters of power production and the status parameters of each equipment. Secondly, a parameter recording table is constructed, and the timestamp corresponding to the full life cycle monitoring results is determined, so that the multi-dimensional dispatching parameters of power production and the status parameters of each equipment can be effectively recorded and managed in the parameter recording table according to the timestamp, thereby facilitating data traceability.

[0203] Embodiment 10:

[0204] Based on Example 9, this embodiment provides a cloud-native-based power production management system, a recording unit, including:

[0205] A parameter analysis subunit is used to extract the state parameters of each device during the power production and dispatching process, and determine the state of each device based on the state parameters;

[0206] Safety monitoring subunit, used for:

[0207] Based on the time series, the state of each device is visualized in a visualization coordinate system, and the state change amplitude of each device is obtained based on the visualization;

[0208] Determine risk devices based on the state change amplitude and the reference amplitude interval, and reallocate monitoring resources of the monitoring mechanism based on the risk devices;

[0209] Based on the reallocation results, risk equipment is monitored and early warning management is carried out when a fault occurs.

[0210] In this embodiment, the state change amplitude refers to the change trend of the state of each device during the power production process.

[0211] In this embodiment, the reference amplitude range is set in advance and is a standard for measuring whether a device is a risky device and can be adjusted.

[0212] In this embodiment, the monitoring resources refer to the database or network requirements etc. required to perform the monitoring operation.

[0213] The working principle and beneficial effects of the above technical solution are: by extracting and analyzing the status parameters of each device in the process of power production and scheduling, the status of each device can be effectively determined; secondly, the status of each device is visualized in a visual coordinate system, so that the status change of each device can be effectively determined according to the visualization result, thereby facilitating the determination of risky equipment according to the status change; finally, the monitoring resources of the monitoring mechanism are reallocated, and key monitoring of risky equipment is achieved according to the reallocation results, thereby ensuring the operating stability and safety of the equipment and improving the management effect of power production.

[0214] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A cloud-native power production management system, characterized in that: include: An application deployment module, which is used to package the power production management application based on cloud native, and deploy the power production management application in a standardized container based on the packaging result; A management module, used to analyze the collected real-time power production data based on the deployment results, and to schedule power production based on the analysis results; The monitoring module is used to monitor the entire life cycle of power production based on the dispatch results, and to record and manage the monitoring results of the entire life cycle.

2. The cloud-native-based power production management system according to claim 1, characterized in that: Application deployment module, including: An application acquisition unit, used to acquire an electric power production management application, extract attribute parameters of the electric power production management application based on a background terminal, and acquire container parameters of a standardized container; An application packaging unit, used to determine a packaging strategy required for the power production management application based on the attribute parameters and the container parameters, and to package the power production management application into an application image file based on the packaging strategy; The upload unit is used to upload the application image file to the standardized container.

3. The cloud-native-based power production management system according to claim 1, characterized in that: Application deployment module, including: An application processing unit, used to parse the packaging results, extract the application structure characteristics of the power production management application, and determine the split nodes of the power production management application based on the application structure characteristics and the business execution process of the power production management application; An application splitting unit, used to split the power production management application into N microservices based on the splitting nodes, and allocate deployment resources to each microservice based on the splitting results; The application deployment unit is used to perform distributed deployment of N microservices based on deployment resources, reserve extension and update interfaces for each microservice based on the distributed deployment results, and complete the deployment of the power production management application in the standardized container based on the reserved results.

4. The cloud-native-based power production management system according to claim 3, characterized in that: Application deployment unit, including: A result acquisition subunit, used to acquire the deployment result and start the power production management application deployed in the standardized container based on the deployment result; The state monitoring subunit is used to obtain the operating state parameters of the power production management application in real time based on the startup result, and analyze the operating state parameters based on the preset state evaluation indicators to obtain the state evaluation results; The optimization subunit is used to determine the optimization direction and optimization parameters of the deployment results based on the operating status parameters when the status evaluation results do not meet the preset requirements, and optimize the deployment results based on the optimization direction and optimization parameters.

5. The cloud-native-based power production management system according to claim 3, characterized in that: Application deployment unit, including: A link opening subunit is used to obtain the deployment result of the power production management application in the standardized container, and to open a real-time interactive link with the management terminal based on the deployment result; Application Update subunit, used to: Based on the real-time interactive link, the application update request and application update target issued by the management terminal are received, and the application update target is parsed to obtain the microservice to be updated; Temporarily split and separate the deployment results of the microservice to be updated in the standardized container, and cache the upper-level processing data of the microservice to be updated based on the temporary split and separation results; At the same time, based on the temporary split, the microservices to be updated are updated independently, and based on the update results, the microservices to be updated are deployed and reset in the standardized container; The cached upper-level processing data is processed based on the deployment reset result.

6. The cloud-native-based power production management system according to claim 1, characterized in that: Management modules, including: A data collection and preparation unit, used to obtain a spatial structure distribution map of a power production scene and extract distribution characteristics of each power device in the power production scene; A parameter mapping unit, used to extract the business parameters of each power device, and map and annotate the business parameters of each power device in a spatial structure distribution diagram of a power production scene based on distribution characteristics; A location determination unit, used to obtain a business layout diagram of the power production scenario based on the mapping and annotation results, and determine the data collection dimension based on the preset power production management requirements; Data acquisition unit for: Match the data collection dimensions with the business parameters of each power device, determine the key data collection points based on the matching results, and provide installation guidance for the target sensors based on the key data collection points; Based on the installed target sensors, each power equipment is monitored in real time to obtain the corresponding real-time power production data.

7. The cloud-native-based power production management system according to claim 1, characterized in that: Management modules, including: Data pre-processing unit, used for: Performing clustering processing on the collected real-time power production data, and obtaining a multi-dimensional power data set corresponding to the real-time power production data based on the clustering processing; Traverse each dimensional power data set, and determine the existing abnormal data based on the traversal results. At the same time, extract the sample representation of each dimensional power data set, and call the target strategy from the preset cleaning strategy library based on the sample representation to clean the abnormal data, so as to obtain a multi-dimensional standard power data set; Data analysis unit for: Determine the subordinate and limiting relationship between the multi-dimensional standard power data sets based on the power production and operation protocol, and assign a corresponding weight value to each dimensional standard power data set based on the subordinate and limiting relationship; Input each dimensional standard power data set and the corresponding weight value into the power demand forecasting model, and analyze each dimensional standard power data set based on the input result to obtain the power label of the current time period; Determine the demand fluctuation characteristics of the power grid in the current time period based on the power tags, and correct the demand fluctuation characteristics based on the weight values ​​corresponding to the standard power data set of each dimension to obtain the demand trend of the power grid in the next stage, and obtain the power load demand based on the demand trend; Power production dispatching unit, used for: Analyze the performance parameters of each device in the power grid to obtain the performance range of each device. At the same time, traverse the power grid to obtain the topological structure and power flow distribution of the power grid, and obtain the line transmission capacity of the power grid based on the topological structure and power flow distribution; Based on the power load demand, the performance range of each device and the line transmission capacity of the power grid, a preliminary dispatching plan for power production is obtained, and a simulation operation is performed on the preliminary dispatching plan. Based on the simulation operation results, the preliminary dispatching plan is adjusted for loopholes to obtain the final dispatching plan; Dispatch and manage power production based on the final dispatch plan.

8. The cloud-native-based power production management system according to claim 7, characterized in that: Electricity production dispatching unit, including: The scheme acquisition subunit is used to obtain the preliminary dispatching scheme and build a virtual power production scenario in the computer based on the structural relationship between the power grid and each device; Analog subunit for: Adding the preliminary dispatching scheme in the background of the virtual power production scenario based on a computer, and simulating the dispatching of power production of the virtual power production scenario according to the preliminary dispatching scheme based on the adding result; Determine the power production status of each production node based on the simulated scheduling, and determine the potential hidden danger factors and corresponding hidden danger representations under the preliminary scheduling plan based on the power production status; The scheme adjustment subunit is used to make loophole adjustments to the preliminary scheduling scheme based on potential hidden danger factors and hidden danger representations to obtain the final scheduling scheme.

9. The cloud-native-based power production management system according to claim 1, characterized in that: Monitoring modules, including: Monitoring unit for: Obtain monitoring requirements for power production and determine monitoring dimensions and monitoring nodes based on the monitoring requirements; Configure monitoring mechanisms based on monitoring dimensions and monitoring nodes, and conduct full life cycle monitoring of the dispatching process of power production based on the monitoring mechanisms; A classification unit is used to obtain multi-dimensional dispatching parameters of power production and status parameters of each device based on the full life cycle monitoring results, and map and associate the status parameters of each device with the multi-dimensional dispatching parameters; Recording unit for: Construct a parameter record table and extract the timestamp corresponding to the full life cycle monitoring results; Based on the timestamp and mapping association results, the status parameters and multi-dimensional scheduling parameters of each device are recorded and managed in the parameter recording table.

10. The cloud-native-based power production management system according to claim 9, characterized in that: Recording unit, including: A parameter analysis subunit is used to extract the state parameters of each device in the power production and dispatching process, and determine the state of each device based on the state parameters; Safety monitoring subunit, used for: Based on the time series, the state of each device is visualized in a visualization coordinate system, and the state change amplitude of each device is obtained based on the visualization; Determine risk devices based on the state change amplitude and the reference amplitude interval, and reallocate monitoring resources of the monitoring mechanism based on the risk devices; Based on the reallocation results, risk equipment is monitored and early warning management is carried out when a fault occurs.

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