Power distribution network project priority determination method, device and equipment and readable storage medium

Abstract

This application relates to a method, apparatus, device, and readable storage medium for determining the priority of distribution network projects. The method includes: acquiring the virtual resources to be allocated for users in a large area, the evaluation index of the distribution network project group for users in a small area, and the sub-evaluation index of each distribution network project, as well as the predicted values ​​of increased electricity sales, increased load supply, medium-voltage line length, transformer capacity, power supply reliability, comprehensive line loss rate, and return on net assets; inputting the evaluation index and other data into a pre-constructed allocation ratio model to obtain the allocation ratio for each user in the small area; then, based on the virtual resources to be allocated and the allocation ratio, obtaining the allocated virtual resources for each distribution network project to be determined; and based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index, obtaining the decision information for each distribution network project to be determined; and determining the priority of each distribution network project based on the decision information and preset constraints. This method can improve the accuracy of determining the priority of distribution network projects.

Description

Technical Field

[0001] This application relates to the field of project optimization technology, and in particular to a method, apparatus, computer equipment, computer-readable storage medium and computer program product for determining the priority of power distribution network projects. Background Technology

[0002] With the development of project selection technology, investment decision optimization methods based on project evaluation and ranking have emerged. These methods are typically used in the investment management of large-scale infrastructure projects or enterprises, and mainly focus on three aspects: project group identification and ranking, optimization, adjustment and monitoring, and project identification and ranking.

[0003] However, current investment decision optimization methods based on project evaluation and ranking suffer from inaccurate results. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can objectively determine the priority of power distribution network projects in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a method for determining the priority of power distribution network projects, including:

[0006] The system acquires the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined. It also acquires the predicted value of the increased electricity sales, the predicted value of the increased load supply, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets for each user in the community. Among these, the community belongs to the region.

[0007] The evaluation index of distribution network improvement effect, the predicted value of distribution network power sales, the predicted value of distribution network load increase, the length of medium voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate and the return on net assets are input into the pre-built virtual resource allocation ratio division model. The virtual resource allocation ratio of each community user is obtained through the virtual resource allocation ratio division model.

[0008] Based on the virtual resources to be allocated and the virtual resource allocation ratio, the allocated virtual resources for each distribution network project to be determined are obtained. Based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index, the ranking decision information for each distribution network project to be determined is obtained.

[0009] Based on the ranking decision information and the preset virtual resource allocation constraints, the priority of each distribution network project to be determined is determined.

[0010] In one embodiment, the virtual resource allocation ratio for each cell user is obtained through a virtual resource allocation ratio partitioning model, including:

[0011] The distribution network indicators and corresponding evaluation standards of each community user are obtained through the acquisition module in the virtual resource allocation ratio partitioning model. The distribution network indicators and corresponding evaluation standards are then input into the decision information acquisition module in the virtual resource allocation ratio partitioning model.

[0012] Based on the distribution network indicators, the evaluation criteria for distribution network indicators, and the pre-set indicator weights for distribution network indicators, virtual resource allocation decision information is obtained through the decision information acquisition module.

[0013] The virtual resource allocation decision information is input into the proportion determination module in the virtual resource allocation ratio division model, and the virtual resource allocation ratio of each community user is obtained through the proportion determination module.

[0014] In one embodiment, the distribution network indicators include distribution network improvement effect indicators, distribution network power supply level indicators, distribution network scale indicators, distribution network operation level indicators, and distribution network profitability indicators.

[0015] The acquisition module in the virtual resource allocation ratio model obtains the distribution network indicators and corresponding evaluation standards for each community user, including:

[0016] Input the distribution network improvement effect evaluation index into the acquisition module, and obtain the distribution network improvement effect indicators and the corresponding distribution network improvement effect indicator evaluation standards through the acquisition module;

[0017] Input the predicted increase in electricity sales and the predicted increase in load supply of the distribution network into the acquisition module, and obtain the power supply level index of the distribution network and the corresponding evaluation standard of the power supply level index of the distribution network through the acquisition module.

[0018] Input the medium-voltage line length and distribution transformer capacity into the acquisition module, and obtain the distribution network scale indicators and corresponding distribution network scale indicator evaluation standards through the acquisition module;

[0019] Input the power supply reliability rate and comprehensive line loss rate into the acquisition module, and obtain the distribution network operation level indicators and the corresponding distribution network operation level indicator evaluation standards through the acquisition module;

[0020] Input the return on net assets into the acquisition module, and obtain the distribution network profitability indicators and corresponding evaluation standards through the acquisition module.

[0021] In one embodiment, the predicted values ​​of increased electricity sales and increased load supply in the distribution network are input into an acquisition module, which then obtains the distribution network power supply level indicators, including:

[0022] By acquiring the first weight pre-set for the predicted increase in electricity sales in the distribution network and the second weight pre-set for the predicted increase in load in the distribution network, the predicted increase in electricity sales in the distribution network and the predicted increase in load in the distribution network are weighted and summed to obtain the power supply level index of the distribution network.

[0023] In an exemplary embodiment, the medium-voltage line length and distribution transformer capacity are input into the acquisition module, and the distribution network scale indicators are obtained through the acquisition module, including:

[0024] By acquiring the third weight pre-set for the length of medium-voltage lines and the fourth weight pre-set for the capacity of distribution transformers in the module, the length of medium-voltage lines and the capacity of distribution transformers are weighted and summed to obtain the distribution network scale index.

[0025] In one embodiment, the power supply reliability rate and the overall line loss rate are input into the acquisition module, and the acquisition module obtains the distribution network operation level indicators, including:

[0026] By acquiring the fifth weight pre-set for power supply reliability and the sixth weight pre-set for comprehensive line loss rate in the module, the power supply reliability and comprehensive line loss rate are weighted and summed to obtain the distribution network operation level index.

[0027] In one embodiment, the evaluation index of the distribution network improvement effect of the undetermined distribution network project group for community users and the evaluation index of the sub-distribution network improvement effect of each undetermined distribution network project are obtained through the following steps:

[0028] Obtain historical implementation data of the distribution network project group to be determined, as well as historical implementation sub-data of the distribution network projects to be determined; historical implementation data includes the original distribution network operation status data before the operation of the distribution network project group to be determined, and the distribution network operation status data after the operation of the distribution network project group to be determined; historical implementation sub-data includes the original distribution network operation status sub-data before the operation of the distribution network projects to be determined, and the distribution network operation status sub-data after the operation of the distribution network projects to be determined.

[0029] Based on the original distribution network operation status data and distribution network operation status data, multiple evaluation indicators for the degree of improvement of the distribution network are obtained, and based on the original distribution network operation status sub-data and distribution network operation status sub-data, multiple evaluation indicators for the degree of improvement of the sub-distribution network are obtained.

[0030] Using pre-set normalization coefficients, the evaluation indicators of the improvement degree of each distribution network and the evaluation indicators of the improvement degree of sub-distribution networks are dimensionless to obtain the processed evaluation indicators of the improvement degree of the distribution network and the evaluation indicators of the improvement degree of sub-distribution networks.

[0031] Based on the pre-set weights of the evaluation indicators for each distribution network improvement level, the processed evaluation indicators for each distribution network improvement level, and the pre-set evaluation criteria, an evaluation index for the distribution network improvement effect is obtained.

[0032] Based on the pre-set indicator weights for the evaluation indicators of the improvement degree of each sub-distribution network, the evaluation indicators of the improvement degree of each processed sub-distribution network, and the pre-set evaluation standards, the evaluation index of the improvement effect of the sub-distribution network is obtained.

[0033] Secondly, this application also provides a distribution network project priority determination device, comprising:

[0034] The data acquisition module is used to acquire the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined, as well as the predicted value of the increased electricity sales, the predicted value of the increased load supply, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets for each user in the community; among them, the community belongs to the region;

[0035] The allocation ratio determination module is used to input the distribution network improvement effect evaluation index, the distribution network power sales forecast, the distribution network load forecast, the medium voltage line length, the distribution transformer capacity, the power supply reliability rate, the comprehensive line loss rate, and the net asset return rate into the pre-built virtual resource allocation ratio division model, and obtain the virtual resource allocation ratio of each community user through the virtual resource allocation ratio division model.

[0036] The ranking decision information acquisition module is used to obtain the allocated virtual resources for each distribution network project to be determined based on the virtual resources to be allocated and the virtual resource allocation ratio, and to obtain the ranking decision information for each distribution network project to be determined based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index.

[0037] The priority determination module is used to determine the priority of each distribution network project to be determined based on the sorting decision information and the preset virtual resource allocation constraints.

[0038] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0039] The system acquires the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined. It also acquires the predicted value of the increased electricity sales, the predicted value of the increased load supply, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets for each user in the community. Among these, the community belongs to the region.

[0040] The evaluation index of distribution network improvement effect, the predicted value of distribution network power sales, the predicted value of distribution network load increase, the length of medium voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate and the return on net assets are input into the pre-built virtual resource allocation ratio division model. The virtual resource allocation ratio of each community user is obtained through the virtual resource allocation ratio division model.

[0041] Based on the virtual resources to be allocated and the virtual resource allocation ratio, the allocated virtual resources for each distribution network project to be determined are obtained. Based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index, the ranking decision information for each distribution network project to be determined is obtained.

[0042] Based on the ranking decision information and the preset virtual resource allocation constraints, the priority of each distribution network project to be determined is determined.

[0043] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0044] The system acquires the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined. It also acquires the predicted value of the increased electricity sales, the predicted value of the increased load supply, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets for each user in the community. Among these, the community belongs to the region.

[0045] The evaluation index of distribution network improvement effect, the predicted value of distribution network power sales, the predicted value of distribution network load increase, the length of medium voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate and the return on net assets are input into the pre-built virtual resource allocation ratio division model. The virtual resource allocation ratio of each community user is obtained through the virtual resource allocation ratio division model.

[0046] Based on the virtual resources to be allocated and the virtual resource allocation ratio, the allocated virtual resources for each distribution network project to be determined are obtained. Based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index, the ranking decision information for each distribution network project to be determined is obtained.

[0047] Based on the ranking decision information and the preset virtual resource allocation constraints, the priority of each distribution network project to be determined is determined.

[0048] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0049] The system acquires the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined. It also acquires the predicted value of the increased electricity sales, the predicted value of the increased load supply, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets for each user in the community. Among these, the community belongs to the region.

[0050] The evaluation index of distribution network improvement effect, the predicted value of distribution network power sales, the predicted value of distribution network load increase, the length of medium voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate and the return on net assets are input into the pre-built virtual resource allocation ratio division model. The virtual resource allocation ratio of each community user is obtained through the virtual resource allocation ratio division model.

[0051] Based on the virtual resources to be allocated and the virtual resource allocation ratio, the allocated virtual resources for each distribution network project to be determined are obtained. Based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index, the ranking decision information for each distribution network project to be determined is obtained.

[0052] Based on the ranking decision information and the preset virtual resource allocation constraints, the priority of each distribution network project to be determined is determined.

[0053] The aforementioned method, apparatus, computer equipment, computer-readable storage medium, and computer program product for prioritizing distribution network projects acquire the virtual resources to be allocated for users in a large area, the distribution network improvement effect evaluation index for the distribution network project group to be determined for users in a small area, and the sub-distribution network improvement effect evaluation index for each distribution network project to be determined, as well as the predicted values ​​of increased electricity sales, increased load supply, medium-voltage line length, transformer capacity, power supply reliability, comprehensive line loss rate, and return on net assets for each user in a small area. This information is then used to determine the distribution network improvement effect evaluation index, the predicted value of increased electricity sales, and the predicted value of increased load supply. The system inputs medium-voltage line length, transformer capacity, power supply reliability, comprehensive line loss rate, and return on net assets into a pre-constructed virtual resource allocation ratio model. This model yields the virtual resource allocation ratio for each user in each community. Then, based on the virtual resources to be allocated and the allocation ratio, the virtual resources allocated to each distribution network project to be determined are obtained. Furthermore, based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index, the system obtains ranking decision information for each project. Finally, based on the ranking decision information and pre-set virtual resource allocation constraints, the priority of each project is determined. By adding basic data for determining the virtual resource allocation ratio, and ensuring the high availability of this data, the accuracy of determining the priority of distribution network projects is improved. Attached Figure Description

[0054] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 This is an application environment diagram of the power distribution network project priority determination method in one embodiment;

[0056] Figure 2 This is a flowchart illustrating a method for determining the priority of power distribution network projects in one embodiment;

[0057] Figure 3 This is an index table for obtaining the evaluation index of the improvement effect of the power distribution network in one embodiment;

[0058] Figure 4 This is a partial schematic diagram of a virtual resource allocation ratio partitioning model in another embodiment;

[0059] Figure 5 Here is a structural block diagram of a power distribution network project priority determination device in one embodiment;

[0060] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0062] The method for determining the priority of power distribution network projects provided in this application can be applied to, for example... Figure 1The application environment shown is as follows. A regional control area comprises multiple sub-regions. Within the regional control area, a central control terminal manages the allocation of virtual resources. Within each sub-region, terminals manage the allocation of virtual resources for individual projects. These terminals and the central control terminal communicate with server 102 via a network. A data storage system stores the data that server 102 needs to process. The data storage system can be integrated onto server 102 or hosted on a cloud or other network server. Server 102 acquires the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined, as well as the predicted values ​​of the distribution network's increased sales volume, increased load, medium-voltage line length, transformer capacity, power supply reliability, comprehensive line loss rate, and net asset return rate for each user in the community. It inputs the evaluation index of the distribution network improvement effect, the predicted values ​​of the distribution network's increased sales volume, the predicted values ​​of the distribution network's increased load, the medium-voltage line length, transformer capacity, power supply reliability, comprehensive line loss rate, and net asset return rate into a pre-constructed virtual resource allocation ratio model. The model obtains the virtual resource allocation ratio for each user in the community. Then, based on the virtual resources to be allocated and the virtual resource allocation ratio, it obtains the allocated virtual resources for each distribution network project to be determined. Based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index, it obtains the decision information for each distribution network project to be determined. Finally, based on the decision information and the preset virtual resource allocation constraints, it determines the priority of each distribution network project to be determined. The terminals and central control terminals can be, but are not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, etc. Server 102 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0063] In one exemplary embodiment, such as Figure 2 As shown, a method for determining the priority of power distribution network projects is provided, which can be applied to... Figure 1 Taking server 102 as an example, the explanation includes the following steps S201 to S204. Wherein:

[0064] Step S201: Obtain the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined, as well as the predicted value of the increased electricity sales, the predicted value of the increased load supply, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets for each user in the community; wherein, the community belongs to the region.

[0065] In this context, "region" can be understood as a provincial-level area, and "regional user" can be understood as a provincial or municipal-level power distribution company, overseeing the flow of virtual resources across a group of power distribution projects within a designated area, down to the flow of virtual resources for individual power distribution projects. "Community" can be understood as a lower-level town or district, and "community user" can be understood as a town or district-level power distribution company, allocating received virtual resources proportionally to the power distribution projects under its jurisdiction. The power distribution network improvement effect evaluation index can be understood as a linear measure of the improvement effect achieved by the power distribution network after the operation of the power distribution project group. The sub-power distribution network improvement effect evaluation parameter index can also be understood as a linear measure of the improvement effect achieved by the power distribution network after the operation of the power distribution project. "Transformer capacity" can be understood as the rated capacity of a power distribution transformer, representing the maximum electrical power that the transformer can safely carry under normal operating conditions.

[0066] Power supply reliability can be understood as the reliability index of the power supply required by users within a specific period, usually expressed as a percentage. It reflects the stability and reliability of the power supply by assessing the frequency and duration of power outages. Power supply reliability can be calculated using the following formula: Power supply reliability = (1 − outage time / total time) × 100%, where outage time includes the total duration of outages caused by equipment failure, maintenance, natural disasters, etc., and total time is the total duration of the observation period (usually an annual period). The comprehensive line loss rate can be understood as the ratio of losses (such as heat loss, induction loss, radiation loss, etc.) caused by current during power transmission and distribution to the total supplied electrical energy within a certain period. It can be expressed as: Comprehensive line loss rate = Total line loss × 100%, where line loss refers to the energy loss caused by the resistance of the conductor during power transmission. Return on equity (ROE) can be understood as a key financial indicator measuring a company's profitability, representing the ratio between the company's net profit and shareholders' net assets within a certain period.

[0067] For example, server 102 acquires the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined, as well as the predicted value of the increased electricity sales, the predicted value of the increased load supply, the length of medium-voltage lines, the capacity of distribution transformers, the power supply considerations, the comprehensive line loss rate, and the return on net assets for each user in the community. By acquiring basic data from multiple sources, a data foundation is laid for subsequently determining the allocation ratio of virtual resources for each user in the community, thereby enhancing the reliability and accuracy of determining the priority of the distribution network projects to be determined.

[0068] Step S202: Input the distribution network improvement effect evaluation index, the predicted value of the distribution network increased electricity sales, the predicted value of the distribution network increased load, the medium-voltage line length, the distribution transformer capacity, the power supply reliability rate, the comprehensive line loss rate, and the net asset return rate into the pre-constructed virtual resource allocation ratio division model, and obtain the virtual resource allocation ratio of each community user through the virtual resource allocation ratio division model.

[0069] The virtual resource allocation ratio can be understood as the allocation ratio of each community user to each power distribution network project. This allocation ratio is the proportion relative to the total virtual resources.

[0070] Optionally, server 102 inputs the distribution network improvement effect evaluation index, the predicted value of increased electricity sales in the distribution network, the predicted value of increased load supply in the distribution network, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets into a pre-constructed virtual resource allocation ratio partitioning model. The virtual resource allocation ratio for each user in each community is obtained through this model. Calculating the virtual resource allocation ratio for each user in each community using multi-source data enhances the reliability of the virtual resource allocation ratio and lays a data foundation for subsequent acquisition of ranking decision information for distribution network projects to be determined.

[0071] Step S203: Based on the virtual resources to be allocated and the virtual resource allocation ratio, obtain the allocated virtual resources for each distribution network project to be determined, and obtain the ranking decision information for each distribution network project to be determined based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index.

[0072] Step S204: Determine the priority of each distribution network project to be determined based on the sorting decision information and the preset virtual resource allocation constraints.

[0073] Among them, the virtual resource allocation constraint can be understood as the total amount of virtual resources obtained by users in the community.

[0074] For example, server 102 obtains the allocated virtual resources for each distribution network project to be determined based on the virtual resources to be allocated and the virtual resource allocation ratio. Then, based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index, it obtains the ranking decision information for each distribution network project to be determined. Finally, based on the ranking decision information and preset virtual resource allocation constraints, it determines the priority of each distribution network project to be determined. This method helps improve the accuracy of determining the priority of distribution network projects to be determined, helps community users to control the priority allocation of virtual resources, and ensures the efficiency of the system.

[0075] In the aforementioned method for determining the priority of distribution network projects, the following steps are taken: First, the virtual resources to be allocated for users in a large region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in a small community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined, along with the predicted values ​​of increased electricity sales, increased load supply, medium-voltage line length, transformer capacity, power supply reliability, comprehensive line loss rate, and net asset return rate for each user in a small community. Then, the evaluation index of the distribution network improvement effect, the predicted values ​​of increased electricity sales, increased load supply, medium-voltage line length, transformer capacity, power supply reliability, comprehensive line loss rate, and net asset return rate are input into a pre-constructed virtual resource allocation ratio model. The virtual resource allocation ratio for each user in a small community is obtained through this model. Next, based on the virtual resources to be allocated and the virtual resource allocation ratio, the allocated virtual resources for each distribution network project to be determined are obtained. Finally, based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index, the decision information for each distribution network project to be determined is obtained. Finally, based on the decision information and the preset virtual resource allocation constraints, the priority of each distribution network project to be determined is determined. By adding basic data for determining the allocation ratio of virtual resources, and by ensuring that the basic data is highly available, the accuracy of prioritizing power distribution network projects is improved.

[0076] In one embodiment, the virtual resource allocation ratio for each cell user is obtained through a virtual resource allocation ratio partitioning model, including:

[0077] The virtual resource allocation ratio partitioning model obtains the distribution network indicators and corresponding evaluation standards for each community user through the acquisition module, and inputs these indicators into the decision information acquisition module. Based on the distribution network indicators, evaluation standards, and pre-set weights for the indicators, the virtual resource allocation decision information is obtained through the decision information acquisition module. This decision information is then input into the ratio determination module, which determines the virtual resource allocation ratio for each community user.

[0078] Among them, the distribution network indicators can be understood as factors that have a significant impact on the allocation of virtual resources.

[0079] Optionally, server 102 obtains the distribution network indicators and corresponding evaluation standards for each community user through the acquisition module in the virtual resource allocation ratio partitioning model. It then inputs these indicators into the decision information acquisition module within the model. The decision information acquisition module, based on the distribution network indicators, evaluation standards, and pre-set weights for each indicator, generates virtual resource allocation decision information. Finally, this information is input into the ratio determination module, which then obtains the virtual resource allocation ratio for each community user. By acquiring distribution network indicators that comprehensively reflect the characteristics of community users and using these indicators as the basis for acquiring other data, the final virtual resource allocation ratio output by the model has high reliability, thereby improving the accuracy of determining the priority of each distribution network project.

[0080] In one embodiment, the distribution network indicators include distribution network improvement effect indicators, distribution network power supply level indicators, distribution network scale indicators, distribution network operation level indicators, and distribution network profitability indicators.

[0081] The acquisition module in the virtual resource allocation ratio model obtains the distribution network indicators and corresponding evaluation standards for each community user, including:

[0082] The distribution network improvement effect evaluation index is input into the acquisition module, which then obtains the distribution network improvement effect indicators and corresponding evaluation standards. The predicted values ​​of increased electricity sales and increased load supply in the distribution network are also input into the acquisition module, which then obtains the distribution network power supply level indicators and corresponding evaluation standards. The length of medium-voltage lines and the capacity of distribution transformers are input into the acquisition module, which then obtains the distribution network scale indicators and corresponding evaluation standards. The power supply reliability rate and comprehensive line loss rate are input into the acquisition module, which then obtains the distribution network operation level indicators and corresponding evaluation standards. Finally, the return on net assets is input into the acquisition module, which then obtains the distribution network profitability indicators and corresponding evaluation standards.

[0083] For example, the distribution network improvement effect evaluation index is input into the acquisition module, which then obtains the distribution network improvement effect indicators and corresponding evaluation standards. Simultaneously, the predicted values ​​of increased electricity sales and increased load supply in the distribution network are input into the acquisition module, which then obtains the distribution network power supply level indicators and corresponding evaluation standards. Next, the medium-voltage line length and transformer capacity are input into the acquisition module, which then obtains the distribution network scale indicators and corresponding evaluation standards. Furthermore, the power supply reliability rate and comprehensive line loss rate are input into the acquisition module, which then obtains the distribution network operation level indicators and corresponding evaluation standards. Finally, the return on net assets is input into the acquisition module, which then obtains the distribution network profitability indicators and corresponding evaluation standards. By comprehensively inputting the data into the model through the acquisition module in the virtual resource allocation ratio partitioning model, the influencing factors are summarized into five aspects, which reduces the number of data processing steps to some extent and allows for timely detection and handling of errors, enhancing the system's robustness.

[0084] In an exemplary embodiment, the predicted value of increased electricity sales and the predicted value of increased load supply in the distribution network are input into the acquisition module. The power supply level index of the distribution network is obtained through the acquisition module, including: by using a first weight preset for the predicted value of increased electricity sales and a second weight preset for the predicted value of increased load supply in the distribution network in the acquisition module, the predicted value of increased electricity sales and the predicted value of increased load supply in the distribution network are weighted and summed to obtain the power supply level index of the distribution network.

[0085] Optionally, server 102 obtains a distribution network power supply level index by weighting and summing the predicted values ​​of increased electricity sales and increased load in the distribution network using a first weight pre-set in the acquisition module and a second weight pre-set in the acquisition module. By assigning matching weights to the predicted values ​​of increased electricity sales and increased load in the distribution network, which together constitute the distribution network power supply level index, and then performing a weighted summation, the reliability and effectiveness of the distribution network power supply level index are ensured.

[0086] In one embodiment, the medium-voltage line length and distribution transformer capacity are input into the acquisition module, and the distribution network scale index is obtained through the acquisition module. This includes: using a third weight pre-set for the medium-voltage line length and a fourth weight pre-set for the distribution transformer capacity in the acquisition module, the medium-voltage line length and distribution transformer capacity are weighted and summed to obtain the distribution network scale index.

[0087] For example, server 102 obtains the distribution network scale index by weighting and summing the medium-voltage line length and distribution transformer capacity by acquiring the third weight pre-set for the medium-voltage line length and the fourth weight pre-set for the distribution transformer capacity in the module. By assigning matching weights to the medium-voltage line length and distribution transformer capacity, which together constitute the distribution network scale index, and performing weighted summation, the reliability and effectiveness of the distribution network scale index are ensured.

[0088] In one embodiment, the power supply reliability rate and the comprehensive line loss rate are input into the acquisition module, and the distribution network operation level index is obtained through the acquisition module. This includes: using the fifth weight pre-set for the power supply reliability rate and the sixth weight pre-set for the comprehensive line loss rate in the acquisition module, the power supply reliability rate and the comprehensive line loss rate are weighted and summed to obtain the distribution network operation level index.

[0089] Optionally, server 102 uses a pre-set fifth weight for power supply reliability and a pre-set sixth weight for comprehensive line loss rate to perform a weighted summation of the power supply reliability rate and comprehensive line loss rate to obtain the distribution network operation level index. By assigning matching weights to the power supply reliability rate and comprehensive line loss rate, which together constitute the distribution network operation level index, and performing a weighted summation, the credibility and effectiveness of the distribution network operation level index are ensured.

[0090] In an exemplary embodiment, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for the community user and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined are obtained through the following:

[0091] Acquire historical implementation data for the distribution network project group to be determined, as well as historical implementation sub-data for each distribution network project. The historical implementation data includes the original distribution network operating status data before the operation of the project group and the distribution network operating status data after the operation of the project group. The historical implementation sub-data includes the original distribution network operating status sub-data before the operation of each distribution network project and the distribution network operating status sub-data after the operation of the project group. Based on the original and current distribution network operating status data, obtain multiple evaluation indicators for the degree of distribution network improvement, and based on the original and current distribution network operating status sub-data, obtain multiple sub-distribution... Evaluation indicators for the degree of improvement of the distribution network: Using pre-set normalization coefficients, dimensionless processing is performed on the evaluation indicators for the degree of improvement of each distribution network and the evaluation indicators for the degree of improvement of each sub-distribution network to obtain the processed evaluation indicators for the degree of improvement of the distribution network and the degree of improvement of each sub-distribution network; Based on the pre-set indicator weights for each evaluation indicator for the degree of improvement of the distribution network, the processed evaluation indicators for the degree of improvement of the distribution network, and the pre-set evaluation criteria, the evaluation index for the improvement effect of the distribution network is obtained; Based on the pre-set indicator weights for each evaluation indicator for the degree of improvement of the sub-distribution network, the processed evaluation indicators for the degree of improvement of the sub-distribution network, and the pre-set evaluation criteria, the evaluation index for the improvement effect of the sub-distribution network is obtained.

[0092] The normalization coefficient can be understood as the reciprocal of the potential improvement space of the indicator before implementation, and the potential improvement space is the difference between the indicator value before implementation and the ideal value. The evaluation indicators for the improvement degree of the distribution network and the evaluation indicators for the improvement degree of the sub-distribution network can be the same or different, and should be adjusted adaptively according to the actual application.

[0093] For example, server 102 obtains the original distribution network operation status data before the operation of the distribution network project group to be determined, the distribution network operation status data after the operation of the distribution network project to be determined, as well as the original distribution network operation status sub-data before the operation of the distribution network project to be determined, and the distribution network operation status sub-data after the operation of the distribution network project to be determined. Then, based on the original distribution network operation status data and the distribution network operation status data, it obtains multiple distribution network improvement evaluation indicators, and based on the original distribution network operation status sub-data and the distribution network operation status sub-data, it obtains multiple sub-distribution network improvement evaluation indicators, and then uses a pre-set normalization coefficient. Dimensionless processing was performed on the evaluation indicators for the improvement degree of each distribution network and sub-distribution network, resulting in processed evaluation indicators for the improvement degree of the distribution network and sub-distribution networks. Finally, based on pre-set indicator weights for each distribution network improvement degree evaluation indicator, the processed indicators, and pre-set evaluation criteria, a distribution network improvement effect evaluation index was obtained. Similarly, based on pre-set indicator weights for each sub-distribution network improvement degree evaluation indicator, the processed indicators, and pre-set evaluation criteria, a sub-distribution network improvement effect evaluation index was obtained. By unifying the dimensions of various operational status data, data comparability was improved, thereby enhancing data evaluability and increasing the usability of the obtained distribution network improvement effect evaluation indices and sub-distribution network improvement effect evaluation indices.

[0094] In an exemplary embodiment, a specific implementation of the method for determining the priority of power distribution network projects is provided, as follows:

[0095] 1. Evaluation system for distribution network optimization effects:

[0096] 1.1 Indicator System:

[0097] The effectiveness of improving the operational status of the distribution network needs to reflect the concerns of relevant stakeholders, namely, indicators such as power supply reliability, overall voltage qualification rate, overall line loss rate, and equipment utilization rate (referred to as the "four rates"). While the "four rates" can demonstrate the results of improvements in the operational status of the distribution network, they cannot directly evaluate its operational status. Therefore, it is necessary to further analyze the factors influencing the "four rates" and select indicators that can clearly reflect the operational status of the distribution network.

[0098] From a macro perspective, the factors influencing the "four rates" (network structure, load supply capacity, and equipment technology) can be divided into three aspects: network structure level, load supply capacity, and equipment technology level. Using a fishbone diagram, this study explores the specific factors affecting the "four rates" from these three aspects, establishes a system of factors influencing the operating status of the distribution network, determines evaluation indicators, uses the analytic hierarchy process (AHP) to establish an indicator system for distribution network improvement effects, and, incorporating opinions from multiple experts, employs the Delphi method to assign indicator weights. (See...) Figure 3 It can be known that Figure 3 The data that appears thereafter are all examples and are not limited to this specific situation in order to implement the method of this application.

[0099] 1.2 Indicator Calculation and Evaluation Standards:

[0100] (1) Calculation of indicators:

[0101] Evaluation indicators focus on reflecting the improvement effect of the distribution network's operating status, which can be calculated by the degree of change in operating status indicators before and after project implementation. However, since the various operating status indicators have different dimensions, the degree of change before and after project implementation will also have different dimensions, making the indicators incomparable. Therefore, to make the indicators have a unified dimension for easier evaluation, a normalization coefficient is used to make each indicator dimensionless. The normalization coefficient is defined as the reciprocal of the potential improvement space of the indicator before implementation, and the potential improvement space is the difference between the indicator value before implementation and the ideal value. The specific calculation method for the indicators is as follows.

[0102] When the operational status indicator is positive, the ideal value of the indicator is 100%. Let N1 and N2 be the indicator values ​​before and after implementation, respectively. Then the normalization coefficient is... The actual improvement value of the indicator is related to the change in the indicator value. The calculation of the indicator value x of the distribution network improvement effect is shown in Equation ①.

[0103] ①

[0104] When the operating status indicator is a negative indicator, the ideal value of the indicator is 0. Let's assume... and Let the indicator values ​​be before and after implementation, respectively. Then the normalization coefficient is... Similarly, the calculation formula for the distribution network improvement effect index value x' can be obtained, as shown in equation ②.

[0105] ②

[0106] Through the above processing, all evaluation indicators have a unified dimension and are all positive indicators, making them comparable.

[0107] (2) Evaluation criteria:

[0108] The evaluation criteria use a percentage system. All indicator values ​​are in percentage form. A linear relationship is established between the indicator value x and the evaluation index y, resulting in the evaluation standard function y = 100x.

[0109] Finally, by combining the index values, index weights, and evaluation criteria, the evaluation index for the improvement effect of the power distribution network can be calculated.

[0110] 2. Distribution network investment allocation model:

[0111] 2.1 Model Architecture:

[0112] The determination of the investment scale of provincial power grid companies (regional users) in municipal power grid companies (local users) mainly takes into account the influence and constraints of two factors: the investment needs of municipal power distribution network development and the investment capacity of municipal power grid companies.

[0113] (1) Investment demand. The improvement effect, power supply level, scale, and operation level of the candidate project group on the distribution network will affect the investment demand for distribution network development. Moreover, these factors can be reflected by more specific factors. The improvement effect of the distribution network can be reflected by the evaluation index of the candidate project group; the power supply level of the distribution network can be reflected by the increase in electricity sales and the increase in load supplied by the distribution network; the scale of the distribution network can be reflected by the length of medium-voltage lines and the capacity of distribution transformers; and the operation level of the distribution network can be reflected by the power supply reliability rate and the comprehensive line loss rate.

[0114] (2) Investment Capacity. Investment capacity is affected by the company's profitability, which can be reflected by the return on net assets. In summary, the scale of distribution network investment is affected by the distribution network improvement effect evaluation index, the increase in distribution network electricity sales, the increase in distribution network load, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets. These factors can be combined to select investment allocation evaluation indicators. The weights of the indicators are determined using the Delphi method, and the results are shown in […]. Figure 4 .

[0115] 2.2 Model Calculation:

[0116] (1) Indicator values. The model calculation results are the investment allocation ratio of the distribution network in the next year. Therefore, the evaluation index of the candidate project group for the next year is taken as the distribution network improvement effect, the power supply level index of the distribution network is taken as the predicted value of the next year, and the scale, operation level and profitability index of the distribution network are taken as the current value of the current year.

[0117] (2) Evaluation Criteria. The evaluation criteria adopt a percentage system. To ensure comparability among different municipal power grid companies, the evaluation criteria are determined based on the ranking of each company's indicator value among all companies' indicator values. The indicator value x'' and the evaluation index y'' are set to have a linear relationship, and the evaluation index of the maximum value of all company indicator values ​​is 100, while the evaluation index of the minimum value is 0. The evaluation criteria function is shown in Equation ③.

[0118] ③

[0119] In the formula: k represents the power grid company number.

[0120] (3) Calculation of investment allocation ratio. By combining the indicator values, indicator weights and evaluation criteria, the investment allocation decision value S of the distribution network can be calculated, and then the investment allocation ratio of the municipal power grid company can be calculated. The calculation formula is shown in equation ④.

[0121] ④

[0122] In the formula: This indicates the number of municipal-level power grid companies.

[0123] 3. Optimal Scheme for Power Distribution Network Construction Project:

[0124] First, based on the evaluation system for the improvement effect of the power distribution network and the investment amount of the project, the comprehensive ranking of individual projects is obtained; then, the investment limit is used as a constraint to obtain the project selection results of the municipal power grid companies.

[0125] 3.1 Overall Project Ranking:

[0126] For a single project in the candidate project group, the comprehensive ranking decision value F is calculated by using the power distribution network improvement effect evaluation system and combining the project investment amount C.

[0127] ⑤

[0128] In the formula: i and j are the primary and secondary indicator numbers, respectively; m and n are the primary and secondary indicator numbers, respectively; and These are the weights of the i-th primary indicator and the j-th secondary indicator, respectively; Let be the value of the j-th secondary indicator.

[0129] Based on the project comprehensive ranking decision value F, the comprehensive ranking of projects of the municipal power grid companies can be obtained.

[0130] 3.2 Project Optimization Results:

[0131] Based on the comprehensive ranking of projects of municipal power grid companies, and constrained by the investment limit of municipal power grid companies calculated by the proportion of total investment in the distribution network of provincial power grid companies and investment allocation ratio of municipal power grid companies, the optimal project results of municipal power grid companies can be determined.

[0132] Compared with the prior art, this application has the following advantages:

[0133] 1. A systematic method for selecting and ranking investment projects has been established, employing a comprehensive evaluation index system and quantitative calculation methods to ensure the scientific and objective nature of project evaluation.

[0134] 2. By using reasonable weight allocation, a comprehensive evaluation model, and a dynamic adjustment mechanism, the flexibility and adaptability of project ranking have been improved.

[0135] 3. Inter-project correlation analysis and sensitivity analysis have been added, optimizing the project implementation plan and overcoming the subjectivity and incompleteness of existing technologies, providing efficient and reliable support for power distribution network investment decisions.

[0136] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0137] Based on the same inventive concept, this application also provides a distribution network project priority determination device for implementing the above-described distribution network project priority determination method. The solution provided by this device is similar to the implementation described in the above-described method. Therefore, the specific limitations in one or more distribution network project priority determination device embodiments provided below can be found in the limitations of the distribution network project priority determination method described above, and will not be repeated here.

[0138] In one exemplary embodiment, such as Figure 5 As shown, a power distribution network project priority determination device is provided, comprising: a data acquisition module 501, an allocation ratio determination module 502, a decision information acquisition module 503, and a priority determination module 504, wherein:

[0139] The data acquisition module 501 is used to acquire the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined, as well as the predicted value of the increased electricity sales, the predicted value of the increased load supply, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets for each user in the community; wherein, the community belongs to the region;

[0140] The allocation ratio determination module 502 is used to input the distribution network improvement effect evaluation index, the distribution network power sales forecast value, the distribution network load forecast value, the medium voltage line length, the distribution transformer capacity, the power supply reliability rate, the comprehensive line loss rate and the net asset return rate into the pre-built virtual resource allocation ratio division model, and obtain the virtual resource allocation ratio of each community user through the virtual resource allocation ratio division model;

[0141] The sorting decision information acquisition module 503 is used to obtain the allocated virtual resources for each distribution network project to be determined based on the virtual resources to be allocated and the virtual resource allocation ratio, and to obtain the sorting decision information for each distribution network project to be determined based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index.

[0142] The priority determination module 504 is used to determine the priority of each distribution network project to be determined based on the sorting decision information and the preset virtual resource allocation constraints.

[0143] In one embodiment, the allocation ratio determination module 502 further includes:

[0144] The acquisition submodule is used to obtain the distribution network indicators and corresponding distribution network indicator evaluation standards of each community user through the acquisition module in the virtual resource allocation ratio partitioning model, and input the distribution network indicators and corresponding distribution network indicator evaluation standards into the decision information acquisition module in the virtual resource allocation ratio partitioning model.

[0145] The allocation ratio determination submodule is used to obtain virtual resource allocation decision information through the decision information acquisition module based on the distribution network indicators, the evaluation standards of the distribution network indicators, and the pre-set indicator weights for the distribution network indicators. The virtual resource allocation decision information is then input into the ratio determination module in the virtual resource allocation ratio division model, and the virtual resource allocation ratio of each community user is obtained through the ratio determination module.

[0146] In one embodiment, the distribution network indicators include distribution network improvement effect indicators, distribution network power supply level indicators, distribution network scale indicators, distribution network operation level indicators, and distribution network profitability indicators; the acquisition submodule further includes:

[0147] The first acquisition subunit is used to input the distribution network improvement effect evaluation index into the acquisition module, and to acquire the distribution network improvement effect indicators and the corresponding distribution network improvement effect indicator evaluation standards through the acquisition module.

[0148] The second acquisition subunit is used to input the predicted value of the increased electricity sales and the predicted value of the increased load supply of the distribution network into the acquisition module, and to obtain the power supply level index of the distribution network and the corresponding evaluation standard of the power supply level index of the distribution network through the acquisition module.

[0149] The third acquisition subunit is used to input the medium-voltage line length and distribution transformer capacity into the acquisition module, and to obtain the distribution network scale indicators and the corresponding distribution network scale indicator evaluation standards through the acquisition module.

[0150] The fourth acquisition subunit is used to input the power supply reliability rate and the comprehensive line loss rate into the acquisition module, and to obtain the distribution network operation level indicators and the corresponding distribution network operation level indicator evaluation standards through the acquisition module.

[0151] The fifth acquisition subunit is used to input the return on net assets into the acquisition module, and the acquisition module obtains the distribution network profitability indicators and the corresponding distribution network profitability indicator evaluation standards.

[0152] In an exemplary embodiment, the second acquisition subunit is further configured to perform a weighted summation of the predicted value of increased electricity sales and the predicted value of increased load in the distribution network using a first weight pre-set in the acquisition module for the predicted value of increased electricity sales in the distribution network and a second weight pre-set in the acquisition module for the predicted value of increased load in the distribution network, thereby obtaining a power supply level index of the distribution network.

[0153] In one embodiment, the third acquisition subunit is further configured to perform a weighted summation of the medium-voltage line length and the distribution transformer capacity by using a third weight pre-set for the medium-voltage line length and a fourth weight pre-set for the distribution transformer capacity in the acquisition module, thereby obtaining the distribution network scale index.

[0154] In one embodiment, the fourth acquisition subunit is further configured to perform a weighted summation of the power supply reliability rate and the comprehensive line loss rate by using the fifth weight pre-set for the power supply reliability rate and the sixth weight pre-set for the comprehensive line loss rate in the acquisition module, so as to obtain the distribution network operation level index.

[0155] In one embodiment, the data acquisition module 501 is further configured to acquire historical implementation data of the distribution network project group to be determined, and historical implementation sub-data of the distribution network project to be determined; the historical implementation data includes the original distribution network operation status data before the operation of the distribution network project group to be determined, and the distribution network operation status data after the operation of the distribution network project group to be determined; the historical implementation sub-data includes the original distribution network operation status sub-data before the operation of the distribution network project to be determined, and the distribution network operation status sub-data after the operation of the distribution network project to be determined; based on the original distribution network operation status data and the distribution network operation status data, multiple distribution network improvement degree evaluation indicators are acquired, and based on the original distribution network operation status sub-data and the distribution network operation status sub-data, multiple distribution network improvement degree evaluation indicators are acquired. Data is collected to obtain multiple sub-distribution network improvement evaluation indicators. Using pre-set normalization coefficients, dimensionless processing is applied to each distribution network improvement evaluation indicator and sub-distribution network improvement evaluation indicator to obtain the processed distribution network improvement evaluation indicators and sub-distribution network improvement evaluation indicators. Based on the pre-set indicator weights for each distribution network improvement evaluation indicator, the processed distribution network improvement evaluation indicators, and the pre-set evaluation standards, a distribution network improvement effect evaluation index is obtained. Finally, based on the pre-set indicator weights for each sub-distribution network improvement evaluation indicator, the processed sub-distribution network improvement evaluation indicators, and the pre-set evaluation standards, a sub-distribution network improvement effect evaluation index is obtained.

[0156] The modules in the aforementioned power distribution network project priority determination device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0157] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores data on virtual resources to be allocated, distribution network improvement evaluation indices, sub-distribution improvement evaluation indices, predicted increases in distribution network electricity sales, predicted increases in distribution network load, medium-voltage line length, transformer capacity, power supply reliability, comprehensive line loss rate, and return on net assets. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a method for determining the priority of distribution network projects.

[0158] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0159] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the power distribution network project priority determination method of the above embodiment.

[0160] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the power distribution network project priority determination method of the above embodiment.

[0161] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the power distribution network project priority determination method of the above embodiments.

[0162] 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, data stored, data displayed, 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 the relevant data must comply with relevant regulations.

[0163] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory 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), magnetic 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. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0164] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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 application.

[0165] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for determining the priority of power distribution network projects, characterized in that, The method includes: The system acquires the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined, as well as the predicted value of the increased electricity sales, the predicted value of the increased load supply, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets for each user in the community; wherein, the community belongs to the region. The evaluation index of the distribution network improvement effect, the predicted value of the distribution network's increased electricity sales, the predicted value of the distribution network's increased load, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets are input into a pre-constructed virtual resource allocation ratio model. The virtual resource allocation ratio for each user in the aforementioned community is obtained through this model, including: The acquisition module in the virtual resource allocation ratio model obtains the distribution network indicators and corresponding evaluation standards for each user in the community. These distribution network indicators include indicators of distribution network improvement effectiveness, power supply level, scale, operation level, and profitability. The power distribution network improvement effect evaluation index is input into the acquisition module, and the power distribution network improvement effect index and the corresponding power distribution network improvement effect index evaluation standard are obtained through the acquisition module. The predicted increase in electricity sales and the predicted increase in load supply of the distribution network are input into the acquisition module, and the power supply level index of the distribution network and the corresponding evaluation standard of the power supply level index of the distribution network are obtained through the acquisition module. The medium-voltage line length and the distribution transformer capacity are input into the acquisition module, and the distribution network scale index and the corresponding distribution network scale index evaluation standard are obtained through the acquisition module. The power supply reliability rate and the comprehensive line loss rate are input into the acquisition module, and the distribution network operation level index and the corresponding distribution network operation level index evaluation standard are obtained through the acquisition module. Input the return on net assets into the acquisition module, and obtain the distribution network profitability indicators and the corresponding distribution network profitability indicator evaluation standards through the acquisition module; The power distribution network indicators and the corresponding power distribution network indicator evaluation criteria are input into the decision information acquisition module of the virtual resource allocation ratio partitioning model; Based on the distribution network indicators, the evaluation criteria for the distribution network indicators, and the pre-set indicator weights for the distribution network indicators, virtual resource allocation decision information is obtained through the decision information acquisition module. The virtual resource allocation decision information is input into the proportion determination module in the virtual resource allocation ratio division model, and the virtual resource allocation ratio of each user in the community is obtained through the proportion determination module. Based on the virtual resources to be allocated and the virtual resource allocation ratio, the allocated virtual resources for each of the distribution network projects to be determined are obtained, and based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index, the ranking decision information for each of the distribution network projects to be determined is obtained. Based on the sorting decision information and the preset virtual resource allocation constraints, the priority of each of the distribution network projects to be determined is determined.

2. The method according to claim 1, characterized in that, The step of inputting the predicted increase in electricity sales and the predicted increase in load supply of the distribution network into the acquisition module, and obtaining the power supply level index of the distribution network through the acquisition module, includes: By using the first weight pre-set for the predicted increase in electricity sales in the distribution network and the second weight pre-set for the predicted increase in load in the distribution network in the acquisition module, the predicted increase in electricity sales in the distribution network and the predicted increase in load in the distribution network are weighted and summed to obtain the power supply level index of the distribution network.

3. The method according to claim 1, characterized in that, The step of inputting the medium-voltage line length and the distribution transformer capacity into the acquisition module, and obtaining the distribution network scale indicators through the acquisition module, includes: By using the third weight pre-set for the medium-voltage line length and the fourth weight pre-set for the distribution transformer capacity in the acquisition module, the medium-voltage line length and the distribution transformer capacity are weighted and summed to obtain the distribution network scale index.

4. The method according to claim 1, characterized in that, The step of inputting the power supply reliability rate and the comprehensive line loss rate into the acquisition module, and obtaining the distribution network operation level indicators through the acquisition module, includes: By using the fifth weight pre-set for the power supply reliability rate and the sixth weight pre-set for the comprehensive line loss rate in the acquisition module, the power supply reliability rate and the comprehensive line loss rate are weighted and summed to obtain the power distribution network operation level index.

5. The method according to claim 1, characterized in that, The evaluation index of the improvement effect of the distribution network of the undetermined distribution network project group for community users and the evaluation index of the improvement effect of the sub-distribution network of each undetermined distribution network project are obtained through the following steps: The historical implementation data of the distribution network project group to be determined, and the historical implementation sub-data of the distribution network project to be determined are obtained; the historical implementation data includes the original distribution network operation status data before the operation of the distribution network project group to be determined, and the distribution network operation status data after the operation of the distribution network project group to be determined; the historical implementation sub-data includes the original distribution network operation status sub-data before the operation of the distribution network project to be determined, and the distribution network operation status sub-data after the operation of the distribution network project to be determined. Based on the original distribution network operation status data and the distribution network operation status data, multiple distribution network improvement evaluation indicators are obtained, and based on the original distribution network operation status sub-data and the distribution network operation status sub-data, multiple sub-distribution network improvement evaluation indicators are obtained. Using a pre-set normalization coefficient, the evaluation indicators for the improvement of the distribution network and the evaluation indicators for the improvement of the sub-distribution network are dimensionless, resulting in the processed evaluation indicators for the improvement of the distribution network and the evaluation indicators for the improvement of the sub-distribution network. Based on the pre-set indicator weights for each of the aforementioned distribution network improvement evaluation indicators, the processed distribution network improvement evaluation indicators, and the pre-set evaluation criteria, the distribution network improvement effect evaluation index is obtained. The sub-distribution network improvement effect evaluation index is obtained based on the pre-set index weights for each sub-distribution network improvement degree evaluation index, the processed sub-distribution network improvement degree evaluation index, and the pre-set evaluation criteria.

6. A device for determining the priority of power distribution network projects, characterized in that, The device includes: The data acquisition module is used to acquire the virtual resources to be allocated for users in the region, the evaluation index of the distribution network improvement effect of the distribution network project group to be determined for users in the community, and the evaluation index of the sub-distribution network improvement effect of each distribution network project to be determined, as well as the predicted value of the increased electricity sales, the predicted value of the increased load supply, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets for each user in the community; wherein, the community belongs to the region; The allocation ratio determination module is used to input the distribution network improvement effect evaluation index, the predicted value of increased electricity sales in the distribution network, the predicted value of increased load in the distribution network, the length of medium-voltage lines, the capacity of distribution transformers, the power supply reliability rate, the comprehensive line loss rate, and the return on net assets into a pre-constructed virtual resource allocation ratio division model. The module obtains the virtual resource allocation ratio for each user in the respective community through the virtual resource allocation ratio division model. This includes: obtaining the distribution network indicators and corresponding evaluation standards for each user in the respective community through an acquisition module in the virtual resource allocation ratio division model. The distribution network indicators include distribution network improvement effect indicators, distribution network power supply level indicators, distribution network scale indicators, distribution network operation level indicators, and distribution network profitability indicators. This includes: inputting the distribution network improvement effect evaluation index into the acquisition module, obtaining the distribution network improvement effect indicators and corresponding evaluation standards through the acquisition module; inputting the predicted value of increased electricity sales in the distribution network and the predicted value of increased load in the distribution network into the acquisition module, obtaining the distribution network power supply level indicators and corresponding evaluation standards through the acquisition module. The evaluation criteria for power supply level indicators are as follows: The medium-voltage line length and the distribution transformer capacity are input into the acquisition module, which then obtains the distribution network scale indicators and corresponding evaluation criteria. The power supply reliability rate and the comprehensive line loss rate are input into the acquisition module, which then obtains the distribution network operation level indicators and corresponding evaluation criteria. The return on net assets is input into the acquisition module, which then obtains the distribution network profitability indicators and corresponding evaluation criteria. The distribution network indicators and corresponding evaluation criteria are input into the decision information acquisition module of the virtual resource allocation ratio division model. Based on the distribution network indicators, the distribution network indicator evaluation criteria, and the pre-set indicator weights for the distribution network indicators, the decision information acquisition module obtains virtual resource allocation decision information. The virtual resource allocation decision information is input into the ratio determination module of the virtual resource allocation ratio division model, which then obtains the virtual resource allocation ratio for each user in the community. The ranking decision information acquisition module is used to obtain the allocated virtual resources for each of the distribution network projects to be determined based on the virtual resources to be allocated and the virtual resource allocation ratio, and to obtain the ranking decision information for each of the distribution network projects to be determined based on the allocated virtual resources and the sub-distribution network improvement effect evaluation index. The priority determination module is used to determine the priority of each of the distribution network projects to be determined based on the sorting decision information and the preset virtual resource allocation constraints.

7. The apparatus according to claim 6, characterized in that, The device further includes: The allocation ratio determination module is further used to perform a weighted summation of the predicted increase in electricity sales and the predicted increase in load in the distribution network using a first weight pre-set in the acquisition module for the predicted increase in electricity sales and a second weight pre-set in the acquisition module for the predicted increase in load in the distribution network, to obtain the power supply level index of the distribution network.

8. The apparatus according to claim 6, characterized in that, The device further includes: The allocation ratio determination module is further used to perform a weighted summation of the medium-voltage line length and the distribution transformer capacity using a third weight preset in the acquisition module for the medium-voltage line length and a fourth weight preset in the distribution transformer capacity, to obtain the distribution network scale index.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

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

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