Distribution network decision analysis method and device related to container cloud platform

Abstract

The invention provides a distribution network decision analysis method and device related to a container cloud platform, and relates to the technical field of power grids. According to the method, the decision analysis request is disassembled to obtain a plurality of intermediate parameters such as power distribution network parameters, the container corresponding to the power distribution network parameters and the analysis result is determined, the computing power task architecture is constructed, the project design data is analyzed, and the analysis result is obtained. In the process, the whole calculation task is divided into multiple container calculation, the calculation time of the decision analysis task is shortened, the calculation rate of the power distribution network project design is improved, the problems that the power distribution engineering project design is difficult and low in efficiency can be solved, the analysis efficiency of the power distribution network project design is improved, and the power distribution network project design efficiency is improved. And decision analysis of design experts and review experts is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power grids, and in particular to a distribution network decision analysis method and device involving a container cloud platform. Background Art

[0002] Under the demand for digital new infrastructure, the scale of distribution network projects is getting larger and larger, and the demand for digital capabilities is becoming more and more urgent. However, there are a series of problems in the current distribution network engineering operations. The distribution network engineering operation sites are scattered, the workload is heavy, there are few management personnel, the construction personnel are highly mobile, and the supervision force is insufficient. To a certain extent, there is a lack of information technology support.

[0003] During the design phase of distribution network engineering, there are problems such as large engineering volume, short cycle, tight time, heavy tasks, and difficulty in organizing design resources. The formulation and testing and verification of key indicators requires a lot of time from design experts and review experts, especially the testing and verification process requires a lot of calculations and takes a long time, which makes the design of distribution engineering projects difficult and inefficient.

[0004] In order to improve the calculation speed and the convenience of expert processing, the distribution network engineering design tasks are often run and analyzed through the distribution network digital cloud platform. The distribution network digital cloud platform analyzes the project design data and related data, stores them on the cloud platform, and stores the decision result data in this system, which is displayed through the front end of this system for review by design experts and review experts. However, the data processing process of the distribution network digital cloud platform is sequential processing, and the single decision analysis process still takes a long time, resulting in low efficiency of distribution network decision analysis. Summary of the invention

[0005] The present invention provides a distribution network decision analysis method and device involving a container cloud platform, which can solve the problems of difficulty and low efficiency in the design of distribution engineering projects, improve the calculation rate of distribution network project design, improve the analysis efficiency of distribution network project design, and facilitate design experts and review experts to perform decision analysis.

[0006] In a first aspect, the present invention provides a distribution network decision analysis method involving a container cloud platform, the method comprising: obtaining project design data and a decision analysis request for the distribution network, the project design data including the type and equipment parameters of the equipment to be added; the decision analysis request including the analysis results to be analyzed; based on the decision analysis request, determining multiple distribution network parameters corresponding to the analysis results; the distribution network parameters are used to characterize the operating status of the distribution network; based on the distribution network parameters and the analysis results, in multiple containers of the container cloud platform, building a computing power task architecture, the computing power task architecture including multiple containers for calculating the distribution network parameters and the analysis results; based on the project design data and the computing power task architecture, calculating the analysis results to achieve distribution network decision analysis.

[0007] In a possible implementation, based on a decision analysis request, multiple distribution network parameters corresponding to the analysis results are determined, including: extracting the analysis type of the analysis result in the decision analysis request; the analysis type includes one of the following: safety analysis, power quality analysis, and implementation cost analysis; based on the analysis type, and a preset mapping relationship, multiple distribution network parameters are determined; the distribution network parameters include one or more of the following: voltage deviation, voltage imbalance rate, overvoltage frequency, frequency deviation, construction cost, and maintenance cost.

[0008] In one possible implementation, based on the distribution network parameters and the analysis results, a computing power task architecture is built in multiple containers of the container cloud platform, including: determining a target container group based on the distribution network parameters and the analysis results; the target container group includes a first container for calculating each distribution network parameter and a second container for calculating the analysis results; based on the analysis results, determining the connection relationship between each container in the target container group; and building a computing power task architecture based on the target container group and the connection relationship.

[0009] In a possible implementation, a target container group is determined based on distribution network parameters and analysis results, including: determining a computing power instance file corresponding to each distribution network parameter and a computing power instance file corresponding to the analysis result based on the distribution network parameters and the analysis result; building an operating environment in multiple new containers based on a preset operating environment image file to obtain multiple basic containers; deploying in multiple basic containers based on the computing power instance file to obtain a first container corresponding to the distribution network parameter and a second container corresponding to the analysis result; and determining a target container group based on the first container and the second container.

[0010] In a possible implementation, a computing task architecture is constructed based on a target container group and a connection relationship, including: determining an input-end container and an output-end container of the computing task architecture based on the target container group and the connection relationship; and connecting the output end of the input-end container to the input end of the output-end container to obtain the computing task architecture.

[0011] In a possible implementation, based on the project design data and the computing power task architecture, the analysis results are calculated to realize the distribution network decision analysis, including: obtaining the connection relationship between the nodes of the distribution network before the project design, and the capacity of the power generation equipment and load equipment of each node; based on the project design data, the connection relationship between the nodes of the distribution network before the project design, and the capacity of the power generation equipment and load equipment of each node, determine the computing power task file; the computing power task file is the connection relationship and equipment capacity of each node after the distribution network project is designed; the computing power task file is input into the input container of the computing power task architecture to calculate the analysis results.

[0012] In a possible implementation, the method also includes: obtaining a review computing task, the review computing task including multiple review indicators and calculation rules; generating a computing power instance file based on the calculation rules; deploying a task container corresponding to the computing task based on the computing power instance file; determining multiple containers corresponding to the review indicators based on multiple review indicators; establishing a connection relationship between the task container and the container corresponding to the review indicator, obtaining multiple review indicators for calculation, and obtaining a review result of the review computing task.

[0013] In a possible implementation, the method also includes: monitoring the computing progress of each container in the computing task architecture; determining the allocated computing resources of each container based on the computing progress of each container; and adjusting the occupied computing resources of each container based on the allocated computing resources of each container to achieve load balancing.

[0014] In a possible implementation, after the analysis results are calculated based on the project design data and the computing task architecture and the distribution network decision analysis is realized, it also includes: extracting the type, node location and equipment parameters of the equipment to be added in the project design data; determining the installation time of each equipment to be added based on the type, node location and equipment parameters of the equipment to be added, and the preset engineering efficiency; the preset engineering efficiency is used to characterize the installation progress of the equipment to be added within a unit time; based on the installation time of each equipment to be added and the preset engineering configuration, determine the project implementation plan, which includes the implementation period of each equipment to be added, and the personnel and machinery conditions allocated to each equipment to be added.

[0015] In the second aspect, an embodiment of the present invention provides a distribution network decision analysis device involving a container cloud platform, the device comprising: a communication module, used to obtain project design data and decision analysis requests of the distribution network, the project design data including the type and equipment parameters of the equipment to be added; the decision analysis request including the analysis results to be analyzed; a task analysis module, used to determine multiple distribution network parameters corresponding to the analysis results based on the decision analysis request; the distribution network parameters are used to characterize the operating status of the distribution network; the decision analysis module, used to build a computing task architecture in multiple containers of the container cloud platform based on the distribution network parameters and the analysis results, the computing task architecture including multiple containers for calculating the distribution network parameters and analysis results; based on the project design data and the computing task architecture, the analysis results are calculated to realize the distribution network decision analysis.

[0016] In a possible implementation, the task analysis module is specifically used to extract the analysis type of the analysis result in the decision analysis request; the analysis type includes one of the following: safety analysis, power quality analysis and implementation cost analysis; based on the analysis type and a preset mapping relationship, multiple distribution network parameters are determined; the distribution network parameters include one or more of the following: voltage deviation, voltage imbalance rate, overvoltage frequency, frequency deviation, construction cost and maintenance cost.

[0017] In a possible implementation, the decision analysis module is specifically used to determine a target container group based on distribution network parameters and analysis results; the target container group includes a first container for calculating each distribution network parameter and a second container for calculating the analysis results; based on the analysis results, the connection relationship between each container in the target container group is determined; based on the target container group and the connection relationship, a computing power task architecture is built.

[0018] In a possible implementation, the decision analysis module is specifically used to determine, based on the distribution network parameters and the analysis results, a computing power instance file corresponding to each distribution network parameter and a computing power instance file corresponding to the analysis result; based on a preset operating environment image file, build an operating environment in multiple new containers to obtain multiple basic containers; based on the computing power instance file, deploy in multiple basic containers to obtain a first container corresponding to the distribution network parameter and a second container corresponding to the analysis result; based on the first container and the second container, determine the target container group.

[0019] In a possible implementation, the decision analysis module is specifically used to determine the input container and the output container of the computing power task architecture based on the target container group and the connection relationship; the output end of the input container is connected to the input end of the output container to obtain the computing power task architecture.

[0020] In a possible implementation, the decision analysis module is specifically used to obtain the connection relationship between each node of the distribution network before the project design, and the capacity of the power generation equipment and load equipment of each node; based on the project design data, the connection relationship between each node of the distribution network before the project design, and the capacity of the power generation equipment and load equipment of each node, determine the computing power task file; the computing power task file is the connection relationship and equipment capacity of each node after the distribution network project is designed; the computing power task file is input into the input container of the computing power task architecture, and the analysis result is calculated.

[0021] In a possible implementation, the communication module is also used to obtain a review computing task, which includes multiple review indicators and calculation rules; the decision analysis module is also used to generate a computing power instance file based on the calculation rules; based on the computing power instance file, a task container corresponding to the computing task is deployed; based on multiple review indicators, multiple containers corresponding to the review indicators are determined; a connection relationship is established between the task container and the container corresponding to the review indicator, multiple review indicators are obtained for calculation, and the review result of the review computing task is obtained.

[0022] In a possible implementation, the communication module is also used to monitor the computing progress of each container in the computing task architecture; the decision analysis module is also used to determine the allocated computing resources of each container based on the computing progress of each container; based on the allocated computing resources of each container, the occupied computing resources of each container are adjusted to achieve load balancing.

[0023] In a possible implementation, the decision analysis module is also used to extract the type, node location and equipment parameters of the equipment to be added in the project design data; based on the type, node location and equipment parameters of the equipment to be added, and the preset engineering efficiency, determine the installation time of each equipment to be added; the preset engineering efficiency is used to characterize the installation progress of the equipment to be added within a unit time; based on the installation time of each equipment to be added, and the preset engineering configuration, determine the project implementation plan, which includes the implementation period of each equipment to be added, and the personnel and machinery conditions allocated to each equipment to be added.

[0024] The present invention provides a distribution network decision analysis method and device involving a container cloud platform. The present invention disassembles the decision analysis request to obtain intermediate parameters such as multiple distribution network parameters, and determines the container corresponding to the distribution network parameters and the analysis results, constructs a computing task architecture, analyzes the project design data, and obtains the analysis results. In this process, the present invention splits the entire calculation task into multiple container calculations, reduces the calculation time of the decision analysis task, and improves the calculation rate of the distribution network project design. It can solve the problems of difficulty and low efficiency in the design of distribution engineering projects, improve the analysis efficiency of the distribution network project design, and facilitate design experts and review experts to perform decision analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0026] Figure 1It is a flow chart of a network configuration decision analysis method involving a container cloud platform provided by an embodiment of the present invention;

[0027] Figure 2 It is a structural diagram of a network distribution decision analysis device involving a container cloud platform provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0029] In the description of the present invention, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, "at least one" and "plurality" refer to two or more. The words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not limit them to be different.

[0030] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0031] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of this application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not limited to the listed steps or modules, but may optionally include other steps or modules that are not listed, or may optionally include other steps or modules that are inherent to these processes, methods, products or devices.

[0032] In order to make the purpose, technical solutions and advantages of the present invention more clear, the following will be described through specific embodiments in conjunction with the accompanying drawings of the present invention.

[0033] As described in the background technology, there are technical problems in the current design process of power distribution engineering projects, such as consuming a lot of time of design experts and review experts, taking a long time to calculate, and making the design of power distribution engineering projects difficult and inefficient.

[0034] To solve the above technical problems, Figure 1 As shown, an embodiment of the present invention provides a network configuration decision analysis method involving a container cloud platform. The method includes steps S101-S104.

[0035] S101. Obtain project design data and decision analysis request for distribution network.

[0036] In the embodiment of the present application, the project design data includes the type and equipment parameters of the equipment to be added; the decision analysis request includes the analysis results that need to be analyzed.

[0037] S102: Based on the decision analysis request, determine a plurality of distribution network parameters corresponding to the analysis results.

[0038] In the embodiment of the present application, the distribution network parameters are used to characterize the operating status of the distribution network.

[0039] In some embodiments, the distribution network parameters include one or more of the following: voltage deviation, voltage imbalance rate, overvoltage frequency, frequency deviation, construction cost, and maintenance cost.

[0040] In some embodiments, the distribution network parameters also include power supply capacity, grid structure, utilization efficiency, equipment level and power supply quality.

[0041] Exemplarily, power supply capacity includes average distribution transformer capacity per household, conductor cross-section ratio, distribution transformer capacity-load ratio, distributed power source penetration rate and access capacity, and controllable load access scale.

[0042] For example, the average household distribution transformer capacity reflects the power supply capacity of the power grid distribution transformer capacity in a certain area for the load. Average household distribution transformer capacity = total distribution transformer capacity / number of users × 100%. Among them, the number of users refers to the number of low-voltage residential users.

[0043] For example, the conductor cross-section ratio mainly reflects the standardization of the line conductor cross-section. 2 The following overhead lines account for 70mm 2 The following overhead line length (km) / total overhead line length (km) x 100%. 185mm 2 The following cable lines account for 185mm 2 The following is cable line length (km) / total cable line length (km) × 100%.

[0044] For example, the distribution transformer capacity-to-load ratio reflects the overall power supply capacity of the distribution transformer capacity of a certain area of ​​the power grid for the load. It is the ratio of the total distribution transformer capacity input at a certain moment in the evaluation area to the corresponding load.

[0045] For example, the statistical caliber of the distributed power penetration rate and access capacity is the distributed power penetration rate of the distribution network where it is connected, as well as the capacity of distributed wind power, photovoltaic power, and small hydropower. Distributed power penetration rate = distributed power supply / power consumption in the distribution network area × 100%.

[0046] For example, the statistical scope of the controllable load access scale is the total scale of controllable load in the distribution network where it is accessed.

[0047] Exemplarily, the grid structure includes the 10 kV grid interconnection rate, the 10 kV N-1 passing rate, the typical wiring ratio and the average power supply radius of the line.

[0048] For example, the interconnection rate of a 10 kV power grid can be calculated as follows: 10(20) kV power grid interconnection rate (%) = number of 10(20) kV lines that meet the interconnection structure / total number of 10(20) kV lines

[0049] For example, the 10 kV N-1 pass rate can be calculated as follows: 10 kV power grid N-1 pass rate (%) = number of lines that meet N-1 / total number of lines. When calculating the N-1 pass rate, the transfer capacity of the current and next level power grids should be considered.

[0050] For example, the proportion of typical connections reflects the distribution of various typical connections. The overhead network separately counts the proportion of single-connection, multi-connection, and radial connections. The cable network separately counts the proportion of double-ring network, single-ring network, double-injection, and single-injection, and the proportion of various typical connection methods. The proportion of single-radial connection in a certain type of supply area at a certain voltage level = (the number of single-radial connection lines in this type of supply area at this voltage level / the total number of lines in this type of supply area at this voltage level) × 100%.

[0051] For example, the average power supply radius of the line reflects the improvement effect of the average power supply radius of the 10 kV line classification supply area. The average power supply radius of the 10 kV line is the average value of the power supply radius of the 10 kV line. The power supply radius of a certain type of supply area of ​​the 10 kV line refers to the line length from the low-voltage side of the substation (distribution transformer) to the farthest load point of its power supply.

[0052] Exemplarily, the utilization efficiency includes line utilization efficiency, distribution transformer utilization efficiency, and line loss rate of distribution networks of 10 kV and below.

[0053] For example, the line utilization efficiency can be calculated as follows: 10 kV line maximum load rate (%) = line maximum operating current (A) / line long-term allowable current carrying capacity (A) Line maximum load rate = line maximum load on the maximum load day / line trunk continuous transmission capacity.

[0054] The maximum load rate distribution of 10 kV lines is divided into five levels: above 80%, 80-60%, 60-40%, 40-20% and below 20%, and the proportion of lines is counted.

[0055] For example, the utilization efficiency of distribution transformers can be calculated as follows: Annual maximum load rate of distribution transformer (%) = Annual maximum load of distribution transformer (10,000 kW) / Distribution transformer capacity (10,000 kVA). The maximum load rate distribution of 10 kV distribution transformers is divided into five levels: above 80%, 80-60%, 60-40%, 40-20% and below 20%, and the proportion of lines is calculated. Annual average operating load rate of 10 kV distribution transformers: Annual equivalent average operating load rate of distribution transformers (%) = Annual power supply of regional distribution network / (distribution transformer capacity × 8760). Line loss rate of 10 kV and below distribution networks = (input power - output power) / input power. Input power: 10 kV voltage level power plant grid-connected power + other voltage level transfer-in power. Output power: 10 kV and below power sales + other voltage level transfer-out power.

[0056] Exemplarily, the equipment level includes the distribution of operating years of equipment (distribution transformers, lines), the proportion of high-loss distribution transformers, and the coverage rate of smart meters.

[0057] For example, the distribution of equipment (distribution transformers, lines) operating years indicates the operating time of the equipment from the year of commissioning to the statistical year. The equipment mainly includes transformers and lines. Transformers are counted by the proportion of units (excluding user transformers), and lines are counted by the proportion of length. This indicator describes the age of the main equipment assets of the power grid. This indicator is counted in three sections: less than 10 years, 10-20 years, and more than 20 years.

[0058] For example, the proportion of high-loss distribution transformers refers to the proportion of the number of S7 (S8) and below distribution transformers in the 10 (20) kV public distribution transformers to the total number of public distribution transformers. The proportion of S7 (S8) and below distribution transformers (%) = the number of S7 (S8) and below distribution transformers (units) / the total number of distribution transformers (units) × 100%.

[0059] For example, the smart meter coverage rate reflects the coverage of smart meters in the region. Smart meter coverage rate = number of smart meters / total number of meters.

[0060] Exemplarily, the power supply quality includes the proportion of low-voltage households, power supply reliability rate, comprehensive voltage compliance rate and 10 kV line fault tripping conditions of each power supply station.

[0061] For example, the proportion of low-voltage households = the number of low-voltage users (households) in the region / the number of low-voltage users (households) in the region.

[0062] For example, the power supply reliability rate (RS-3) does not take into account the situation where power is limited due to insufficient system power supply.

[0063] For example, the comprehensive voltage qualification rate is applicable to distribution networks at all levels, and is divided into four categories: A, B, C, and D. Among them, the Class A voltage qualification rate is the 10 kV bus voltage qualification rate of substations and power plants with regional power supply loads; the Class B voltage qualification rate is the user-end voltage qualification rate of 35 kV, 66 kV dedicated power supply and 110 kV and above power supply; the Class C voltage qualification rate is the voltage qualification rate of users at the end of 10 kV lines; the Class D voltage qualification rate is the voltage qualification rate of the head and end of the low-voltage distribution network and some major users. According to the different voltage levels of the distribution network, the high-voltage distribution network adopts the Class A and B voltage qualification rates; the medium and low voltage distribution network adopts the Class C and D voltage qualification rates.

[0064] For example, the fault and tripping of the 10 kV lines of each power supply station, statistics on frequent tripping of 10 kV lines in the entire county, each power supply section, and power supply station, the number of power outages and other indicators.

[0065] As a possible implementation manner, the embodiment of the present invention can calculate multiple distribution network parameters based on steps S1021-S1022.

[0066] S1021. Extract the analysis type of the analysis result in the decision analysis request.

[0067] In some embodiments, the analysis type includes one of: a safety analysis, a power quality analysis, and an implementation cost analysis.

[0068] S1022. Determine multiple distribution network parameters based on the analysis type and preset mapping relationship.

[0069] S103. Based on the distribution network parameters and analysis results, a computing task architecture is built in multiple containers of the container cloud platform.

[0070] In an embodiment of the present application, the computing task architecture includes multiple containers for calculating distribution network parameters and analyzing results.

[0071] As a possible implementation method, the embodiment of the present invention can build a computing task architecture based on steps S1031-S1033.

[0072] S1031. Determine the target container group based on the distribution network parameters and analysis results.

[0073] In some embodiments, the target container group includes a first container for calculating each power distribution network parameter and a second container for calculating the analysis result.

[0074] Illustratively, the embodiment of the present invention may determine the target container group based on steps A1-A4.

[0075] A1. Based on the distribution network parameters and analysis results, determine the computing power instance file corresponding to each distribution network parameter and the computing power instance file corresponding to the analysis results.

[0076] A2. Based on the preset operating environment image file, build the operating environment in multiple new containers to obtain multiple basic containers.

[0077] A3. Based on the computing power instance file, deployment is performed in multiple basic containers to obtain a first container corresponding to the distribution network parameters and a second container corresponding to the analysis results.

[0078] A4. Determine a target container group based on the first container and the second container.

[0079] S1032. Determine the connection relationship between the containers in the target container group based on the analysis result;

[0080] S1033. Build a computing task architecture based on the target container group and connection relationship.

[0081] Exemplarily, an embodiment of the present invention can build a computing task architecture based on steps B1-B2.

[0082] B1. Based on the target container group and connection relationship, determine the input container and output container of the computing task architecture.

[0083] B2. Connect the output end of the input-end container to the input end of the output-end container to obtain the computing task architecture.

[0084] S104. Based on the project design data and computing task architecture, the analysis results are calculated to achieve distribution network decision analysis.

[0085] As a possible implementation manner, step S104 may be specifically implemented as step S1041 to step S1043.

[0086] S1041. Obtain the connection relationship between the nodes of the distribution network before project design, as well as the capacity of the power generation equipment and load equipment of each node.

[0087] S1042. Determine the computing task file based on the project design data, the connection relationship between the nodes of the distribution network before the project design, and the capacity of the power generation equipment and load equipment of each node.

[0088] In some embodiments, the computing power task file is the connection relationship and equipment capacity of each node after the distribution network project is designed.

[0089] S1043. Input the computing task file into the input container of the computing task architecture, and calculate to obtain the analysis result.

[0090] The present invention provides a distribution network decision analysis method involving a container cloud platform, which disassembles a decision analysis request to obtain intermediate parameters such as multiple distribution network parameters, determines containers corresponding to the distribution network parameters and analysis results, constructs a computing task architecture, analyzes project design data, and obtains analysis results. In this process, the present invention splits the entire computing task into multiple container calculations, reduces the computing time of the decision analysis task, and improves the computing rate of the distribution network project design, which can solve the problems of difficulty and low efficiency in the design of distribution engineering projects, improve the analysis efficiency of the distribution network project design, and facilitates design experts and review experts to perform decision analysis.

[0091] Optionally, the network configuration decision analysis method involving a container cloud platform provided in an embodiment of the present invention further includes steps S201-S205.

[0092] S201. Obtain review calculation tasks.

[0093] In some embodiments, the review calculation task includes multiple review indicators and calculation rules.

[0094] S202: Generate a computing power instance file based on the calculation rules.

[0095] S203: Based on the computing power instance file, a task container corresponding to the computing task is deployed.

[0096] S204: Based on the multiple review indicators, determine multiple containers corresponding to the review indicators.

[0097] S205: Establish a connection relationship between the task container and the container corresponding to the review indicator, obtain multiple review indicators for calculation, and obtain the review result of the review calculation task.

[0098] In this way, the embodiment of the present invention can receive review calculation tasks from design experts and review experts, establish containers in real time to perform calculations for the review calculation tasks, obtain review results, improve the convenience of the distribution network decision analysis process, and improve the analysis efficiency of the distribution network decision analysis.

[0099] Optionally, the network configuration decision analysis method involving a container cloud platform provided in an embodiment of the present invention further includes steps S301-S303.

[0100] S301. Monitor the computing progress of each container in the computing task architecture.

[0101] S302: Determine the allocated computing resources for each container based on the computing progress of each container.

[0102] S303: Based on the allocated computing resources of each container, the occupied computing resources of each container are adjusted to achieve load balancing.

[0103] In this way, the embodiment of the present invention can monitor the computing progress of each container in the computing task architecture, adjust the allocated resources of each container based on the computing progress, achieve computing resource balance, and improve the analysis efficiency of distribution network decision analysis.

[0104] Optionally, the network configuration decision analysis method involving a container cloud platform provided in an embodiment of the present invention further includes steps S401-S403.

[0105] S401, extracting the type, node location and equipment parameters of the equipment to be added in the project design data;

[0106] S402: Determine the installation time of each device to be added based on the type, node location and device parameters of the device to be added, as well as the preset engineering efficiency.

[0107] In some embodiments, the preset engineering efficiency is used to characterize the installation progress of the equipment to be added within a unit time.

[0108] S403: Determine the project implementation plan based on the installation time of each device to be added and the preset engineering configuration.

[0109] In some embodiments, the engineering configuration includes the personnel and machinery to be assigned, wherein the personnel and machinery are used to install the equipment to be added.

[0110] In some embodiments, the implementation plan includes the implementation period of each equipment to be added, and the personnel and machinery conditions assigned to each equipment to be added.

[0111] In this way, the embodiment of the present invention can calculate the real-time status of the project of the equipment to be added by presetting the project efficiency and project configuration, determine the project implementation plan, and improve the convenience of distribution network decision-making analysis.

[0112] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0113] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0114] Figure 2 The schematic diagram of the structure of a network configuration decision analysis device involving a container cloud platform provided by an embodiment of the present invention is shown. The analysis device 500 includes a communication module 501, a task analysis module 502 and a decision analysis module 503.

[0115] The communication module 501 is used to obtain the project design data and decision analysis request of the distribution network, the project design data includes the type and equipment parameters of the equipment to be added. The decision analysis request includes the analysis results to be obtained;

[0116] The task analysis module 502 is used to determine a plurality of distribution network parameters corresponding to the analysis results based on the decision analysis request; the distribution network parameters are used to characterize the operating status of the distribution network.

[0117] The decision analysis module 503 is used to build a computing task architecture in multiple containers of the container cloud platform based on the distribution network parameters and the analysis results. The computing task architecture includes multiple containers for calculating the distribution network parameters and the analysis results; based on the project design data and the computing task architecture, the analysis results are calculated to realize the distribution network decision analysis.

[0118] In one possible implementation, the task analysis module 502 is specifically used to extract the analysis type of the analysis result in the decision analysis request; the analysis type includes one of the following: safety analysis, power quality analysis and implementation cost analysis; based on the analysis type and a preset mapping relationship, multiple distribution network parameters are determined; the distribution network parameters include one or more of the following: voltage deviation, voltage imbalance rate, overvoltage frequency, frequency deviation, construction cost and maintenance cost.

[0119] In a possible implementation, the decision analysis module 503 is specifically used to determine a target container group based on distribution network parameters and analysis results; the target container group includes a first container for calculating each distribution network parameter and a second container for calculating the analysis results; based on the analysis results, the connection relationship between each container in the target container group is determined; based on the target container group and the connection relationship, a computing task architecture is built.

[0120] In a possible implementation, the decision analysis module 503 is specifically used to determine, based on the distribution network parameters and the analysis results, a computing power instance file corresponding to each distribution network parameter and a computing power instance file corresponding to the analysis result; based on a preset operating environment image file, build an operating environment in multiple new containers to obtain multiple basic containers; based on the computing power instance file, deploy in multiple basic containers to obtain a first container corresponding to the distribution network parameter and a second container corresponding to the analysis result; based on the first container and the second container, determine the target container group.

[0121] In one possible implementation, the decision analysis module 503 is specifically used to determine the input container and the output container of the computing power task architecture based on the target container group and the connection relationship; the output end of the input container is connected to the input end of the output container to obtain the computing power task architecture.

[0122] In one possible implementation, the decision analysis module 503 is specifically used to obtain the connection relationship between the nodes of the distribution network before the project design, and the capacity of the power generation equipment and load equipment of each node; based on the project design data, the connection relationship between the nodes of the distribution network before the project design, and the capacity of the power generation equipment and load equipment of each node, determine the computing power task file; the computing power task file is the connection relationship and equipment capacity of each node after the distribution network project is designed; the computing power task file is input into the input container of the computing power task architecture, and the analysis result is calculated.

[0123] In one possible implementation, the communication module 501 is also used to obtain a review computing task, which includes multiple review indicators and calculation rules; the decision analysis module 503 is also used to generate a computing power instance file based on the calculation rules; based on the computing power instance file, deploy a task container corresponding to the computing task; based on multiple review indicators, determine multiple containers corresponding to the review indicators; establish a connection relationship between the task container and the container corresponding to the review indicator, obtain multiple review indicators for calculation, and obtain the review result of the review computing task.

[0124] In one possible implementation, the communication module 501 is also used to monitor the computing progress of each container in the computing task architecture; the decision analysis module 503 is also used to determine the allocated computing resources of each container based on the computing progress of each container; based on the allocated computing resources of each container, the occupied computing resources of each container are adjusted to achieve load balancing.

[0125] In a possible implementation, the decision analysis module 503 is also used to extract the type, node location and equipment parameters of the equipment to be added in the project design data; based on the type, node location and equipment parameters of the equipment to be added, and the preset engineering efficiency, determine the installation time of each equipment to be added; the preset engineering efficiency is used to characterize the installation progress of the equipment to be added within a unit time; based on the installation time of each equipment to be added, and the preset engineering configuration, determine the project implementation plan, the implementation plan includes the implementation period of each equipment to be added, and the personnel and machinery conditions allocated to each equipment to be added.

[0126] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A network configuration decision analysis method involving a container cloud platform, characterized in that: include: Obtaining project design data and decision analysis requests for the distribution network, wherein the project design data includes the type and equipment parameters of the equipment to be added; The decision analysis request includes the analysis result to be obtained by analysis; Based on the decision analysis request, determining a plurality of distribution network parameters corresponding to the analysis result; the distribution network parameters are used to characterize the operating state of the distribution network; Based on the distribution network parameters and the analysis results, a computing task architecture is built in multiple containers of the container cloud platform, wherein the computing task architecture includes multiple containers for calculating the distribution network parameters and the analysis results; Based on the project design data and the computing power task architecture, the analysis results are calculated to achieve distribution network decision analysis.

2. The network configuration decision analysis method involving the container cloud platform according to claim 1 is characterized in that: The determining, based on the decision analysis request, a plurality of distribution network parameters corresponding to the analysis result comprises: Extracting the analysis type of the analysis result in the decision analysis request; the analysis type includes one of the following: safety analysis, power quality analysis and implementation cost analysis; Based on the analysis type and the preset mapping relationship, the multiple distribution network parameters are determined; the distribution network parameters include one or more of the following: voltage deviation, voltage imbalance rate, overvoltage frequency, frequency deviation, construction cost and maintenance cost.

3. The network configuration decision analysis method involving the container cloud platform according to claim 1 is characterized in that: The step of building a computing task architecture in multiple containers of a container cloud platform based on the distribution network parameters and the analysis results includes: Based on the distribution network parameters and the analysis results, a target container group is determined; the target container group includes a first container for calculating each distribution network parameter and a second container for calculating the analysis results; Based on the analysis result, determining the connection relationship between the containers in the target container group; Based on the target container group and the connection relationship, the computing task architecture is constructed.

4. The network configuration decision analysis method involving the container cloud platform according to claim 3 is characterized in that: The determining of the target container group based on the distribution network parameter and the analysis result includes: Based on the distribution network parameters and the analysis results, determining a computing power instance file corresponding to each distribution network parameter and a computing power instance file corresponding to the analysis result; Based on the preset operating environment image file, build the operating environment in multiple new containers to obtain multiple basic containers; Based on the computing power instance file, deploy in the multiple basic containers to obtain a first container corresponding to the distribution network parameter and a second container corresponding to the analysis result; The target container group is determined based on the first container and the second container.

5. The network configuration decision analysis method involving the container cloud platform according to claim 3 is characterized in that: The step of building the computing task architecture based on the target container group and the connection relationship includes: Based on the target container group and the connection relationship, determine the input-end container and the output-end container of the computing task architecture; The output end of the input end container is connected to the input end of the output end container to obtain the computing task architecture.

6. The network configuration decision analysis method involving the container cloud platform according to claim 1 is characterized in that: The step of calculating the analysis result based on the project design data and the computing power task architecture to implement the distribution network decision analysis includes: Obtain the connection relationship between the nodes of the distribution network mentioned before the project design, as well as the capacity of the power generation equipment and load equipment of each node; Based on the project design data, the connection relationship between the nodes of the distribution network before the project design, and the capacity of the power generation equipment and load equipment of each node, a computing power task file is determined; the computing power task file is the connection relationship and equipment capacity of each node after the distribution network project is designed; The computing task file is input into the input end container of the computing task architecture, and the analysis result is obtained by calculation.

7. The network configuration decision analysis method involving the container cloud platform according to claim 1 is characterized in that: The method further comprises: Obtaining a review calculation task, wherein the review calculation task includes a plurality of review indicators and calculation rules; Based on the calculation rules, generate a computing power instance file; Based on the computing power instance file, deploy a task container corresponding to the computing task; Based on the multiple review indicators, determining multiple containers corresponding to the review indicators; A connection relationship is established between the task container and the container corresponding to the review indicator, and multiple review indicators are obtained for calculation to obtain the review result of the review calculation task.

8. The network configuration decision analysis method involving the container cloud platform according to claim 1 is characterized in that: The method further comprises: Monitor the computing progress of each container in the computing task architecture; Determining the allocated computing resources for each container based on the computing progress of each container; Based on the allocated computing resources of each container, the occupied computing resources of each container are adjusted to achieve load balancing.

9. The network configuration decision analysis method involving the container cloud platform according to claim 1 is characterized in that: After the analysis result is calculated based on the project design data and the computing task architecture to implement the distribution network decision analysis, the method further includes: Extracting the type, node location and equipment parameters of the equipment to be added from the project design data; Determine the installation time of each device to be added based on the type, node location and device parameters of the device to be added, and the preset engineering efficiency; the preset engineering efficiency is used to characterize the installation progress of the device to be added within a unit time; Based on the installation time of each equipment to be added and the preset engineering configuration, the project implementation plan is determined, which includes the implementation period of each equipment to be added and the personnel and machinery conditions allocated to each equipment to be added.

10. A network distribution decision analysis device involving a container cloud platform, characterized in that: include: A communication module, used to obtain project design data and decision analysis requests for the distribution network, wherein the project design data includes the type and equipment parameters of the equipment to be added; The decision analysis request includes the analysis result to be obtained by analysis; A task analysis module, used to determine a plurality of distribution network parameters corresponding to the analysis result based on the decision analysis request; the distribution network parameters are used to characterize the operating state of the distribution network; A decision analysis module, used to build a computing task architecture in multiple containers of the container cloud platform based on the distribution network parameters and the analysis results, wherein the computing task architecture includes multiple containers for calculating the distribution network parameters and the analysis results; Based on the project design data and the computing power task architecture, the analysis results are calculated to achieve distribution network decision analysis.

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