A method and device for evaluating energy efficiency of distribution network

Abstract

The application discloses a kind of power distribution network energy efficiency evaluation method and device.The method comprises: according to the model parameter data of pre-set power distribution network model and power distribution network, determine model parameter variation rate, through the correlation analysis of energy efficiency index data and model parameter data of power distribution network, determine the sensitivity coefficient of each energy efficiency index in energy efficiency index data to each model parameter in model parameter data;According to model parameter variation rate and sensitivity coefficient, determine the importance value of the importance degree of energy efficiency index to the energy efficiency influence;According to the importance value of each energy efficiency index to the energy efficiency influence, determine the weight value of each energy efficiency index;According to the weight value of each energy efficiency index and the value of each energy efficiency index obtained, determine the energy efficiency score of power distribution network.The energy efficiency score of power distribution network determined by the scheme has higher rationality, accuracy and practicality, and can better guide the supervision, management and scheduling of power distribution network.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis and evaluation, and in particular to a method and device for evaluating energy efficiency of a distribution network. Background Art

[0002] The distribution network refers to an electric power network that receives electricity from the transmission network or regional power plants and distributes it locally through distribution facilities or distributes it step by step according to voltage to various users. It is a key link in the entire power grid and has the characteristics of complex structure and huge amount of data.

[0003] As my country's economic strength continues to grow, electricity users across various industries are increasingly demanding the quality and reliability of power supply from distribution networks. This is particularly evident in recent years with new energy consumption trends such as new energy vehicles, new home appliances, and coal-to-electricity heating. This has led to a demand for more refined planning and construction of distribution networks. In recent years, my country's power grid has shifted its focus to developing distribution networks that are more closely connected to the user side. Older grids that cannot meet existing electricity demand are being continuously optimized and retrofitted to improve their energy efficiency. Therefore, evaluating distribution network energy efficiency is crucial to optimizing and retrofitting these networks.

[0004] However, existing technologies lack a systematic and scientific evaluation of the energy efficiency of distribution networks, and a clear understanding of the location and severity of existing and upcoming problems in distribution networks. These technologies cannot provide a good basis for the construction and transformation of distribution networks, resulting in many problems still existing in the transformed distribution networks and failing to meet the requirements of the majority of users. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a method and device for evaluating energy efficiency of a distribution network that overcomes the above problems or at least partially solves the above problems.

[0006] In a first aspect, an embodiment of the present invention provides a method for evaluating energy efficiency of a distribution network, comprising:

[0007] For a preset distribution network model, determine the model parameter change rate based on the model and the model parameter data of the distribution network, and determine the sensitivity coefficient of each energy efficiency indicator in the energy efficiency index data to each model parameter in the model parameter data through correlation analysis between the energy efficiency index data of the distribution network and the model parameter data;

[0008] Determining an importance value representing the importance of the energy efficiency indicator to the energy efficiency according to the model parameter change rate and the sensitivity coefficient;

[0009] Determine the weight of each energy efficiency indicator based on its importance to energy efficiency;

[0010] An energy efficiency score of the distribution network is determined according to the weight value of each energy efficiency indicator and the obtained value of each energy efficiency indicator.

[0011] In an optional embodiment, for a preset distribution network model, determining a model parameter change rate based on the model and model parameter data of the distribution network specifically includes:

[0012] For each preset distribution network model, the partial derivative of each model parameter of the model is calculated to determine the change rate relationship of each model parameter;

[0013] The parameter change rate of the model is determined based on the model parameter data of each model and the change rate relationship formula of the model parameters.

[0014] In an optional embodiment, the distribution network model includes a transformer model and a line model;

[0015] The transformer model is:

[0016]

[0017] In the above formula (1): ΔP z =P0+k T P k β 2 , ΔP z is the transformer loss; the model parameters of the transformer model include the transformer load rate β, the power factor of the transformer load side and the transformer's load fluctuation coefficient K T ; P0 is the no-load loss of the transformer; P K is the rated load power loss of the transformer; S N is the rated capacity of the transformer;

[0018] The circuit model is:

[0019]

[0020] In the above formula (2), ΔA is the daily loss of the line; the model parameters of the line model include the square of the daily active power of the line A a 2 , the daily average voltage at the head end of the line U and the line resistance R; Ar is the daily reactive energy; K is the shape coefficient of the load curve; t is time.

[0021] In an optional embodiment, the sensitivity coefficient of each energy efficiency indicator in the energy efficiency indicator data to each model parameter in the model parameter data is determined by correlation analysis between the energy efficiency indicator data of the distribution network and the values ​​of the model parameter data, specifically including:

[0022] For the transformer model parameter matrix of each transformer in the distribution network, according to the Pearson coefficient method, the energy efficiency index in the energy efficiency index matrix and the transformer model parameters in the transformer model parameter matrix of the transformer are subjected to correlation analysis to obtain the sensitivity coefficient matrix Z of the energy efficiency index matrix to the transformer model parameter matrix. i :

[0023]

[0024] In the above formula (3), i is the serial number of the transformer, i = 1, 2, ..., n, n is the total number of transformers in the distribution network; Xr is the value of each time period corresponding to the r-th energy efficiency indicator in the energy efficiency indicator matrix, r = 1, 2, ..., h, h is the number of energy efficiency indicators; β i is the value of each time period corresponding to the load rate in the transformer model parameter matrix of the i-th transformer; is the value of the power factor on the load side in the transformer model parameter matrix of the i-th transformer corresponding to each time period; is the value of the load fluctuation coefficient in each time period corresponding to the transformer model parameter matrix of the i-th transformer;

[0025] For the line model parameter matrix of each line in the distribution network, according to the Pearson coefficient method, the energy efficiency index in the energy efficiency index matrix and the line model parameters in the line model parameter matrix of the line are subjected to correlation analysis to obtain the sensitivity coefficient matrix Y of the energy efficiency index matrix to the line model parameter matrix. j :

[0026]

[0027] In the above formula (4), j is the serial number of the line, j = 1, 2, ..., m, m is the total number of lines in the distribution network; A a 2 j is the value of the square of daily active energy in the line model parameter matrix of the j-th line in each time period; U j is the value of each time period corresponding to the daily average value of the head-end voltage in the line model parameter matrix of the j-th line; R j is the value of the line resistance in each time period corresponding to the line model parameter matrix of the j-th line.

[0028] In an optional embodiment, determining an importance value representing the importance of the impact of the energy efficiency indicator on energy efficiency according to the model parameter change rate and the sensitivity coefficient includes:

[0029] According to the transformer model parameter change rate matrix P of each transformer i, the sensitivity coefficient matrix Z of the energy efficiency index matrix to the transformer model parameter matrix of each transformer i , the line model parameter change rate matrix T of each line j The sensitivity coefficient matrix Y of the line model parameter matrix of each line and the energy efficiency index matrix j , use the following formula (5) to determine the importance matrix that characterizes the importance of the impact of energy efficiency indicators on energy efficiency:

[0030]

[0031] In (5) above, i is the serial number of the transformer, i = 1, 2, ..., n, where n is the total number of transformers in the distribution network; j is the serial number of the line, j = 1, 2, ..., m, where m is the total number of lines in the distribution network; Er is the importance value of the rth energy efficiency indicator on energy efficiency, r = 1, 2, ..., h, where h is the number of energy efficiency indicators.

[0032] In an optional embodiment, the weight value of each energy efficiency indicator is determined according to the importance value of each energy efficiency indicator on energy efficiency, specifically including:

[0033] According to the importance value E of each energy efficiency index on energy efficiency r , use the following formula (6) to determine the weight value ω of each energy efficiency index r :

[0034]

[0035] In (6) above, Er is the importance value of the r-th energy efficiency indicator on energy efficiency, r = 1, 2, ..., h, h is the number of energy efficiency indicators; E f is the importance value of the f-th energy efficiency index on energy efficiency, f=1,2,……,h; E k is the importance value of the kth energy efficiency indicator on energy efficiency, k = 1, 2, ..., h.

[0036] In an optional embodiment, determining the energy efficiency score of the distribution network according to the weight value of each energy efficiency indicator and the obtained value of each energy efficiency indicator specifically includes:

[0037] The energy efficiency score V of the distribution network is determined using the following formula (7):

[0038]

[0039] In the above formula (7), ω r is the weight value of the rth energy efficiency index, r=1,2,……,h, h is the number of energy efficiency indicators; s r is the value of the rth energy efficiency index.

[0040] In an optional embodiment, the energy efficiency index data is the value of the first-level energy efficiency index in the hierarchical energy efficiency index system of the distribution network; correspondingly, determining the energy efficiency score of the distribution network according to the weight value of each energy efficiency index and the obtained value of each energy efficiency index further includes:

[0041] For each energy efficiency indicator of the second level in the hierarchical energy efficiency indicator system, determine a score for the energy efficiency indicator based on the values ​​and weights of the energy efficiency indicators of the next level below the energy efficiency indicator;

[0042] Starting from the energy efficiency indicator of the third level in the hierarchical energy efficiency indicator system, for each energy efficiency indicator of the current level, the score of the energy efficiency indicator is determined according to the score of the energy efficiency indicator of the next level below the energy efficiency indicator; until the score of the energy efficiency indicator of the highest level is determined.

[0043] In an optional embodiment, the highest-level energy efficiency indicators in the hierarchical energy efficiency indicator system of the distribution network include the main equipment of the distribution network and the distribution network system;

[0044] The next level of energy efficiency indicators of the main equipment of the distribution network include main equipment safety, main equipment reliability and main equipment economy, and the next level of energy efficiency indicators of the distribution network system include system power supply capacity, system reliability and system economy.

[0045] In an optional embodiment, the next level of energy efficiency indicators for the main equipment safety include equipment monitoring and maintenance coverage, line insulation rate, trunk line cross-section qualification rate, and branch cross-section qualification rate;

[0046] The next level of energy efficiency indicators for the reliability of the main equipment include the main transformer N-1 pass rate, line N-1 pass rate, line connection rate, medium voltage grid ring rate and inter-station connection rate;

[0047] The next level of energy efficiency indicators for the main equipment economy include the qualified rate of main transformer power factor, qualified rate of distribution transformer power factor, qualified rate of line power factor, proportion of high-loss distribution transformers, proportion of distribution transformer reactive power compensation devices, proportion of trunk lines that are too long, and coverage rate of energy-saving conductors;

[0048] The next level of energy efficiency indicators of the system power supply capability include substation outgoing line spacing margin, main transformer heavy load ratio, main transformer light load ratio, distribution transformer load factor, distribution transformer heavy load ratio, distribution transformer light load ratio, line load factor, line heavy load ratio, line light load ratio, substation capacity load ratio, and substation load factor;

[0049] The next level of energy efficiency indicators of system reliability include average power outage time for users, average power outage frequency for users and comprehensive voltage qualification rate;

[0050] The next level of energy efficiency indicators of the system economy include line loss rate, power supply radius qualification rate and three-phase imbalance ratio.

[0051] In a second aspect, an embodiment of the present invention provides a distribution network energy efficiency evaluation device, comprising:

[0052] A first determination module is configured to determine, for a preset distribution network model, a model parameter change rate based on the model and model parameter data of the distribution network, and determine a sensitivity coefficient of each energy efficiency indicator in the energy efficiency index data to each model parameter in the model parameter data through correlation analysis between the energy efficiency index data of the distribution network and the model parameter data;

[0053] a second determining module, configured to determine an importance value representing the importance of the energy efficiency indicator to the energy efficiency according to the model parameter change rate and the sensitivity coefficient determined by the first determining module;

[0054] a third determining module, configured to determine a weight value of each energy efficiency indicator according to the importance value of each energy efficiency indicator on energy efficiency determined by the second determining module;

[0055] The fourth determination module is configured to determine the energy efficiency score of the distribution network according to the weight values ​​of the energy efficiency indicators determined by the third determination module and the acquired values ​​of the energy efficiency indicators.

[0056] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, which implement the above-mentioned distribution network energy efficiency evaluation method when the instructions are executed by a processor.

[0057] In a fourth aspect, an embodiment of the present invention provides a server, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned distribution network energy efficiency evaluation method when executing the program.

[0058] The beneficial effects of the above technical solutions provided by the embodiments of the present invention include at least:

[0059] (1) The distribution network energy efficiency evaluation method described in the embodiment of the present invention determines the model parameter change rate based on a preset distribution network model and the model parameter data of the distribution network, and determines the sensitivity coefficient of each energy efficiency indicator in the energy efficiency indicator data to each model parameter in the model parameter data through correlation analysis between the energy efficiency index data of the distribution network and the model parameter data; determines the importance value representing the importance of the energy efficiency index on energy efficiency based on the model parameter change rate and the sensitivity coefficient; determines the weight value of each energy efficiency index based on the importance value of the energy efficiency index on energy efficiency; and determines the energy efficiency score of the distribution network based on the weight value of each energy efficiency index and the obtained value of each energy efficiency index. The weight values ​​of each energy efficiency indicator in this scheme are determined not only based on the numerical values ​​of each energy efficiency indicator, but also taking into account the model parameter data of the distribution network. The sensitivity coefficient of the energy efficiency indicator data is determined through correlation analysis between the energy efficiency indicator data and the model parameter data. Then, the weight value of each energy efficiency indicator is determined according to the model parameter change rate and the sensitivity coefficient. The energy efficiency score of the distribution network is determined according to the weight value of each energy efficiency indicator and the obtained value of each energy efficiency indicator, so that the final score has higher rationality, accuracy and practicality, which can better guide the supervision, management and scheduling of the distribution network.

[0060] (2) At the same time, since the weight values ​​of various energy efficiency indicators of the distribution network are reasonably determined, the location of existing or upcoming problems in the distribution network can be more accurately determined by combining the values ​​of various energy efficiency indicators obtained, and their severity can be determined.

[0061] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0063] Figure 1 This is a flow chart of the distribution network energy efficiency evaluation method described in Example 1 of the present invention;

[0064] Figure 2 This is a flowchart of a specific implementation of the distribution network energy efficiency evaluation method described in the second embodiment of the present invention;

[0065] Figure 3 Schematic diagram of the structure of the distribution network energy efficiency evaluation device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0066] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0067] To address the current inability to effectively and rationally evaluate the energy efficiency of distribution networks, the present invention provides a method and apparatus for evaluating the energy efficiency of distribution networks. The resulting energy efficiency score is more reasonable, accurate, and practical, providing better guidance for the supervision, management, and scheduling of distribution networks. This solution can be applied not only to energy efficiency evaluation of distribution networks but also to the performance parameter evaluation of complex systems in other fields.

[0068] Example 1

[0069] The first embodiment of the present invention provides a method for evaluating the energy efficiency of a distribution network, the process of which is as follows: Figure 1 As shown, the following steps are included:

[0070] Step S11: for a preset distribution network model, determine the model parameter change rate according to the model and model parameter data of the distribution network.

[0071] In one embodiment, the method may include: for each preset distribution network model, respectively calculating partial derivatives of each model parameter of the model to determine a relationship between the rate of change of each model parameter; and determining the parameter change rate of the model based on the model parameter data of each model and the relationship between the rate of change of the model parameters.

[0072] Specifically, the aforementioned model may include a transformer model and a line model of the distribution network. Partial derivatives are taken for each model parameter of the model to determine a relationship for the rate of change of each model parameter. For example, in a model including three variables, x, y, and z, taking a partial derivative of the model parameter x may include assuming that y and z in the model are constants, y0 and z0, taking a partial derivative of the model parameter x to obtain a relationship for the rate of change of x. Based on the obtained model parameter data, the values ​​of each parameter are substituted into the relationship to determine the rate of change of the model parameter x.

[0073] Step S12: determining the sensitivity coefficient of each energy efficiency indicator in the energy efficiency indicator data to each model parameter in the model parameter data by performing a correlation analysis between the energy efficiency indicator data of the distribution network and the model parameter data.

[0074] Specifically, the energy efficiency index data for the distribution network is the value of each energy efficiency index within different time periods. For example, it can be an energy efficiency index matrix, where each row in the matrix represents the value of each energy efficiency index within the same time period, and each column represents the value of the same energy efficiency index within different time periods. Model parameter data can be multiple matrices. Taking the transformer model as an example, the transformer model parameter data can be a transformer model parameter matrix corresponding to each transformer in the distribution network, where each row in the transformer model parameter matrix represents the value of each transformer model parameter of the corresponding transformer within the same time period, and each column in the transformer model parameter matrix represents the value of the same transformer model parameter of the corresponding transformer within each time period.

[0075] Performing a correlation analysis on the energy efficiency index data and model parameter data of the distribution network may include performing a pairwise correlation analysis on the values ​​of each energy efficiency index in the energy efficiency index data of the distribution network and the values ​​of each model parameter in each set of model parameter data. Taking the correlation analysis of the energy efficiency index matrix and the transformer model parameter matrix of a transformer as an example, a correlation analysis is performed on each column in the energy efficiency index matrix (representing the value of the same energy efficiency index in different time periods) and each column in the transformer model parameter matrix (representing the value of the same transformer model parameter of the transformer in different time periods). Assuming that the energy efficiency index matrix includes h energy efficiency indicators and the transformer model parameter matrix includes a transformer model parameters, the resulting sensitivity coefficient matrix has h rows and a columns, each row representing the correlation between the same energy efficiency index and different transformer model parameters (the sensitivity coefficients of the same energy efficiency index to different transformer model parameters), and each column representing the correlation between different energy efficiency indicators and the same transformer model parameters (the sensitivity coefficients of different energy efficiency indicators to the same transformer model parameters).

[0076] Step S13: determining an importance value representing the importance of the energy efficiency indicator to the energy efficiency according to the model parameter change rate and the sensitivity coefficient.

[0077] Specifically, the importance value representing the importance of the energy efficiency indicator to the energy efficiency may be determined according to the product of the model parameter change rate and the sensitivity coefficient.

[0078] In one embodiment, the method may include: i , the sensitivity coefficient matrix Z of the energy efficiency index matrix to the transformer model parameter matrix of each transformer i , the line model parameter change rate matrix T of each line j The sensitivity coefficient matrix Y of the line model parameter matrix of each line and the energy efficiency index matrix j , use the following formula (1) to determine the importance matrix that characterizes the importance of the impact of energy efficiency indicators on energy efficiency:

[0079]

[0080] In (1) above, i is the serial number of the transformer, i = 1, 2, ..., n, n is the total number of transformers in the distribution network; j is the serial number of the line, j = 1, 2, ..., m, m is the total number of lines in the distribution network; Er is the importance value of the r-th energy efficiency indicator on energy efficiency, r = 1, 2, ..., h, h is the number of energy efficiency indicators. When the energy efficiency indicator is a multi-level energy efficiency indicator system, Er is the energy efficiency indicator of the r-th lowest level in the energy efficiency indicator system, and h is the number of energy efficiency indicators of the lowest level in the energy efficiency indicator system.

[0081] Step S14: Determine the weight value of each energy efficiency indicator according to the importance value of each energy efficiency indicator in affecting energy efficiency.

[0082] In one embodiment, it may include the importance value E of each energy efficiency indicator on the energy efficiency. r , use the following formula (2) to determine the weight value ω of each energy efficiency index r :

[0083]

[0084] In (2) above, Er is the importance value of the r-th energy efficiency indicator on energy efficiency, r = 1, 2, ..., h, h is the number of energy efficiency indicators; E f is the importance value of the f-th energy efficiency index on energy efficiency, f=1,2,……,h; E k is the importance value of the kth energy efficiency indicator on energy efficiency, k = 1, 2, ..., h.

[0085] Specifically, when the energy efficiency index is a multi-level energy efficiency index system, the above energy efficiency index is the energy efficiency index of the lowest level in the energy efficiency index system.

[0086] Step S15: determining the energy efficiency score of the distribution network according to the weight value of each energy efficiency indicator and the acquired value of each energy efficiency indicator.

[0087] In one embodiment, the energy efficiency score V of the distribution network may be determined using the following formula (3):

[0088]

[0089] In the above formula (3), ω r is the weight value of the rth energy efficiency index, r=1,2,……,h, h is the number of energy efficiency indicators; s r is the value of the rth energy efficiency index.

[0090] The above-mentioned scheme recorded in the first embodiment of the present application determines the model parameter change rate based on the preset distribution network model and the model parameter data of the distribution network, determines the sensitivity coefficient of each energy efficiency indicator in the energy efficiency indicator data to each model parameter in the model parameter data through correlation analysis of the energy efficiency index data of the distribution network and the model parameter data; determines the importance value representing the importance of the energy efficiency index to the energy efficiency according to the model parameter change rate and the sensitivity coefficient; determines the weight value of each energy efficiency index according to the importance value of the energy efficiency index to the energy efficiency; determines the energy efficiency score of the distribution network according to the weight value of each energy efficiency index and the obtained value of each energy efficiency index. This scheme can determine the weight value of each energy efficiency index according to the model parameter data and energy efficiency index data of the distribution network, and the determination of the weight value of the energy efficiency index comprehensively considers the model parameter data of each device in the distribution network; and then determines the energy efficiency score of the distribution network according to the weight value of each energy efficiency index and the obtained value of each energy efficiency index, so that the final determined score has higher rationality, accuracy and practicality, which can better guide the supervision, management and scheduling of the distribution network. At the same time, since the weight values ​​of various energy efficiency indicators of the distribution network are reasonably determined, the location of existing or upcoming problems in the distribution network can be more accurately determined by combining the values ​​of various energy efficiency indicators obtained, and their severity can be determined.

[0091] Example 2

[0092] A second embodiment of the present invention provides a specific application implementation of a distribution network energy efficiency evaluation method.

[0093] The pre-established distribution network models are two models of transformers and lines. Referring to Table 1 below, the pre-built distribution network energy efficiency index system can be a system that includes three levels of energy efficiency indicators. The third-level energy efficiency indicators, that is, the highest-level energy efficiency indicators, include the main equipment of the distribution network and the distribution network system; the next-level energy efficiency indicators of the main equipment of the distribution network include the second-level main equipment safety, main equipment reliability and main equipment economy, and the next-level energy efficiency indicators of the distribution network system include the second-level system power supply capacity, system reliability and system economy; the next-level energy efficiency indicators of equipment safety include the third-level equipment monitoring and maintenance coverage rate, line insulation rate, main line cross-section qualification rate and branch cross-section qualification rate; the next-level energy efficiency indicators of main equipment reliability include the third-level main transformer N-1 pass rate, line N-1 pass rate, line connection rate, medium-voltage grid ring rate and inter-station connection rate; main equipment The next level of energy efficiency indicators for economy include the third-level main transformer power factor qualification rate, distribution transformer power factor qualification rate, line power factor qualification rate, high-loss distribution transformer ratio, distribution transformer reactive compensation device ratio, trunk line length ratio and energy-saving conductor coverage rate; the next level of energy efficiency indicators for system power supply capacity include the third-level substation line spacing margin, main transformer heavy load ratio, main transformer light load ratio, distribution transformer load rate, distribution transformer heavy load ratio, distribution transformer light load ratio, line load rate, line heavy load ratio, line light load ratio, substation capacity load ratio and substation load rate; the next level of energy efficiency indicators for system reliability include the third-level average power outage time for users, average power outage frequency for users and comprehensive voltage qualification rate; the next level of energy efficiency indicators for system economy include the third-level line loss rate, power supply radius qualification rate and three-phase imbalance ratio.

[0094] Table 1 Distribution network energy efficiency index system

[0095]

[0096] The factors affecting energy efficiency are analyzed from two aspects: the main equipment of the distribution network and the distribution network system. Furthermore, from the perspective of the core value of the users of the distribution network, the most important stakeholders of the distribution network are power companies, power users and the social environment. Among them, the fundamental demand of the power company is the economy of the grid operation, the fundamental demand of the power user is the power supply capacity of the grid, and the development of the social environment is the reliability consideration of energy conservation, environmental protection and sustainable development. Therefore, the above-mentioned distribution network energy efficiency index system established in Example 2 of the present invention systematically and rationally establishes a hierarchical index system that affects the performance of the distribution network, so that the distribution network energy efficiency score obtained by analysis based on this index system has higher rationality and scientificity.

[0097] Reference Figure 2 As shown in FIG, the specific application implementation process of the distribution network energy efficiency evaluation method may include the following steps:

[0098] Step S21: for a preset distribution network model, determine a model parameter change rate matrix according to the model and the model parameter matrix of the distribution network.

[0099] In one embodiment, the distribution network model includes a transformer model and a line model.

[0100] Among them, the transformer model is:

[0101]

[0102] In the above formula (4): ΔP z =P0+k T P k β 2 , ΔP z is the transformer loss; the model parameters of the transformer model include the transformer load rate β, the power factor of the transformer load side and the transformer's load fluctuation coefficient K T ; P0 is the no-load loss of the transformer; P K is the rated load power loss of the transformer; S N is the rated capacity of the transformer.

[0103] The line model is:

[0104]

[0105] In the above formula (5), ΔA is the daily loss of the line; the model parameters of the line model include the square of the daily active power of the line A a 2 , the daily average voltage at the head end of the line U and the line resistance R; Ar is the daily reactive energy; K is the shape coefficient of the load curve; t is time.

[0106] The transformer model parameters of each transformer in the distribution network: load rate β, power factor on the load side and load fluctuation coefficient K T The values ​​of the transformer model parameter matrix Where i is the serial number of the transformer, i = 1, 2, ..., n, n is the total number of transformers in the distribution network; tn represents the transformer model parameter matrix including the values ​​of the transformer model parameters in tn time periods;

[0107] The transformer loss ΔP in the transformer model is z The parameters β, K T Calculate the partial derivative and combine the parameter matrices of each transformer model to obtain the parameter change rate matrix of each transformer model:

[0108]

[0109] The line model parameters of each line in the distribution network are: The values ​​of U and R constitute the line model parameter matrix Where j is the line number, j = 1, 2, ..., m, m is the total number of lines in the distribution network; tm represents the line model parameter matrix including the values ​​of the line model parameters in tm time periods;

[0110] By adjusting the parameter A of the line daily loss ΔA in the line model a 2 , U and R are calculated separately, and the parameter change rate matrix of each line model is obtained by combining the parameter matrix of each line model:

[0111]

[0112] Step S22: determining a sensitivity coefficient matrix of each energy efficiency indicator in the energy efficiency indicator data to each model parameter in the model parameter data through correlation analysis between the energy efficiency indicator matrix of the distribution network and the model parameter matrix.

[0113] In one embodiment, the method may include, for each transformer model parameter matrix of the distribution network, performing a correlation analysis on each energy efficiency index in the energy efficiency index matrix and each transformer model parameter in the transformer model parameter matrix of the transformer according to the Pearson coefficient method, and obtaining a sensitivity coefficient matrix Z of the energy efficiency index matrix to the transformer model parameter matrix. i :

[0114]

[0115] In the above formula (6), i is the serial number of the transformer, i = 1, 2, ..., n, n is the total number of transformers in the distribution network; Xr is the value of each time period corresponding to the r-th energy efficiency indicator in the energy efficiency indicator matrix (the first level in the energy efficiency indicator system, that is, the lowest level energy efficiency indicator), r = 1, 2, ..., h, h is the number of first-level energy efficiency indicators in the energy efficiency indicator system; β i is the value of each time period corresponding to the load rate in the transformer model parameter matrix of the i-th transformer; is the value of the power factor on the load side in the transformer model parameter matrix of the i-th transformer corresponding to each time period; is the value of the load fluctuation coefficient in each time period corresponding to the transformer model parameter matrix of the i-th transformer;

[0116] For the line model parameter matrix of each line in the distribution network, according to the Pearson coefficient method, the energy efficiency index in the energy efficiency index matrix and the line model parameters in the line model parameter matrix of the line are correlated and analyzed to obtain the sensitivity coefficient matrix Y of the energy efficiency index matrix to the line model parameter matrix. j :

[0117]

[0118] In the above formula (7), j is the serial number of the line, j = 1, 2, ..., m, m is the total number of lines in the distribution network; A a 2 j is the value of the square of daily active energy in the line model parameter matrix of the j-th line in each time period; U j is the value of each time period corresponding to the daily average value of the head-end voltage in the line model parameter matrix of the j-th line; R j is the value of the line resistance in each time period corresponding to the line model parameter matrix of the j-th line.

[0119] Step S23: determining an importance matrix representing the importance of the energy efficiency index to the energy efficiency according to the model parameter change rate matrix and the sensitivity coefficient matrix.

[0120] According to the method in step S13 of the first embodiment, the importance matrix E=[E1…E r …E h ], Er is the importance value of the rth energy efficiency indicator on energy efficiency.

[0121] Step S24: determining the relative importance matrix of the energy efficiency indicators according to the importance matrix of the energy efficiency indicators.

[0122] According to the importance matrix of energy efficiency indicators, by comparing the importance of the r1th energy efficiency indicator and the r2th energy efficiency indicator, the relative importance is quantified as a r1r2 , The number of energy efficiency indicators is h, then the relative importance matrix of energy efficiency indicators is a matrix of h×h

[0123] Step S25: Determine whether the consistency test of the relative importance matrix of the energy efficiency index is qualified.

[0124] Assign a value to each element in the relative importance matrix A according to the 1-9 scaling method; determine the consistency index CI of the matrix A, and then determine the consistency ratio CR of the matrix A.

[0125]

[0126]

[0127] In the above formula (8), λ maxis the maximum eigenvalue of matrix A (the maximum value assigned to each element in matrix A according to the 1-9 scaling method); in the above formula (9), RI is the average random consistency index corresponding to the matrix dimension h, as shown in Table 2 below.

[0128] Table 2 Comparison table of matrix dimensions and RI values

[0129] h 1 2 3 4 5 6 7 8 9 10 11 RI 0 0 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49 1.51

[0130] When CR<0.1, the consistency test is satisfied, and it is determined that the consistency test of the relative importance matrix of the energy efficiency index is qualified, and step S26 is executed; otherwise, it is determined that the consistency test of the relative importance matrix of the energy efficiency index is unqualified, and the matrix A is corrected and improved. For example, the matrix A can be modified according to the correction value input by the user until it is determined that the consistency test of the relative importance matrix A of the energy efficiency index is qualified, and step S26 is executed.

[0131] Step S26: Determine the weight value of each energy efficiency indicator according to the relative importance matrix of the energy efficiency indicators.

[0132] Use the geometric mean method to determine the weight value ω of each energy efficiency index r :

[0133]

[0134] Step S27: determining the energy efficiency score of the distribution network according to the weight values ​​of the energy efficiency indicators of the first level in the hierarchical energy efficiency indicator system and the acquired values ​​of the energy efficiency indicators.

[0135] Step S28: for each energy efficiency indicator of the second level in the hierarchical energy efficiency indicator system, determine the score of the energy efficiency indicator according to the values ​​and weight values ​​of the energy efficiency indicators of the next level below the energy efficiency indicator.

[0136] Specifically, for each energy efficiency indicator of the second level in the hierarchical energy efficiency indicator system, the sum of the products of the values ​​of the energy efficiency indicators of the next level below the energy efficiency indicator and the weight value is determined as the score of the energy efficiency indicator.

[0137] Step S29: Starting from the energy efficiency indicator of the third level in the hierarchical energy efficiency indicator system, for each energy efficiency indicator of the current level, determine the score of the energy efficiency indicator according to the score of the energy efficiency indicator of the next level; until the score of the energy efficiency indicator of the highest level is determined.

[0138] Specifically, starting from the energy efficiency indicator of the third level in the hierarchical energy efficiency indicator system, for each energy efficiency indicator of the current level, the sum of the scores of the energy efficiency indicators of the next level of the energy efficiency indicator is determined as the score of the energy efficiency indicator.

[0139] Preferably, in the distribution network energy efficiency evaluation method of the above embodiment, the model parameter data and the energy efficiency index data are standardized data. The specific standardization method of the model parameter data and the energy efficiency index data, taking the energy efficiency index as an example, may include:

[0140] Determine the positive and negative direction of each energy efficiency indicator;

[0141] According to the positive and negative directions and index values ​​of each energy efficiency index, the standard value of each energy efficiency index is determined using the following formula (11):

[0142]

[0143] In the above formula (11), is the standard value of the r1th positive energy efficiency indicator in the t1th time period, t1 = 1, 2, ..., th, th is the total number of time periods; is the actual value of the r1th positive energy efficiency indicator in the t1th time period; is the standard value of the r2th negative energy efficiency indicator in the t2th time period, t2 = 1, 2, ..., th, th is the total number of time periods; is the actual value of the r2th negative energy efficiency indicator in the t2th time period.

[0144] Based on the inventive concept of the present invention, an embodiment of the present invention further provides a distribution network energy efficiency evaluation device, the structure of which is as follows: Figure 3 As shown, including:

[0145] A first determination module 31 is configured to determine, for a preset distribution network model, a model parameter change rate based on the model and model parameter data of the distribution network, and determine a sensitivity coefficient of each energy efficiency indicator in the energy efficiency indicator data to each model parameter in the model parameter data by performing a correlation analysis between the energy efficiency indicator data of the distribution network and the model parameter data;

[0146] A second determining module 32 is configured to determine an importance value representing the importance of the energy efficiency indicator to the energy efficiency according to the model parameter change rate and sensitivity coefficient determined by the first determining module 31;

[0147] A third determining module 33 is configured to determine a weight value of each energy efficiency indicator according to the importance value of each energy efficiency indicator on energy efficiency determined by the second determining module 32;

[0148] The fourth determining module 34 is configured to determine the energy efficiency score of the distribution network according to the weight values ​​of the energy efficiency indicators determined by the third determining module 33 and the acquired values ​​of the energy efficiency indicators.

[0149] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0150] Based on the inventive concept of the present invention, an embodiment of the present invention further provides a computer-readable storage medium having computer instructions stored thereon, which implement the above-mentioned distribution network energy efficiency evaluation method when the instructions are executed by a processor.

[0151] Based on the inventive concept of the present invention, an embodiment of the present invention further provides a server, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned distribution network energy efficiency evaluation method when executing the program.

[0152] Unless otherwise specifically stated, terms such as process, calculate, compute, determine, display, and the like may refer to the actions and / or processes of one or more processing or computing systems, or similar devices, that manipulate and convert data represented as physical (e.g., electronic) quantities within registers or memories of a processing system into other data similarly represented as physical quantities within the memories, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals may be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0153] It should be understood that the specific order or hierarchy of steps in the disclosed processes is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process can be rearranged without departing from the scope of the present disclosure. The accompanying method claims present elements of the various steps in an exemplary order and are not intended to be limited to the specific order or hierarchy described.

[0154] In the foregoing detailed description, various features are grouped together in a single embodiment to simplify the disclosure. This method of disclosure should not be interpreted as reflecting an intention that embodiments of the claimed subject matter require more features than are expressly recited in each claim. On the contrary, as reflected in the appended claims, the invention comprises less than all the features of any individual disclosed embodiment. The appended claims are therefore hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate preferred embodiment of the invention.

[0155] Those skilled in the art will also appreciate that the various illustrative logic blocks, modules, circuits, and algorithmic steps described in conjunction with the embodiments herein may be implemented as electronic hardware, computer software, or a combination thereof. In order to clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described around their functions. Whether such functions are implemented as hardware or software depends on the specific application and the design constraints imposed on the entire system. A skilled person may implement the described functions in an adaptable manner for each specific application, but such implementation decisions should not be interpreted as departing from the scope of protection of this disclosure.

[0156] The steps of the methods or algorithms described in conjunction with the embodiments herein may be directly embodied as hardware, software modules executed by a processor, or a combination thereof. The software module may be located in a RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, register, hard disk, removable disk, CD-ROM, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium may also be an integral part of the processor. The processor and storage medium may be located in an ASIC. The ASIC may be located in a user terminal. Of course, the processor and storage medium may also be present in a user terminal as discrete components.

[0157] For software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. These software codes can be stored in a memory unit and executed by a processor. The memory unit can be implemented within the processor or external to the processor. In the latter case, it is communicatively coupled to the processor via various means, which are well known in the art.

[0158] The foregoing description includes examples of one or more embodiments. Of course, it is not possible to describe all possible combinations of components or methods for the purposes of describing the above embodiments, but one of ordinary skill in the art will recognize that the various embodiments may be further combined and arranged. Therefore, the embodiments described herein are intended to encompass all such changes, modifications and variations that fall within the scope of the appended claims. Furthermore, to the extent the term "comprising" is used in the specification or claims, the term is intended to be encompassed in a manner similar to the term "including," as explained in terms of "including," used as a transitional word in the claims. Furthermore, any use of the term "or" in the specification of the claims is intended to mean a "non-exclusive or."

Claims

1. A method for evaluating energy efficiency of a distribution network, characterized in that: include: For each preset distribution network model, the partial derivative of each model parameter of the model is calculated to determine the change rate relationship of each model parameter; Determining the parameter change rate of the model according to the model parameter data of each model and the relationship between the change rate of the model parameters; the distribution network model includes a transformer model and a line model; For the transformer model parameter matrix of each transformer in the distribution network, according to the Pearson coefficient method, the energy efficiency index in the energy efficiency index matrix and the transformer model parameters in the transformer model parameter matrix of the transformer are subjected to correlation analysis to obtain the sensitivity coefficient matrix Z of the energy efficiency index matrix to the transformer model parameter matrix. i For the line model parameter matrix of each line in the distribution network, according to the Pearson coefficient method, the energy efficiency index in the energy efficiency index matrix and the line model parameters in the line model parameter matrix of the line are subjected to correlation analysis to obtain the sensitivity coefficient matrix Y of the energy efficiency index matrix to the line model parameter matrix j ; According to the transformer model parameter change rate matrix P of each transformer i , the sensitivity coefficient matrix Z of the energy efficiency index matrix to the transformer model parameter matrix of each transformer i , the line model parameter change rate matrix T of each line j The sensitivity coefficient matrix Y of the line model parameter matrix of each line and the energy efficiency index matrix j , use the following formula (1) to determine the importance matrix that characterizes the importance of the impact of energy efficiency indicators on energy efficiency: In the above formula (1), i is the serial number of the transformer, i = 1, 2, ..., n, n is the total number of transformers in the distribution network; j is the serial number of the line, j = 1, 2, ..., m, m is the total number of lines in the distribution network; Er is the importance value of the rth energy efficiency indicator on energy efficiency, r = 1, 2, ..., h, h is the number of energy efficiency indicators; According to the importance value E of each energy efficiency index on energy efficiency r , use the following formula (2) to determine the weight value ω of each energy efficiency index r : In the above formula (2), E f is the importance value of the f-th energy efficiency index on energy efficiency, f=1,2,……,h; E k is the importance value of the k-th energy efficiency indicator on energy efficiency, k = 1, 2, ..., h; An energy efficiency score of the distribution network is determined according to the weight value of each energy efficiency indicator and the obtained value of each energy efficiency indicator.

2. The method according to claim 1, wherein The transformer model is: In the above formula (3): ΔP z =P0+k T P k β 2 , ΔP z is the transformer loss; the model parameters of the transformer model include the transformer load rate β, the power factor of the transformer load side and the transformer's load fluctuation coefficient K T ; P0 is the no-load loss of the transformer; P K is the rated load power loss of the transformer; S N is the rated capacity of the transformer; The circuit model is: In the above formula (4), ΔA is the daily loss of the line; the model parameters of the line model include the square of the daily active power of the line A a 2 , the daily average voltage at the head end of the line U and the line resistance R; Ar is the daily reactive energy; K is the shape coefficient of the load curve; t is time.

3. The method according to claim 2, wherein Get the sensitivity coefficient matrix Z of the energy efficiency index matrix to the transformer model parameter matrix i for: In the above formula (5), Xr is the value of each time period corresponding to the r-th energy efficiency indicator in the energy efficiency indicator matrix; β i is the value of each time period corresponding to the load rate in the transformer model parameter matrix of the i-th transformer; is the value of the power factor on the load side in the transformer model parameter matrix of the i-th transformer corresponding to each time period; is the value of the load fluctuation coefficient in each time period corresponding to the transformer model parameter matrix of the i-th transformer; Get the sensitivity coefficient matrix Y of the energy efficiency index matrix to the line model parameter matrix j for: In the above formula (6), A a 2 j is the value of the square of daily active energy in the line model parameter matrix of the j-th line in each time period; U j is the value of each time period corresponding to the daily average value of the head-end voltage in the line model parameter matrix of the j-th line; R j is the value of the line resistance in each time period corresponding to the line model parameter matrix of the j-th line.

4. The method according to claim 1, wherein The energy efficiency score of the distribution network is determined based on the weights of each energy efficiency indicator and the values ​​of each energy efficiency indicator obtained, including: The energy efficiency score V of the distribution network is determined using the following formula (7): In the above formula (7), ω r is the weight value of the rth energy efficiency index, s r is the value of the rth energy efficiency index.

5. The method according to claim 1, wherein The energy efficiency index data is the value of the first-level energy efficiency index in the hierarchical energy efficiency index system of the distribution network; correspondingly, determining the energy efficiency score of the distribution network according to the weight value of each energy efficiency index and the obtained value of each energy efficiency index, further comprising: For each energy efficiency indicator of the second level in the hierarchical energy efficiency indicator system, determine a score for the energy efficiency indicator based on the values ​​and weights of the energy efficiency indicators of the next level below the energy efficiency indicator; Starting from the energy efficiency indicator of the third level in the hierarchical energy efficiency indicator system, for each energy efficiency indicator of the current level, the score of the energy efficiency indicator is determined according to the score of the energy efficiency indicator of the next level below the energy efficiency indicator; until the score of the energy efficiency indicator of the highest level is determined.

6. The method according to claim 5, wherein The highest level energy efficiency indicators in the hierarchical energy efficiency indicator system of the distribution network include the main equipment of the distribution network and the distribution network system; The next level of energy efficiency indicators of the main equipment of the distribution network includes main equipment safety, main equipment reliability and main equipment economy. The next level of energy efficiency indicators of the distribution network system includes system power supply capacity, system reliability and system economy. The next level of energy efficiency indicators for the safety of the main equipment include equipment monitoring and maintenance coverage, line insulation rate, trunk line cross-section qualification rate, and branch line cross-section qualification rate; The next level of energy efficiency indicators for the reliability of the main equipment include the main transformer N-1 pass rate, line N-1 pass rate, line connection rate, medium voltage grid ring rate and inter-station connection rate; The next level of energy efficiency indicators for the main equipment economy include the qualified rate of main transformer power factor, qualified rate of distribution transformer power factor, qualified rate of line power factor, proportion of high-loss distribution transformers, proportion of distribution transformer reactive power compensation devices, proportion of trunk lines that are too long, and coverage rate of energy-saving conductors; The next level of energy efficiency indicators of the system power supply capability include substation outgoing line spacing margin, main transformer heavy load ratio, main transformer light load ratio, distribution transformer load factor, distribution transformer heavy load ratio, distribution transformer light load ratio, line load factor, line heavy load ratio, line light load ratio, substation capacity load ratio, and substation load factor; The next level of energy efficiency indicators of system reliability include average power outage time for users, average power outage frequency for users and comprehensive voltage qualification rate; The next level of energy efficiency indicators of the system economy include line loss rate, power supply radius qualification rate and three-phase imbalance ratio.

7. A distribution network energy efficiency evaluation device, characterized in that: include: The first determination module is used to calculate the partial derivative of each model parameter of each preset distribution network model and determine the change rate relationship of each model parameter; The parameter change rate of the model is determined according to the relationship between the model parameter data of each model and the change rate of the model parameters; the distribution network model includes a transformer model and a line model; for the transformer model parameter matrix of each transformer in the distribution network, according to the Pearson coefficient method, the energy efficiency index in the energy efficiency index matrix and the transformer model parameters in the transformer model parameter matrix of the transformer are subjected to correlation analysis to obtain the sensitivity coefficient matrix Z of the energy efficiency index matrix to the transformer model parameter matrix i For the line model parameter matrix of each line in the distribution network, according to the Pearson coefficient method, the energy efficiency index in the energy efficiency index matrix and the line model parameters in the line model parameter matrix of the line are subjected to correlation analysis to obtain the sensitivity coefficient matrix Y of the energy efficiency index matrix to the line model parameter matrix j ; The second determination module is used to determine the transformer model parameter change rate matrix P of each transformer according to the transformer model parameter change rate matrix P of each transformer i , the sensitivity coefficient matrix Z of the energy efficiency index matrix to the transformer model parameter matrix of each transformer i , the line model parameter change rate matrix T of each line j The sensitivity coefficient matrix Y of the line model parameter matrix of each line and the energy efficiency index matrix j , use the following formula (1) to determine the importance matrix that characterizes the importance of the impact of energy efficiency indicators on energy efficiency: In the above formula (1), i is the serial number of the transformer, i = 1, 2, ..., n, n is the total number of transformers in the distribution network; j is the serial number of the line, j = 1, 2, ..., m, m is the total number of lines in the distribution network; Er is the importance value of the rth energy efficiency indicator on energy efficiency, r = 1, 2, ..., h, h is the number of energy efficiency indicators; The third determination module is used to determine the importance value E of each energy efficiency indicator on energy efficiency. r , use the following formula (2) to determine the weight value ω of each energy efficiency index r : In the above formula (2), E f is the importance value of the f-th energy efficiency indicator on energy efficiency, f = 1, 2, ..., h; E k is the importance value of the k-th energy efficiency indicator on energy efficiency, k = 1, 2, ..., h; The fourth determination module is configured to determine the energy efficiency score of the distribution network according to the weight values ​​of the energy efficiency indicators determined by the third determination module and the acquired values ​​of the energy efficiency indicators.

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