Power distribution network output determination method and device, computer equipment and storage medium

Abstract

The invention relates to a power distribution network output determination method and device, computer equipment and a storage medium. The method comprises the steps of obtaining operation state data and planning project output evaluation indexes of the power distribution network, evaluating each planning project of the power distribution network based on the planning project output evaluation indexes, determining output data of each planning project, and taking the operation state data of the power distribution network and the output data of each planning project as input, a trained power distribution network output model is called, output data of the power distribution network are determined, and the power distribution network output model is obtained through training based on the historical operation state data and the historical project output data. By adopting the method, the output evaluation accuracy of the power distribution network can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of distribution network planning, and in particular to a method, apparatus, computer equipment, storage medium and computer program product for determining distribution network output. Background Art

[0002] Power grid companies are important enterprises that are related to national economy, people's livelihood and energy security. In recent years, with the continuous advancement of the "dual carbon" work, the number of projects undertaken by power grid companies has gradually increased. However, due to the complex network characteristics of the power grid and the input-output relationship, the output of the distribution network is difficult to evaluate.

[0003] When evaluating the output of distribution networks, traditional solutions often simply focus on different projects in the distribution network and evaluate the impact of projects on the output of the grid from the financial indicators within the grid company. For example, by calculating the net present value of the project, the project's contribution to the output of the distribution network at the economic level is judged.

[0004] However, the distribution network is a complex network system. Different projects may have mutual impacts during implementation. Traditional solutions that simply rely on the financial indicators of each project may result in inaccurate distribution network output data obtained through analysis. Summary of the invention

[0005] Based on this, it is necessary to provide a distribution network output determination method, device, computer equipment, computer-readable storage medium and computer program product that can improve the accuracy of distribution network output evaluation in response to the above technical problems.

[0006] In a first aspect, the present application provides a method for determining output of a distribution network. The method comprises:

[0007] Obtain the operating status data of the distribution network and the output evaluation indicators of the planned projects;

[0008] Based on the output evaluation index of the planned project, evaluate each planned project of the distribution network and determine the output data of each planned project;

[0009] Taking the operation status data of the distribution network and the output data of each of the planned projects as input, calling the trained distribution network output model to determine the output data of the distribution network;

[0010] The distribution network output model is trained based on historical operation status data and historical project output data.

[0011] In one embodiment, after determining the output data of the distribution network, the method further includes:

[0012] Obtaining resource input data of the distribution network;

[0013] Determining resource return data of the distribution network and resource return data of each of the planned projects according to the output data of the distribution network and the resource input data;

[0014] Based on the resource return data of the distribution network and the resource return data of each of the planned projects, the planned projects of the distribution network are adjusted.

[0015] In one embodiment, adjusting the planned projects of the distribution network based on the resource return data of the distribution network and the resource return data of each of the planned projects includes:

[0016] The priority of each of the planned projects is determined according to the resource return data of each of the planned projects.

[0017] With the goal of maximizing the resource return data of the distribution network, the planning projects of the distribution network are adjusted according to the priority of each planning project.

[0018] In one embodiment, the step of obtaining the output evaluation index of the planned project of the distribution network includes:

[0019] Obtain multiple distribution network output evaluation indicators;

[0020] The output evaluation indicators of each distribution network are disassembled to determine the output evaluation indicators of the planned projects of the distribution network.

[0021] In one embodiment, the output evaluation index of the distribution network includes the power supply rate of the distribution network, the feeder automation coverage rate, the overload distribution transformer ratio, and the proportion of public substations with low voltage; the output evaluation index of each distribution network is disassembled to obtain the output evaluation index of the planning project of the distribution network, including:

[0022] Decomposing the distribution network transferable power supply rate into the number of newly added transferable power supply lines;

[0023] Decomposing the feeder automation coverage rate into the number of newly added lines of the automated covered feeder;

[0024] Decomposing the overload distribution transformer ratio into the number of overload distribution transformers to be solved;

[0025] Decomposing the proportion of public transformer areas with low voltage into the number of public transformer areas with low voltage to be solved;

[0026] The output evaluation indicators of the planning project include the number of newly added convertible power supply lines, the number of newly added lines with automated coverage of feeders, the number of overloaded distribution transformers resolved, and the number of public substations with low voltage resolved.

[0027] In a second aspect, the present application also provides a device for determining output of a distribution network. The device comprises:

[0028] Data acquisition module, used to obtain the operating status data of the distribution network and the output evaluation indicators of the planning project;

[0029] A project evaluation module, which evaluates each planned project of the distribution network based on the planned project output evaluation index and determines the output data of each planned project;

[0030] An output evaluation module, used to take the operation status data of the distribution network and the output data of each of the planned projects as input, call the trained distribution network output model, and determine the output data of the distribution network;

[0031] The distribution network output model is trained based on historical operation status data and historical project output data.

[0032] In a third aspect, the present application further provides a computer device, wherein the computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps in the above-mentioned distribution network output determination method embodiment are implemented.

[0033] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in the above-mentioned method for determining the output of a power distribution network are implemented.

[0034] In a fifth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method for determining the output of a power distribution network are implemented.

[0035] The above-mentioned distribution network output determination method, device, computer equipment, storage medium and computer program product are different from the traditional scheme of unilaterally evaluating the power grid output based on financial indicators. This scheme obtains the operating status data of the distribution network and the output evaluation indicators of the planned projects, and first analyzes each planned project based on the output evaluation indicators of the planned projects, and then inputs the actual operating status data of the distribution network and the output data of each planned project into the trained distribution network output model. Since the distribution network output model is trained based on historical operating status data and historical project output data, the distribution network output model can comprehensively analyze the actual operating status data of the distribution network and the output data of each planned project, and simulate the comprehensive output of the entire distribution network system after the implementation of these planned projects, so as to more scientifically and accurately determine the output data of the distribution network and improve the accuracy of evaluating the distribution network output. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 An application environment diagram of a method for determining output of a distribution network in one embodiment;

[0037] Figure 2 A schematic diagram of a flow chart of a method for determining output of a distribution network in one embodiment;

[0038] Figure 3 Another is a flow chart of a method for determining output of a distribution network in an embodiment;

[0039] Figure 4 A schematic diagram of a process for adjusting a planning project of a power distribution network in one embodiment;

[0040] Figure 5 It is also a flow chart of a method for determining output of a distribution network in one embodiment;

[0041] Figure 6 A schematic diagram of a flow chart of a method for determining output of a distribution network in an embodiment is shown below;

[0042] Figure 7 A schematic diagram of a flow chart of a method for determining output of a distribution network in a detailed embodiment;

[0043] Figure 8 It is a structural block diagram of a device for determining output of a distribution network in one embodiment;

[0044] Fig. 9 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0046] The method for determining the output of a distribution network provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the server 104 through a network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or placed on the cloud or other network servers.

[0047] Specifically, the staff of the distribution network may upload the operating status data of the distribution network and the output evaluation indicators of the planned projects to the server 104 through the terminal 102, and then the server 104 evaluates each planned project of the distribution network based on the output evaluation indicators of the planned projects, and determines the output data of each planned project. Furthermore, the server 104 takes the operating status data of the distribution network and the output data of each planned project as input, calls the distribution network output model pre-stored in the data storage system, and determines the output data, wherein the distribution network output model is trained based on historical operating status data and historical project output data.

[0048] The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0049] In one embodiment, Figure 2 As shown, a method for determining the output of a distribution network is provided, and the method is applied to Figure 1 Taking the server 104 in the example as an example, the following steps are included:

[0050] S100, obtaining the operation status data of the distribution network and the output evaluation index of the planning project.

[0051] The operating status data of the distribution network includes, but is not limited to, the voltage amplitude and phase angle information of each node in the distribution network, the real-time current size and power flow direction of different lines, and the working power and working time of different power equipment. Planning projects refer to projects proposed to meet the long-term development planning needs of the distribution network, aiming to improve the performance of the distribution network in many aspects such as power supply capacity, power supply quality, reliability, and new energy absorption capacity. Planning project output evaluation indicators are indicators used to measure the contribution to the development of the distribution network after the implementation of the planning project, such as measuring how much the distribution network can increase power supply and how much new energy absorption can be increased after the implementation of the planning project.

[0052] Specifically, the operating status data of the distribution network can be collected through the power grid monitoring system, which is equipped with a large number of sensors distributed in key locations such as substations, lines, and switchgear. For example, current transformers and voltage transformers can monitor the current and voltage amplitude in the line in real time.

[0053] S200, based on the output evaluation index of the planning project, evaluate each planning project of the distribution network and determine the output data of each planning project.

[0054] Among them, the output evaluation indicators of the planning project include but are not limited to the number of newly added convertible power supply lines, the number of newly added lines with automated coverage of feeders, the number of overloaded distribution transformers resolved, and the number of public substations with low voltage resolved.

[0055] Specifically, a transferable power supply line refers to a line to which the power supply load can be transferred when a line fails or needs maintenance. The more new transferable power supply lines are added, the greater the power supply flexibility and reliability of the distribution network. Specifically, before the implementation of the planning project, the number of existing lines with transfer power supply capacity can be sorted out through the power grid topology map, operation records and other information.

[0056] Feeder lines are an important part of the distribution network that transmits electric energy from the substation to the user end. Effective automation coverage means that these feeder lines are equipped with automation equipment (such as smart switches, automation terminals, etc.), and these automation equipment can function normally to achieve automatic fault location, isolation, and rapid power restoration. The more feeder lines that are effectively covered by automation, the higher the automation level of the distribution network. Before the planning project is carried out, the number of feeder lines that have been effectively covered by automation can be counted, which can be determined by checking the equipment ledger and operation status monitoring records in the automation system.

[0057] Overloaded distribution transformers (transformers) can cause equipment overheating, accelerated insulation aging, and even cause power outages, affecting the quality and reliability of power supply. Solving the problem of overloaded distribution transformers through planning projects can ensure the safe and stable operation of the distribution network and improve the quality of power supply. The more overloaded distribution transformers are solved, the safer the operation of the distribution network. Before the project is implemented, the real-time load data of each transformer is collected through the distribution transformer load monitoring system, and the number of overloaded distribution transformers whose load rate exceeds the specified upper limit (i.e. overload) is screened out.

[0058] Public substations with low voltage will affect the normal use of various electrical equipment at the user end, reduce the user's power consumption experience, and may even damage some voltage-sensitive equipment. Therefore, solving the problem of public substations with low voltage will help improve the quality of power supply. The more public substations with low voltage are solved, the higher the power supply quality of the distribution network will be. Before the implementation of the planned project, the voltage monitoring device installed in the public substation can be used to count the number of substations with voltage below the normal specified range.

[0059] Then, by consulting the scientific research reports of the planning projects or expert forecasts, we can find out the output data of each planning project on indicators such as the number of newly added transferable power supply lines, the number of newly added lines with automated coverage of feeders, the number of overloaded distribution transformers resolved, and the number of public substations with low voltage resolved.

[0060] S300, taking the operation status data of the distribution network and the output data of each planning project as input, calling the trained distribution network output model, and determining the output data of the distribution network.

[0061] The distribution network output model is trained based on historical operation status data and historical project output data. Historical operation status data refers to the voltage values ​​of different nodes in different time periods, the current size of each line, the power flow direction, the time, scope, and frequency of power outages, and the operating parameters of power equipment during the past operation of the distribution network. Historical project output data refers to the actual output data of various distribution network planning projects that have been implemented and completed in the past, which can be obtained by consulting project scientific research reports, manual calculations, etc.

[0062] Based on the above historical operating status data and historical project output data, a neural network model can be trained to allow the neural network model to learn the inherent rules in the data, so that it can accurately predict the output based on the input and obtain the distribution network output model.

[0063] Following the above steps, after obtaining the operating status data of the current distribution network and the output data of each planned project, these operating status data and the output data of the planned projects are sorted and standardized in the format required by the distribution network output model, and then input into the trained distribution network output model. The distribution network output model will analyze and process these input data based on the historical rules it has learned, and predict the output data at the distribution network level after the implementation of the above-mentioned planning projects, that is, the distribution network output data.

[0064] The above-mentioned method for determining the output of the distribution network is different from the traditional solution that unilaterally evaluates the output of the power grid based on financial indicators. This solution obtains the operating status data of the distribution network and the output evaluation indicators of the planned projects, and first analyzes each planned project based on the output evaluation indicators of the planned projects, and then inputs the actual operating status data of the distribution network and the output data of each planned project into the trained distribution network output model. Since the distribution network output model is trained based on historical operating status data and historical project output data, the distribution network output model can comprehensively analyze the actual operating status data of the distribution network and the output data of each planned project, and simulate the comprehensive output of the entire distribution network system after the implementation of these planned projects, so as to determine the output data of the distribution network more scientifically and accurately, and improve the accuracy of evaluating the output of the distribution network.

[0065] In one embodiment, Figure 3 As shown, after S300, the method further includes:

[0066] S410, obtaining resource input data of the distribution network.

[0067] S420, determining resource return data of the distribution network and resource return data of each planned project according to the output data and resource input data of the distribution network.

[0068] S430, adjusting the planned projects of the distribution network based on the resource return data of the distribution network and the resource return data of each planned project.

[0069] Among them, the resource input data of the distribution network includes but is not limited to monetary resource input, human resource input, time resource input and other data. For example, monetary resource input includes the initial investment in the planning project construction phase, the construction cost of infrastructure such as substations and lines, equipment purchase costs (such as the purchase price of transformers, switches, cables, etc.), installation and commissioning costs (labor expenses of construction personnel, commissioning costs of professional equipment, etc.), land acquisition costs (if new sites need to occupy land), etc. Human resource input includes the number of personnel involved in the planning, construction, operation and maintenance of the distribution network, working hours and corresponding labor costs.

[0070] Following the above embodiment, the output data of the distribution network includes the convertible power supply rate, the newly added power supply capacity, the improvement of the voltage qualification rate, the reduction of the frequency deviation, the shortening of the average power outage time of the system, the reduction of the average power outage frequency of the system, the improvement of the new energy consumption rate, the reduction of the power abandonment rate, etc. According to the output data and resource input data of the distribution network, the resource return data of the distribution network and the resource return data of each planning project can be determined. For example, at the distribution network level, the contribution of the unit resource input data to the convertible power supply rate and the contribution of the unit resource investment to the newly added power supply capacity can be calculated respectively. At the planning project level, the resource input data of the above distribution network can be split into each planning project, and the contribution of the unit resource input data of each planning project to the number of newly added convertible power supply lines, the contribution of the unit resource input data to the number of newly added lines of the automated coverage feeder, the contribution of the unit resource input data to the number of overload distribution transformers solved, and the contribution of the unit resource input data to the number of public substations with low voltage solved can be calculated. In this way, the resource return data of the distribution network and the resource return data of each planning project can be obtained.

[0071] Furthermore, after obtaining the resource return data of the distribution network as a whole and the resource return data of each planned project, each planned project can be adjusted based on this. For example, if the resource return data of the distribution network as a whole is lower than the expected standard or the industry average, it means that there may be problems with the overall resource allocation and project implementation effect, and it is necessary to further judge the rationality of each planned project. For each planned project, a planned project with high resource return data usually means high resource utilization efficiency and good benefits. Such planned projects can appropriately increase investment, expand the scale of construction, or continue to promote similar planned projects in subsequent distribution network planning. Planning projects with low resource return data indicate that there may be waste of resources and poor output effects. The specific reasons can be further analyzed, and then corresponding measures can be taken, such as optimizing and transforming the planned project, adjusting the content of the planned project, reducing the scale of investment, or even suspending or canceling the planned project.

[0072] In this embodiment, the process of obtaining resource input data, determining resource return data, and adjusting planning projects based on this can continuously optimize the planning projects of the distribution network through such dynamic adjustments, so that resources can be more reasonably allocated and the overall input-output efficiency of the distribution network can be improved.

[0073] In one embodiment, Figure 4 As shown, S430 includes:

[0074] S431, determining the priority of each planning project according to the resource return data of each planning project.

[0075] S432, with the goal of maximizing the resource return data of the distribution network, adjust the planning projects of the distribution network according to the priority of each planning project.

[0076] Continuing with the above embodiment, after determining the resource return data of each planning project, each planning project can be arranged in descending order according to its resource return data. The planning project with a higher resource return data should be given a higher priority in resource allocation and implementation order. In this way, when resources are limited, those planning projects that can generate higher benefit returns can be promoted first.

[0077] Furthermore, with the goal of maximizing the resource return data of the distribution network, the input resources of the distribution network are reallocated according to the determined priority of the planning projects. Specifically, for projects with high priority, increase the investment in resources such as funds, manpower, and equipment. For example, sufficient construction funds can be allocated to those high-priority planning projects, and experienced engineering teams can be deployed. For planning projects with lower priority, resource investment can be appropriately reduced, or their implementation plans can be delayed, and resources can be concentrated on planning projects with higher priority, so as to maximize the resource return data of the distribution network. In this way, different planning project investment portfolios can be formed, and the planning project investment portfolio that maximizes the resource return data of the distribution network can be selected, and then the planning projects of the distribution network can be adjusted according to the planning project investment portfolio.

[0078] In this embodiment, the priority of the planning project is determined based on the planning project resource return data, and the distribution network planning project is adjusted according to the priority of each planning project, so that the resources of the distribution network can be more reasonably configured and the overall resource return data at the distribution network level can be improved.

[0079] In one embodiment, Figure 5 As shown, S100 includes:

[0080] S110, obtaining operation status data of the distribution network and a plurality of distribution network output evaluation indicators.

[0081] S120, disassembling the output evaluation indicators of each distribution network and determining the output evaluation indicators of the planned project of the distribution network.

[0082] Among them, there are a series of standards and specifications in the power industry to measure the output of the distribution network. The power grid companies to which the distribution network belongs will also formulate some evaluation indicators based on development strategies and operational goals. According to industry standards and specifications and the evaluation indicators formulated by the power grid companies themselves, multiple distribution network output evaluation indicators can be obtained. Specifically, the distribution network output evaluation indicators include but are not limited to specific indicators of the distribution network in terms of power supply quality, power supply reliability, equipment utilization efficiency, new energy access level, new load utilization rate, new energy storage utilization rate, power grid structure, power supply guarantee capability, comprehensive carrying capacity and comprehensive benefits.

[0083] Furthermore, the output evaluation indicators of the distribution network at the distribution network level are decomposed into various planning projects, and the output evaluation indicators of the planning projects of the distribution network can be obtained. For example, if the output evaluation indicator of the distribution network is the power supply capacity indicator, in order to improve the power supply capacity of the distribution network, the planning project may include substation expansion, new transmission lines, etc., and the corresponding output evaluation indicators of the planning project may be the new transformer capacity, the new line transmission capacity, etc. For another example, if the output evaluation indicator of the distribution network is the maximum load supply capacity indicator, the relevant planning project may be the transformation and upgrading of the existing line to improve the current carrying capacity, or the optimization of the grid structure of the power grid. The output evaluation indicators of the planning project may be the maximum allowable current carrying capacity increase value of the line after the transformation, the maximum load growth ratio of the power supply area after the grid structure is optimized, etc. If the output evaluation indicator of the distribution network is the new energy consumption rate indicator, the planning project may include the construction of energy storage facilities, the upgrading of the power grid dispatching system, etc. The output evaluation indicators of the planning project may be the increase in the energy storage capacity of the energy storage facilities, the improvement in the prediction accuracy of the dispatching system for new energy power generation, etc.

[0084] In this embodiment, by decomposing the distribution network output evaluation indicators into planning project output evaluation indicators, the specific goals and tasks of each planning project can be determined more accurately, so that each planning project has clear, specific and measurable goals, and obtains more accurate and suitable planning project output evaluation indicators.

[0085] In one embodiment, Figure 6 As shown in Figure 1, the distribution network output evaluation indicators include the distribution network transfer power supply rate, feeder automation coverage rate, overload distribution transformer ratio, and the proportion of public substations with low voltage. S120 includes:

[0086] S121, decomposing the distribution network convertible power supply rate into the number of newly added convertible power supply lines.

[0087] S122, decomposing the feeder automation coverage rate into the number of newly added feeder lines covered by automation.

[0088] S123, decomposing the overload distribution transformer ratio into the number of overload distribution transformers to be solved.

[0089] S124, breaking down the proportion of public substations with low voltage into the number of public substations with low voltage to be resolved.

[0090] Among them, the output evaluation indicators of the planning projects include the number of newly added convertible power supply lines, the number of newly added lines with automated coverage of feeders, the number of overloaded distribution transformers solved, and the number of public substations with low voltage solved.

[0091] Specifically, the transferable power supply rate of the distribution network refers to the proportion of the load of a certain line in the distribution network that can be transferred to other lines through interconnection switches and other means. It can reflect the flexibility and reliability of the distribution network's power supply. For each specific planning project, the transferable power supply rate of the distribution network can be broken down into the number of newly added transferable power supply lines. The number of newly added transferable power supply lines refers to the number of lines with transfer power supply capacity added through planning projects (such as new interconnection lines, transformation of switchgear, etc.).

[0092] Feeder automation coverage (also known as feeder automation effective coverage) refers to the ratio of the length or number of feeder lines that realize automation functions (such as automatic fault location, isolation and power restoration) in the distribution network to the total length or number of feeder lines. Improving the effective coverage of feeder automation is a gradual process, involving multiple links such as the installation, commissioning and system integration of automation equipment. It can be broken down into the number of newly added lines of feeders covered by automation. The number of newly added lines of feeders covered by automation refers to the number of feeder lines that are newly added after the implementation of the planned project and can effectively realize the automation function. In this way, the specific contribution of each planned project to improving the level of feeder automation can be clearly presented.

[0093] The overload distribution transformer ratio refers to the ratio of the number of overloaded transformers in the distribution network to the total number of transformers, reflecting the load balance of the distribution network transformers and whether the capacity meets the demand. The overload distribution transformer ratio is a macro indicator that reflects the severity of the overall problem. It is broken down into the number of overload distribution transformers solved. The number of overload distribution transformers solved refers to the number of overloaded transformers solved through planned projects (such as transformer capacity increase, load transfer, etc.). This can more specifically measure the contribution of planned projects in solving overload distribution transformer problems.

[0094] The proportion of public substations with low voltage refers to the proportion of public substations with voltage lower than the normal range in the distribution network to the total number of public substations, which reflects the degree of guarantee of the voltage quality of the distribution network to the user end. It can be broken down into the number of public substations with low voltage solved. The number of public substations with low voltage solved refers to the number of public substations whose voltage has been restored to normal through planned projects (such as installation of reactive power compensation devices, line reconstruction, etc.), which can more clearly evaluate the contribution of planned projects in improving voltage quality.

[0095] In this embodiment, by breaking down the macro distribution network output evaluation indicators into more specific planning project output evaluation indicators, it is possible to more accurately measure the contribution of each planning project to the development of the distribution network, thereby obtaining more accurate distribution network output data.

[0096] In order to make a clearer description of the method for determining the output of the distribution network provided in this application, Figure 7 and one A detailed embodiment is explained, and the detailed embodiment includes the following steps:

[0097] S701, obtaining operation status data of the distribution network and multiple distribution network output evaluation indicators.

[0098] S702, decomposing the convertible power supply rate of the distribution network into the number of newly added convertible power supply lines, and decomposing the feeder automation coverage rate into the number of newly added lines of the automated coverage feeder.

[0099] S703, decomposing the proportion of overloaded distribution transformers into the number of overloaded distribution transformers to be solved, and decomposing the proportion of low-voltage public substations into the number of low-voltage public substations to be solved.

[0100] S704, based on the output evaluation index of the planning project, evaluate each planning project of the distribution network, determine the output data of each planning project, take the operating status data of the distribution network and the output data of each planning project as input, call the trained distribution network output model, and determine the output data of the distribution network.

[0101] S705, obtaining resource input data of the distribution network. According to the output data and resource input data of the distribution network, the resource return data of the distribution network and the resource return data of each planned project are determined.

[0102] S706: Determine the priority of each planning project according to the resource return data of each planning project.

[0103] S707, with the goal of maximizing the resource return data of the distribution network, adjusting the planning projects of the distribution network according to the priority of each planning project.

[0104] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0105] Based on the same inventive concept, the embodiment of the present application also provides a distribution network output determination device for implementing the distribution network output determination method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more distribution network output determination device embodiments provided below can refer to the limitations of the distribution network output determination method above, and will not be repeated here.

[0106] In one embodiment, Figure 8 As shown, a distribution network output determination device 800 is provided, comprising: a data acquisition module 810, a project evaluation module 820 and an output evaluation module 830, wherein:

[0107] The data acquisition module 810 is used to obtain the operating status data of the distribution network and the output evaluation indicators of the planning project.

[0108] The project evaluation module 820 evaluates each planned project of the distribution network based on the planned project output evaluation index and determines the output data of each planned project.

[0109] The output evaluation module 830 is used to take the operating status data of the distribution network and the output data of each of the planned projects as input, call the trained distribution network output model, and determine the output data of the distribution network.

[0110] The distribution network output model is trained based on historical operation status data and historical project output data.

[0111] In one embodiment, the distribution network output determination device 800 is also used to obtain the resource input data of the distribution network, determine the resource return data of the distribution network and the resource return data of each of the planned projects according to the output data of the distribution network and the resource input data, and adjust the planned projects of the distribution network based on the resource return data of the distribution network and the resource return data of each of the planned projects.

[0112] In one embodiment, the distribution network output determination device 800 is also used to determine the priority of each of the planned projects based on the resource return data of each of the planned projects, and to adjust the planned projects of the distribution network according to the priority of each of the planned projects with the goal of maximizing the resource return data of the distribution network.

[0113] In one embodiment, the data acquisition module 810 is further used to acquire multiple distribution network output evaluation indicators, decompose each distribution network output evaluation indicator, and determine the output evaluation indicator of the planned project of the distribution network.

[0114] In one embodiment, the distribution network output evaluation indicators include the distribution network's convertible power supply rate, feeder automation coverage rate, overloaded distribution transformer ratio, and low voltage public substation ratio. The data acquisition module 810 is also used to decompose the distribution network's convertible power supply rate into the number of newly added convertible power supply lines, the feeder automation coverage rate into the number of newly added lines of automated covered feeders, the overloaded distribution transformer ratio into the number of overloaded distribution transformers solved, and the proportion of low voltage public substations into the number of low voltage public substations solved. The planning project output evaluation indicators include the number of newly added convertible power supply lines, the number of newly added lines of automated covered feeders, the number of overloaded distribution transformers solved, and the number of low voltage public substations solved.

[0115] Each module in the above-mentioned distribution network output determination device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0116] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Fig. 9As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data such as the operating status data of the distribution network and the output evaluation indicators of the planned project. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining the output of a distribution network is implemented.

[0117] Those skilled in the art will understand that Fig. 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0118] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the steps in the above-mentioned distribution network output determination method embodiment are implemented.

[0119] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned distribution network output determination method embodiment are implemented.

[0120] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps in the above-mentioned distribution network output determination method embodiment.

[0121] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions.

[0122] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0123] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0124] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for determining the output of a distribution network, characterized in that: The method comprises: Obtain the operating status data of the distribution network and the output evaluation indicators of the planned projects; Based on the output evaluation index of the planned project, evaluate each planned project of the distribution network and determine the output data of each planned project; Taking the operation status data of the distribution network and the output data of each of the planned projects as input, calling the trained distribution network output model to determine the output data of the distribution network; The distribution network output model is trained based on historical operation status data and historical project output data.

2. The method according to claim 1, characterized in that After determining the output data of the distribution network, the method further includes: Obtaining resource input data of the distribution network; Determining resource return data of the distribution network and resource return data of each of the planned projects according to the output data of the distribution network and the resource input data; Based on the resource return data of the distribution network and the resource return data of each of the planned projects, the planned projects of the distribution network are adjusted.

3. The method according to claim 2, characterized in that The adjusting the planned projects of the distribution network based on the resource return data of the distribution network and the resource return data of each of the planned projects includes: Determining the priority of each of the planned projects according to the resource return data of each of the planned projects; With the goal of maximizing the resource return data of the distribution network, the planning projects of the distribution network are adjusted according to the priority of each planning project.

4. The method according to any one of claims 1 to 3, characterized in that: The output evaluation index of the distribution network planning project is obtained, including: Obtain multiple distribution network output evaluation indicators; The output evaluation indicators of each distribution network are disassembled to obtain the output evaluation indicators of the planned projects of the distribution network.

5. The method according to claim 4, characterized in that The distribution network output evaluation indicators include the distribution network transferable power supply rate, feeder automation coverage rate, overload distribution transformer ratio, and the proportion of public substations with low voltage; The output evaluation indicators of each distribution network are disassembled to obtain the output evaluation indicators of the planned project of the distribution network, including: Decomposing the distribution network transferable power supply rate into the number of newly added transferable power supply lines; Decomposing the feeder automation coverage rate into the number of newly added lines of the automated covered feeder; Decomposing the overload distribution transformer ratio into the number of overload distribution transformers to be solved; Decomposing the proportion of public transformer areas with low voltage into the number of public transformer areas with low voltage to be solved; The output evaluation indicators of the planning project include the number of newly added convertible power supply lines, the number of newly added lines with automated coverage of feeders, the number of overloaded distribution transformers resolved, and the number of public substations with low voltage resolved.

6. A distribution network output determination device, characterized in that: The device comprises: Data acquisition module, used to obtain the operating status data of the distribution network and the output evaluation indicators of the planning project; A project evaluation module, which evaluates each planned project of the distribution network based on the planned project output evaluation index and determines the output data of each planned project; An output evaluation module, used to take the operation status data of the distribution network and the output data of each of the planned projects as input, call the trained distribution network output model, and determine the output data of the distribution network; The distribution network output model is trained based on historical operation status data and historical project output data.

7. The device according to claim 6, characterized in that The device is also used to obtain the resource input data of the distribution network, determine the resource return data of the distribution network and the resource return data of each of the planned projects according to the output data of the distribution network and the resource input data, and adjust the planned projects of the distribution network based on the resource return data of the distribution network and the resource return data of each of the planned projects.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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