Power grid infrastructure project transfer level prediction method and device

Abstract

The invention provides a power grid infrastructure project transfer level prediction method and device, and the method comprises the steps: carrying out the construction progress prediction based on a construction progress plan of each milestone node of each single project of a target power grid infrastructure project, and obtaining a construction progress prediction result; determining a target winter shutdown duration corresponding to the target power grid infrastructure project according to the region where the target power grid infrastructure project is located; correcting the construction progress prediction result according to the target winter shutdown duration to obtain a construction progress prediction result correction value; performing entry progress prediction based on the construction progress prediction result correction value and an entry progress prediction model of each item of cost of each single project in the target power grid infrastructure project to obtain an entry progress prediction result; and obtaining a transfer level prediction result of the target power grid infrastructure project according to the posting progress prediction result and the transfer reference of the target power grid infrastructure project. According to the invention, a more accurate transfer level prediction result of the power grid infrastructure project can be obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular, to a method and device for predicting the transfer of assets level of power grid infrastructure projects. Background Art

[0002] The full chain of investment and asset transfer is: start of construction, construction, commissioning, settlement, final accounts, and asset transfer. "Project asset transfer" refers to a way of allocating the project cost value on the financial accounts to the actual assets formed by the completion of the project according to certain rules. Predicting the transfer of assets level of power grid infrastructure projects is conducive to discovering and managing problem projects, thereby supporting the efficient transformation of the company's fixed assets.

[0003] However, the inventors found that: currently, when analyzing the data of investment and asset transfer of power grid infrastructure projects, on the one hand, due to the differences in construction regions and internal and external influencing factors of power grid infrastructure projects, the prediction of the construction progress of power grid infrastructure projects usually does not conform to the actual situation. On the other hand, the changes in project plans, engineering quantities, fluctuations in labor and prices during the construction process of power grid infrastructure projects also affect the prediction of the transfer of assets level of power grid infrastructure projects. Summary of the Invention

[0004] Embodiments of the present invention provide a method and device for predicting the transfer of assets level of power grid infrastructure projects to solve the problem of inaccurate prediction of the transfer of assets level of power grid infrastructure projects.

[0005] In a first aspect, embodiments of the present invention provide a method for predicting the transfer of assets level of power grid infrastructure projects, including:

[0006] Predicting the construction progress based on the construction progress plan of each milestone node of each individual project of the target power grid infrastructure project to obtain the construction progress prediction result of the target power grid infrastructure project;

[0007] Determining the winter shutdown duration corresponding to the target power grid infrastructure project according to the region where the target power grid infrastructure project is located, denoted as the target winter shutdown duration;

[0008] Correcting the construction progress prediction result according to the target winter shutdown duration to obtain a corrected value of the construction progress prediction result;

[0009] Predicting the posting progress based on the corrected value of the construction progress prediction result and the posting progress prediction model of each expense of each individual project in the target power grid infrastructure project to obtain the posting progress prediction result;

[0010] Obtaining the prediction result of the transfer of assets level of the target power grid infrastructure project according to the posting progress prediction result and the asset transfer benchmark of the target power grid infrastructure project.

[0011] In a possible implementation manner, determining the winter shutdown duration corresponding to the target grid infrastructure project according to the region where the target grid infrastructure project is located, denoted as the target winter shutdown duration, includes:

[0012] Obtain the construction period data of historical grid infrastructure projects in different regions;

[0013] Determine the winter shutdown duration corresponding to each region according to the construction period data of each region;

[0014] Select the winter shutdown duration corresponding to the region where the target grid infrastructure project is located from the winter shutdown durations corresponding to each region, denoted as the target winter shutdown duration.

[0015] In a possible implementation manner, the recorded progress prediction model includes a construction cost recording prediction model, an equipment cost recording prediction model, and other cost recording prediction models;

[0016] The construction cost recording prediction model is:

[0017]

[0018] Where J′ is the predicted result of the construction cost recording progress, T is the construction month of each individual project, JT1 is the first project payment settlement month, JT2 is the second project payment settlement month, JT3 is the project completion settlement month, JT4 is the project final settlement month, μ[X( JT1-JT2 )] is to take the average of X( JT1-JT2 )], X( JT1-JT2 ) is the correction value of the construction progress prediction result from the first project payment settlement month JT1 to the second project payment settlement month JT2, and X JT3 is the correction value of the construction progress prediction result of the project completion settlement month JT3;

[0019] The equipment cost recording prediction model is:

[0020]

[0021] Where S′ is the predicted result of the equipment cost recording progress, T is the construction month of each individual project, ST1 is the month when the first batch of equipment arrives at the site, ST2 is the month when the second batch of equipment arrives at the site, ST3 is the completion settlement month, ST4 is the project final settlement month, μ[X( ST1-ST2 )] is to take the average of X( ST1-ST2 )], and X( ST1-ST2 ) is the correction value of the construction progress prediction result from the month when the first batch of equipment arrives at the site ST1 to the month when the second batch of equipment arrives at the site ST2;

[0022] The other cost recording prediction model is:

[0023]

[0024] Among them, Q' is the prediction result of the progress of other expenses recorded, and Q 开工 is the progress of the preliminary expenses recorded, T is the construction month of each individual project, QT1 is the production start month, QT2 is the completion settlement month, QT3 is the project final accounts month, and X T is the correction value of the prediction result of the construction progress of the construction month of each individual project.

[0025] In a possible implementation manner, the process of determining the capital transfer benchmark of the target power grid infrastructure project includes:

[0026] Obtain the balance rate data of each expense of each individual project of the historical power grid infrastructure projects of each voltage level;

[0027] Select, from each of the balance rate data, the balance rate data of each expense with the same voltage level and the same individual project as the target power grid infrastructure project as the target balance rate data;

[0028] Calculate the capital transfer benchmark of each individual project in the target power grid infrastructure project based on the target balance rate data and the estimated or contract cost of each expense of each individual project in the target power grid infrastructure project;

[0029] Calculate the capital transfer benchmark of the target power grid infrastructure project based on the capital transfer benchmarks of all individual projects in the target power grid infrastructure project.

[0030] In a possible implementation manner, the capital transfer benchmark of each individual project includes the capital transfer benchmark of the construction engineering cost and the installation engineering cost of each individual project, the capital transfer benchmark of the equipment purchase cost, and the capital transfer benchmark of other expenses;

[0031] After calculating the capital transfer benchmark of each individual project in the target power grid infrastructure project based on the target balance rate data and the estimated or contract cost of each expense of each individual project in the target power grid infrastructure project, it further includes:

[0032] Obtain the actual project quantity change data, labor cost change data, and equipment price change data of each individual project during the construction process of the target power grid infrastructure project;

[0033] Correct the capital transfer benchmark of the construction engineering cost and the installation engineering cost of each individual project according to each of the actual project quantity change data and each of the labor cost change data to obtain the capital construction engineering cost benchmark of each individual project;

[0034] Correct the capital transfer benchmark of the equipment purchase cost of each individual project according to each of the equipment price change data to obtain the equipment cost benchmark of each individual project;

[0035] According to the construction and installation project cost benchmark, the equipment cost benchmark, and the capital transfer benchmark of other expenses for each individual project, calculate the corrected value of the capital transfer benchmark for each individual project in the target power grid infrastructure project;

[0036] The calculation of the capital transfer benchmark for the target power grid infrastructure project based on the capital transfer benchmarks of all individual projects in the target power grid infrastructure project includes:

[0037] Calculate the capital transfer benchmark for the target power grid infrastructure project based on the corrected values of the capital transfer benchmarks of all individual projects in the target power grid infrastructure project.

[0038] In a possible implementation, correct the capital transfer benchmarks for the construction project cost and installation project cost of each individual project according to each actual project quantity change data and each labor cost change data to obtain the construction and installation project cost benchmark for each individual project, including:

[0039] According to J = j * (1 - c j ) * (1 + x%) * (1 + y%), obtain the construction and installation project cost benchmark for each individual project;

[0040] Where J is the construction and installation project cost benchmark for each individual project, j is the estimated or contract cost of the construction project cost and installation project cost for each individual project, c j is the target surplus rate data for the construction project cost and installation project cost of each individual project, j * (1 - c j ) is the capital transfer benchmark for the construction project cost and installation project cost of each individual project, x is each labor cost change data, and y is each actual project quantity change data.

[0041] In a possible implementation, correct the capital transfer benchmark for the equipment purchase cost of each individual project according to each equipment price change data to obtain the equipment cost benchmark for each individual project, including:

[0042] According to S = s * (1 - c s ) * (1 + z%), obtain the equipment cost benchmark for each individual project;

[0043] Where S is the equipment cost benchmark for each individual project, s is the estimated or contract cost of the equipment purchase cost for each individual project, c s is the target surplus rate data for the equipment purchase cost of each individual project, s * (1 - c s ) is the capital transfer benchmark for the equipment purchase cost of each individual project, and z is each equipment price change data.

[0044] In a possible implementation, according to the construction and installation project cost benchmark, the equipment cost benchmark, and the capital transfer benchmark of other expenses for each individual project, a capital transfer benchmark correction value for each individual project in the target power grid infrastructure project is calculated, including:

[0045] According to R = J + S + Q, calculate the capital transfer benchmark correction value for each individual project in the target power grid infrastructure project;

[0046] Wherein, R is the capital transfer benchmark correction value for each individual project in the target power grid infrastructure project, J is the construction and installation project cost benchmark for each individual project, S is the equipment cost benchmark for each individual project, and Q is the capital transfer benchmark of other expenses.

[0047] In a possible implementation, the method for predicting the capital transfer level of the power grid infrastructure project further includes:

[0048] According to the method for obtaining the prediction result of the capital transfer level of the target power grid infrastructure project, obtain the prediction result of the capital transfer level of each power grid infrastructure project at the unit dimension;

[0049] Compare the prediction result of the capital transfer level of each power grid infrastructure project with the target value of the capital transfer level, and determine the risk projects at the unit dimension according to the comparison result.

[0050] In a second aspect, an embodiment of the present invention provides a device for predicting the capital transfer level of a power grid infrastructure project, including:

[0051] A construction progress prediction module, configured to perform construction progress prediction based on the construction progress plan of each milestone node of each individual project of the target power grid infrastructure project, and obtain the construction progress prediction result of the target power grid infrastructure project;

[0052] A construction progress impact determination module, configured to determine the winter shutdown duration corresponding to the target power grid infrastructure project according to the region where the target power grid infrastructure project is located, denoted as the target winter shutdown duration;

[0053] A construction progress correction module, configured to correct the construction progress prediction result according to the target winter shutdown duration to obtain a corrected value of the construction progress prediction result;

[0054] An entry progress prediction module, configured to perform entry progress prediction based on the corrected value of the construction progress prediction result and the entry progress prediction model of each expense of each individual project in the target power grid infrastructure project, and obtain the entry progress prediction result;

[0055] A capital transfer level prediction module, configured to obtain the prediction result of the capital transfer level of the target power grid infrastructure project according to the entry progress prediction result and the capital transfer benchmark of the target power grid infrastructure project.

[0056] An embodiment of the present invention provides a method and device for predicting the capital transfer level of a power grid infrastructure project. First, based on the construction progress plan of each milestone node of each individual project of the target power grid infrastructure project, a construction progress prediction is carried out to obtain the construction progress prediction result of the target power grid infrastructure project. Then, according to the region where the target power grid infrastructure project is located, the winter shutdown duration corresponding to the target power grid infrastructure project is determined, denoted as the target winter shutdown duration. Thus, the construction progress prediction result is corrected according to the target winter shutdown duration to obtain the corrected value of the construction progress prediction result. Furthermore, based on the corrected value of the construction progress prediction result and the capital entry progress prediction model of each item of cost of each individual project in the target power grid infrastructure project, a capital entry progress prediction is carried out to obtain the capital entry progress prediction result. According to the capital entry progress prediction result and the capital transfer benchmark of the target power grid infrastructure project, the capital transfer level prediction result of the target power grid infrastructure project is obtained. Therefore, by considering factors such as winter shutdown and rolling prediction of the project construction progress, a more realistic corrected value of the construction progress prediction result is obtained, which helps to improve the accuracy of the capital transfer level prediction of the power grid infrastructure project, stabilize the capital transfer level, better support the efficient transformation of the company's fixed assets, guide the compliance, reasonable construction and capital entry of the project, and assist in the efficient achievement of the capital transfer target. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0058] Figure 1 is the implementation flowchart of the method for predicting the capital transfer level of the power grid infrastructure project provided by the embodiment of the present invention;

[0059] Figure 2 is the architecture diagram of the project capital transfer level prediction model provided by the embodiment of the present invention;

[0060] Figure 3 is the construction progress prediction flowchart provided by the embodiment of the present invention;

[0061] Figure 4 is the schematic diagram of the construction and installation cost capital entry prediction model of the main transformer expansion project provided by the embodiment of the present invention;

[0062] Figure 5 is the schematic diagram of the key parameter setting of the construction and installation cost capital entry prediction model of the main transformer expansion project provided by the embodiment of the present invention;

[0063] Figure 6 is the schematic diagram of the equipment cost capital entry prediction model of the main transformer expansion project provided by the embodiment of the present invention;

[0064] Figure 7 It is a schematic diagram of key parameter settings for the equipment cost accounting prediction model of the main transformer expansion project provided by the embodiment of the present invention;

[0065] Figure 8 It is a schematic diagram of the other cost accounting prediction model of the main transformer expansion project provided by the embodiment of the present invention;

[0066] Figure 9 It is a schematic diagram of key parameter settings for the other cost accounting prediction model of the main transformer expansion project provided by the embodiment of the present invention;

[0067] Figure 10 It is a schematic diagram of the power grid infrastructure project capital conversion level prediction device provided by the embodiment of the present invention. Detailed implementation manners

[0068] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present invention.

[0069] To make the purpose, technical solutions, and advantages of the present invention clearer, the following will be described through specific embodiments with reference to the accompanying drawings.

[0070] Figure 1 It is a flowchart for implementing the power grid infrastructure project capital conversion level prediction method provided by the embodiment of the present invention, which is described in detail as follows:

[0071] Step S101, based on the construction progress plan of each milestone node of each individual project of the target power grid infrastructure project, perform construction progress prediction to obtain the construction progress prediction result of the target power grid infrastructure project.

[0072] Exemplarily, the target power grid infrastructure project is a power grid infrastructure project for which the capital conversion level is to be predicted, and the individual projects of the power grid infrastructure project include but are not limited to the main transformer new construction project, the main transformer expansion project, the overhead line project, and the cable line project.

[0073] Exemplarily, the milestone nodes of the substation project can include civil engineering, equipment installation, and equipment commissioning, the milestone nodes of the line project can include foundation construction, tower erection, and wire stringing, and the milestone nodes of the cable line project can include channel, laying, and commissioning.

[0074] In this embodiment, according to the general management logic of the construction progress of grid infrastructure projects, the construction framework of the construction progress prediction model is refined, that is, the construction progress prediction model is constructed according to the framework of "monthly construction progress prediction of milestone nodes - monthly construction progress prediction of individual projects - monthly construction progress prediction of projects".

[0075] Exemplarily, based on the construction progress plan of each milestone node of each individual project of the target grid infrastructure project, it can be obtained that:

[0076] Monthly construction progress prediction value of each milestone node = monthly construction period / total planned construction period of the milestone node.

[0077] Monthly construction progress prediction value of each individual project = ∑(monthly construction progress prediction value of each milestone node × weight of each milestone node).

[0078] Monthly construction progress prediction value of the target grid infrastructure project = ∑(monthly construction progress prediction value of each individual project × weight of each individual project).

[0079] Among them, the construction progress plan can be determined according to the reasonable construction period, and the reasonable construction period can be determined by referring to the established milestone plan of project management personnel or combining historical project duration data, and the corresponding reasonable construction period can be determined separately according to different voltage levels and individual project types.

[0080] Among them, the weight of each milestone node and the weight of each individual project can be the weights corresponding to the individual project and the milestone node in the infrastructure control system, such as the project cost weight of the individual project and the cost weight of the milestone node.

[0081] Step S102: Determine the winter shutdown duration corresponding to the target grid infrastructure project according to the region where the target grid infrastructure project is located, and record it as the target winter shutdown duration.

[0082] Optionally, the duration data of historical grid infrastructure projects in different regions can be obtained; according to the duration data of each region, the winter shutdown duration corresponding to each region can be determined; from the winter shutdown durations corresponding to each region, the winter shutdown duration corresponding to the region where the target grid infrastructure project is located is selected and recorded as the target winter shutdown duration.

[0083] In this embodiment, since the construction progress prediction model refined according to the general management logic of the construction progress of grid infrastructure projects does not consider the influence of other special project types and winter shutdown and other factors, it only predicts the construction progress on the condition that the project is not affected by any construction obstruction factors and is assumed to be able to be executed normally according to the plan. In order to make the construction progress prediction more in line with the actual situation, the influence of the winter shutdown factor on the construction progress is considered.

[0084] Among them, in order to quantify the differences in the impact of winter shutdowns on construction progress in different regions, relevant samples can be collected to obtain the construction period data of historical power grid infrastructure projects in different regions, and then based on the construction period data of each region, the winter shutdown characteristics of different regions can be identified to obtain the winter shutdown duration of each region.

[0085] For example, based on the construction period data of historical power grid infrastructure projects in different regions, it can be analyzed that the winter shutdown time in region 1 is 38 days, the winter shutdown time in region 2 is 30 days, and the winter shutdown time in region 3 is 29 days. The winter shutdown time in this embodiment is only an example and does not limit the winter shutdown time in each region.

[0086] Step S103, correcting the construction progress prediction result according to the target winter shutdown duration to obtain a correction value of the construction progress prediction result.

[0087] In this embodiment, on the basis of the general construction progress prediction model, the winter shutdown characteristics of different project types and different construction areas are taken into consideration, and the construction progress prediction results are corrected using the winter shutdown duration as a differentiated parameter to obtain a construction progress prediction result correction value that is more in line with reality.

[0088] Among them, combined Figure 2 In this embodiment, the construction progress forecast result is corrected, which can be done beforehand (that is, before the construction of the target power grid infrastructure project) or during the construction (that is, during the construction of the target power grid infrastructure project).

[0089] For example, Figure 3 As shown, based on this embodiment, when predicting the construction progress during the project, the current milestone node can be determined first; then, based on the current milestone node, combined with a reasonable construction schedule, and according to the difference principle, the subsequent milestone nodes can be predicted; then, it can be determined whether winter shutdown is involved. If it is involved, the milestone node schedule of the single project is obtained after considering the delayed construction period; if it is not involved, the milestone node schedule of the single project is directly obtained; then, based on the milestone node scheduling, the monthly construction progress forecast value of the milestone plan node (that is, the monthly construction progress forecast value of each milestone node), the monthly construction progress forecast value of the single project (that is, the monthly construction progress forecast value of each single project), and the monthly construction progress forecast value of the project level (that is, the monthly construction progress forecast value of the target power grid infrastructure project) are obtained, thereby outputting the monthly construction progress forecast results.

[0090] Step S104, performing accounting progress prediction based on the construction progress prediction result correction value and the accounting progress prediction model of each expense of each single project in the target power grid infrastructure project to obtain the accounting progress prediction result.

[0091] Optionally, the incoming payment progress prediction model may include a construction cost incoming payment prediction model, an equipment cost incoming payment prediction model, and an other cost incoming payment prediction model.

[0092] Among them, the construction cost incoming payment prediction model is:

[0093]

[0094] Among them, J′ is the prediction result of the construction cost incoming payment progress, T is the construction month of each individual project, JT1 is the first project payment settlement month, JT2 is the second project payment settlement month, JT3 is the project completion settlement month, JT4 is the project final accounts month, μ[X( JT1-JT2 )] is to take the average of X( JT1-JT2 )], X( JT1-JT2 ) is the correction value of the construction progress prediction result from the first project payment settlement month JT1 to the second project payment settlement month JT2, and X JT3 is the correction value of the construction progress prediction result of the project completion settlement month JT3.

[0095] Among them, the equipment cost incoming payment prediction model is:

[0096]

[0097] Among them, S′ is the prediction result of the equipment cost incoming payment progress, T is the construction month of each individual project, ST1 is the first batch of equipment arrival month, ST2 is the second batch of equipment arrival month, ST3 is the completion settlement month, ST4 is the project final accounts month, μ[X( ST1-ST2 )] is to take the average of X( ST1-ST2 )], and X( ST1-ST2 ) is the correction value of the construction progress prediction result from the first batch of equipment arrival month ST1 to the second batch of equipment arrival month ST2.

[0098] Among them, the other cost incoming payment prediction model is:

[0099]

[0100] Among them, Q′ is the prediction result of the other cost incoming payment progress, Q 开工 is the incoming payment progress of the upfront cost, T is the construction month of each individual project, QT1 is the production start month, QT2 is the completion settlement month, QT3 is the project final accounts month, and X T is the correction value of the construction progress prediction result of each individual project's construction month.

[0101] Exemplarily, the construction cost incoming payment prediction model of the main transformer expansion project can be as Figure 4 shown, and the key parameter settings of the construction cost incoming payment prediction model of the main transformer expansion project can refer to Figure 5 . The equipment cost incoming payment prediction model of the main transformer expansion project can be as Figure 6As shown, the key parameter settings of the equipment cost entry prediction model for the main transformer expansion project can refer to Figure 7 . The other cost entry prediction model for the main transformer expansion project can be as Figure 8 shown. The key parameter settings of the other cost entry prediction model for the main transformer expansion project can refer to Figure 9 . The cost entry prediction models for other individual projects such as the main transformer new project, overhead line project, and cable line project can refer to the cost entry prediction models for the main transformer expansion project.

[0102] This embodiment can achieve a long-term prediction of the entry progress, and can study the entry progress trend by project type and four types of costs, and combine the settlement requirements stipulated in the contract, consider the coupling relationship between the entry and construction progress of different projects, and flexibly correct the entry prediction results.

[0103] Step S105: Obtain the predicted result of the capital transfer level of the target grid infrastructure project according to the predicted result of the entry progress and the capital transfer benchmark of the target grid infrastructure project.

[0104] Optionally, the determination process of the capital transfer benchmark of the target grid infrastructure project may include:

[0105] Obtain the balance rate data of each cost item of each individual project of the historical grid infrastructure projects at each voltage level.

[0106] Select, from each balance rate data, the balance rate data of each cost item with the same voltage level and the same individual project as the target grid infrastructure project as the target balance rate data.

[0107] Calculate the capital transfer benchmark of each individual project in the target grid infrastructure project according to the target balance rate data and the estimated or contract cost of each cost item of each individual project in the target grid infrastructure project.

[0108] Calculate the capital transfer benchmark of the target grid infrastructure project according to the capital transfer benchmarks of all individual projects in the target grid infrastructure project.

[0109] Optionally, the capital transfer benchmark of each individual project may include the capital transfer benchmarks of the construction engineering cost and installation engineering cost of each individual project, the capital transfer benchmark of the equipment purchase cost, and the capital transfer benchmark of other costs.

[0110] After calculating the capital transfer benchmark of each individual project in the target grid infrastructure project according to the target balance rate data and the estimated or contract cost of each cost item of each individual project in the target grid infrastructure project, it may further include:

[0111] Obtain the actual engineering quantity change data, labor cost change data, and equipment price change data of each individual project during the construction process of the target grid infrastructure project.

[0112] Revise the capital transfer benchmark for the construction project cost and installation project cost of each individual project according to each actual project quantity change data and each labor cost change data, and obtain the capital construction project cost benchmark for each individual project.

[0113] Revise the capital transfer benchmark for the equipment purchase cost of each individual project according to each equipment price change data, and obtain the equipment cost benchmark for each individual project.

[0114] Calculate the revised value of the capital transfer benchmark for each individual project in the target power grid infrastructure project according to the capital construction project cost benchmark, equipment cost benchmark and capital transfer benchmark of other expenses for each individual project.

[0115] Correspondingly, calculate the capital transfer benchmark of the target power grid infrastructure project according to the capital transfer benchmarks of all individual projects in the target power grid infrastructure project, which may include:

[0116] Calculate the capital transfer benchmark of the target power grid infrastructure project according to the revised values of the capital transfer benchmarks of all individual projects in the target power grid infrastructure project.

[0117] Exemplarily, the capital construction project cost benchmark for each individual project can be obtained according to J = j * (1 - c j ) * (1 + x%) * (1 + y%).

[0118] Wherein, J is the capital construction project cost benchmark for each individual project, j is the estimated or contract cost of the construction project cost and installation project cost of each individual project, c j is the target surplus rate data of the construction project cost and installation project cost of each individual project, and j * (1 - c j ) is the capital transfer benchmark of the construction project cost and installation project cost of each individual project, x is the labor cost change data of each individual project, and y is the actual project quantity change data of each individual project.

[0119] Exemplarily, the equipment cost benchmark for each individual project can be obtained according to S = s * (1 - c s ) * (1 + z%).

[0120] Wherein, S is the equipment cost benchmark for each individual project, s is the estimated or contract cost of the equipment purchase cost of each individual project, c s is the target surplus rate data of the equipment purchase cost of each individual project, and s * (1 - c s ) is the capital transfer benchmark of the equipment purchase cost of each individual project, and z is the equipment price change data of each individual project.

[0121] Exemplarily, the revised value of the capital transfer benchmark for each individual project in the target power grid infrastructure project can be calculated according to R = J + S + Q.

[0122] Among them, R is the revised value of the capital transfer benchmark for each individual project in the target power grid infrastructure project, J is the benchmark of the construction and installation project cost for each individual project, S is the benchmark of the equipment cost for each individual project, and Q is the capital transfer benchmark for other expenses.

[0123] Exemplarily, during the revision process, record the increase rate of labor cost as x%, and the change rate of project quantity as y%. Then the benchmark of the construction and installation project cost J = the budget estimate of the construction and installation project cost * (1 - the surplus rate parameter) * (1 + x%) * (1 + y%).

[0124] Record the increase rate of equipment price as z%. The benchmark of the equipment cost S = the budget estimate of the equipment cost * (1 - the surplus rate parameter) * (1 + z%).

[0125] The capital transfer benchmark = the benchmark of the construction and installation project cost J + the benchmark of the equipment cost S + the benchmark of other expenses Q. Among them, Q = the budget estimate of other expenses * the surplus rate parameter.

[0126] In this embodiment, it can be known from the data analysis results that: the capital transfer level of the project is the final accounts entry level. On this basis, as Figure 2 shown, for projects of 35 kV and above, historical surplus can be input in advance to calculate the capital transfer benchmark. Then input the construction period and the law of capital transfer time sequence to complete the construction execution deduction. Then input the settlement regulations and the historical entry law to complete the entry execution deduction. Finally, output the prediction results of the capital transfer time sequence and level. And during the process, influence parameters such as design changes and price fluctuations can be input to correct the capital transfer benchmark. Input parameters such as winter shutdown and policy impacts to correct the construction execution situation. Input influence parameters such as settlement lag and material inventory to correct the entry execution. Finally, output the correction results of the capital transfer time sequence and level. Thus, the effect of predicting the final capital transfer situation in the early and middle stages of project construction can be achieved.

[0127] Optionally, for the method for predicting the capital transfer level of the power grid infrastructure project provided in this embodiment, the prediction results of the capital transfer level of each power grid infrastructure project at the unit dimension can also be obtained according to the method for obtaining the prediction results of the capital transfer level of the target power grid infrastructure project; compare the prediction results of the capital transfer level of each power grid infrastructure project with the target value of the capital transfer level, and determine the risk projects at the unit dimension according to the comparison results.

[0128] In this embodiment, based on the prediction of the capital transfer level of the power grid infrastructure project at the project level, the individual projects put into production in the predicted year at the unit level are screened, and the final accounts entry amounts of the individual projects expected to be put into production in the predicted year are summarized, and the predicted annual capital transfer amount (or the capital transfer level) at the unit level can be obtained.

[0129] On the basis of completing the prediction of the capital transfer level, an investment and capital transfer monitoring index system can be constructed to assist in problem discovery and governance.

[0130] After discovering a project with a capital transfer level lower than expected, it is possible to analyze the reasons for the project's capital transfer level being lower than expected based on Monitoring Dimension 1: Timeliness of commissioning (projects that should have been commissioned in the current year but were not actually commissioned), specifically including: lagging construction progress, lagging material supply, and completed projects not reported for commissioning in a timely manner. Monitoring Dimension 2: Rationality of recording (whether the recording is completed in a timely and compliant manner), specifically including lagging recording of construction costs, abnormal write-off of material costs, and lagging recording of other costs. Then, apply the unit-level capital transfer level deduction model to predict the unit-level capital transfer level within the regulatory cycle, compare the predicted value with the target value output by the capital transfer level deduction model, monitor and give early warnings for the company's voltage-level and type-based recording and commissioning situations, and make timely corrections to ensure the achievement of the capital transfer target; for the problems existing in the actual implementation process of investment capital transfer, put forward optimization suggestions for the internal management system of project recording, commissioning, and capital transfer.

[0131] In the embodiment of the present invention, first, based on the construction progress plan of each milestone node of each individual project of the target power grid infrastructure project, the construction progress prediction is carried out to obtain the construction progress prediction result of the target power grid infrastructure project; then, according to the region where the target power grid infrastructure project is located, the winter shutdown duration corresponding to the target power grid infrastructure project is determined, denoted as the target winter shutdown duration; thus, the construction progress prediction result is corrected according to the target winter shutdown duration to obtain the corrected value of the construction progress prediction result; furthermore, based on the corrected value of the construction progress prediction result and the recording progress prediction model of each item of cost of each individual project in the target power grid infrastructure project, the recording progress prediction is carried out to obtain the recording progress prediction result; according to the recording progress prediction result and the capital transfer benchmark of the target power grid infrastructure project, the capital transfer level prediction result of the target power grid infrastructure project is obtained. Therefore, by considering factors such as winter shutdown and rollingly predicting the project construction progress, a more realistic corrected value of the construction progress prediction result can be obtained, which helps to improve the accuracy of the capital transfer level prediction of the power grid infrastructure project, stabilize the capital transfer level, better support the efficient conversion of the company's fixed assets, guide the compliant and reasonable construction and recording of the project, and assist in the efficient achievement of the capital transfer target.

[0132] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0133] The following is the device embodiment of the present invention. For the details not described in detail, reference can be made to the corresponding method embodiments above.

[0134] Figure 10 The structural schematic diagram of the device for predicting the capital transfer level of the power grid infrastructure project provided by the embodiment of the present invention is shown. For the sake of convenience of description, only the parts related to the embodiment of the present invention are shown and are described in detail as follows:

[0135] AsFigure 10 As shown in Figure 10 , the device for predicting the capital transfer level of power grid infrastructure projects includes: a construction progress prediction module 101, a construction progress impact determination module 102, a construction progress correction module 103, a posting progress prediction module 104, and a capital transfer level prediction module 105.

[0136] The construction progress prediction module 101 is used to predict the construction progress based on the construction progress plan of each milestone node of each individual project of the target power grid infrastructure project, and obtain the construction progress prediction result of the target power grid infrastructure project;

[0137] The construction progress impact determination module 102 is used to determine the winter shutdown duration corresponding to the target power grid infrastructure project according to the region where the target power grid infrastructure project is located, denoted as the target winter shutdown duration;

[0138] The construction progress correction module 103 is used to correct the construction progress prediction result according to the target winter shutdown duration to obtain a corrected value of the construction progress prediction result;

[0139] The posting progress prediction module 104 is used to predict the posting progress based on the corrected value of the construction progress prediction result and the posting progress prediction model of each expense of each individual project in the target power grid infrastructure project, and obtain the posting progress prediction result;

[0140] The capital transfer level prediction module 105 is used to obtain the capital transfer level prediction result of the target power grid infrastructure project according to the posting progress prediction result and the capital transfer benchmark of the target power grid infrastructure project.

[0141] In the embodiment of the present invention, first, the construction progress prediction is carried out based on the construction progress plan of each milestone node of each individual project of the target power grid infrastructure project to obtain the construction progress prediction result of the target power grid infrastructure project; then, according to the region where the target power grid infrastructure project is located, the winter shutdown duration corresponding to the target power grid infrastructure project is determined, denoted as the target winter shutdown duration; thus, the construction progress prediction result is corrected according to the target winter shutdown duration to obtain a corrected value of the construction progress prediction result; furthermore, the posting progress prediction is carried out based on the corrected value of the construction progress prediction result and the posting progress prediction model of each expense of each individual project in the target power grid infrastructure project to obtain the posting progress prediction result; according to the posting progress prediction result and the capital transfer benchmark of the target power grid infrastructure project, the capital transfer level prediction result of the target power grid infrastructure project is obtained. Therefore, factors such as winter shutdown are considered to predict the project construction progress in a rolling manner, and a more realistic corrected value of the construction progress prediction result is obtained. Furthermore, it helps to improve the accuracy of predicting the capital transfer level of power grid infrastructure projects, stabilize the capital transfer level, better support the efficient conversion of the company's fixed assets, guide the compliance, reasonable construction and posting of projects, and assist in the efficient achievement of the capital transfer target.

[0142] In a possible implementation, the construction progress impact determination module 102 can be used to obtain the construction period data of historical power grid infrastructure projects in different regions; determine the winter shutdown duration corresponding to each region according to the construction period data of each region; and select, from the winter shutdown durations corresponding to each region, the winter shutdown duration corresponding to the region where the target power grid infrastructure project is located, denoted as the target winter shutdown duration.

[0143] In a possible implementation, the recorded progress prediction model includes a construction and installation cost recorded progress prediction model, an equipment cost recorded progress prediction model, and an other cost recorded progress prediction model;

[0144] The construction and installation cost recorded progress prediction model is:

[0145]

[0146] where J′ is the predicted result of the construction and installation cost recorded progress, T is the construction month of each individual project, JT1 is the first project payment settlement month, JT2 is the second project payment settlement month, JT3 is the project completion settlement month, JT4 is the project final settlement month, μ[X( JT1-JT2 )] is the average of X( JT1-JT2 )], X( JT1-JT2 ) is the correction value of the construction progress prediction result from the first project payment settlement month JT1 to the second project payment settlement month JT2, and X JT3 is the correction value of the construction progress prediction result of the project completion settlement month JT3;

[0147] The equipment cost recorded progress prediction model is:

[0148]

[0149] where S′ is the predicted result of the equipment cost recorded progress, T is the construction month of each individual project, ST1 is the first batch of equipment arrival month, ST2 is the second batch of equipment arrival month, ST3 is the completion settlement month, ST4 is the project final settlement month, μ[X( ST1-ST2 )] is the average of X( ST1-ST2 )], and X( ST1-ST2 ) is the correction value of the construction progress prediction result from the first batch of equipment arrival month ST1 to the second batch of equipment arrival month ST2;

[0150] The other cost recorded progress prediction model is:

[0151]

[0152] where Q′ is the predicted result of the other cost recorded progress, Q 开工 is the recorded progress of the upfront cost, T is the construction month of each individual project, QT1 is the commissioning month, QT2 is the completion settlement month, QT3 is the project final settlement month, and X TThe revised value of the construction progress prediction result for each monthly construction of a single project.

[0153] In a possible implementation, the capital transfer level prediction module 105 can also be used to obtain the balance rate data of each expense item of each historical power grid infrastructure project at each voltage level for each single project; select, from each of the balance rate data, the balance rate data of each expense item with the same voltage level and the same single project as the target power grid infrastructure project as the target balance rate data; calculate the capital transfer benchmark for each single project in the target power grid infrastructure project based on the target balance rate data and the budget estimate or contract cost of each expense item of each single project in the target power grid infrastructure project; and calculate the capital transfer benchmark of the target power grid infrastructure project based on the capital transfer benchmarks of all single projects in the target power grid infrastructure project.

[0154] In a possible implementation, the capital transfer benchmark for each single project includes the capital transfer benchmarks for the construction engineering cost and installation engineering cost of each single project, the capital transfer benchmark for the equipment purchase cost, and the capital transfer benchmark for other expenses.

[0155] The capital transfer level prediction module 105 can also be used to obtain the actual engineering quantity change data, labor cost change data, and equipment price change data of each single project during the construction of the target power grid infrastructure project; revise the capital transfer benchmarks for the construction engineering cost and installation engineering cost of each single project based on each of the actual engineering quantity change data and each of the labor cost change data to obtain the construction and installation engineering cost benchmark for each single project; revise the capital transfer benchmark for the equipment purchase cost of each single project based on each of the equipment price change data to obtain the equipment cost benchmark for each single project; calculate the revised value of the capital transfer benchmark for each single project in the target power grid infrastructure project based on the construction and installation engineering cost benchmark, the equipment cost benchmark, and the capital transfer benchmark for other expenses of each single project; and calculate the capital transfer benchmark of the target power grid infrastructure project based on the revised values of the capital transfer benchmarks of all single projects in the target power grid infrastructure project.

[0156] In a possible implementation, the capital transfer level prediction module 105 can be used to obtain the construction and installation engineering cost benchmark for each single project according to J = j * (1 - c j ) * (1 + x%) * (1 + y%).

[0157] Where J is the construction and installation engineering cost benchmark for each single project, j is the budget estimate or contract cost of the construction engineering cost and installation engineering cost of each single project, c j is the target balance rate data of the construction engineering cost and installation engineering cost of each single project, and j * (1 - c j) is the capital transfer benchmark for the construction cost and installation cost of each individual project, x is the change data of each human cost, and y is the change data of each actual project quantity.

[0158] In a possible implementation, the capital transfer level prediction module 105 can be used to obtain the equipment cost benchmark for each individual project according to S = s*(1 - c s )*(1 + z%);

[0159] where S is the equipment cost benchmark for each individual project, s is the estimated or contract cost of the equipment purchase for each individual project, c s is the target balance rate data of the equipment purchase cost for each individual project, s*(1 - c s ) is the capital transfer benchmark of the equipment purchase cost for each individual project, and z is the change data of each equipment price.

[0160] In a possible implementation, the capital transfer level prediction module 105 can be used to calculate the capital transfer benchmark correction value for each individual project in the target power grid infrastructure project according to R = J + S + Q;

[0161] where R is the capital transfer benchmark correction value for each individual project in the target power grid infrastructure project, J is the construction and installation project cost benchmark for each individual project, S is the equipment cost benchmark for each individual project, and Q is the capital transfer benchmark of other costs.

[0162] In a possible implementation, the capital transfer level prediction module 105 can also be used to obtain the capital transfer level prediction result of each power grid infrastructure project at the unit dimension according to the method of obtaining the capital transfer level prediction result of the target power grid infrastructure project; compare the capital transfer level prediction result of each power grid infrastructure project with the capital transfer level target value, and determine the risk projects at the unit dimension according to the comparison result.

[0163] In the above embodiments, the descriptions of the respective embodiments have their own focuses. For parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0164] Those of ordinary skill in the art can realize that the templates, units, and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0165] If the above-mentioned module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above-mentioned method embodiments of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned method embodiments for predicting the capital transfer level of each power grid infrastructure project can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0166] The above-mentioned embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for predicting the capital transfer level of power grid infrastructure projects, characterized in that: include: Based on the construction schedule of each milestone node of each single project of the target power grid infrastructure project, a construction progress forecast is performed to obtain a construction progress forecast result of the target power grid infrastructure project; According to the region where the target power grid infrastructure project is located, the winter shutdown duration corresponding to the target power grid infrastructure project is determined, which is recorded as the target winter shutdown duration; Correcting the construction progress forecast result according to the target winter shutdown duration to obtain a correction value of the construction progress forecast result; Based on the construction progress forecast result correction value and the accounting progress forecast model of each expense of each single project in the target power grid infrastructure project, an accounting progress forecast is performed to obtain an accounting progress forecast result; According to the forecast result of the progress of the account entry and the capital transfer benchmark of the target power grid infrastructure project, the forecast result of the capital transfer level of the target power grid infrastructure project is obtained.

2. The method for predicting the capital transfer level of power grid infrastructure projects according to claim 1, characterized in that: Determining the winter shutdown duration corresponding to the target power grid infrastructure project according to the region where the target power grid infrastructure project is located, recorded as the target winter shutdown duration, includes: Obtain the construction period data of historical power grid infrastructure projects in different regions; Determine the corresponding winter shutdown duration for each region based on the construction period data for each region; From the corresponding winter shutdown duration for each region, select the winter shutdown duration corresponding to the region where the target power grid infrastructure project is located and record it as the target winter shutdown duration.

3. The method for predicting the capital transfer level of power grid infrastructure projects according to claim 1, characterized in that: The accounting progress prediction model includes the accounting prediction model for construction and installation costs, the accounting prediction model for equipment costs and the accounting prediction model for other costs; The construction and installation cost accounting prediction model is: Among them, J′ is the forecast result of the construction and installation fee entry progress, T is the construction month of each single project, JT1 is the first engineering payment settlement month, JT2 is the second engineering payment settlement month, JT3 is the project completion settlement month, and JT4 is the project final settlement month. JT1-JT2 )] is for X( JT1-JT2 ) take the average, X( JT1-JT2 ) is the revised value of the construction progress forecast result from the first engineering payment settlement month JT1 to the second engineering payment settlement month JT2, X JT3 It is the revised value of the construction progress forecast result of the project completion settlement month JT3; The equipment expense accounting prediction model is: Among them, S′ is the forecast result of the equipment fee entry progress, T is the construction month of each single project, ST1 is the month when the first batch of equipment arrives on site, ST2 is the month when the second batch of equipment arrives on site, ST3 is the month when the completion settlement is made, and ST4 is the month when the project is settled. ST1-ST2 )] is for X( ST1-ST2 ) take the average, X( ST1-ST2 ) is the revised value of the construction progress forecast result from ST1, the month when the first batch of equipment arrives on site, to ST2, the month when the second batch of equipment arrives on site; The other fee accounting prediction model is: Among them, Q′ is the forecast result of the progress of other fees, Q 开工 is the progress of the advance payment, T is the construction month of each single project, QT1 is the production month, QT2 is the completion settlement month, QT3 is the project final settlement month, X T A revised value for the monthly construction progress forecast results for each individual project.

4. The method for predicting the capital transfer level of power grid infrastructure projects according to claim 1, characterized in that: The process of determining the transfer base of the target power grid infrastructure project includes: Obtain the surplus rate data of each cost of each single project in the historical power grid infrastructure projects of each voltage level; From the various surplus rate data, select the surplus rate data of each expense with the same voltage level and the same single project as the target power grid infrastructure project as the target surplus rate data; Calculate the capital transfer benchmark for each individual project in the target power grid infrastructure project based on the target surplus rate data and the estimated cost or contract cost of each individual project in the target power grid infrastructure project; The capital transfer benchmark of the target power grid infrastructure project is calculated based on the capital transfer benchmarks of all individual projects in the target power grid infrastructure project.

5. The method for predicting the capital transfer level of power grid infrastructure projects according to claim 4, characterized in that: The transfer basis of each single project includes the transfer basis of the construction engineering cost and installation engineering cost, the transfer basis of the equipment purchase cost and the transfer basis of other costs of each single project; After calculating the capital transfer basis of each single project in the target power grid infrastructure project based on the target surplus rate data and the estimated cost or contract cost of each single project in the target power grid infrastructure project, it also includes: Obtain the actual engineering quantity change data, labor cost change data and equipment price change data of each single project during the construction process of the target power grid infrastructure project; According to each of the actual engineering quantity change data and each of the labor cost change data, the capital conversion basis of the construction engineering cost and the installation engineering cost of each single project is revised to obtain the construction engineering cost basis of each single project; According to each of the equipment price change data, the capital conversion basis of the equipment purchase cost of each single project is corrected to obtain the equipment cost basis of each single project; According to the construction cost benchmark, equipment cost benchmark and other cost benchmark of each single project, the capital conversion benchmark of each single project in the target power grid infrastructure project is calculated to obtain the capital conversion benchmark correction value; The calculation of the capital transfer benchmark of the target power grid infrastructure project based on the capital transfer benchmarks of all individual projects in the target power grid infrastructure project includes: The capital transfer benchmark of the target power grid infrastructure project is calculated based on the capital transfer benchmark correction values ​​of all individual projects in the target power grid infrastructure project.

6. The method for predicting the capital transfer level of power grid infrastructure projects according to claim 5, characterized in that: According to each of the actual engineering quantity change data and each of the labor cost change data, the capital conversion basis of the construction engineering cost and the installation engineering cost of each single project is revised to obtain the construction engineering cost basis of each single project, including: According to J = j / (1-c j )*(1+x%)*(1+y%), to obtain the construction cost benchmark for each individual project; Among them, J is the construction and installation cost basis of each single project, j is the estimated or contractual cost of the construction and installation costs of each single project, and c is the construction and installation cost of each single project. j For each single project, the target surplus rate data of the construction project cost and installation project cost is j*(1-c j ) is the capital conversion basis of the construction engineering cost and installation engineering cost of each single project, x is each said labor cost change data, and y is each said actual engineering quantity change data.

7. The method for predicting the capital transfer level of power grid infrastructure projects according to claim 5, characterized in that: According to each of the equipment price change data, the capital conversion basis of the equipment purchase cost of each single project is revised to obtain the equipment cost basis of each single project, including: According to S = s*(1-c s ) / (1+z%), and obtain the equipment cost benchmark for each single project; Among them, S is the equipment cost basis for each single project, s is the estimated or contractual cost of equipment purchase for each single project, and c is the equipment cost of each single project. s The target surplus rate data of equipment purchase cost for each single project, s*(1-c s ) is the capital conversion basis of the equipment purchase cost for each single project, and z is the price change data of each of the aforementioned equipment.

8. The method for predicting the capital transfer level of power grid infrastructure projects according to claim 5, characterized in that: According to the construction cost benchmark, equipment cost benchmark and other cost transfer benchmark of each single project, the capital transfer benchmark correction value of each single project in the target power grid infrastructure project is calculated, including: According to R=J+S+Q, the capital conversion benchmark correction value of each single project in the target power grid infrastructure project is calculated; Among them, R is the capital transfer benchmark correction value of each individual project in the target power grid infrastructure project, J is the construction cost benchmark of each individual project, S is the equipment cost benchmark of each individual project, and Q is the capital transfer benchmark for other costs.

9. The method for predicting the capital transfer level of power grid infrastructure projects according to claim 1, characterized in that: Also includes: According to the method for obtaining the prediction result of the capital transfer level of the target power grid infrastructure project, the prediction result of the capital transfer level of each power grid infrastructure project in the unit dimension is obtained; The predicted results of the capital transfer level of each power grid infrastructure project are compared with the target value of the capital transfer level, and the risk projects under the unit dimension are determined based on the comparison results.

10. A device for predicting the capital transfer level of power grid infrastructure projects, characterized in that: include: A construction progress prediction module is used to predict the construction progress based on the construction progress plan of each milestone node of each single project of the target power grid infrastructure project, and obtain the construction progress prediction result of the target power grid infrastructure project; A construction progress impact determination module is used to determine the winter shutdown duration corresponding to the target power grid infrastructure project according to the region where the target power grid infrastructure project is located, which is recorded as the target winter shutdown duration; A construction progress correction module is used to correct the construction progress prediction result according to the target winter shutdown duration to obtain a correction value of the construction progress prediction result; A billing progress prediction module is used to perform billing progress prediction based on the construction progress prediction result correction value and the billing progress prediction model of each expense of each single project in the target power grid infrastructure project to obtain a billing progress prediction result; The capital transfer level prediction module is used to obtain the capital transfer level prediction result of the target power grid infrastructure project according to the account entry progress prediction result and the capital transfer benchmark of the target power grid infrastructure project.

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