Multi-dimensional quality and efficiency evaluation method and device for cluster and domain power grid projects

Abstract

The invention provides a multi-dimensional quality and efficiency evaluation method and device for cluster and field power grid projects, and the method comprises the steps: taking a project cluster and a project field as research objects, obtaining a project data set corresponding to a power grid project cluster / field, fully considering the relevance between projects, determining the key evaluation dimension and evaluation index of the project cluster / field, and achieving the quality and efficiency evaluation of the power grid project cluster / field. A comprehensive quality and efficiency evaluation index system is constructed by combining existing data setting specific indexes and calculation formulas thereof, the index weight of each evaluation index is determined according to a rough set theory, the objectivity of weight distribution of each evaluation index is improved, and comprehensive evaluation of project clusters and fields is achieved.

Description

Technical Field

[0001] This application relates to the field of energy digitization, and particularly to a multi-dimensional quality and efficiency evaluation method and device for cluster and domain power grid projects. Background Art

[0002] Project quality and efficiency evaluation is a systematic method for comprehensively evaluating the quality and effect of projects. At present, the relevant research on project quality and efficiency evaluation focuses on the index system, and there have been many studies on the dimensions and comprehensiveness of project evaluation. However, most of the attention is still on the project evaluation at the individual level, and the dimensionality of the evaluation system and the singularity of the setting of specific indicators are obvious, lacking quality and efficiency evaluation technologies for project clusters and domains. Therefore, it is urgent to construct a project cluster / domain evaluation system covering multi-dimensional perspectives, making the project selection in the reserve stage lack a certain degree of scientificity. Summary of the Invention

[0003] This application provides a multi-dimensional quality and efficiency evaluation method and device for cluster and domain power grid projects. Taking project clusters and project domains as the research objects, fully considering the relevance between projects, determining the key evaluation dimensions and their evaluation indicators for project clusters / domains, and combining the existing data to set specific indicators and their calculation formulas, a comprehensive quality and efficiency evaluation index system is constructed, and an evaluation index fusion method based on rough sets is used to improve the objectivity of the weight distribution of each evaluation index, realizing the comprehensive evaluation of project clusters and domains.

[0004] In a first aspect, this application provides a multi-dimensional quality and efficiency evaluation method for cluster and domain power grid projects, the method comprising: obtaining a project data set corresponding to the power grid project cluster / domain, the power grid project cluster / domain including at least two power grid projects; constructing a multi-dimensional quality and efficiency evaluation index system for the power grid project cluster / domain, the multi-dimensional quality and efficiency evaluation index system including at least two evaluation dimensions, at least two evaluation indicators for each evaluation dimension, and the index calculation formula for each evaluation dimension; establishing an automated calculation model according to the multi-dimensional quality and efficiency evaluation index system, and calculating the evaluation data of each evaluation indicator; determining the index weight of each evaluation indicator according to the rough set theory; and constructing a multi-dimensional index fusion model according to the index weight to obtain the comprehensive quality and efficiency evaluation result of the project cluster / domain.

[0005] In some embodiments, the at least two evaluation dimensions include at least two of an economic evaluation dimension, a timeliness evaluation dimension, and a stability evaluation dimension. The evaluation indicators of the economic evaluation dimension include at least two of the power supply contribution rate, the loss reduction contribution rate, and the new overall cost. The evaluation indicators of the timeliness evaluation dimension include at least two of the strategic implementation rate, the key direction implementation rate, and the reserve support rate. The stability evaluation dimension includes at least two of the impact rate of power grid system stability, the impact rate of frequency stability, and the improvement rate of load balance degree.

[0006] In some embodiments, the power supply contribution rate includes the local power supply contribution rate and the overall line power supply contribution rate. The loss reduction contribution rate includes the local loss reduction contribution rate and the overall line loss reduction contribution rate. The index calculation formula of the local power supply contribution rate is as shown in formula (1) below:

[0007] B1 = ∑((D e -D p (R)) / D p (R)) Formula (1)

[0008] Where, B1 is the regional power supply contribution rate, D e is the power supply in the budget period after the project is put into production in the power grid project cluster / field, unit: KWh; R is the region where the project in the power grid project cluster / field belongs; D p (R) is the power supply in the previous period of region R where the project in the power grid project cluster / field belongs, unit: KWh;

[0009] The index calculation formula of the overall line power supply contribution rate is as shown in formula (2) below:

[0010] B2 = ∑((D e -D p ) / D p ) Formula (2)

[0011] Where, B2 is the overall line power supply contribution rate, D p is the power supply in the previous period on the overall line of the power grid project cluster / field, unit: KWh;

[0012] The index calculation formula of the local loss reduction contribution rate is as shown in formula (3) below:

[0013] B3 = ∑(D e ×(L p (R)-L e ) / (D p (R)×L p (R))) Formula (3)

[0014] Where, B3 is the regional loss reduction contribution rate, R is the region where the project in the project group belongs; Lp (R) is the previous period line loss rate of the area R where the project belongs in the power grid project cluster / domain; L e is the budget period line loss rate of the power grid project cluster / domain;

[0015] The index calculation formula of the contribution rate of the overall line loss reduction amount is shown in the following formula (4):

[0016] B4 = ∑(D e ×(L p - L e ) / (D p ×L p )) Formula (4)

[0017] where B4 is the contribution rate of the overall line loss reduction amount, and L p is the previous period line loss rate of the power grid project cluster / domain;

[0018] The index calculation formula of the newly added overall cost is shown in the following formula (5):

[0019] B5 = (C p + C m ) × P i Formula (5)

[0020] B5 is the newly added overall cost; C p is the estimated cost increased at the human resource level, including personnel training and communication costs; C m is the estimated cost increased at the management level, considering the increased management complexity due to geographical location and special project span; P i is the overall risk factor of the power grid project cluster / domain.

[0021] In some embodiments, the index calculation formula of the strategic implementation rate is shown in the following formula (6):

[0022] TL1 = (N a / N t ) × F t Formula (6)

[0023] where TL1 is the strategic implementation rate, N a is the number of projects implementing the corresponding strategic tasks in the power grid project cluster / domain; N t is the total number of projects during the planning period; F t is the time impact coefficient;

[0024] The index calculation formula of the implementation rate of the key direction is shown in the following formula (7):

[0025] TL2 = (N i / N t ) ± I d Formula (7)

[0026] Among them, TL2 is the implementation rate of key directions, and N i is the number of projects implementing the corresponding key directions in the power grid project cluster / domain; I d is the implementation index of the corresponding key direction;

[0027] The index calculation formula of the reserve support rate is shown in the following formula (8):

[0028] TL3 = S g / S r Formula (8)

[0029] Among them, TL3 is the reserve support rate, and S g is the total investment scale of all projects in the power grid project cluster / domain; S r is the total planned scale of the corresponding special project / direction / strategy project during the planning period;

[0030] The index calculation formula of the power grid system stability influence rate is shown in the following formula (9):

[0031] ST = α·VSI + β·SI + γ·PI Formula (9)

[0032] Among them, ST is the power grid system stability influence rate; VSI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of voltage; SI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of the power grid architecture; PI is the improvement factor of the power grid project cluster / domain in terms of security; α, β, and γ are respectively the relative importance of the corresponding voltage stability, power grid architecture, and security improvement, and α + β + γ = 1;

[0033] The index calculation formula of the frequency stability influence rate is shown in the following formula (10):

[0034] FSI = λ·FI + μ·AI Formula (10)

[0035] Among them, FSI is the frequency stability influence rate, FI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of frequency regulation; AI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of automatic generation control; λ and μ are respectively the relative importance of the corresponding frequency regulation and automatic generation control, and λ + μ = 1;

[0036] The index calculation formula of the load balance improvement rate is shown in the following formula (11):

[0037]

[0038] Among them, LBI is the load balance improvement rate, and L piThe load of each region before the implementation of the power grid project cluster / domain, L ei The load of each region after the implementation of the power grid project cluster / domain, and n is the number of regions divided in the power grid project cluster / domain.

[0039] In some embodiments, determining the index weight of each evaluation index according to the rough set theory includes: obtaining the classification information of the at least two power grid projects, where the classification information is used to characterize the quality and efficiency evaluation level of a single power grid project; determining one piece of classification information as the target decision attribute from the classification information; establishing a decision matrix according to the evaluation data of each evaluation index, where each row of the decision matrix is used to characterize a power grid project, and each column of the decision matrix is used to characterize an evaluation index or the classification information; calculating the dependence degree of each evaluation index on the target decision attribute according to the decision matrix and the dependence degree calculation formula, where the dependence degree is used to characterize the support degree of each evaluation index for the target decision attribute; calculating the assigned weight of each evaluation index according to the dependence degree of each evaluation index.

[0040] Among them, the dependence degree calculation formula is shown as formula (12) below:

[0041]

[0042] Among them, D is the target decision attribute, A is the evaluation index, and POS A (D) is the set of all power grid projects that can be determined to belong to the target decision attribute D under the evaluation index A. The dependence degree (D, A) represents the dependence degree of the evaluation index A on the target decision attribute D, and |D| is the number of power grid projects in the power grid project cluster / domain.

[0043] In some embodiments, calculating the assigned weight of each evaluation index according to the dependence degree of each evaluation index includes: calculating the assigned weight of the evaluation index according to the following formula (13):

[0044]

[0045] Among them, i is the serial number of the evaluation index, and w i is the assigned weight of the evaluation index A i and n is the total number of evaluation indexes.

[0046] In some embodiments, constructing a multi-dimensional index fusion model according to the index weights to obtain the comprehensive quality and efficiency evaluation result of the project cluster / domain includes: obtaining the assigned weight and the evaluation data of each evaluation index in the power grid project cluster / domain; calculating the comprehensive quality and efficiency evaluation data of the power grid project cluster / domain according to the evaluation data and the assigned weight; and determining the comprehensive quality and efficiency evaluation result of the power grid project cluster / domain according to the correspondence between the comprehensive quality and efficiency evaluation data and the classification information.

[0047] In a second aspect, the present application provides a multi-dimensional quality and efficiency evaluation device for power grid projects in clusters and domains. The device includes: an acquisition unit, configured to acquire a project data set corresponding to a power grid project cluster / domain, where the power grid project cluster / domain includes at least two power grid projects; a processing unit, configured to construct a multi-dimensional quality and efficiency evaluation index system for the power grid project cluster / domain, where the multi-dimensional quality and efficiency evaluation index system includes at least two evaluation dimensions, at least two evaluation indexes for each evaluation dimension, and an index calculation formula for each evaluation dimension; and establishing an automated calculation model according to the multi-dimensional quality and efficiency evaluation index system to calculate the evaluation data of each evaluation index; and determining the index weight of each evaluation index according to the rough set theory;

[0048] an output unit, configured to construct a multi-dimensional index fusion model according to the index weights to obtain the comprehensive quality and efficiency evaluation result of the project cluster / domain.

[0049] In a third aspect, the present application provides a server, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and executed by the processor, and the programs include instructions for performing the steps in the method according to any one of the first aspect.

[0050] In a fourth aspect, the present application provides a computer program / instruction stored thereon, and when the computer program / instruction is executed by a processor, the steps of the method according to any one of the first aspect are implemented.

[0051] It can be seen that in the embodiments of the present application, by obtaining the project data set corresponding to the power grid project cluster / domain, a multi-dimensional quality and efficiency evaluation index system for the power grid project cluster / domain is constructed. Among them, the power grid project cluster / domain includes at least two power grid projects, and the multi-dimensional quality and efficiency evaluation index system includes at least two evaluation dimensions, at least two evaluation indexes for each evaluation dimension, and the index calculation formula for each evaluation dimension; then an automated calculation model is established according to the multi-dimensional quality and efficiency evaluation index system to calculate the evaluation data of each evaluation index; the index weight of each evaluation index is determined according to the rough set theory; a multi-dimensional index fusion model is constructed according to the index weights to obtain the comprehensive quality and efficiency evaluation result of the project cluster / domain. Therefore, in the present application, taking the project cluster and project domain as the research objects, fully considering the relevance between projects, determining the key evaluation dimensions and their evaluation indexes of the project cluster / domain, and setting specific indexes and their calculation formulas in combination with the existing data, a comprehensive quality and efficiency evaluation index system is constructed, and an evaluation index fusion method based on rough sets is adopted to improve the objectivity of the weight allocation of each evaluation index and realize the comprehensive evaluation of the project cluster and domain. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings. Among them,

[0053] Figure 1 is a schematic structural diagram of a server provided by an embodiment of the present application;

[0054] Figure 2 is a schematic flowchart of a multi-dimensional quality and efficiency evaluation method for power grid projects facing clusters and domains provided by an embodiment of the present application;

[0055] Figure 3 is a functional unit structural block diagram of a multi-dimensional quality and efficiency evaluation device for power grid projects facing clusters and domains provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0056] In order to enable those skilled in the art to better understand the solutions of the present application, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present application.

[0057] In the description, claims, and the above-mentioned drawings of this application, terms such as "first" and "second" are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but in some embodiments, it further includes steps or units that are not listed, or in some embodiments, it further includes other steps or units inherent to these processes, methods, products, or devices.

[0058] Reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of this application. The phrase appears in various places in the description and does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0059] The "and / or" in the embodiments of this application describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent the following three situations: A exists alone; A and B exist simultaneously; B exists alone. Among them, A and B can be singular or plural.

[0060] In the embodiments of this application, the symbol " / " can represent an "or" relationship between the preceding and following associated objects. Additionally, the symbol " / " can also represent a division sign, that is, perform a division operation. For example, A / B can represent A divided by B.

[0061] The "at least one (item)" or its similar expression in the embodiments of this application refers to any combination of these items, including any combination of a single item (item) or multiple items (items), and means one or more, where multiple means two or more. For example, at least one (item) of a, b, or c can represent the following seven situations: a, b, c, a and b, a and c, b and c, a, b, and c. Among them, each of a, b, and c can be an element or a set containing one or more elements.

[0062] The "equal to" in the embodiments of this application can be used in combination with "greater than" and is applicable to the technical solutions adopted when it is greater than, or can also be used in combination with "less than" and is applicable to the technical solutions adopted when it is less than. When "equal to" is used in combination with "greater than", it is not used in combination with "less than"; when "equal to" is used in combination with "less than", it is not used in combination with "greater than".

[0063] At present, the related research on project quality and efficiency evaluation focuses on the index system, and there have been many studies on the dimensions and comprehensiveness of project evaluation. Although some technologies have considered the relevance between projects, this consideration is usually limited to the evaluation of specific dimensions. Currently, the evaluation object is still a single project, and the transformation from individual projects to project group evaluation objects has not been achieved. To sum up, the existing technical solutions still have the following disadvantages:

[0064] 1) Due to the lack of comprehensive evaluation of the overall benefits of the project group, the synergy of the project group cannot be fully demonstrated, resulting in deficiencies in the project configuration and optimization plan from the perspective of the project group.

[0065] 2) The existing technology often uses subjective weighting methods in calculating the index weights, fully absorbing the subjective experience of experts, but lacking a certain degree of objectivity, resulting in deviations in the accuracy of the evaluation results.

[0066] To address the above technical problems, the present application provides a multi-dimensional quality and efficiency evaluation method and device for cluster and domain power grid projects. Taking project clusters and project domains as the research objects, fully considering the relevance between projects, determining the key evaluation dimensions and their evaluation indexes of the project cluster / domain, and setting specific indexes and their calculation formulas in combination with the existing data, a comprehensive quality and efficiency evaluation index system is constructed, and an evaluation index fusion method based on rough sets is used to improve the objectivity of the weight allocation of each evaluation index, realizing the comprehensive evaluation of project clusters and domains.

[0067] The following will specifically describe the technical solutions of the present application and how the technical solutions of the present application solve the above technical problems with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0068] The application subject of a multi-dimensional quality and efficiency evaluation method for cluster and domain power grid projects provided by the implementation of the present application is a server. Specifically, the server can specifically include a server responsible for data processing on the back end that can realize functions such as data transmission and data processing on one side of the network platform. It can be a physical server, or a server cluster or distributed system composed of multiple physical servers. In this embodiment, the number of servers is not specifically limited. Alternatively, it can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, Content Delivery Network (CDN), and big data and artificial intelligence platforms.

[0069] For specific implementation, please refer to Figure 1 ,Figure 1 A schematic structural diagram of a server provided by an embodiment of the present application is shown as Figure 1 shown. The server 10 includes a processor 11, a memory 13, a communication interface 12, and one or more programs 131. Among them, the one or more programs 131 are stored on the memory 13 and are configured to be executed by the above-mentioned processor 11. The one or more programs 131 include instructions for executing any step in the following embodiments of the grid reserve project association cluster mining method.

[0070] Please refer to Figure 2 , Figure 2 A schematic flow diagram of a multi-dimensional quality and efficiency evaluation method for cluster-oriented and domain power grid projects provided by an embodiment of the present application is shown as Figure 2 shown. The method is executed by the server shown as Figure 1 shown, and specifically includes the following steps S201 - step S205:

[0071] Step S201, obtain a project data set corresponding to the power grid project cluster / domain.

[0072] Among them, the power grid project cluster / domain includes at least two power grid projects, which refers to a set or category formed by integrating and classifying at least two power grid-related projects. There are various association relationships among the power grid projects within the cluster, such as geographical correlation, functional complementarity, strategic consistency, technical relevance, resource relevance, etc. Exemplarily, the evaluation scope of the multi-dimensional quality and efficiency evaluation method for cluster-oriented and domain power grid projects provided by the embodiments of the present application includes two key cost-related project transfers: power grid infrastructure construction and production technology transformation. Power grid infrastructure projects mainly involve the construction of power grid infrastructure, such as building new substations, erecting transmission lines, and constructing distribution facilities. These projects are the basis for power grid expansion and upgrading, and can increase the power supply capacity and coverage of the power grid. Production technology transformation projects focus on technically transforming and upgrading existing power grid production equipment and systems to improve equipment performance, reduce losses, and enhance the reliability and efficiency of power grid operation, such as replacing old transformers, insulating transformation of transmission lines, and upgrading of automation control systems.

[0073] Both of these types of projects have obvious characteristics of cost investment and require a large amount of resources such as funds, manpower, and material resources during the implementation process. Therefore, when evaluating their quality and efficiency, it is necessary to focus on considering the relationship between cost and benefit to ensure the rational use of resources and the economic feasibility of projects.

[0074] Among them, the project data set includes important data such as scientific research reports, estimation books, and project middle platform data of the established power grid project cluster or power grid project domain and its reserve stage.

[0075] Step S202, construct a multi-dimensional quality and efficiency evaluation index system for the power grid project cluster / domain.

[0076] Among them, the multi-dimensional quality and efficiency evaluation index system includes at least two evaluation dimensions, at least two evaluation indicators for each evaluation dimension, and the index calculation formula for each evaluation dimension.

[0077] In some embodiments, the at least two evaluation dimensions include at least two of the economic evaluation dimension, the timeliness evaluation dimension, and the stability evaluation dimension. The evaluation indicators of the economic evaluation dimension include at least two of the power supply contribution rate, the loss reduction contribution rate, and the new overall cost. The evaluation indicators of the timeliness evaluation dimension include at least two of the strategic implementation rate, the key direction implementation rate, and the reserve support rate. The stability evaluation dimension includes at least two of the power grid system stability impact rate, the frequency stability impact rate, and the load balance improvement rate.

[0078] Among them, this application fully combines project management requirements and expert knowledge to comprehensively evaluate the power grid project cluster / domain from evaluation dimensions such as economy, timeliness, and stability. This application can also comprehensively evaluate the power grid project cluster / domain from other evaluation dimensions, which is not limited here.

[0079] Among them, the economic evaluation dimension mainly considers the comprehensive benefit contribution of the power grid project cluster / domain in terms of power supply and loss reduction, including the power supply contribution rate and the loss reduction contribution rate. At the same time, it takes into account the overall cost increase in project management and when the evaluation object changes from individual projects to project clusters and project domains.

[0080] Specifically, the power supply contribution rate reflects the contribution degree of the project cluster / domain in terms of power supply after production. By calculating the ratio of the difference between the budgeted power supply of the project group after production and the power supply of the previous period to the power supply of the previous period, the improvement effect of the project group on power supply is reflected. The higher the ratio, the greater the contribution of the project cluster / domain in increasing power supply and the more significant the role in meeting the power demand of the region or power grid system. The loss reduction contribution rate mainly considers the overall contribution of the project cluster / domain in reducing power losses. Usually, it calculates the ratio relationship between the reduced power loss after the implementation of the project group and the originally expected or previous power loss. The higher this index, the better the results achieved by the project cluster / domain in optimizing power transmission and reducing energy losses, which helps to improve the efficiency and economy of the power system and reduce operating costs. These two indicators evaluate the performance of the project cluster / domain in power supply and loss control from different aspects, providing an important economic evaluation basis for project management and helping to comprehensively measure the comprehensive benefits of the project.

[0081] Among them, the timeliness evaluation dimension mainly considers the timeliness of the project cluster / domain in terms of strategy and reserve planning, which is specifically reflected in the strategic implementation rate of the project cluster / domain in the corresponding strategic plan, and the overall planning rate of key directions and reserve scale in the reserve plan, manifested as the implementation rate of key directions and the reserve support rate.

[0082] Specifically, the strategic implementation rate is an indicator used to evaluate the implementation of relevant strategies by the project cluster / domain. This indicator reflects the overall progress and effect of the project cluster / domain in implementing the strategic plan. The higher the strategic implementation rate, the better the project cluster / domain performs in achieving strategic goals and the more it can promote project implementation according to the predetermined strategic plan. The implementation rate of key directions is mainly used to evaluate the implementation of key directions in the reserve of the project cluster / domain. This indicator focuses on the focus and implementation of key directions in the reserve plan by the project cluster / domain. The higher the implementation rate of key directions, the more accurately the project cluster / domain grasps the key directions in the reserve plan, the more reasonable the resource allocation, and the more conducive it is to achieving specific development goals. The reserve support rate is an indicator used to evaluate the implementation of the reserve scale by the project cluster / domain. This indicator reflects the degree of support of the project cluster / domain for the reserve plan in terms of capital investment. The higher the reserve support rate, the closer or exceeding the actual investment scale of the project cluster / domain is to the planned scale, which can provide more sufficient capital guarantee for the reserve plan, contribute to ensuring the smooth implementation and development of reserve projects, and enhance the development potential and competitiveness of the project cluster / domain in the future. If the reserve support rate is low, it may mean that the project cluster / domain has insufficient funds and needs to further adjust the investment strategy or strive for more resources to meet the requirements of the reserve plan.

[0083] Among them, the stability evaluation dimension refers to the possible stability fluctuations caused by the project cluster / domain to the power grid system, including at least two of the power grid system stability influence rate, frequency stability influence rate, and load balance improvement rate.

[0084] Specifically, the power grid system stability impact rate is an indicator used to measure the enhancement effect of a project group on the stability / security of the power grid system. It is calculated by comprehensively considering the impact of the project group on the power grid system stability in terms of voltage and power grid architecture, as well as the improvement in terms of security. The higher the value of this indicator, the more obvious the enhancement effect of the project group on the power grid system stability and security. Conversely, the lower the value, the smaller the positive impact of the project group on the power grid system stability, and there may even be a certain negative effect, requiring further analysis and improvement of the relevant design or operation mode of the project group. The frequency stability impact rate is used to measure the effect of a project cluster / domain on the frequency stability of the power grid system, reflecting the suppression or exacerbation effect of the project group on the power grid frequency fluctuation. When the frequency stability impact rate is too large and positive, it indicates that the project cluster / domain has a significant effect on improving the power grid frequency. When dealing with load changes, faults, etc., it can restore to a stable frequency more quickly, reducing the amplitude and duration of the frequency fluctuation. If the frequency stability impact rate is too small or even a large negative value, it means that the project cluster / domain has a greater negative impact on the power grid frequency stability. It may cause the power grid frequency to easily deviate from the reference value. During peak loads or in case of faults, the frequency drops too quickly, putting the power grid at risk of frequency collapse. The load balance improvement rate is used to evaluate the improvement degree of a project cluster / domain on the load distribution balance in the power grid. There are often differences in the load distribution among different regions of the power grid. The load balance improvement rate aims to measure the role played by the project group in optimizing the load distribution in each region of the power grid and reducing the phenomenon of load concentration after the implementation of the project group. A too large load balance improvement rate means that the project cluster / domain has achieved remarkable results in optimizing the power grid load distribution. This helps to make full use of the power transmission and supply capabilities of the power grid, avoiding the situation where some regional lines and equipment are overloaded while other regions have insufficient utilization. When the load balance improvement rate is too small or even negative, it means that the project cluster / domain has not effectively improved the power grid load imbalance situation, and may even make the load distribution more unreasonable.

[0085] In some embodiments, the power supply contribution rate includes the local power supply contribution rate and the overall line power supply contribution rate, and the loss reduction contribution rate includes the local loss reduction contribution rate and the overall line loss reduction contribution rate;

[0086] The index calculation formula of the local power supply contribution rate is as shown in formula (1) below:

[0087] B1 = ∑((D e -D p (R)) / D p (R)) Formula (1)

[0088] Wherein, B1 is the regional power supply contribution rate, D eThe power supply of the project in the power grid project cluster / field in the budget period after it is put into operation is in KWh; R is the region where the project belongs in the power grid project cluster / field; D p (R) is the power supply in the previous period in the region R to which the project belongs in the power grid project cluster / field, unit: KWh;

[0089] The calculation formula of the overall line power supply contribution rate is shown in the following formula (2):

[0090] B2=∑((D e -D p ) / D p ) Formula (2)

[0091] Among them, B2 is the contribution rate of the overall line power supply, D p The power supply in the previous period on the overall line of the power grid project cluster / field, unit: KWh;

[0092] The calculation formula of the local loss reduction contribution rate is as follows:

[0093] B3=∑(D e ×(L p (R)-L e ) / (D p (R)×L p (R))) Formula (3)

[0094] Among them, B3 is the contribution rate of regional loss reduction, R is the region to which the project belongs in the project group; L p (R) is the previous period line loss rate of the project region R in the power grid project cluster / field; L e Line loss rate for the budget period of the power grid project cluster / area;

[0095] The calculation formula of the overall line loss reduction contribution rate is shown in the following formula (4):

[0096] B4=∑(D e ×(L p -L e ) / (D p ×L p )) Formula (4)

[0097] Among them, B4 is the contribution rate of overall line loss reduction, L p The previous period line loss rate of the power grid project cluster / sector;

[0098] The calculation formula for the new overall cost indicator is as shown in the following formula (5):

[0099] B5=(C p +C m )×P iFormula (5)

[0100] Wherein, B5 is the newly added overall cost; C p is the estimated cost increased at the human resources level, including personnel training and communication costs; C m is the estimated cost increased at the management level, considering the increased management complexity due to geographical location and special project span; P i is the overall risk factor of the power grid project cluster / field.

[0101] Wherein, D e , D p (R), D p , L p (R), L e , L p , C p , C m , P i are extracted from the project data set through a pre-trained text processing model. According to the data characteristics and task requirements, a suitable text processing model is selected, such as recurrent neural network (RNN) and its variants long short-term memory network (LSTM), gated recurrent unit (GRU), or more advanced Transformer architectures such as BERT, etc.

[0102] Wherein, the regional power supply contribution rate measures the contribution degree of the project group to the power supply of the region where it is located from the regional aspect. It is obtained by calculating the difference between the budgeted power supply in the post-operation period of the projects in the project group and the total power supply in the previous period of the region to which the projects in the project group belong, and then dividing by the total power supply in the previous period. This indicator can help understand the improvement effect of the project group on the power supply in a specific region and reflects the contribution of the project group to the power supply at the regional level. The overall line power supply contribution rate measures the contribution degree of the project group to the power supply from the overall perspective of the power grid system. It is calculated by taking the difference between the budgeted power supply in the post-operation period of the projects in the project group and the power supply in the previous period of the power grid system, and then dividing by the power supply in the previous period. This indicator is mainly used to evaluate the impact of the project group on the power supply within the entire power grid system and enables managers to grasp the contribution of the project group to the overall power supply capacity of the power grid from a macroscopic perspective.

[0103] In some embodiments, the index calculation formula of the strategic implementation rate is as shown in Formula (6) below:

[0104] TL1 = (N a / N t ) × F t Formula (6)

[0105] Wherein, TL1 is the strategic implementation rate, N a is the number of projects implementing the corresponding strategic tasks in the power grid project cluster / field; N t is the total number of projects during the planning period; Ft is the time impact coefficient;

[0106] The index calculation formula of the implementation rate of the key direction is as shown in the following formula (7):

[0107] TL2 = (N i / N t ) ± I d Formula (7)

[0108] where TL2 is the implementation rate of the key direction, N i is the number of projects implementing the corresponding key direction in the power grid project cluster / domain; I d is the implementation index of the corresponding key direction;

[0109] The index calculation formula of the reserve support rate is as shown in the following formula (8):

[0110] TL3 = S g / S r Formula (8)

[0111] where TL3 is the reserve support rate, S g is the total investment scale of all projects in the power grid project cluster / domain; S r is the total planned scale of the corresponding special project / direction / strategy project during the planning period;

[0112] The index calculation formula of the influence rate of the power grid system stability is as shown in the following formula (9):

[0113] ST = α·VSI + β·SI + γ·PI Formula (9)

[0114] where ST is the influence rate of the power grid system stability; VSI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of voltage; SI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of the power grid architecture; PI is the improvement factor of the power grid project cluster / domain in terms of security; α, β, and γ are the relative importance of the corresponding voltage stability, power grid architecture, and security improvement respectively, and α + β + γ = 1;

[0115] The index calculation formula of the influence rate of the frequency stability is as shown in the following formula (10):

[0116] FSI = λ·FI + μ·AI Formula (10)

[0117] Among them, FSI is the frequency stability influence rate, FI is the image parameter of the power grid project cluster / domain on the stability of the power grid system in terms of frequency regulation; AI is the image parameter of the power grid project cluster / domain on the stability of the power grid system in terms of automatic generation control; λ and μ are the relative importance corresponding to frequency regulation and automatic generation control respectively, and λ + μ = 1;

[0118] The index calculation formula of the load balance improvement rate is shown in the following formula (11):

[0119]

[0120] Among them, LBI is the load balance improvement rate, and L pi is the load of each region before the implementation of the power grid project cluster / domain, and L ei is the load of each region after the implementation of the power grid project cluster / domain, and n is the number of regions divided in the power grid project cluster / domain.

[0121] Step S203, establish an automated calculation model according to the multi-dimensional quality and efficiency evaluation index system, and calculate the evaluation data of each evaluation index.

[0122] Among them, the automated calculation model can input the project data set and automatically output the evaluation data of each evaluation index. The automated calculation model is established through existing functions and calculation methods.

[0123] Exemplarily, the calculation steps of the automated calculation model for the regional power supply contribution rate of the project cluster / domain are as follows:

[0124] Step 1, input the project report set set(D) corresponding to the project cluster / domain;

[0125] Step 2, observe and extract the text segments containing parameters;

[0126] Step 3, extract the specific parameter values, and realize the logic of extracting D e , R, D p (R) parameters, and return D e , R, D p (R);

[0127] Step 4, calculate the final index value according to the formula (1) B1 = ∑((D e -D p (R)) / D p (R)) and return the final index B1.

[0128] Step S204, determine the index weight of each evaluation index according to the rough set theory.

[0129] In some embodiments, determining the index weight of each evaluation index according to the rough set theory includes: obtaining the classification information of the at least two power grid projects, where the classification information is used to characterize the quality and efficiency evaluation level of a single power grid project; determining one piece of classification information as the target decision attribute from the classification information; establishing a decision matrix based on the evaluation data of each evaluation index, where each row in the decision matrix is used to characterize a power grid project, and each column of the decision matrix is used to characterize an evaluation index or the classification information; calculating the dependence degree of each evaluation index on the target decision attribute according to the decision matrix and the dependence degree calculation formula, where the dependence degree is used to characterize the support degree of each evaluation index for the target decision attribute; calculating the assigned weight of each evaluation index according to the dependence degree of each evaluation index; where the dependence degree calculation formula is shown as formula (12) below:

[0130]

[0131] Where D is the target decision attribute, A is the evaluation index, and POS A (D) is the set of all power grid projects that can be determined to belong to the target decision attribute D under the evaluation index A, the dependence degree (D, A) represents the dependence degree of the evaluation index A on the target decision attribute D, and |D| is the number of power grid projects in the power grid project cluster / domain.

[0132] Where each power grid project has a quality and efficiency evaluation level, and the quality and efficiency evaluation level includes normal projects (D1) and inferior projects (D2). For example, projects that have been reserved for many years without implementation can be regarded as inferior projects.

[0133] In addition, each evaluation index calculates an evaluation score through an automated calculation model, and the continuous evaluation scores are divided into discrete levels (such as low, medium, high) according to business rules or data distribution, as shown in Table 1 below by way of example.

[0134] Table 1 shows the level division rules of the evaluation data of an evaluation index provided by an embodiment of the present application

[0135]

[0136] Where the logic of calculating the assigned weight of the evaluation index by the rough set theory is as follows:

[0137] Establish a decision matrix based on the evaluation data calculated for each evaluation index. Among them, each row in the decision matrix represents a power grid project, and each column represents an evaluation index or the classification information of the project. By way of example, see Table 2 below. Table 2 is an example of a decision matrix containing partial evaluation indexes provided by an embodiment of the present application.

[0138] Item B1 B2 B3 B4 B5 TL1 TL2 TL3 ST Classification Item 1 High Medium Low High Medium High High Low Medium Normal Item 2 Medium Low Medium Medium Low Medium Medium Medium High Inferior Item 3 Low High High Low High Low Low High Low Inferior Item 4 High High [[ID= ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​

[0139] The project cluster shown in Table 2 includes 5 projects. Among them, if the normal project is determined as the target decision attribute, the steps to calculate the dependence degree of each evaluation index on the target decision attribute according to the decision matrix and the dependence degree calculation formula are as follows: Under the same evaluation index, compare whether the classification information of projects with the same evaluation data level is the same. If it is the same, the classification information of the project can be clarified. If it is different or there is only one, the classification information of the project cannot be clarified. Specifically, if at least two projects belong to normal projects, determine their classification information as normal projects; if at least two projects belong to inferior projects, determine their classification information as inferior projects; if at least two projects, one is a normal project and the other is an inferior project, neither of these two projects can be determined as a normal project; if there is only one project with the evaluation data level, the classification information of the project cannot be clarified.

[0140] Exemplarily, for the contribution rate of local power supply B1, when B1 is "high", the classification information of Project 1 and Project 4 are both normal projects. Therefore, under the evaluation index B1, the projects that can be determined to belong to normal projects are Project 1 and Project 4; when B1 is "medium", Project 2 is an inferior project and Project 5 is a normal project. Therefore, it cannot be determined whether it belongs to a normal project; when B1 is "low", Project 3 is an inferior project and it cannot be determined whether it belongs to a normal project. Therefore, under the evaluation index B1, the projects that belong to normal projects are Project 1 and Project 4, that is, POS A1 (D1)=2, |D|=5, then the dependence degree (D1, A1)=2 / 5 = 0.4.

[0141] For the contribution rate of the overall line power supply B2, when B2 is "high", the classification information of Project 3 and Project 4 is different. Therefore, it cannot be determined whether it belongs to a normal project; when B2 is "medium", the classification information of Project 1 and Project 5 are both normal projects. Therefore, under the evaluation index B2, the projects that can be determined to belong to normal projects are Project 1 and Project 5; when B2 is "low", Project 2 is an inferior project and it cannot be determined whether it belongs to a normal project. Therefore, under the evaluation index B2, the projects that belong to normal projects are Project 1 and Project 5, that is, POS A2 (D1)=2, |D|=5, then the dependence degree (D1, A2)=2 / 5 = 0.4.

[0142] By analogy, the dependence degrees of the other 7 evaluation indicators are calculated. The specific process is omitted here. According to Table 2 above, the dependence degree (D1, A3) = 2 / 5 = 0.4, the dependence degree (D1, A4) = 2 / 5 = 0.4, the dependence degree (D1, A5) = 3 / 5 = 0.6, the dependence degree (D1, A6) = 2 / 5 = 0.4, the dependence degree (D1, A7) = 2 / 5 = 0.4, the dependence degree (D1, A8) = 2 / 5 = 0.4, the dependence degree (D1, A9) = 2 / 5 = 0.4.

[0143] In some embodiments, calculating the allocation weight of each evaluation indicator according to the dependence degree of each evaluation indicator includes: calculating the allocation weight of the evaluation indicator according to the following formula (13):

[0144]

[0145] where i is the serial number of the evaluation indicator, and w i is the allocation weight of the evaluation indicator A i , and n is the total number of evaluation indicators.

[0146] Continuing with the above example, the dependence degree (D, A j ) = 0.4 + 0.4 + 0.4 + 0.4 + 0.6 + 0.4 + 0.4 + 0.4 + 0.4 = 3.8. Then the weights of the above 9 evaluation indicators are respectively w1 = 0.4 / 3.8 ≈ 0.1053, w2 = 0.4 / 3.8 ≈ 0.1053, w3 = 0.4 / 3.8 ≈ 0.1053, w4 = 0.4 / 3.8 ≈ 0.1053, w5 = 0.6 / 3.8 ≈ 0.1579, w6 = 0.4 / 3.8 ≈ 0.1053, w7 = 0.4 / 3.8 ≈ 0.1053, w8 = 0.4 / 3.8 ≈ 0.1053, w9 = 0.4 / 3.8 ≈ 0.1053.

[0147] Step S205, construct a multi-dimensional index fusion model according to the index weights to obtain the comprehensive quality and efficiency evaluation result of the project cluster / domain.

[0148] In some embodiments, constructing a multi-dimensional index fusion model according to the index weights to obtain the comprehensive quality and efficiency evaluation result of the project cluster / domain includes: obtaining the allocation weight and the evaluation data of each evaluation indicator in the power grid project cluster / domain; calculating the comprehensive quality and efficiency evaluation data of the power grid project cluster / domain according to the evaluation data and the allocation weight; determining the comprehensive quality and efficiency evaluation result of the power grid project cluster / domain according to the corresponding relationship between the comprehensive quality and efficiency evaluation data and the classification information.

[0149] It can be seen that in this embodiment, indicators such as the power supply contribution rate and the loss reduction contribution rate can quantify the benefits of the project cluster in terms of increased power supply and reduced losses. At the same time, considering the overall cost, it helps managers clearly understand the economic performance of the project group and determine whether it has achieved the effective utilization of resources and the maximization of economic benefits. Indicators such as the strategic implementation rate, the implementation rate of key directions, and the reserve support rate can reflect the implementation of the project cluster in terms of strategy and reserve planning, ensure that the project group is consistent with the overall strategic direction, respond to the needs of market and industry development in a timely manner, and avoid the disconnection between project implementation and strategic goals. The grid system stability impact rate indicator focuses on evaluating the impact of the project group on the stability of the grid system, ensuring the safety and reliability of grid operation, and avoiding unstable factors in the grid caused by project implementation, which affect the quality of power supply. By establishing a quality and efficiency evaluation system through the above-mentioned indicators in each dimension and comprehensively evaluating the project cluster / field, the comprehensiveness and accuracy of the quality and efficiency evaluation of the project cluster / field can be enhanced.

[0150] The above mainly introduces the solution of the embodiment of the present application from the perspective of the execution process on the method side. It can be understood that in order for the server to implement the above functions, it includes the corresponding hardware structure and / or software module for executing each function. Those skilled in the art should easily realize that, combined with the units and algorithm steps of each example described in the embodiments provided in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware 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 application.

[0151] The embodiment of the present application can divide the functional units of the server according to the above method examples. For example, each functional unit can be divided corresponding to each function, or two or more functions can be integrated into one processing module. The above integrated units can be implemented in the form of hardware or in the form of software program modules. It should be noted that the division of units in the embodiment of the present application is illustrative, only a logical function division, and there may be other division methods in actual implementation.

[0152] In the case of adopting integrated units, please refer to ​ , ​ which is a functional unit structure block diagram of a multi-dimensional quality and efficiency evaluation device for grid projects facing clusters and fields provided by the embodiment of the present application. The multi-dimensional quality and efficiency evaluation device 3 includes:

[0153] An acquisition unit 301, configured to acquire a project data set corresponding to a grid project cluster / field, where the grid project cluster / field includes at least two grid projects;

[0154] A processing unit 302, configured to construct a multi-dimensional quality and efficiency evaluation index system for the power grid project cluster / domain, where the multi-dimensional quality and efficiency evaluation index system includes at least two evaluation dimensions, at least two evaluation indexes for each evaluation dimension, and an index calculation formula for each evaluation dimension; and, establish an automated calculation model according to the multi-dimensional quality and efficiency evaluation index system, calculate evaluation data for each evaluation index; and, determine the index weight of each evaluation index according to the rough set theory;

[0155] An output unit 303, configured to construct a multi-dimensional index fusion model according to the index weight to obtain a comprehensive quality and efficiency evaluation result of the project cluster / domain.

[0156] It can be seen that in the embodiment of the present application, by obtaining the project data set corresponding to the power grid project cluster / domain, a multi-dimensional quality and efficiency evaluation index system for the power grid project cluster / domain is constructed, where the power grid project cluster / domain includes at least two power grid projects, and the multi-dimensional quality and efficiency evaluation index system includes at least two evaluation dimensions, at least two evaluation indexes for each evaluation dimension, and an index calculation formula for each evaluation dimension; then an automated calculation model is established according to the multi-dimensional quality and efficiency evaluation index system, and the evaluation data for each evaluation index is calculated; the index weight of each evaluation index is determined according to the rough set theory; a multi-dimensional index fusion model is constructed according to the index weight to obtain a comprehensive quality and efficiency evaluation result of the project cluster / domain. Therefore, in the present application, taking the project cluster and project domain as the research objects, fully considering the relevance between projects, determining the key evaluation dimensions and their evaluation indexes of the project cluster / domain, and combining the existing data to set specific indexes and their calculation formulas, a comprehensive quality and efficiency evaluation index system is constructed, and a rough set-based evaluation index fusion method is used to improve the objectivity of the weight distribution of each evaluation index and realize the comprehensive evaluation of the project cluster and domain.

[0157] In some embodiments, at least two of the at least two evaluation dimensions include an economic evaluation dimension, a timeliness evaluation dimension, and a stability evaluation dimension. The evaluation indexes of the economic evaluation dimension include at least two of the power supply contribution rate, the loss reduction contribution rate, and the new overall cost; the evaluation indexes of the timeliness evaluation dimension include at least two of the strategic implementation rate, the key direction implementation rate, and the reserve support rate; the stability evaluation dimension includes at least two of the power grid system stability influence rate, the frequency stability influence rate, and the load balance improvement rate.

[0158] In some embodiments, the power supply contribution rate includes the local power supply contribution rate and the overall line power supply contribution rate, and the loss reduction contribution rate includes the local loss reduction contribution rate and the overall line loss reduction contribution rate; the index calculation formula of the local power supply contribution rate is shown in the following formula (1):

[0159] B1 = ∑((D e - D p (R)) / D p (R)) Formula (1)

[0160] Among them, B1 is the contribution rate of regional power supply, D e is the power supply in the budget period after the project is put into production in the power grid project cluster / field, unit: KWh; R is the region where the project in the power grid project cluster / field is located; D p (R) is the previous period's power supply in region R where the project in the power grid project cluster / field is located, unit: KWh;

[0161] The index calculation formula for the overall line power supply contribution rate is as shown in the following Formula (2):

[0162] B2 = ∑((D e - D p ) / D p ) Formula (2)

[0163] Among them, B2 is the contribution rate of the overall line power supply, D p is the previous period's power supply on the overall line of the power grid project cluster / field, unit: KWh;

[0164] The index calculation formula for the contribution rate of local loss reduction is as shown in the following Formula (3):

[0165] B3 = ∑(D e × (L p (R) - L e ) / (D p (R) × L p (R))) Formula (3)

[0166] Among them, B3 is the contribution rate of regional loss reduction, R is the region where the project in the project group is located; L p (R) is the previous period's line loss rate in region R where the project in the power grid project cluster / field is located; L e is the budget period line loss rate of the power grid project cluster / field;

[0167] The index calculation formula for the contribution rate of the overall line loss reduction is as shown in the following Formula (4):

[0168] B4 = ∑(D e × (L p - L e ) / (D p × L p )) Formula (4)

[0169] Among them, B4 is the contribution rate of the overall line loss reduction, L pis the previous line loss rate of the power grid project cluster / domain;

[0170] The index calculation formula for the newly added overall cost is shown as formula (5) below:

[0171] B5 = (C p + C m ) × P i Formula (5)

[0172] B5 is the newly added overall cost; C p is the estimated cost increased at the human level, including personnel training and communication costs; C m is the estimated cost increased at the management level, considering the increased management complexity due to region and special project span; P i is the overall risk factor of the power grid project cluster / domain.

[0173] In some embodiments, the index calculation formula for the strategic implementation rate is shown as formula (6) below:

[0174] TL1 = (N a / N t ) × F t Formula (6)

[0175] Wherein, TL1 is the strategic implementation rate, N a is the number of projects implementing the corresponding strategic tasks in the power grid project cluster / domain; N t is the total number of projects during the planning period; F t is the time impact coefficient;

[0176] The index calculation formula for the implementation rate of the key direction is shown as formula (7) below:

[0177] TL2 = (N i / N t ) ± I d Formula (7)

[0178] Wherein, TL2 is the implementation rate of the key direction, N i is the number of projects implementing the corresponding key direction in the power grid project cluster / domain; I d is the implementation index of the corresponding key direction;

[0179] The index calculation formula for the reserve support rate is shown as formula (8) below:

[0180] TL3 = S g / S r Formula (8)

[0181] Wherein, TL3 is the reserve support rate, S g is the total investment scale of all projects in the power grid project cluster / domain; Sr is the total planned scale of the corresponding special project / direction / strategic project during the planning period;

[0182] The index calculation formula for the influence rate of the power grid system stability is shown in the following formula (9):

[0183] ST = α·VSI + β·SI + γ·PI Formula (9)

[0184] Where, ST is the influence rate of the power grid system stability; VSI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of voltage; SI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of the power grid architecture; PI is the improvement factor of the power grid project cluster / domain in terms of security; α, β, and γ are the relative importance of the corresponding voltage stability, power grid architecture, and security improvement respectively, and α + β + γ = 1;

[0185] The index calculation formula for the influence rate of the frequency stability is shown in the following formula (10):

[0186] FSI = λ·FI + μ·AI Formula (10)

[0187] Where, FSI is the influence rate of the frequency stability, FI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of frequency regulation; AI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of automatic generation control; λ and μ are the relative importance of the corresponding frequency regulation and automatic generation control respectively, and λ + μ = 1;

[0188] The index calculation formula for the improvement rate of the load balance degree is shown in the following formula (11):

[0189]

[0190] Where, LBI is the improvement rate of the load balance degree, L pi is the load of each region before the implementation of the power grid project cluster / domain, L ei is the load of each region after the implementation of the power grid project cluster / domain, and n is the number of regions divided in the power grid project cluster / domain.

[0191] In some embodiments, the processing unit 302 determines the index weights of each evaluation index according to the rough set theory, including: obtaining the classification information of the at least two power grid projects, where the classification information is used to characterize the quality and efficiency evaluation level of a single power grid project; determining one piece of classification information from the classification information as the target decision attribute; establishing a decision matrix according to the evaluation data of each evaluation index, where each row in the decision matrix is used to characterize a power grid project, and each column of the decision matrix is used to characterize an evaluation index or the classification information; calculating the dependence degree of each evaluation index on the target decision attribute according to the decision matrix and the dependence degree calculation formula, where the dependence degree is used to characterize the support degree of each evaluation index for the target decision attribute; calculating the assigned weight of each evaluation index according to the dependence degree of each evaluation index.

[0192] Among them, the dependence degree calculation formula is shown in the following formula (12):

[0193]

[0194] Among them, D is the target decision attribute, A is the evaluation index, POS A (D) is the set of all power grid projects that can be determined to belong to the target decision attribute D under the evaluation index A. The dependence degree (D, A) represents the dependence degree of the evaluation index A on the target decision attribute D, and |D| is the number of power grid projects in the power grid project cluster / domain.

[0195] In some embodiments, the processing unit 302 calculates the assigned weight of each evaluation index according to the dependence degree of each evaluation index, including: calculating the assigned weight of the evaluation index according to the following formula (13):

[0196]

[0197] Among them, i is the serial number of the evaluation index, w i is the assigned weight of the evaluation index A i , and n is the total number of evaluation indexes.

[0198] In some embodiments, constructing a multi-dimensional index fusion model according to the index weights to obtain the comprehensive quality and efficiency evaluation result of the project cluster / domain includes: obtaining the assigned weight and the evaluation data of each evaluation index in the power grid project cluster / domain; calculating the comprehensive quality and efficiency evaluation data of the power grid project cluster / domain according to the evaluation data and the assigned weight; determining the comprehensive quality and efficiency evaluation result of the power grid project cluster / domain according to the corresponding relationship between the comprehensive quality and efficiency evaluation data and the classification information.

[0199] An embodiment of the present application provides a computer-readable storage medium, on which computer programs / instructions are stored. When the computer programs / instructions are executed by a processor, the steps of the method according to any possible embodiment are implemented.

[0200] It should be noted that, for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0201] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0202] In several embodiments provided by the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the above division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in an electrical or other form.

[0203] The units described as separate components above may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0204] In addition, in each embodiment of the present application, the functional units can be integrated into one processing unit, or each unit exists physically alone, or two or more units are integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0205] If the above integrated 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 memory. Based on such an understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the above methods in various embodiments of this application. The aforementioned memory includes: various media such as USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0206] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing relevant hardware through a program. This program can be stored in a computer-readable memory, and the memory can include: flash drives, read-only memories (English: Read-Only Memory, abbreviated as: ROM), random access memories (English: Random Access Memory, abbreviated as: RAM), magnetic disks, or optical discs, etc.

[0207] The above has introduced the embodiments of this application in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A multi-dimensional quality and efficiency evaluation method for cluster and domain power grid projects, characterized in that The method includes: Obtaining a set of project data corresponding to a power grid project cluster / domain, where the power grid project cluster / domain includes at least two power grid projects; Constructing a multi-dimensional quality and efficiency evaluation index system for the power grid project cluster / domain, where the multi-dimensional quality and efficiency evaluation index system includes at least two evaluation dimensions, at least two evaluation indexes for each evaluation dimension, and index calculation formulas for the indexes of each evaluation dimension; Establishing an automated calculation model according to the multi-dimensional quality and efficiency evaluation index system, and calculating evaluation data for each evaluation index; Determining the index weights of each evaluation index according to the rough set theory; Constructing a multi-dimensional index fusion model according to the index weights to obtain the comprehensive quality and efficiency evaluation result of the project cluster / domain.

2. The method according to claim 1, wherein The at least two evaluation dimensions include at least two of an economic evaluation dimension, a timeliness evaluation dimension, and a stability evaluation dimension. The evaluation indexes of the economic evaluation dimension include at least two of a power supply contribution rate, a loss reduction contribution rate, and a new overall cost; the evaluation indexes of the timeliness evaluation dimension include at least two of a strategic implementation rate, a key direction implementation rate, and a reserve support rate; the stability evaluation dimension includes at least two of a power grid system stability influence rate, a frequency stability influence rate, and a load balance improvement rate.

3. The method according to claim 2, wherein The power supply contribution rate includes a local power supply contribution rate and an overall line power supply contribution rate, and the loss reduction contribution rate includes a local loss reduction contribution rate and an overall line loss reduction contribution rate; The index calculation formula of the local power supply contribution rate is shown as formula (1) below: B1 = ∑((D e - D p (R)) / D p (R)) Equation (1) Among them, B1 is the contribution rate of regional power supply, and D e is the power supply in the budget period after the project is put into production in the power grid project cluster / field, unit: KWh; R is the region to which the project in the power grid project cluster / field belongs; D p (R) is the power supply in the previous period of region R to which the project in the power grid project cluster / field belongs, unit: KWh; The index calculation formula of the overall line power supply contribution rate is shown as formula (2) below: B2 = ∑((D e - D p ) / D p ) Equation (2) Among them, B2 is the contribution rate of the overall line power supply, and D p is the previous period power supply on the overall line of the power grid project cluster / domain, unit: KWh; The index calculation formula of the local loss reduction contribution rate is shown as formula (3) below: B3 = ∑(D e ×(L p (R)-L e )) / (D p (R)×L p (R))) Formula (3) Among them, B3 is the contribution rate of regional loss reduction, R is the region to which the projects in the project group belong; L p (R) is the previous period line loss rate of region R to which the projects in the power grid project cluster / field belong; L e is the line loss rate of the budget period of the power grid project cluster / field; The index calculation formula of the overall line loss reduction contribution rate is shown as formula (4) below: B4 = ∑(D e ×(L p - L e ) / (D p ×L p )) Formula (4) Among them, B4 is the contribution rate of the overall line loss reduction, and L p is the previous period line loss rate of the power grid project cluster / domain; The index calculation formula of the new overall cost is shown as formula (5) below: B5 = (C p + C m ) × P i Equation (5) B5 is the newly added overall cost; C p is the estimated cost increased at the human resources level, including personnel training and communication costs; C m is the estimated cost increased at the management level, considering the increased management complexity due to geographical location and special project span; P i is the overall risk factor for power grid project clusters / fields.

4. The method according to claim 2, wherein The index calculation formula of the strategic implementation rate is shown as formula (6) below: TL1=(N a / N t )×F t Formula (6) Among them, TL1 is the strategic implementation rate, N a is the number of projects implementing the corresponding strategic tasks in the power grid project cluster / domain; N t is the total number of projects during the planning period; F t is the time impact coefficient; The index calculation formula of the key direction implementation rate is shown as formula (7) below: TL2 = (N i / N t ) ± I d Equation (7) Among them, TL2 is the implementation rate of key directions, and N i is the number of projects implementing the corresponding key directions in the power grid project cluster / domain; I d is the implementation index of the corresponding key direction. The index calculation formula of the reserve support rate is shown as formula (8) below: TL3 = S g / S r Formula (8) Among them, TL3 is the reserve support ratio, and S g is the total investment scale of all projects in the power grid project cluster / domain; S r is the total planned scale of the corresponding special project / direction / strategic project during the planning period; The index calculation formula of the power grid system stability influence rate is shown as formula (9) below: ST = α·VSI + β·SI + γ·PI Formula (9) Where, ST is the power grid system stability influence rate; VSI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of voltage; SI is the influence parameter of the power grid project cluster / domain on the power grid system stability in terms of the power grid architecture; PI is the improvement factor of the power grid project cluster / domain in terms of security; α, β, and γ are respectively the relative importance corresponding to voltage stability, power grid architecture, and security improvement, and α + β + γ = 1; The index calculation formula of the frequency stability influence rate is shown as formula (10) below: FSI = λ·FI + μ·AI Formula (10) Among them, FSI is the frequency stability influence rate, FI is the image parameter of the power grid project cluster / domain on the stability of the power grid system in terms of frequency regulation; AI is the image parameter of the power grid project cluster / domain on the stability of the power grid system in terms of automatic generation control; λ and μ are the relative importance corresponding to frequency regulation and automatic generation control respectively, and λ + μ = 1; The index calculation formula of the load balance improvement rate is shown in the following formula (11): Among them, LBI is the improvement rate of load balancing degree, L pi is the load of each region before the implementation of the power grid project cluster / field, L ei is the load of each region after the implementation of the power grid project cluster / field, and n is the number of regions divided in the power grid project cluster / field.

5. The method according to claim 2, wherein Determining the index weight of each evaluation index according to the rough set theory includes: Obtaining the classification information of the at least two power grid projects, where the classification information is used to characterize the quality and efficiency evaluation level of a single power grid project; Determining one piece of classification information from the classification information as the target decision attribute; Establishing a decision matrix according to the evaluation data of each evaluation index, where each row in the decision matrix is used to characterize a power grid project, and each column of the decision matrix is used to characterize an evaluation index or the classification information; Calculating the dependence degree of each evaluation index on the target decision attribute according to the decision matrix and the dependence degree calculation formula, where the dependence degree is used to characterize the support degree of each evaluation index for the target decision attribute; Calculating the assigned weight of each evaluation index according to the dependence degree of each evaluation index; Among them, the dependence degree calculation formula is shown in the following formula (12): Among them, D is the target decision attribute, A is the evaluation index, and POS A (D) is the set of all power grid projects that can be determined to belong to the target decision attribute D under the evaluation index A. The dependence degree (D, A) represents the dependence degree of the evaluation index A on the target decision attribute D, and |D| is the number of power grid projects in the power grid project cluster / domain.

6. The method according to claim 5, characterized in that, Calculating the assigned weight of each evaluation index according to the dependence degree of each evaluation index includes: Calculating the assigned weight of the evaluation index according to the following formula (13): where i is the serial number of the evaluation index, and w i is the allocation weight of evaluation index A i , and n is the total number of evaluation indexes.

7. The method according to claim 6, wherein Constructing a multi-dimensional index fusion model according to the index weight to obtain the comprehensive quality and efficiency evaluation result of the project cluster / domain includes: Obtaining the assigned weight and the evaluation data of each evaluation index in the power grid project cluster / domain; Calculating the comprehensive quality and efficiency evaluation data of the power grid project cluster / domain according to the evaluation data and the assigned weight; Determining the comprehensive quality and efficiency evaluation result of the power grid project cluster / domain according to the corresponding relationship between the comprehensive quality and efficiency evaluation data and the classification information.

8. A multi-dimensional quality and efficiency evaluation device for cluster and domain power grid projects, characterized in that, The device includes: An acquisition unit, configured to acquire a project data set corresponding to a power grid project cluster / domain, where the power grid project cluster / domain includes at least two power grid projects; A processing unit, configured to construct a multi-dimensional quality and efficiency evaluation index system for the power grid project cluster / domain, where the multi-dimensional quality and efficiency evaluation index system includes at least two evaluation dimensions, at least two evaluation indexes for each evaluation dimension, and the index calculation formula for each evaluation dimension; and, establishing an automatic calculation model according to the multi-dimensional quality and efficiency evaluation index system, calculating the evaluation data of each evaluation index; and, determining the index weight of each evaluation index according to the rough set theory; An output unit, configured to construct a multi-dimensional index fusion model according to the index weight to obtain the comprehensive quality and efficiency evaluation result of the project cluster / domain.

9. A server, characterized in that, Comprising a processor, a memory, a communication interface, and one or more programs, the one or more programs being stored in the memory and executed by the processor, the programs comprising instructions for performing the steps in the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, On which a computer program / instructions are stored, and when the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1-7 are implemented.

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