Power quality management priority determination method and device

Abstract

The invention relates to the technical field of electric energy quality management, and particularly provides an electric energy quality management priority determination method and device, and the method comprises the steps: obtaining an index value of each electric energy quality management priority evaluation index corresponding to each user; determining the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index; wherein the weight coefficient is obtained by adopting a fuzzy comprehensive evaluation algorithm. According to the technical scheme provided by the invention, the electric energy quality treatment work in the park can be carried out in a targeted manner, the electric energy quality is precisely and orderly treated, and the electric energy quality treatment efficiency and treatment level in the area are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power quality management, and in particular to a method and device for determining power quality management priority. Background Art

[0002] As an area of ​​industrial agglomeration, the power quality of industrial parks is directly related to the production efficiency and equipment safety of enterprises in the park. There are a large number of new electrical equipment based on power electronics technology in industrial parks, and the interaction of multiple users such as electric vehicles and impact loads causes waveform distortion in the power supply system, which can easily cause a series of power quality problems such as harmonics, voltage fluctuations, and three-phase imbalance in the park. The quality of power has become a symbol of the operation and management level of industrial parks and even power grids. How to solve power quality problems efficiently and economically is not only a basic technical problem of the power system, but also related to the overall benefits and development strategy of the national economy.

[0003] The traditional power quality management model is to use corresponding management equipment to manage on-site when the power quality of a certain user exceeds the standard. There is no effective management plan, which results in a large investment in manpower and material resources for management in the long run. Scientific and reasonable evaluation of management priorities is conducive to the overall planning of economic and social development and other factors, and has important guiding significance for the development of power quality management. It is also conducive to applying limited manpower and funds to users who are most in need of management. The identification of the early priority of power quality management is the prerequisite for carrying out efficient power quality management, and it is also conducive to users to coordinate the timing of power quality management work from a macro perspective. Therefore, it is necessary to evaluate the priority of power quality problem management. At present, there is still a gap in the research on priority evaluation of power quality problem management. Summary of the invention

[0004] In order to overcome the above-mentioned defects, the present invention proposes a method and device for determining power quality management priority.

[0005] In a first aspect, a method for determining a priority of power quality management is provided, the method comprising:

[0006] Obtain the index value of each power quality management priority evaluation index corresponding to each user;

[0007] Determine the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index;

[0008] Wherein, the weight coefficient is obtained by using a fuzzy comprehensive evaluation algorithm.

[0009] Preferably, the power quality management priority evaluation index includes at least one of the following: severity of power quality problem emission, tolerance of power quality problems, investment in power quality problem management, benefits of power quality problem management, and impact range of power quality problems.

[0010] Furthermore, the power quality problem emission severity q1 is as follows:

[0011]

[0012] In the above formula, E is the number of preset power quality emission indicators, λ e is the weight of the e-th power quality emission index, a e is the index standard value of the e-th power quality emission index, and the index standard value of the e-th power quality emission index is as follows:

[0013]

[0014] In the above formula, a 1e is the index value of the e-th power quality emission index, θ e It is the index limit value of the e-th power quality emission index.

[0015] Furthermore, the power quality problem tolerance level q2 is as follows:

[0016]

[0017] In the above formula, W is the preset power quality problem tolerance index number, η w is the weight of the wth power quality problem tolerance index, b w is the index standard value of the w-th power quality problem tolerance index, and the index standard value of the w-th power quality problem tolerance index is as follows:

[0018]

[0019] In the above formula, b 1w is the index value of the wth power quality problem tolerance index, θ w is the indicator limit value of the w-th power quality problem tolerance indicator.

[0020] Furthermore, the power quality problem management investment q3 is as follows:

[0021]

[0022] In the above formula, r is the investment in power quality problem management, r min is the lower limit of investment in power quality management, r max Set an upper limit for investment in power quality management.

[0023] Furthermore, the power quality problem management benefits q4 are as follows:

[0024]

[0025] In the above formula, C is the loss caused by power quality problems, and d is the cost of managing power quality problems.

[0026] Furthermore, the power quality problem affects the following range q5:

[0027]

[0028] In the above formula, x is the number of users covered by the power quality problem, and f is the total number of users in the area.

[0029] Further, the power quality management priority of each user is determined based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index, including:

[0030] For m users, a sample set of power quality management priority evaluation index data {x(i,j)|i=1~n,j=1~m} is established, where x(i,j) is the index value of the i-th power quality management priority evaluation index corresponding to the j-th user, n is the number of power quality management priority evaluation indicators, and m is the total number of users;

[0031] Perform normalization correction on the x(i,j) to obtain the standardized data r(i,j) corresponding to x(i,j);

[0032] The power quality management priority of each user is determined based on the standardized data r(i,j) corresponding to the x(i,j) and the weight coefficient of each power quality management priority evaluation index.

[0033] Furthermore, the power quality management priority of each user is as follows:

[0034]

[0035] In the above formula, P j is the power quality management priority of the jth user, w i The weight coefficient of the i-th power quality management priority evaluation index.

[0036] Furthermore, in the process of obtaining the weight coefficient using the fuzzy comprehensive evaluation algorithm, the element values ​​of the judgment matrix are as follows:

[0037]

[0038] In the above formula, biy is the value of the element in the i-th row and y-th column of the judgment matrix, s(i) is the standard deviation of the i-th power quality management priority evaluation index, s(y) is the standard deviation of the y-th power quality management priority evaluation index, and s max is the maximum value of each power quality management priority evaluation index, s min is the minimum value of each power quality management priority evaluation index, b m is the importance parameter value, i,y∈[1,n].

[0039] Furthermore, the importance parameter value is as follows:

[0040] b m =min{4,int[s max / s min +0.5]}

[0041] The standard deviation of the i-th power quality management priority evaluation index is as follows:

[0042]

[0043] In the above formula, min and int are the small function and the integer function respectively. is the mean value of the index value of the i-th power quality management priority evaluation index.

[0044] In a second aspect, a device for determining a priority of power quality management is provided, the device for determining a priority of power quality management comprising:

[0045] An acquisition module is used to obtain the index value of each power quality management priority evaluation index corresponding to each user;

[0046] An analysis module, used to determine the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index;

[0047] Wherein, the weight coefficient is obtained by using a fuzzy comprehensive evaluation algorithm.

[0048] Preferably, the power quality management priority evaluation index includes at least one of the following: severity of power quality problem emission, tolerance of power quality problems, investment in power quality problem management, benefits of power quality problem management, and impact range of power quality problems.

[0049] Furthermore, the power quality problem emission severity q1 is as follows:

[0050]

[0051] In the above formula, E is the number of preset power quality emission indicators, λ e is the weight of the e-th power quality emission index, a e is the index standard value of the e-th power quality emission index, and the index standard value of the e-th power quality emission index is as follows:

[0052]

[0053] In the above formula, a 1e is the index value of the e-th power quality emission index, θ e It is the index limit value of the e-th power quality emission index.

[0054] Furthermore, the power quality problem tolerance level q2 is as follows:

[0055]

[0056] In the above formula, W is the preset power quality problem tolerance index number, η w is the weight of the wth power quality problem tolerance index, b w is the index standard value of the w-th power quality problem tolerance index, and the index standard value of the w-th power quality problem tolerance index is as follows:

[0057]

[0058] In the above formula, b 1w is the index value of the wth power quality problem tolerance index, θ w is the indicator limit value of the w-th power quality problem tolerance indicator.

[0059] Furthermore, the power quality problem management investment q3 is as follows:

[0060]

[0061] In the above formula, r is the investment in power quality problem management, r min is the lower limit of investment in power quality control, r max Set an upper limit for investment in power quality management.

[0062] Furthermore, the power quality problem management benefits q4 are as follows:

[0063]

[0064] In the above formula, C is the loss caused by power quality problems, and d is the cost of managing power quality problems.

[0065] Furthermore, the power quality problem affects the following range q5:

[0066]

[0067] In the above formula, x is the number of users covered by the power quality problem, and f is the total number of users in the area.

[0068] Further, the power quality management priority of each user is determined based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index, including:

[0069] For m users, a sample set of power quality management priority evaluation index data {x(i,j)|i=1~n,j=1~m} is established, where x(i,j) is the index value of the i-th power quality management priority evaluation index corresponding to the j-th user, n is the number of power quality management priority evaluation indicators, and m is the total number of users;

[0070] Perform normalization correction on the x(i,j) to obtain the standardized data r(i,j) corresponding to x(i,j);

[0071] The power quality management priority of each user is determined based on the standardized data r(i,j) corresponding to the x(i,j) and the weight coefficient of each power quality management priority evaluation index.

[0072] Furthermore, the power quality management priority of each user is as follows:

[0073]

[0074] In the above formula, P j is the power quality management priority of the jth user, w i The weight coefficient of the i-th power quality management priority evaluation index.

[0075] Furthermore, in the process of obtaining the weight coefficient using the fuzzy comprehensive evaluation algorithm, the element values ​​of the judgment matrix are as follows:

[0076]

[0077] In the above formula, b iy is the value of the element in the i-th row and y-th column of the judgment matrix, s(i) is the standard deviation of the i-th power quality management priority evaluation index, s(y) is the standard deviation of the y-th power quality management priority evaluation index, and s max is the maximum value of each power quality management priority evaluation index, s min is the minimum value of each power quality management priority evaluation index, b m is the importance parameter value, i,y∈[1,n].

[0078] Furthermore, the importance parameter value is as follows:

[0079] b m =min{4,int[s max / s min +0.5]}

[0080] The standard deviation of the i-th power quality management priority evaluation index is as follows:

[0081]

[0082] In the above formula, min and int are the small function and the integer function respectively, r i is the mean value of the index value of the i-th power quality management priority evaluation index.

[0083] In a third aspect, a computer device is provided, comprising: one or more processors;

[0084] The processor is configured to execute one or more programs;

[0085] When the one or more programs are executed by the one or more processors, the method for determining the power quality management priority is implemented.

[0086] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed, the method for determining the power quality management priority is implemented.

[0087] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects:

[0088] The present invention provides a method and device for determining the priority of power quality management, including: obtaining the index value of each power quality management priority evaluation index corresponding to each user; determining the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index; wherein the weight coefficient is obtained by a fuzzy comprehensive evaluation algorithm. The technical solution provided by the present invention can grasp the priority of power quality management, which is helpful to more reasonably and efficiently allocate management resources and formulate management strategies under limited resources, and is of great significance for improving the operation quality of the power system, protecting the interests of users, and promoting the intensive development of society.

[0089] Specifically, it brings the following benefits:

[0090] 1. Optimize resource allocation: Prioritize which power quality issues need to be solved first, which helps to invest limited financial, human and technical resources in solving the most critical problems, thereby avoiding waste of resources and duplication of work.

[0091] 2. Improve governance efficiency: By giving priority to the issues that have the greatest impact on system stability and user equipment safety, the overall operation quality and reliability of the power system can be quickly improved, and failures and losses caused by power quality issues can be reduced.

[0092] 3. Protecting user interests: Power quality is directly related to the user's power experience and equipment safety. Clarifying governance priorities can ensure that those issues that have the greatest impact on users are resolved in a timely manner, thereby protecting user interests and satisfaction.

[0093] 4. Prevent major accidents: If serious power quality problems are not solved in time, they may cause major power accidents and cause huge losses to the power grid and users. Clarifying the priority of power quality management can ensure that these problems are paid attention to and solved in time, thus preventing major accidents from happening. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 It is a flow chart of the main steps of the method for determining the priority of power quality management according to an embodiment of the present invention. DETAILED DESCRIPTION

[0095] The specific implementation modes of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0096] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0097] As disclosed in the background technology, as an area of ​​industrial agglomeration, the power quality of industrial parks is directly related to the production efficiency and equipment safety of enterprises in the parks. There are a large number of new electrical equipment based on power electronics technology in industrial parks, and the interaction of multiple users such as electric vehicles and impact loads causes waveform distortion in the power supply system, which can easily cause a series of power quality problems such as harmonics, voltage fluctuations, and three-phase imbalance in the park. The quality of power has become a symbol of the operation and management level of industrial parks and even power grids. How to efficiently and economically solve power quality problems is not only a basic technical problem of the power system, but also related to the overall benefits and development strategic direction of the national economy.

[0098] The traditional power quality management model is to use corresponding management equipment to manage on-site when the power quality of a certain user exceeds the standard. There is no effective management plan, which results in a large investment in manpower and material resources for management in the long run. Scientific and reasonable management priority evaluation is conducive to the overall planning of economic and social development and other factors, and has important guiding significance for the development of power quality management. It is also conducive to applying limited manpower and funds to users who are most in need of management. The identification of the priority of power quality management in the early stage is the premise for carrying out efficient power quality management, and it is also conducive to users to coordinate the timing of power quality management work from a macro perspective. Therefore, it is necessary to evaluate the priority of power quality problem management. At present, there is still a gap in the research on priority evaluation of power quality problem management.

[0099] In order to improve the above-mentioned problems, the present invention provides a method and device for determining the priority of power quality management, including: obtaining the index value of each power quality management priority evaluation index corresponding to each user; determining the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index; wherein the weight coefficient is obtained by a fuzzy comprehensive evaluation algorithm. The technical solution provided by the present invention can grasp the priority of power quality management, which is helpful to allocate management resources and formulate management strategies more reasonably and efficiently under the condition of limited resources, and is of great significance for improving the operation quality of the power system, protecting the interests of users, and promoting the intensive development of society. Specifically, it brings the following benefits:

[0100] 1. Optimize resource allocation: Prioritize which power quality issues need to be solved first, which helps to invest limited financial, human and technical resources in solving the most critical problems, thereby avoiding waste of resources and duplication of work.

[0101] 2. Improve governance efficiency: By giving priority to the issues that have the greatest impact on system stability and user equipment safety, the overall operation quality and reliability of the power system can be quickly improved, and failures and losses caused by power quality issues can be reduced.

[0102] 3. Protecting user interests: Power quality is directly related to the user's power experience and equipment safety. Clarifying governance priorities can ensure that those issues that have the greatest impact on users are resolved in a timely manner, thereby protecting user interests and satisfaction.

[0103] 4. Prevent major accidents: If serious power quality problems are not solved in time, they may cause major power accidents and cause huge losses to the power grid and users. Clarifying the priority of power quality management can ensure that these problems are paid attention to and solved in time, thus preventing major accidents from happening.

[0104] The above scheme is described in detail below.

[0105] Example 1

[0106] See attached Figure 1 , Figure 1 FIG. 1 is a flow chart showing the main steps of a method for determining power quality management priority according to an embodiment of the present invention. Figure 1 As shown, the method for determining the priority of power quality management in the embodiment of the present invention mainly includes the following steps:

[0107] Step S101: Obtain the index value of each power quality management priority evaluation index corresponding to each user;

[0108] Step S102: determining the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index;

[0109] Wherein, the weight coefficient is obtained by using a fuzzy comprehensive evaluation algorithm.

[0110] In this embodiment, the power quality management priority evaluation index includes at least one of the following: the severity of power quality problem emission, the tolerance of power quality problems, the investment in power quality problem management, the benefit of power quality problem management, and the impact range of power quality problems.

[0111] In one embodiment, the power quality problem emission severity q1 is as follows:

[0112]

[0113] In the above formula, E is the number of preset power quality emission indicators, λ e is the weight of the e-th power quality emission index, a e is the index standard value of the e-th power quality emission index, and the index standard value of the e-th power quality emission index is as follows:

[0114]

[0115] In the above formula, a 1e is the index value of the e-th power quality emission index, θ e It is the index limit value of the e-th power quality emission index.

[0116] In one embodiment, the power quality problem tolerance level q2 is as follows:

[0117]

[0118] In the above formula, W is the preset power quality problem tolerance index number, η w is the weight of the wth power quality problem tolerance index, b w is the index standard value of the w-th power quality problem tolerance index, and the index standard value of the w-th power quality problem tolerance index is as follows:

[0119]

[0120] In the above formula, b 1w is the index value of the wth power quality problem tolerance index, θ w is the indicator limit value of the w-th power quality problem tolerance indicator.

[0121] In a specific implementation, the weight of the power quality emission index and the weight of the power quality problem tolerance index are both obtained by using a hierarchical analysis method, specifically including:

[0122] First, we compare the indicators in pairs according to their sorting order and obtain the corresponding scale values, as shown in Table 1.

[0123] Table 1

[0124]

[0125] Secondly, establish the comparison matrix R1 = (r ij )m×m, where m represents the number of power quality indicators to be managed, r ij Represents the element in the i-th row and j-th column of the comparison matrix R.

[0126] Then, the importance ranking index k is calculated i , and construct the judgment matrix C, where the element value calculation method is as follows:

[0127]

[0128] Where: k max k i The maximum value of k min k i The minimum value of c ij is the element in the i-th row and j-th column of the judgment matrix C.

[0129] Construct the transfer matrix G:

[0130] g ij =lgc ij

[0131] Where: g ij is the i-th row and j-th column element of the transfer matrix G.

[0132] Construct the optimal transfer matrix H:

[0133]

[0134] Where: h ij is the i-th row and j-th column element of the optimal transfer matrix H.

[0135] Construct the optimal consistent matrix B:

[0136]

[0137] Where: b ij is the element in the i-th row and j-th column of the optimal consistent matrix B.

[0138] Finally, the eigenvector corresponding to the maximum eigenvalue of the optimal consistent matrix B is obtained, and the subjective weight vector of the power quality index to be managed is obtained after normalization.

[0139] In one embodiment, the power quality problem management investment q3 is as follows:

[0140]

[0141] In the above formula, r is the investment in power quality problem management, r min is the lower limit of investment in power quality management, r max Set an upper limit for investment in power quality management.

[0142] In one embodiment, the power quality problem management benefit q4 is as follows:

[0143]

[0144] In the above formula, C is the loss caused by power quality problems, and d is the cost of managing power quality problems.

[0145] In one embodiment, the power quality problem impact range q5 is as follows:

[0146]

[0147] In the above formula, x is the number of users covered by the power quality problem, and f is the total number of users in the area.

[0148] In one embodiment, the determining the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index includes:

[0149] For m users, a sample set of power quality management priority evaluation index data {x(i,j)|i=1~n,j=1~m} is established, where x(i,j) is the index value of the i-th power quality management priority evaluation index corresponding to the j-th user, n is the number of power quality management priority evaluation indicators, and m is the total number of users;

[0150] Perform normalization correction on the x(i,j) to obtain the standardized data r(i,j) corresponding to x(i,j);

[0151] The power quality management priority of each user is determined based on the standardized data r(i,j) corresponding to the x(i,j) and the weight coefficient of each power quality management priority evaluation index.

[0152] In one embodiment, the power quality management priority of each user is as follows:

[0153]

[0154] In the above formula, P j is the power quality management priority of the jth user, w i The weight coefficient of the i-th power quality management priority evaluation index.

[0155] In one embodiment, in the process of obtaining the weight coefficient using the fuzzy comprehensive evaluation algorithm, the element values ​​of the judgment matrix are as follows:

[0156]

[0157] In the above formula, b iy is the value of the element in the i-th row and y-th column of the judgment matrix, s(i) is the standard deviation of the i-th power quality management priority evaluation index, s(y) is the standard deviation of the y-th power quality management priority evaluation index, and s max is the maximum value of each power quality management priority evaluation index, s min is the minimum value of each power quality management priority evaluation index, b m is the importance parameter value, i,y∈[1,n].

[0158] In one embodiment, the importance parameter value is as follows:

[0159] b m =min{4,int[s max / s min +0.5]}

[0160] The standard deviation of the i-th power quality management priority evaluation index is as follows:

[0161]

[0162] In the above formula, min and int are the small function and the integer function respectively. is the mean value of the index value of the i-th power quality management priority evaluation index.

[0163] Example 2

[0164] Based on the same inventive concept, the present invention also provides a device for determining a priority of power quality management, the device for determining a priority of power quality management comprising:

[0165] An acquisition module is used to obtain the index value of each power quality management priority evaluation index corresponding to each user;

[0166] An analysis module, used to determine the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index;

[0167] Wherein, the weight coefficient is obtained by using a fuzzy comprehensive evaluation algorithm.

[0168] Preferably, the power quality management priority evaluation index includes at least one of the following: severity of power quality problem emission, tolerance of power quality problems, investment in power quality problem management, benefits of power quality problem management, and impact range of power quality problems.

[0169] Furthermore, the power quality problem emission severity q1 is as follows:

[0170]

[0171] In the above formula, E is the number of preset power quality emission indicators, λ e is the weight of the e-th power quality emission index, a e is the index standard value of the e-th power quality emission index, and the index standard value of the e-th power quality emission index is as follows:

[0172]

[0173] In the above formula, a 1e is the index value of the e-th power quality emission index, θ e It is the index limit value of the e-th power quality emission index.

[0174] Furthermore, the power quality problem tolerance level q2 is as follows:

[0175]

[0176] In the above formula, W is the preset power quality problem tolerance index number, ηw is the weight of the wth power quality problem tolerance index, b w is the index standard value of the w-th power quality problem tolerance index, and the index standard value of the w-th power quality problem tolerance index is as follows:

[0177]

[0178] In the above formula, b 1w is the index value of the wth power quality problem tolerance index, θ w is the indicator limit value of the w-th power quality problem tolerance indicator.

[0179] Furthermore, the power quality problem management investment q3 is as follows:

[0180]

[0181] In the above formula, r is the investment in power quality problem management, r min is the lower limit of investment in power quality management, r max Set an upper limit for investment in power quality management.

[0182] Furthermore, the power quality problem management benefits q4 are as follows:

[0183]

[0184] In the above formula, C is the loss caused by power quality problems, and d is the cost of managing power quality problems.

[0185] Furthermore, the power quality problem affects the following range q5:

[0186]

[0187] In the above formula, x is the number of users covered by the power quality problem, and f is the total number of users in the area.

[0188] Further, the power quality management priority of each user is determined based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index, including:

[0189] For m users, a sample set of power quality management priority evaluation index data {x(i,j)|i=1~n,j=1~m} is established, where x(i,j) is the index value of the i-th power quality management priority evaluation index corresponding to the j-th user, n is the number of power quality management priority evaluation indicators, and m is the total number of users;

[0190] Perform normalization correction on the x(i,j) to obtain the standardized data r(i,j) corresponding to x(i,j);

[0191] The power quality management priority of each user is determined based on the standardized data r(i,j) corresponding to the x(i,j) and the weight coefficient of each power quality management priority evaluation index.

[0192] Furthermore, the power quality management priority of each user is as follows:

[0193]

[0194] In the above formula, P j is the power quality management priority of the jth user, w i The weight coefficient of the i-th power quality management priority evaluation index.

[0195] Furthermore, in the process of obtaining the weight coefficient using the fuzzy comprehensive evaluation algorithm, the element values ​​of the judgment matrix are as follows:

[0196]

[0197] In the above formula, b iy is the value of the element in the i-th row and y-th column of the judgment matrix, s(i) is the standard deviation of the i-th power quality management priority evaluation index, s(y) is the standard deviation of the y-th power quality management priority evaluation index, and s max is the maximum value of each power quality management priority evaluation index, s min is the minimum value of each power quality management priority evaluation index, b m is the importance parameter value, i,y∈[1,n].

[0198] Furthermore, the importance parameter value is as follows:

[0199] b m =min{4,int[s max / s min +0.5]}

[0200] The standard deviation of the i-th power quality management priority evaluation index is as follows:

[0201]

[0202] In the above formula, min and int are the small function and the integer function respectively. is the mean value of the index value of the i-th power quality management priority evaluation index.

[0203] Example 3

[0204] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of a method for determining the priority of power quality management in the above embodiment.

[0205] Example 4

[0206] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It can be understood that the computer-readable storage medium here can include both built-in storage media in a computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space that stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of a method for determining a priority of power quality management in the above embodiment.

[0207] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0208] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0209] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0210] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0211] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for determining power quality management priority, characterized in that: The method comprises: Obtain the index value of each power quality management priority evaluation index corresponding to each user; Determine the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index; Wherein, the weight coefficient is obtained by using a fuzzy comprehensive evaluation algorithm.

2. The method according to claim 1, characterized in that The power quality management priority evaluation index includes at least one of the following: power quality problem emission severity, power quality problem tolerance, power quality problem management investment, power quality problem management benefits, and power quality problem impact range.

3. The method according to claim 2, characterized in that The power quality problem emission severity q1 is as follows: In the above formula, E is the number of preset power quality emission indicators, λ e is the weight of the e-th power quality emission index, a e is the index standard value of the e-th power quality emission index, and the index standard value of the e-th power quality emission index is as follows: In the above formula, a 1e is the index value of the e-th power quality emission index, θ e It is the index limit value of the e-th power quality emission index.

4. The method according to claim 2, characterized in that The power quality problem tolerance level q2 is as follows: In the above formula, W is the preset power quality problem tolerance index number, η w is the weight of the wth power quality problem tolerance index, b w is the index standard value of the w-th power quality problem tolerance index, and the index standard value of the w-th power quality problem tolerance index is as follows: In the above formula, b 1w is the index value of the wth power quality problem tolerance index, θ w is the indicator limit value of the w-th power quality problem tolerance indicator.

5. The method according to claim 2, characterized in that The power quality problem management investment q3 is as follows: In the above formula, r is the investment in power quality problem management, r min is the lower limit of investment in power quality control, r max Set an upper limit for investment in power quality management.

6. The method according to claim 2, characterized in that The benefits of power quality problem management q4 are as follows: In the above formula, C is the loss caused by power quality problems, and d is the cost of managing power quality problems.

7. The method according to claim 2, characterized in that The impact range of the power quality problem q5 is as follows: In the above formula, x is the number of users covered by the power quality problem, and f is the total number of users in the area.

8. The method according to claim 2, characterized in that The determining of the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index includes: For m users, a sample set of power quality management priority evaluation index data {x(i,j)|i=1~n,j=1~m} is established, where x(i,j) is the index value of the i-th power quality management priority evaluation index corresponding to the j-th user, n is the number of power quality management priority evaluation indicators, and m is the total number of users; Perform normalization correction on the x(i,j) to obtain the standardized data r(i,j) corresponding to x(i,j); The power quality management priority of each user is determined based on the standardized data r(i,j) corresponding to the x(i,j) and the weight coefficient of each power quality management priority evaluation index.

9. The method according to claim 8, characterized in that The power quality management priorities of each user are as follows: In the above formula, P j is the power quality management priority of the jth user, w i The weight coefficient of the i-th power quality management priority evaluation index.

10. The method according to claim 8, characterized in that In the process of obtaining the weight coefficient using the fuzzy comprehensive evaluation algorithm, the element values ​​of the judgment matrix are as follows: In the above formula, b iy is the value of the element in the i-th row and y-th column of the judgment matrix, s(i) is the standard deviation of the i-th power quality management priority evaluation index, s(y) is the standard deviation of the y-th power quality management priority evaluation index, and s max is the maximum value of each power quality management priority evaluation index, s min is the minimum value of each power quality management priority evaluation index, b m is the importance parameter value, i,y∈[1,n].

11. The method according to claim 10, characterized in that The importance parameter values ​​are as follows: b m =min{4,int[s max / s min +0.5]} The standard deviation of the i-th power quality management priority evaluation index is as follows: In the above formula, min and int are the small function and the integer function respectively. is the mean value of the index value of the i-th power quality management priority evaluation index.

12. A device for determining priority of power quality management, characterized in that: The device comprises: An acquisition module is used to obtain the index value of each power quality management priority evaluation index corresponding to each user; An analysis module, used to determine the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index; Wherein, the weight coefficient is obtained by using a fuzzy comprehensive evaluation algorithm.

13. The device according to claim 12, characterized in that The power quality management priority evaluation index includes at least one of the following: power quality problem emission severity, power quality problem tolerance, power quality problem management investment, power quality problem management benefits, and power quality problem impact range.

14. The device according to claim 13, characterized in that The power quality problem emission severity q1 is as follows: In the above formula, E is the number of preset power quality emission indicators, λ e is the weight of the e-th power quality emission index, a e is the index standard value of the e-th power quality emission index, and the index standard value of the e-th power quality emission index is as follows: In the above formula, a 1e is the index value of the e-th power quality emission index, θ e It is the index limit value of the e-th power quality emission index.

15. The device according to claim 13, characterized in that The power quality problem tolerance level q2 is as follows: In the above formula, W is the preset power quality problem tolerance index number, η w is the weight of the wth power quality problem tolerance index, b w is the index standard value of the w-th power quality problem tolerance index, and the index standard value of the w-th power quality problem tolerance index is as follows: In the above formula, b 1w is the index value of the wth power quality problem tolerance index, θ w is the indicator limit value of the w-th power quality problem tolerance indicator.

16. The device according to claim 13, characterized in that The power quality problem governance investment q3 is as follows: In the above formula, r is the investment in power quality problem management, r min is the lower limit of investment in power quality control, r max Set an upper limit for investment in power quality management.

17. The device according to claim 13, characterized in that The benefits of power quality problem management q4 are as follows: In the above formula, C is the loss caused by power quality problems, and d is the cost of managing power quality problems.

18. The device according to claim 13, characterized in that The impact range of the power quality problem q5 is as follows: In the above formula, x is the number of users covered by the power quality problem, and f is the total number of users in the area.

19. The device according to claim 13, characterized in that The determining of the power quality management priority of each user based on the index value of each power quality management priority evaluation index and the weight coefficient of each power quality management priority evaluation index includes: For m users, a sample set of power quality management priority evaluation index data {x(i,j)|i=1~n,j=1~m} is established, where x(i,j) is the index value of the i-th power quality management priority evaluation index corresponding to the j-th user, n is the number of power quality management priority evaluation indicators, and m is the total number of users; Perform normalization correction on the x(i,j) to obtain the standardized data r(i,j) corresponding to x(i,j); The power quality management priority of each user is determined based on the standardized data r(i,j) corresponding to the x(i,j) and the weight coefficient of each power quality management priority evaluation index.

20. The device according to claim 19, characterized in that The power quality management priorities of each user are as follows: In the above formula, P j is the power quality management priority of the jth user, w i The weight coefficient of the i-th power quality management priority evaluation index.

21. The device according to claim 19, characterized in that In the process of obtaining the weight coefficient using the fuzzy comprehensive evaluation algorithm, the element values ​​of the judgment matrix are as follows: In the above formula, b iy is the value of the element in the i-th row and y-th column of the judgment matrix, s(i) is the standard deviation of the i-th power quality management priority evaluation index, s(y) is the standard deviation of the y-th power quality management priority evaluation index, and s max is the maximum value of each power quality management priority evaluation index, s min is the minimum value of each power quality management priority evaluation index, b m is the importance parameter value, i,y∈[1,n].

22. The device according to claim 21, characterized in that The importance parameter values ​​are as follows: b m =min{4,int[s max / s min +0.5]} The standard deviation of the i-th power quality management priority evaluation index is as follows: In the above formula, min and int are the small function and the integer function respectively. is the mean value of the index value of the i-th power quality management priority evaluation index.

23. A computer device, characterized in that: include: one or more processors; The processor is configured to execute one or more programs; When the one or more programs are executed by the one or more processors, the method for determining the power quality management priority as described in any one of claims 1 to 11 is implemented.

24. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, it implements the method for determining the power quality management priority as described in any one of claims 1 to 11.

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