Method, device and system for evaluating digital transformation maturity of power grid enterprise

Abstract

The invention provides a power grid enterprise digital transformation maturity evaluation method, device and system, and belongs to the field of power grid enterprise transformation. The method comprises the steps of obtaining a digitized index data set of a to-be-evaluated power grid enterprise; the index data set comprises a data set of performance evaluation indexes and a data set of basic guarantee indexes, and the performance evaluation indexes comprise a plurality of first indexes; inputting the index data set into a maturity evaluation model to obtain a digital score of the to-be-evaluated power grid enterprise, and determining a digital maturity grade of the to-be-evaluated power grid enterprise based on the score, the maturity evaluation model comprising a performance evaluation index and a basic guarantee index, the weight of the basic guarantee index is determined based on an analytic hierarchy process and an entropy weight method, and the weight of each first index in the performance evaluation indexes is obtained by correcting a second weight based on the first weight of each first index. According to the method, the maturity of the digital transformation of the power grid can be accurately evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid enterprise transformation, and particularly to an evaluation method, device and system for the digital transformation maturity of power grid enterprises. Background Art

[0002] With the transformation of the global energy structure and the rapid development of digital technologies, power grid enterprises are facing unprecedented opportunities and challenges for transformation. Digital transformation has become the key path for power grid enterprises to improve operational efficiency, enhance energy supply security, and achieve sustainable development goals.

[0003] The digital transformation of power grid enterprises is the only way to promote energy transformation and conform to the dual-carbon goal. By measures such as the intelligent upgrade of the power grid and the coordinated interaction of the power source-grid-load-energy storage, the access capabilities of new energy, distributed power sources, and microgrids are improved, accelerating the pace of the power grid's upgrade to an energy Internet and achieving the goal of high-quality development of power grid enterprises.

[0004] Most of the current evaluation methods for digital transformation maturity determine the digital transformation maturity through expert scoring or questionnaires, with a large degree of subjectivity and unable to objectively evaluate. However, the digital transformation process is a dynamic process of continuous optimization of resources. How to construct a convenient and accurate evaluation tool to analyze the digital transformation capabilities according to the digital transformation stage of the enterprise and dynamically adjust digital resources based on the analysis results is a technical problem that urgently needs to be solved at present. Summary of the Invention

[0005] Embodiments of the present invention provide an evaluation method, device and system for the digital transformation maturity of power grid enterprises to solve the problem that there is currently no tool that can accurately evaluate digital transformation.

[0006] In a first aspect, embodiments of the present invention provide an evaluation method for the digital transformation maturity of power grid enterprises, including:

[0007] Obtaining an index data set of the digitalization of the power grid enterprise to be evaluated; the index data set includes a data set of performance evaluation indicators and a data set of basic guarantee indicators, and the performance evaluation indicators include multiple first indicators;

[0008] Inputting the index data set into a maturity evaluation model to obtain a score for the digitalization of the power grid enterprise to be evaluated, and determining a maturity rating for the digitalization of the power grid enterprise to be evaluated based on the score;

[0009] Among them, the maturity evaluation model includes performance evaluation indicators and basic guarantee indicators. The weights of the basic guarantee indicators are determined based on the analytic hierarchy process and the entropy weight method. The weights of the first indicators in the performance evaluation indicators are obtained by correcting the second weights based on the first weights of the first indicators. The first weights are obtained based on the standard matrix composed of all the first indicators, and the second weights are obtained based on the entropy weight method.

[0010] In a possible implementation, before inputting the indicator data set into the maturity evaluation model, it further includes:

[0011] Performing standardization processing on the indicator data set to obtain a standardized standard indicator data set;

[0012] Inputting the standard indicator data set into the maturity evaluation model.

[0013] In a possible implementation, the determination process of the first weights of the first indicators is as follows:

[0014] Constructing a first matrix; the first matrix is determined by the product of the standard matrix and the transpose matrix of the standard matrix, and the standard matrix is composed of the first indicators after standardization processing;

[0015] Determining the first weights corresponding to each first indicator based on the first matrix.

[0016] In a possible implementation, determining the first weights corresponding to each first indicator based on the first matrix includes:

[0017] Calculating the singular value set of the first matrix; the singular value set includes multiple singular values;

[0018] Multiplying each singular value in the singular value set by the corresponding first indicator to obtain a new standard matrix;

[0019] Determining the information entropy redundancy of each first indicator based on the entropy values of the first indicators in the new standard matrix;

[0020] Determining the first weights of each first indicator based on the information entropy redundancy of each first indicator.

[0021] In a possible implementation, the method for determining the weights of the first indicators is as follows:

[0022] Determining the weight of each target indicator based on the square root of the product of the first weight and the second weight of each first indicator.

[0023] In a possible implementation, the basic guarantee indicators include multiple second indicators;

[0024] The weight of each second-level indicator is determined by taking the square root of the product of the third-level weight obtained based on the analytic hierarchy process and the fourth-level weight obtained by the entropy weight method.

[0025] In a possible implementation, the basic guarantee indicators include the data management and service foundation, production digitalization foundation, customer service digitalization foundation, operation management digitalization foundation, digital industrial integration and upgrading, and digital guarantee system construction.

[0026] The data management and service foundation includes the proportion of Internet of Things terminal devices, the proportion of remotely controlled devices, the proportion of intelligent automation devices, the proportion of big data computing modes, the proportion of power data collection, and the network utilization rate of the enterprise.

[0027] The production digitalization foundation includes the intelligent terminal application rate, the construction proportion of three-dimensional digital channels, the coverage rate of unmanned aerial vehicle autonomous inspection, the number of Beidou base stations, the online visualization coverage rate of the power grid, the system warning release accuracy rate, the electricity consumption information collection coverage rate, the new energy power generation power prediction accuracy rate, the new energy consumption capacity, the intelligent electricity meter coverage rate, the device networking rate, the online service rate, the correct rate of remote control actions, the data access integrity rate, the power generation power prediction accuracy rate, the digital coverage rate of production line equipment, etc., the application rate of robot artificial intelligence technology, and the radiation rate of the digitalization of the power grid industrial chain.

[0028] The customer service digitalization foundation includes: the digital coverage rate of the client side, the proportion of products with online monitoring status, the detection accuracy of the product monitoring system, the proportion of products included in the online fault maturity, the diagnosis accuracy rate of the fault diagnosis system, and the customer service work order reply rate.

[0029] The operation management digitalization foundation includes: the digital proportion of the capital flow link, the usage rate of financial information software, the digital proportion of financial analysis, the construction proportion of digital audit workrooms, the construction proportion of digital audit data warehouses, the digital audit technology development proportion, the digital proportion of performance management, the digital proportion of salary and welfare management, the electronic procurement coverage rate, the online business processing rate, and the digitalization of procurement management.

[0030] The digital industrial integration and upgrading includes: the integration proportion of the internal supply chain of the enterprise, the digital business coverage rate, the proportion of charging piles, the proportion of smart vehicle networking services, and the proportion of rooftop distributed photovoltaic access.

[0031] The digital guarantee system construction includes: the cloudification rate of IT basic resources, IT efficiency, and IT benefits.

[0032] In a possible implementation, the performance evaluation indicators include benefit indicators, efficiency indicators, and comprehensive contribution rate indicators.

[0033] The benefit indicators include the penetration rate of the energy Internet marketing service system, the proportion of online payments, the proportion of automatic electricity bill review and issuance, the coverage rate of automatic reconciliation, and the coverage rate of online refund services;

[0034] The efficiency indicators include the information transmission efficiency, the accuracy rate of power outage judgment, the power outage repair efficiency, the R & D cycle efficiency, the production efficiency, the market response rate, the failure rate in the target area, and the equipment aging replacement rate;

[0035] The comprehensive contribution rate indicators include the output value contribution rate, the profit contribution rate, the income increase contribution rate, the cost savings contribution rate, the comprehensive benefit growth contribution rate, the investment return rate, and the loss rate.

[0036] In the second aspect, the embodiments of the present invention provide an evaluation device for the digital transformation maturity of power grid enterprises, including:

[0037] An acquisition module, configured to acquire an index data set for evaluating the digitalization of a power grid enterprise to be evaluated; the index data set includes a data set of performance evaluation indicators and a data set of basic guarantee indicators, and the performance evaluation indicators include a plurality of first indicators;

[0038] A rating module, configured to input the index data set into a maturity evaluation model to obtain a score for evaluating the digitalization of the power grid enterprise to be evaluated, and determine the maturity rating of the digitalization of the power grid enterprise to be evaluated based on the score;

[0039] Among them, the maturity evaluation model includes performance evaluation indicators and basic guarantee indicators. The weights of the basic guarantee indicators are determined based on the analytic hierarchy process and the entropy weight method. The weights of the first indicators in the performance evaluation indicators are obtained by correcting the second weights based on the first weights of the first indicators. The first weights are obtained based on a standard matrix composed of all the first indicators, and the second weights are obtained based on the entropy weight method.

[0040] In the third aspect, the embodiments of the present invention provide an evaluation system for the digital transformation maturity of power grid enterprises. The system includes an evaluation server, and a computer program is stored in the evaluation server. When the computer program is executed by a processor, the steps of any method in the first aspect are implemented.

[0041] An embodiment of the present invention provides a method, device, and system for evaluating the maturity of the digital transformation of power grid enterprises. First, an index data set for evaluating the digitalization of power grid enterprises is obtained, and then by inputting the obtained data set into a maturity evaluation model, the score of the digitalization of the power grid enterprise to be evaluated can be obtained. In addition, after obtaining the score, the maturity rating can also be determined based on the obtained score. To ensure the accuracy of the score, multiple indicators are selected, and the performance evaluation indicators also include multiple indicators. In addition, the weight of each indicator is also determined based on multiple weights, so that the final maturity rating is more accurate. Thus, an accurate evaluation of the digital transformation ability of the power grid to be evaluated is realized, and then the digital transformation ability can be analyzed according to the digital transformation stage of the enterprise to be evaluated, and the digital resources can be further adjusted according to the analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0043] Figure 1 is the implementation flowchart of the method for evaluating the maturity of the digital transformation of power grid enterprises provided by the embodiment of the present invention;

[0044] Figure 2 is the structural schematic diagram of the maturity evaluation model provided by the embodiment of the present invention;

[0045] Figure 3 is the structural schematic diagram of the device for evaluating the maturity of the digital transformation of power grid enterprises provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, the detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present invention.

[0047] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will be described through specific embodiments with reference to the drawings.

[0048] Figure 1 is the implementation flowchart of the method for evaluating the maturity of the digital transformation of power grid enterprises provided by the embodiment of the present invention, which is described in detail as follows:

[0049] S110. Obtain the index dataset for evaluating the digitalization of the power grid enterprise to be evaluated.

[0050] As introduced in the background technology, the current evaluation indexes are relatively single and cannot accurately evaluate the maturity of power grid digitalization. Therefore, it is necessary to collect multiple data for evaluation.

[0051] The index dataset includes the dataset of performance evaluation indexes and the dataset of basic guarantee indexes, and the performance evaluation indexes include multiple first-level indexes.

[0052] The performance evaluation indexes are used to finally quantitatively evaluate the overall digital level of the enterprise, and then measure the changes in economic and social benefits during the digitalization process of the power grid enterprise. As shown in Table 1, the performance evaluation indexes in this application include benefit indexes, efficiency indexes, and comprehensive contribution rate indexes. The benefit indexes include the penetration rate of the energy Internet marketing service system, the proportion of online payment, the proportion of automatic electricity bill review and issuance, the coverage rate of automatic reconciliation, and the coverage rate of online refund business. The efficiency indexes include information transmission efficiency, accuracy rate of power outage judgment, power outage repair efficiency, R & D cycle efficiency, production efficiency, market response rate, failure incidence rate in the target area, and equipment aging replacement rate. The comprehensive contribution rate indexes include output value contribution rate, profit contribution rate, income increase contribution rate, cost saving contribution rate, comprehensive benefit growth contribution rate, return on investment, and loss rate.

[0053] Table 1 Performance

[0054]

[0055]

[0056] In some embodiments, the basic guarantee indexes include data management and service foundation, production digitalization foundation, customer service digitalization foundation, operation management digitalization foundation, digital industry integration and upgrading, and digital guarantee system construction.

[0057] The setting of the data management and service foundation aims to evaluate the situation of the enterprise's data in enhancing data management capabilities and strengthening data applications. As the most basic element in the digitalization process, this index will set different secondary indexes according to the different roles played by data in the enterprise, and can be considered from aspects such as data collection, storage, calculation, and transmission. Specifically, as shown in Table 2:

[0058] Table 2 Data Management and Service Foundation

[0059]

[0060] The setting of the digital foundation for production aims to measure the promotion effect on strengthening power grid control, constructing an intelligent management system, and establishing a new mode of coordinated control through the evaluation of the digitization of production links. Considering the enabling effect of production digitization on power grid production, this indicator is also used to measure the level of digital transformation in power grid production. Specifically, it is shown in Table 3 as follows:

[0061] Table 3 Digital Foundation for Production

[0062]

[0063]

[0064] The digital foundation for customer service is used to evaluate the digitalization degree of different types of services when power grid enterprises face the market and customers. The digitalization degree of customer service is positively correlated with service quality and efficiency, that is, the higher the digitalization degree, the higher the corresponding service quality and convenience. This indicator is also used to evaluate the ability to empower customer service, which is mainly composed of the construction of an intelligent marketing system and the construction of an integrated power market service platform. Specifically, it is shown in Table 4 as follows:

[0065] Table 4 Digital Foundation for Customer Service

[0066]

[0067] The setting of the digital foundation for operation and management aims to evaluate the enabling effect of operation and management digitization on enterprise operation and management, so as to measure the level of digital transformation of power grid enterprise operation. Further multi-dimensional evaluations are carried out from aspects such as financial audit, human resources, and integrated intelligent supply chain. Specifically, it is shown in Table 5 as follows:

[0068] Table 5 Digital Foundation for Operation and Management

[0069]

[0070]

[0071] The setting of digital industry integration and upgrading aims to evaluate the integration degree of the power grid enterprise's own energy value chain and the enabling effect of power grid enterprise digitization on emerging industries, so as to measure the power grid enterprise's digital restructuring ability and its industrial driving ability. Specifically, it is shown in Table 6 as follows:

[0072] Table 6 Digital Industry Integration and Upgrading

[0073]

[0074] The setting of the digital security system construction aims to evaluate the ability of power grid enterprises to ensure security and stability during the digitalization process, and to evaluate the strengthening degree of enterprise security protection, technology leadership, and operation support based on this. The overall index setting should comprehensively consider the perfection degree of the digital security system construction from four aspects: leadership organization, security protection construction, operation management mechanism, and enterprise IT architecture. Specifically, as shown in Table 7:

[0075] Table 7 Digital Security System Construction

[0076]

[0077] S120. Input the index data set into the maturity evaluation model to obtain the score of the digitalization of the power grid enterprise to be evaluated, and determine the maturity rating of the digitalization of the power grid enterprise to be evaluated based on this score.

[0078] In some embodiments, since there are many types of data in the index data set, before use, it is necessary to first perform standardization processing on the index data set to obtain the standardized index data set after processing. Only after the processing is completed can the standardized index data set be input into the maturity evaluation model.

[0079] As Figure 2 shown, the maturity evaluation model includes performance evaluation indicators and basic guarantee indicators. The weights of the basic guarantee indicators are determined based on the analytic hierarchy process (AHP) and entropy weight method. The weights of the first indicators in the performance evaluation indicators are obtained by correcting the second weights based on the first weights of the first indicators. The first weights are obtained based on the first matrix composed of all first indicators, and the second weights are obtained based on the entropy weight method.

[0080] The weights of each indicator in the maturity evaluation model are all determined through the obtained index data set.

[0081] The basic guarantee indicators are relatively stable and can be determined based on the analytic hierarchy process (AHP) and entropy weight method.

[0082] The calculation process of the analytic hierarchy process (AHP) is as follows:

[0083] First, give the judgment matrix A (k) . The judgment matrix can objectively explain the importance of each element. By using the 1-9 ratio scale to assign the importance degree, the judgment matrix can be obtained:

[0084]

[0085] Then, calculate the weights of each layer of indicators. Based on the judgment matrix, by obtaining the eigenvector corresponding to the maximum eigenvalue, the weight values of each factor are further calculated, that is

[0086]

[0087] Next, perform consistency check. Conduct a consistency check based on the obtained weight values of each factor. When the consistency ratio C R < 0.10, the judgment matrix is valid; otherwise, corrective measures need to be taken.

[0088] Secondly, establish the initial evaluation matrix. Establish the initial evaluation matrix X = [x ij m×n , where x ij is the measured value of the target layer element i with respect to the evaluation index j.

[0089] Finally, calculate the normalized evaluation matrix Y. Since the selected evaluation indexes have different dimensions, dimensionless processing is required to make them comparable. Therefore, establish the evaluation matrix Y = [y ij m×n . Among them,

[0090] The calculation process of the entropy weight method is as follows:

[0091] Entropy, originally from the thermodynamic concept in physics. At the non - physics level, the entropy value is often used to represent the degree of chaos within a system. That is to say, the entropy value is a measure of the uncertainty factors within a system and has uncertainty. It has been widely applied in multiple fields such as information, society, and economy.

[0092] In information theory, entropy is a measure of the degree of chaos of a system, while information is a measure of the degree of order. Their absolute values are equal, but the signs are opposite. In the index data matrix Y = [y ij m×n composed of m targets to be evaluated and n evaluation indexes, the greater the degree of data dispersion, the smaller the information entropy, the greater the amount of information it provides, the greater the impact of this index on the comprehensive evaluation, and the greater its weight should be; conversely, the smaller the difference between the index values, the greater the information entropy, the smaller the amount of information it provides, the smaller the impact of this index on the evaluation result, and the smaller the weight should be. Using the entropy value method to determine the index weight can not only overcome the randomness and arbitrariness problems that cannot be avoided by the subjective weighting method but also effectively solve the problem of information overlap among multi - index variables.

[0093] The established normalized initial matrix Y gives the evaluation index value P ij , and combined with the information entropy theory, the objective weight values of different indexes are obtained, that is

[0094]

[0095] The actual value of the evaluation index P ij ​​​should be between 0 and 1, from the dimensionless processing of the original data (y ij ) and the calculation of the index proportion (p j ). The calculation method is

[0096]

[0097] where: y jmax = max i {y ij}. In addition, if P ij = 0, it is agreed that lnP ij = 0.

[0098] Calculate the difference coefficient of different indicators according to the entropy value, that is

[0099] d j = 1 - e j ;

[0100] Based on this, the weights corresponding to each indicator are given:

[0101]

[0102] Thus, an objective weight vector W EN = (ω 1 , ω 2 , …, ω n ) is obtained.

[0103] Among the basic guarantee indicators, there are multiple second indicators. After using the above method to determine the third weight of the second indicator based on the analytic hierarchy process and the fourth weight based on the entropy weight method, the weight of the second indicator can be determined by taking the square root of the product of the third weight and the fourth weight.

[0104] For the performance evaluation indicators among many indicators, its evaluation of the maturity of the power grid digital transformation has a greater impact. The inventors have conducted long-term experiments and found that if the weights are still determined based on the analytic hierarchy process and the entropy weight method, the weights are inaccurate and will affect the final evaluation result. Therefore, other methods need to be adopted to determine the weights.

[0105] In some embodiments, the process of determining the first weight of each first indicator is as follows:

[0106] First, construct a first matrix.

[0107] The first matrix is determined by the product of the standard matrix and the transpose matrix of the standard matrix. The standard matrix is composed of the standardized first indicators.

[0108] Specifically, based on each first index after standardization processing, a standard matrix is constructed. For ease of understanding, this standard matrix can be determined as X. Each row in the standard matrix X corresponds to a first index.

[0109] Based on the standard matrix X, a first matrix is determined. The first matrix is the product of the standard matrix X and the transpose matrix of the standard matrix X.

[0110] The standard matrix is X, and the transpose of X is X T , and the first matrix constructed is S n×n = X * X T .

[0111] Then, the singular value set of the first matrix is calculated. The singular value set includes multiple singular values σ i .

[0112] Next, each singular value in the singular value set is multiplied by the corresponding first index to obtain a new standard matrix. Specifically, by multiplying each singular value by its corresponding first index, a new first index is obtained. The new first index y i = x i × σ i , and the product of the i-th singular value and the i-th first index is the new i-th first index. All the new first indices form a new standard matrix T n×1 .

[0113] Secondly, based on the entropy values of each first index in the new standard matrix, the information entropy redundancy of each first index is determined.

[0114] Calculate the entropy value e of each first index in the new standard matrix T n×1 , j ,

[0115]

[0116] Where: y jmax = max i {y ij}. In addition, if P ij = 0, it is agreed that lnP ij = 0.

[0117] The information entropy redundancy d of each first index j is:

[0118] d j = 1 - e j ;

[0119] Finally, based on the information entropy redundancy of each first index, the first weight of each first index is determined.

[0120] Weights corresponding to each indicator:

[0121]

[0122] The second weights of each first indicator are obtained based on the entropy weight method, which will not be elaborated here.

[0123] In some embodiments, after obtaining the first weight and the second weight of each first indicator, the weight of each target indicator can be determined based on the square root of the product of the first weight and the second weight of each first indicator.

[0124] In some embodiments, the maturity evaluation model is a model composed of each indicator in the indicator dataset and the weights of each indicator. The result of the maturity evaluation model is a score, and the input is the numerical value of each indicator. Each indicator has a corresponding weight, so that the score of the digitalization of the power grid enterprise to be evaluated can be obtained.

[0125] According to the scoring results, the digital maturity of power grid enterprises is divided into five stages, namely the digital germination stage, the digital growth stage, the digital maturity stage, the digital leading stage, and the digital excellence stage.

[0126] For enterprises in the digital germination stage, their digital projects are in the pre-preparation stage, and managers pay attention to the development prospects of digitalization. Enterprises in the digital growth stage match their digital strategies according to the development needs of digitalization and conduct intelligent transformation of the infrastructure. For enterprises in the digital maturity stage, the digital transformation work is basically completed, and the digital-related needs of the power grid are basically met. For enterprises in the digital leading stage, the digital transformation work is comprehensively deepened, and the transformation results are applied on a large scale. For enterprises in the digital excellence stage, their digital needs have been fully met, and the enterprise has even become a benchmark for other enterprises in the industry to learn from.

[0127] The embodiments of the present invention provide a method, device, and system for evaluating the digital transformation maturity of power grid enterprises. First, an indicator dataset for evaluating the digitalization of power grid enterprises is obtained, and then by inputting the obtained dataset into the maturity evaluation model, the score of the digitalization of the power grid enterprise to be evaluated can be obtained. In addition, after obtaining the score, the maturity rating can also be determined based on the obtained score. To ensure the accuracy of the score, multiple indicators are selected, and the performance evaluation indicators also include multiple indicators. In addition, the weight of each indicator is also determined based on multiple weights, so that the final maturity rating is more accurate. Thus, an accurate evaluation of the digital transformation ability of the power grid to be evaluated is achieved. Furthermore, the digital transformation ability can be analyzed according to the digital transformation stage of the enterprise to be evaluated, and the digital resources can be further adjusted according to the analysis results.

[0128] It should be understood that the sequence numbers of the steps in the above embodiments do not indicate the order of execution, and the execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0129] The following is an apparatus embodiment of the present invention. For the details not described in detail, reference may be made to the corresponding method embodiments above.

[0130] Figure 3 The structural schematic diagram of the evaluation apparatus for the digital transformation maturity of power grid enterprises provided by the embodiments of the present invention is shown. For the sake of convenience of description, only the parts related to the embodiments of the present invention are shown and are described in detail as follows:

[0131] As Figure 3 shown, the evaluation apparatus 300 for the digital transformation maturity of power grid enterprises includes:

[0132] An acquisition module 310, configured to acquire an index data set of the digitalization of the power grid enterprise to be evaluated; the index data set includes a data set of performance evaluation indexes and a data set of basic guarantee indexes, and the performance evaluation indexes include a plurality of first indexes;

[0133] A rating module 320, configured to input the index data set into the maturity evaluation model to obtain a score of the digitalization of the power grid enterprise to be evaluated, and determine the maturity rating of the digitalization of the power grid enterprise to be evaluated based on the score;

[0134] Among them, the maturity evaluation model includes performance evaluation indexes and basic guarantee indexes. The weight of the basic guarantee indexes is determined based on the analytic hierarchy process and the entropy weight method. The weight of each first index in the performance evaluation indexes is obtained by correcting the second weight with the first weight of each first index. The first weight is obtained based on the standard matrix composed of all first indexes, and the second weight is obtained based on the entropy weight method.

[0135] In a possible implementation manner, the acquisition module 310 is configured to perform standardization processing on the index data set to obtain a standardized standard index data set;

[0136] Input the standardized standard index data set into the maturity evaluation model.

[0137] In a possible implementation manner, the rating module 320 is configured to construct a first matrix; the first matrix is determined by the product of the standard matrix and the transposed matrix of the standard matrix, and the standard matrix is composed of the standardized first indexes;

[0138] Determine the first weight corresponding to each first index based on the first matrix.

[0139] In a possible implementation, the rating module 320 is configured to calculate the singular value set of the first matrix; the singular value set includes a plurality of singular values;

[0140] Multiply each singular value in the singular value set by the corresponding first index to obtain a new standard matrix;

[0141] Based on the entropy values of the first indices in the new standard matrix, determine the information entropy redundancy of each first index;

[0142] Based on the information entropy redundancy of each first index, determine the first weight of each first index.

[0143] In a possible implementation, the rating module 320 is configured to determine the weight of each target index based on the square root of the product of the first weight and the second weight of each first index.

[0144] In a possible implementation, the basic guarantee indicators include a plurality of second indicators;

[0145] The weight of each second indicator is determined based on the square root of the product of the third weight obtained by the analytic hierarchy process and the fourth weight obtained by the entropy weight method.

[0146] In a possible implementation, the basic guarantee indicators include data management and service foundation, production digitalization foundation, customer service digitalization foundation, operation management digitalization foundation, digital industry integration and upgrading, and digital guarantee system construction;

[0147] The data management and service foundation includes the proportion of Internet of Things terminal devices, the proportion of remotely controlled devices, the proportion of intelligent automation devices, the proportion of big data computing modes, the proportion of power data collection, and the network utilization rate of the enterprise;

[0148] The production digitalization foundation includes the intelligent terminal application rate, the proportion of three-dimensional digital channel construction, the coverage rate of unmanned aerial vehicle autonomous inspection, the number of Beidou base stations, the coverage rate of power grid online visualization, the accuracy rate of system warning release, the coverage rate of electricity information collection, the accuracy rate of new energy power generation prediction, the new energy consumption capacity, the coverage rate of smart meters, the equipment networking rate, the online service rate, the correct rate of remote control actions, the data access integrity rate, the accuracy rate of power generation prediction, the digital coverage rate of production line equipment, etc., the application rate of robot artificial intelligence technology, and the radiation rate of power grid industrial chain digitalization;

[0149] The customer service digitalization foundation includes: the digital coverage rate of the client side, the proportion of products with online monitoring status, the detection accuracy of the product monitoring system, the proportion of products included in the online fault maturity, the diagnostic accuracy of the fault diagnosis system, and the customer service work order response rate;

[0150] The digital foundation of operation and management includes: the digitalization ratio of the capital flow link, the usage rate of financial information software, the digitalization ratio of financial analysis, the construction ratio of digital audit studios, the construction ratio of digital audit data warehouses, the development ratio of digital audit technologies, the digitalization ratio of performance management, the digitalization ratio of salary and welfare management, the electronic procurement coverage rate, the online business processing rate, and the digitalization of procurement management;

[0151] The digital industrial integration and upgrading includes: the integration ratio of the internal supply chain of the enterprise, the digital business coverage rate, the proportion of charging piles, the proportion of intelligent vehicle networking services, and the proportion of rooftop distributed photovoltaic access;

[0152] The construction of the digital guarantee system includes: the cloudification rate of IT basic resources, IT efficiency, and IT benefits.

[0153] In a possible implementation manner, the performance evaluation indicators include benefit indicators, efficiency indicators, and comprehensive contribution rate indicators;

[0154] The benefit indicators include the penetration rate of the energy Internet marketing service system, the proportion of online payments, the proportion of automatic audit and issuance of electricity bills, the automatic reconciliation coverage rate, and the online refund business coverage rate;

[0155] The efficiency indicators include information transmission efficiency, power outage judgment accuracy rate, power outage repair efficiency, R & D cycle efficiency, production efficiency, market response rate, failure incidence rate in the target area, and equipment aging replacement rate;

[0156] The comprehensive contribution rate indicators include output value contribution rate, profit contribution rate, income increase contribution rate, cost savings contribution rate, comprehensive benefit growth contribution rate, return on investment, and loss rate.

[0157] In addition, the present invention also provides an evaluation system for the digital transformation maturity of power grid enterprises. The system includes an evaluation server. A computer program is stored in the evaluation server, and when the computer program is executed by a processor, the steps of any method in the first aspect are implemented.

[0158] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For parts not detailed or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0159] Those of ordinary skill in the art can realize that the templates, units, and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0160] When the module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above-described embodiment methods of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described embodiments of the evaluation method for the digital transformation maturity of each power grid enterprise can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0161] The above-described embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for evaluating the maturity of digital transformation of power grid enterprises, characterized in that: include: Obtain the indicator data set of digitalization of the power grid enterprise to be evaluated; The indicator data set includes a data set of performance evaluation indicators and a data set of basic guarantee indicators, and the performance evaluation indicators include a plurality of first indicators; Inputting the indicator data set into the maturity evaluation model to obtain a score of the digitalization of the power grid enterprise to be evaluated, and determining a maturity rating of the digitalization of the power grid enterprise to be evaluated based on the score; Among them, the maturity evaluation model includes the performance evaluation indicators and the basic guarantee indicators. The weights of the basic guarantee indicators are determined based on the hierarchical analysis method and the entropy weight method. The weights of each first indicator in the performance evaluation indicator are obtained by correcting the second weight based on the first weight of each first indicator. The first weight is obtained based on the standard matrix composed of all first indicators, and the second weight is obtained based on the entropy weight method.

2. The method for evaluating the digital transformation maturity of power grid enterprises according to claim 1 is characterized in that: Before inputting the indicator data set into the maturity evaluation model, the method further includes: Performing standardization processing on the indicator data set to obtain a standardized indicator data set after standardization processing; The standard indicator data set is input into the maturity evaluation model.

3. The method for evaluating the digital transformation maturity of power grid enterprises according to claim 2 is characterized in that: The process of determining the first weight of each first indicator is as follows: Constructing a first matrix; the first matrix is ​​determined by the product of a standard matrix and a transposed matrix of the standard matrix, the standard matrix is ​​constructed based on the first indicators after standardization, and each row is a value of each first indicator; A first weight corresponding to each first indicator is determined based on the first matrix.

4. The method for evaluating the digital transformation maturity of power grid enterprises according to claim 3 is characterized in that: The determining, based on the first matrix, first weights corresponding to the first indicators includes: Calculate a singular value set of the first matrix; wherein the singular value set includes a plurality of singular values; Multiply each singular value in the singular value set by the corresponding first index to obtain a new standard matrix; Determining the information entropy redundancy of each first indicator based on the entropy value of each first indicator in the new standard matrix; Based on the information entropy redundancy of each of the first indicators, a first weight of each of the first indicators is determined.

5. The method for evaluating the digital transformation maturity of a power grid enterprise according to any one of claims 1 to 4, characterized in that: The method for determining the weight of each first indicator is: The weight of each target indicator is determined based on the square root of the product of the first weight and the second weight of each first indicator.

6. The method for evaluating the digital transformation maturity of power grid enterprises according to claim 1 is characterized in that: The basic guarantee index includes a plurality of second indexes; The weight of each second indicator is determined by taking the square root of the product of the third weight obtained by the hierarchical analysis method and the fourth weight obtained by the entropy weight method.

7. The method for evaluating the digital transformation maturity of power grid enterprises according to claim 6 is characterized in that: The basic guarantee indicators include data management and service foundation, production digital foundation, customer service digital foundation, business management digital foundation, digital industry integration and upgrading, and digital guarantee system construction; The data management and service foundation includes the proportion of IoT terminal devices, the proportion of remote control equipment, the proportion of intelligent automation equipment, the proportion of big data computing models, the proportion of power data collection and the network utilization rate of the enterprise; The production digitalization foundation includes the application rate of intelligent terminals, the proportion of three-dimensional digital channel construction, the coverage rate of autonomous drone inspections, the number of Beidou base stations, the coverage rate of online visualization of power grids, the accuracy rate of system early warning release, the coverage rate of electricity consumption information collection, the accuracy rate of prediction of new energy power generation, the new energy consumption capacity, the coverage rate of smart meters, the equipment networking rate, the online service rate, the correctness rate of remote control actions, the completeness rate of data access, the accuracy rate of power generation prediction, the digital coverage rate of production line equipment, the application rate of robot artificial intelligence technology and the radiation rate of digitalization of the power grid industry chain; The digital foundation of customer service includes: digital coverage of clients, proportion of products with online monitoring status, detection accuracy of product monitoring system, proportion of products with online fault diagnosis, diagnosis accuracy of fault diagnosis system, timely response rate of customer service work orders and customer problem escalation rate; The digital foundation of business management includes: the digitalization ratio of capital flow links, the utilization rate of financial information software, the digitalization ratio of financial analysis, the construction ratio of digital audit studios, the construction ratio of digital audit data warehouses, the development ratio of digital audit technology, the digitalization ratio of performance management, the digitalization ratio of salary and welfare management, the electronic procurement coverage rate, the online business processing rate and the digitalization ratio of procurement management; The digital industry integration and upgrading include: the proportion of internal supply chain integration, digital business coverage, charging pile ratio, smart car networking business ratio and rooftop distributed photovoltaic access ratio; The construction of the digital guarantee system includes: cloudification rate of IT basic resources, IT efficiency and IT benefits.

8. The method for evaluating the digital transformation maturity of power grid enterprises according to claim 1 is characterized in that: The performance evaluation indicators include benefit indicators, efficiency indicators and comprehensive contribution rate indicators; The efficiency indicators include the penetration rate of the energy Internet marketing service system, the proportion of online payment, the proportion of automatic review and issuance of electricity bills, the coverage rate of automatic reconciliation and the coverage rate of online refund services; The efficiency indicators include information transmission efficiency, power outage assessment accuracy, power outage repair efficiency, R&D cycle efficiency, production efficiency, market response rate, failure rate in target areas, and equipment aging replacement rate; The comprehensive contribution rate indicators include output value contribution rate, profit contribution rate, revenue increase contribution rate, expenditure saving contribution rate, comprehensive benefit growth contribution rate, investment return rate and loss rate.

9. A device for evaluating the maturity of digital transformation of power grid enterprises, characterized in that: include: An acquisition module is used to obtain the digital indicator data set of the power grid enterprise to be evaluated; The indicator data set includes a data set of performance evaluation indicators and a data set of basic guarantee indicators, and the performance evaluation indicators include a plurality of first indicators; A rating module, used to input the indicator data set into the maturity evaluation model to obtain the score of the digitalization of the power grid enterprise to be evaluated, and determine the maturity rating of the digitalization of the power grid enterprise to be evaluated based on the score; Among them, the maturity evaluation model includes the performance evaluation indicators and the basic guarantee indicators. The weights of the basic guarantee indicators are determined based on the hierarchical analysis method and the entropy weight method. The weights of each first indicator in the performance evaluation indicator are obtained by correcting the second weight based on the first weight of each first indicator. The first weight is obtained based on the standard matrix composed of all first indicators, and the second weight is obtained based on the entropy weight method.

10. An evaluation system for the digital transformation maturity of power grid enterprises, characterized in that: The system comprises an evaluation server, in which a computer program is stored, wherein the computer program implements the steps of the method according to any one of claims 1 to 8 when executed by a processor.

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