Post-evaluation method for success degree of small capital construction project of power grid

Abstract

The invention discloses a power grid small capital construction project success degree post-evaluation method, and relates to the technical field of project evaluation, and the method comprises the following steps: constructing a power grid small capital construction project success degree post-evaluation index system based on the characteristics, targets and full life cycle management requirements of a power grid small capital construction project; collecting data of each evaluation index and constructing an evaluation matrix; the subjective index weight is determined through the AHP method, the objective index weight is determined through the entropy method, the subjectivity and objectivity of the evaluation indexes are comprehensively considered, the weight of each evaluation index can be determined more comprehensively and scientifically, and the limitation of a single weight calculation method is avoided. An evaluation model is established through a TOPSIS method, relative proximity is calculated, sorting evaluation is carried out by using the size of the relative proximity, a trace tracking analysis model is accessed and utilized to carry out reverse analysis on an evaluation result, attributes and specific indexes with problems are found out, clear improvement directions and measures are provided, and optimization of project management and improvement of project benefits are facilitated.

Description

Technical Field

[0001] The present invention relates to the field of small-scale infrastructure projects of power grids, and more specifically, to a post-success evaluation method for small-scale infrastructure projects of power grids. Background Art

[0002] Small-scale infrastructure projects in power grids play an important role in ensuring the safe and stable operation of power grids. With the continuous increase in electricity consumption in society, the proportion of power grid investment has increased year by year, and the investment scale of small-scale infrastructure projects in power grids has also expanded rapidly. These projects directly affect many aspects of the company's production and operation, including dispatching control, production management, operation and maintenance, marketing services, material warehousing, and scientific research and testing. Due to the diversity of project types and functions, as well as complex and changeable economic, social and environmental factors, project results are prone to deviate from the expected goals, and may even lead to production interruptions and construction delays, resulting in losses.

[0003] There are many post-evaluation tasks for small-scale infrastructure projects in power grids. In order to conduct a comprehensive and objective analysis of the project implementation process and transformation benefits, and to deeply analyze the existing problems, it is of practical significance to carry out research on the post-evaluation index system. However, the existing technology lacks an evaluation system for small-scale infrastructure projects in power grids, which makes it difficult to carry out related post-evaluation work smoothly. Systematic post-evaluation can help identify and summarize the problems and lessons learned during the entire implementation process of the project, provide guidance for future projects, and ensure accurate investment and lean management of the project.

[0004] The above disclosed technical solutions have at least the following technical problems: lack of an evaluation system for small-scale infrastructure projects of power grids, and the limitation of a single weight calculation method is large, which makes it difficult to carry out relevant post-evaluation work smoothly. In view of the above problems, the present invention proposes a solution. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a post-evaluation method for the success of a small-scale infrastructure project in a power grid. The subjective indicator weights are determined by the AHP method and the objective indicator weights are determined by the entropy method. The subjectivity and objectivity of the evaluation indicators are comprehensively considered, and the weights of various evaluation indicators can be determined more comprehensively and scientifically to solve the problem that a single weight calculation method has large limitations.

[0006] To achieve the above object, the present invention provides the following technical solutions: A post-evaluation method for the success of small-scale infrastructure projects in power grids comprises the following steps: constructing a post-evaluation index system for the success of small-scale infrastructure projects in power grids based on the characteristics, objectives and full life cycle management requirements of small-scale infrastructure projects in power grids; collecting original data of various evaluation indicators and constructing an evaluation matrix for standardization; obtaining the objective weight of each evaluation indicator based on an entropy weight method, obtaining the subjective weight of each evaluation indicator by using an AHP method, and calculating the combined weight by using a linear weighted combination method; ranking the success of small-scale infrastructure projects in power grids, calculating relative proximity by using a TOPSIS method, and ranking the success of small-scale infrastructure projects in power grids according to the relative proximity; and performing reverse analysis by using a trace tracking analysis model, and obtaining the attributes and specific indicators of the existing problems through the evaluation results.

[0007] In a preferred embodiment, the post-success evaluation index system of the small-scale infrastructure project of the power grid is divided into two levels: general indicators and key indicators: general indicators include specific evaluation contents of the preliminary decision-making stage, bidding stage, design stage, construction stage and final acceptance stage; key indicators include evaluation contents of compliance, safety quality, cost control, engineering quality, green buildings and project benefits.

[0008] In a preferred embodiment, the original data of each evaluation index is collected and an evaluation matrix is ​​constructed for standardization, specifically: for each small-scale infrastructure project of a power grid, the original data of each evaluation index is collected; according to the corresponding data information of the evaluation index, a specific index value is assigned to each evaluation index, and an initial matrix, i.e., an original data matrix, is listed; wherein the rows represent different small-scale infrastructure projects of a power grid, and the columns represent various evaluation indexes; the index data is standardized based on a preset standardized formula to obtain a standardized decision matrix.

[0009] In a preferred embodiment, the objective weight of each evaluation indicator is obtained based on the entropy weight method, the subjective weight of each evaluation indicator is obtained by the AHP method, and the combination weight is calculated by the linear weighted combination method, specifically: according to the decision matrix, the proportion of each evaluation indicator is calculated, and the entropy value of each evaluation indicator is calculated based on the proportion of each evaluation indicator; the difference coefficient of each evaluation indicator is calculated; the objective weight of each evaluation indicator is calculated according to the difference coefficient of each evaluation indicator; the success evaluation of small-scale infrastructure projects of power grid is used as the target layer, and the evaluation indicator system is used as the criterion layer to construct a hierarchical structure model; the importance of each indicator of the criterion layer relative to the target layer is compared by experts, and a judgment matrix is ​​constructed; the eigenvector of the judgment matrix is ​​calculated and normalized to obtain the subjective weight of each indicator; the corresponding average random consistency indicator is found according to the order of the judgment matrix; the consistency ratio is calculated so that the judgment matrix passes the consistency test; the weight is determined according to the combination method of entropy weight and AHP.

[0010] In a preferred embodiment, the success ranking of small-scale infrastructure projects in the power grid is carried out by calculating relative proximity using the TOPSIS method, and the success ranking of small-scale infrastructure projects in the power grid is carried out according to the relative proximity, specifically: calculating and determining the weighted evaluation value matrix of indicators, considering the weight of each indicator, and weighting the normalized data to form a weighted normalized matrix; calculating the positive ideal solution and the negative ideal solution based on the weighted normalized matrix; calculating the Euler distance of each project to the positive ideal solution and the Euler distance of each project to the negative ideal solution; calculating the relative proximity of each project based on the weighted Euclidean distance; and sorting the small-scale infrastructure projects in the power grid in descending order according to the relative proximity; the larger the relative proximity, the closer the project is to the positive ideal solution and the farther it is from the negative ideal solution, that is, the higher the success of the project; conversely, the smaller the relative proximity, the lower the success of the project.

[0011] The technical effects and advantages of the post-evaluation method for the success of a small-scale infrastructure project of a power grid according to the present invention are as follows: 1. The present invention constructs a post-success evaluation index system and divides each index into two levels: general index and key index. General index includes specific evaluation contents in the preliminary decision-making stage, bidding stage, design stage, construction stage and completion acceptance stage; key index includes evaluation contents in compliance, safety quality, cost control, engineering quality, green building and project benefits.

[0012] 2. The present invention combines the entropy weight method and the AHP method, comprehensively considers the subjectivity and objectivity of the evaluation indicators, and can determine the weights of various evaluation indicators more comprehensively and scientifically, avoiding the limitations of a single weight calculation method. Through the trace tracking analysis model, the evaluation results can be reversely analyzed to find out the attributes and specific indicators with problems, providing clear improvement directions and measures, which is helpful to optimize project management and improve project benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 The present invention is a schematic diagram of the structure of a post-evaluation method for the success of a small-scale infrastructure project in a power grid. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] Embodiment 1, Figure 1 The present invention provides a method for post-evaluation of the success of a small-scale infrastructure project of a power grid, comprising the following steps: S1, based on the characteristics, objectives and life cycle management requirements of small-scale power grid infrastructure projects, a post-success evaluation index system for small-scale power grid infrastructure projects is constructed; The post-success evaluation index system for small-scale grid infrastructure projects is divided into two levels: general indicators and key indicators. General indicators include specific evaluation contents of the preliminary decision-making stage, bidding stage, design stage, construction stage and final acceptance stage; key indicators include evaluation contents of compliance, safety quality, cost control, engineering quality, green buildings and project benefits.

[0016] S2, collect the original data of each evaluation index and construct the evaluation matrix for standardization; The original data of various evaluation indicators are collected and an evaluation matrix is ​​constructed for standardization, specifically: For each small-scale infrastructure project of the power grid, collect the original data of various evaluation indicators; According to the corresponding data information of the evaluation index, each evaluation index is assigned a specific index value, and an initial matrix, i.e., an original data matrix, is listed; wherein the rows represent different small-scale infrastructure projects of power grids, and the columns represent various evaluation indexes; The indicator data is standardized based on the preset standardization formula to obtain a standardized decision matrix.

[0017] The standardized formula is specifically:

[0018] in, is the original data, is the standardized data, and are the maximum and minimum values ​​of the jth indicator in all projects respectively.

[0019] Original Matrix There are m evaluation items and n evaluation indicators. Each indicator is assigned a value to form an initial matrix M, which represents the jth indicator value of the i-th evaluation object.

[0020] Decision Matrix

[0021] S3, based on the entropy weight method, the objective weight of each evaluation index is obtained, the AHP method is used to obtain the subjective weight of each evaluation index, and the linear weighted combination method is used to calculate the combined weight; The entropy weight method is used to obtain the objective weight of each evaluation index, the AHP method is used to obtain the subjective weight of each evaluation index, and the linear weighted combination method is used to calculate the combined weight, which is specifically: According to the decision matrix, the weight of each evaluation indicator is calculated, and the entropy value of each evaluation indicator is calculated based on the weight of each evaluation indicator; Calculate the coefficient of variation of each evaluation indicator; Calculate the objective weight of each evaluation indicator according to the coefficient of difference of each evaluation indicator; Taking the success evaluation of small-scale infrastructure projects of power grid as the target layer and the evaluation index system as the criterion layer, a hierarchical structure model is constructed. The judgment matrix is ​​constructed by experts comparing the importance of each indicator in the criterion layer relative to the target layer. Calculate the eigenvector of the judgment matrix and normalize it to obtain the subjective weight of each indicator; Find the corresponding average random consistency index according to the order of the judgment matrix; Calculate the consistency ratio so that the judgment matrix passes the consistency test; The weights are determined based on the combination of entropy weight and AHP.

[0022] The calculation of the proportion of each indicator is specifically as follows:

[0023] The calculation of the entropy value of each indicator is specifically as follows:

[0024]

[0025] The calculation of the coefficient of difference is specifically as follows:

[0026] The objective weight is calculated as follows:

[0027] The calculation of subjective weight is specifically as follows:

[0028] in, is the weight of the jth index, n is the number of evaluation indicators, is the jth index of the i-th project, is the entropy value of the jth indicator, m is the number of solutions, is the coefficient of difference of the jth indicator, is the objective weight of the jth indicator, is the subjective weight of the jth indicator, is the maximum eigenvalue of the judgment matrix, is the relative importance of the i-th factor and the j-th factor in the judgment matrix.

[0029] S4, sorting the success of small-scale infrastructure projects of power grid, calculating the relative proximity using TOPSIS method, and sorting the success of small-scale infrastructure projects of power grid according to the relative proximity; The success ranking of small-scale infrastructure projects in the power grid is carried out by calculating the relative proximity using the TOPSIS method, and the success ranking of small-scale infrastructure projects in the power grid is carried out according to the relative proximity, specifically: Calculate and determine the index weighted evaluation value matrix, consider the weight of each index, and weight the normalized data to form a weighted normalized matrix; Computing positive and negative ideal solutions based on a weighted normalized matrix; Calculate the Euler distance from each item to the positive ideal solution and the Euler distance from each item to the negative ideal solution; The relative proximity of each item is calculated based on the weighted Euclidean distance; The small-scale infrastructure projects of the power grid are sorted in descending order according to the relative proximity; the larger the relative proximity, the closer the project is to the positive ideal solution and the farther it is from the negative ideal solution, that is, the higher the success of the project; conversely, the smaller the relative proximity, the lower the success of the project.

[0030] The index weighted evaluation value matrix establishment process is as follows:

[0031]

[0032] The specific calculation formulas for the positive ideal solution and the negative ideal solution are:

[0033] In the formula, is a positive ideal solution, is a negative ideal solution, represents a set of efficiency indicators, represents a set of cost indicators, is the maximum value of the product corresponding to each indicator, The minimum value of the product corresponding to each indicator.

[0034] The calculation formula of the weighted Euclidean distance is as follows:

[0035]

[0036] The calculation formula of the relative proximity is as follows:

[0037] Among them, i is the total number of projects, j is the total number of evaluation indicators, is the jth index value of the i-th item after standardization, is the i-th component of the positive ideal solution, is the i-th component of the negative ideal solution, is the jth data of the positive ideal solution, is the jth data of the negative ideal solution, is the relative proximity of the j-th item.

[0038] S5, use the trace tracking analysis model to perform reverse analysis, and obtain the properties and specific indicators of the problem through evaluation results.

[0039] The trace tracking analysis model is used to perform reverse analysis, and the properties and specific indicators of the problem are obtained through evaluation results, which are specifically: Constructing the evaluation value matrix; Compare the comprehensive evaluation values ​​to obtain the object with the best evaluation value; Based on the evaluation value matrix, the basic deviation rate is calculated to obtain the basic deviation rate and deviation rate matrix of each region and the optimal region; Calculate the deviation contribution of each attribute of each evaluation object; Calculate the attribute deviation rate of each evaluation object through the deviation contribution of each attribute; Based on the attribute deviation rate of each evaluation object, the attribute with the largest deviation rate of each evaluation object is obtained; Sort the indicators by their deviation contribution. According to the deviation contribution rate of each basic indicator, the indicators are sorted. The indicator with the largest deviation rate is the main factor causing the difference between the evaluation object and the optimal evaluation object. Similarly, analyze the factors that cause the difference between the evaluation object and the optimal evaluation object, and provide relevant explanations.

[0040] The evaluation value matrix is ​​as follows:

[0041] Compare the comprehensive evaluation values ​​and find the object with the best evaluation value :

[0042] The basic deviation rate and deviation rate matrix of each region and the optimal region are as follows:

[0043]

[0044] Preferably, the deviation contribution of each attribute of each evaluation object is The calculation of is as follows:

[0045] Preferably, the attribute deviation rate of each evaluation object is calculated as follows:

[0046] Preferably, determine the attribute with the largest deviation rate for each evaluation object , the calculation formula is as follows:

[0047] Preferably, the basic indicator deviation rate The calculation is as follows:

[0048] Preferably, the basic indicator deviation contributes and contribution rate The calculation of is as follows:

[0049]

[0050] Among them, i is the serial number of the evaluation object, j is the serial number of the evaluation index, is the basic deviation rate between each region and the optimal region, is the contribution of each attribute deviation of each evaluation object, is the attribute deviation rate of each evaluation object, is the attribute with the largest deviation rate of each evaluation object. is the basic indicator deviation rate, Contribute to the basic indicator deviation, is the indicator weight, It is the contribution rate of basic indicator deviation.

[0051] Sort the indicators by their deviation contribution. According to the deviation contribution rate of each basic indicator, the indicators are sorted. The indicator with the largest deviation rate is the main factor causing the difference between the evaluation object and the optimal evaluation object. Similarly, analyze the factors that cause the difference between the evaluation object and the optimal evaluation object, and provide relevant explanations.

[0052] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0053] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0054] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0055] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0056] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0057] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for post-evaluation of the success of a small-scale infrastructure project in a power grid, characterized in that: The following steps are involved: Based on the characteristics, goals and life cycle management requirements of small-scale power grid infrastructure projects, a post-success evaluation index system for small-scale power grid infrastructure projects is constructed; Collect the original data of each evaluation indicator and construct an evaluation matrix for standardization; The objective weight of each evaluation index is obtained based on the entropy weight method, the subjective weight of each evaluation index is obtained by the AHP method, and the linear weighted combination method is used to calculate the combined weight; The success of small-scale infrastructure projects of power grid is ranked, and the relative proximity is calculated using the TOPSIS method, and the success of small-scale infrastructure projects of power grid is ranked according to the relative proximity; The trace tracking analysis model is used to conduct reverse analysis, and the properties and specific indicators of the problems are obtained through the evaluation results.

2. The method for post-success evaluation of a small-scale infrastructure project in a power grid according to claim 1, characterized in that: The post-success evaluation index system for small-scale grid infrastructure projects is divided into two levels: general indicators and key indicators. General indicators include specific evaluation contents of the preliminary decision-making stage, bidding stage, design stage, construction stage and final acceptance stage; key indicators include evaluation contents of compliance, safety quality, cost control, engineering quality, green buildings and project benefits.

3. The method for post-evaluation of success of a small-scale infrastructure project in a power grid according to claim 2, characterized in that: The original data of various evaluation indicators are collected and an evaluation matrix is ​​constructed for standardization, specifically: For each small-scale infrastructure project of the power grid, collect the original data of various evaluation indicators; According to the corresponding data information of the evaluation index, each evaluation index is assigned a specific index value, and an initial matrix, i.e., an original data matrix, is listed, in which the rows represent different small-scale infrastructure projects of power grids, and the columns represent various evaluation indexes; The indicator data is standardized based on the preset standardization formula to obtain a standardized decision matrix.

4. The method for post-success evaluation of a small-scale infrastructure project of a power grid according to claim 3, characterized in that: The entropy weight method is used to obtain the objective weight of each evaluation index, the AHP method is used to obtain the subjective weight of each evaluation index, and the linear weighted combination method is used to calculate the combined weight, which is specifically: According to the decision matrix, the weight of each evaluation indicator is calculated, and the entropy value of each evaluation indicator is calculated based on the weight of each evaluation indicator; Calculate the coefficient of variation of each evaluation indicator; Calculate the objective weight of each evaluation indicator according to the coefficient of difference of each evaluation indicator; Taking the success evaluation of small-scale infrastructure projects of power grid as the target layer and the evaluation index system as the criterion layer, a hierarchical structure model is constructed. The judgment matrix is ​​constructed by experts comparing the importance of each indicator in the criterion layer relative to the target layer. Calculate the eigenvector of the judgment matrix and normalize it to obtain the subjective weight of each indicator; Find the corresponding average random consistency index according to the order of the judgment matrix; Calculate the consistency ratio so that the judgment matrix passes the consistency test; The weights are determined based on the combination of entropy weight and AHP.

5. The method for post-evaluation of success of a small-scale infrastructure project in a power grid according to claim 4, characterized in that: The success ranking of small-scale infrastructure projects in the power grid is carried out by calculating the relative proximity using the TOPSIS method, and the success ranking of small-scale infrastructure projects in the power grid is carried out according to the relative proximity, specifically: Calculate and determine the index weighted evaluation value matrix, consider the weight of each index, and weight the normalized data to form a weighted normalized matrix; Computing positive and negative ideal solutions based on a weighted normalized matrix; Calculate the Euler distance from each item to the positive ideal solution and the Euler distance from each item to the negative ideal solution; The relative proximity of each item is calculated based on the weighted Euclidean distance; Rank the grid small infrastructure projects in descending order based on relative proximity; The larger the relative closeness is, the closer the project is to the positive ideal solution and the farther it is from the negative ideal solution, that is, the higher the success of the project; conversely, the smaller the relative closeness is, the lower the success of the project.

6. The method for post-evaluation of success of a small-scale infrastructure project of a power grid according to claim 5, characterized in that: The standardized formula is specifically: in, is the original data, is the standardized data, and are the maximum and minimum values ​​of the jth indicator in all projects respectively.

7. The method for post-evaluation of success of a small-scale infrastructure project of a power grid according to claim 6, characterized in that: The calculation of the proportion of each indicator is specifically as follows: The calculation of the entropy value of each indicator is specifically as follows: The calculation of the coefficient of difference is specifically as follows: The objective weight is calculated as follows: The calculation of subjective weight is specifically as follows: in, is the weight of the jth indicator, n is the number of evaluation indicators, is the jth index of the i-th project, is the entropy value of the jth indicator, m is the number of solutions, is the coefficient of difference of the jth indicator, is the objective weight of the jth indicator, is the subjective weight of the jth indicator, is the maximum eigenvalue of the judgment matrix, is the relative importance of the i-th factor and the j-th factor in the judgment matrix.

8. The method for post-evaluation of success of a small-scale infrastructure project of a power grid according to claim 7, characterized in that: The index weighted evaluation value matrix establishment process is as follows: The specific calculation formulas for the positive ideal solution and the negative ideal solution are: In the formula, is a positive ideal solution, is a negative ideal solution, represents a set of efficiency indicators, represents a set of cost indicators, is the maximum value of the product corresponding to each indicator, The minimum value of the product corresponding to each indicator.

9. The method for post-evaluation of success of a small-scale infrastructure project in a power grid according to claim 8, characterized in that: The calculation formula of the weighted Euclidean distance is as follows: The calculation formula of the relative proximity is as follows: Among them, i is the total number of projects, j is the total number of evaluation indicators, is the jth index value of the i-th item after standardization, is the i-th component of the positive ideal solution, is the i-th component of the negative ideal solution, is the jth data of the positive ideal solution, is the jth data of the negative ideal solution, is the relative proximity of the j-th item.

10. The method for post-success evaluation of a small-scale infrastructure project of a power grid according to claim 9, characterized in that: The evaluation value matrix is ​​as follows: The object with the best evaluation value is obtained by comparing the comprehensive evaluation values. : The basic deviation rate and deviation rate matrix of each region and the optimal region are as follows: The deviation contribution of each attribute of each evaluation object The calculation of is as follows: The attribute deviation rate of each evaluation object The calculation is as follows: Determine the attribute with the largest deviation rate of each evaluation object , the calculation formula is as follows: The basic indicator deviation rate The calculation is as follows: The basic indicator deviation contribution and contribution rate The calculation of is as follows: Among them, i is the serial number of the evaluation object, j is the serial number of the evaluation index, is the basic deviation rate between each region and the optimal region, is the contribution of each attribute deviation of each evaluation object, is the attribute deviation rate of each evaluation object, is the attribute with the largest deviation rate of each evaluation object. is the basic indicator deviation rate, Contribute to the basic indicator deviation, is the indicator weight, It is the contribution rate of basic indicator deviation.

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