Security risk evaluation index screening method and device suitable for novel power distribution network

Abstract

The invention provides a safety risk evaluation index screening method and device suitable for a novel power distribution network, and belongs to the field of power systems. The method comprises the following steps: acquiring an initial index set for performing safety risk evaluation on the novel power distribution network; determining a target weight of each index in the initial index set, and optimizing the initial index set according to the target weight of each index in the initial index set to obtain an optimized index set; determining an information contribution rate of the optimization index set, and performing rationality verification on the optimization index set according to the information contribution rate of the optimization index set to obtain a rationality verification result; and if the rationality verification result is that the verification is passed, taking the optimization index set as a safety risk evaluation system of the novel power distribution network. According to the invention, the safety risk evaluation system of the novel power distribution network can be scientifically and quantitatively selected, so that the indexes for performing safety risk evaluation on the novel power distribution network are not single any more, and the method is suitable for the novel power distribution network.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and in particular to a method and device for screening safety risk assessment indicators suitable for a new type of power distribution network. Background Art

[0002] The distribution network is closely related to the vast number of users and plays an important role in reliable power supply and promoting regional economic and social development. In order to accelerate the development of the distribution network and improve the scientific nature of distribution network planning and the rationality of construction, it is necessary to carry out distribution network evaluation work seriously.

[0003] At present, the evaluation and analysis of distribution networks in various regions has been widely carried out. However, the indicators used for distribution network evaluation are usually determined manually, resulting in some urgent problems in distribution network evaluation, such as single indicators for distribution network evaluation, unscientific selection of indicators and inapplicability to new distribution networks, etc. Therefore, it is necessary to establish a relatively complete safety risk evaluation system for new distribution networks, identify the weak links in the development of new distribution networks, provide support for the planning of new distribution networks, and carry out targeted construction and transformation to make the development of new distribution networks safer, more reliable, high-quality and economical. Summary of the invention

[0004] The embodiment of the present invention provides a method and device for screening safety risk assessment indicators applicable to a new distribution network, so as to solve the problem that the indicators for safety risk assessment of distribution networks in the existing methods are single, unscientific and not applicable to new distribution networks.

[0005] In a first aspect, an embodiment of the present invention provides a method for screening security risk assessment indicators applicable to a new distribution network, comprising:

[0006] Obtaining an initial set of indicators for security risk assessment of new distribution networks;

[0007] Determine the target weight of each indicator in the initial indicator set, and optimize the initial indicator set according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set;

[0008] Determine the information contribution rate of the optimization indicator set, and verify the rationality of the optimization indicator set based on the information contribution rate of the optimization indicator set to obtain a rationality verification result;

[0009] If the rationality verification result is passed, the optimized indicator set will be used as the safety risk assessment system of the new distribution network.

[0010] In a possible implementation, determining the information contribution rate of the optimization indicator set includes:

[0011] Obtain the indicator data set corresponding to each indicator in the initial indicator set;

[0012] Based on the indicator data set corresponding to each indicator in the initial indicator set, the sum of the variances of each indicator in the initial indicator set and the sum of the variances of each indicator in the optimized indicator set are calculated;

[0013] Based on the sum of the variances of the indicators in the initial indicator set and the sum of the variances of the indicators in the optimized indicator set, the information contribution rate of the optimized indicator set is determined.

[0014] In a possible implementation, the information contribution rate of the optimized indicator set is determined based on the sum of the variances of the indicators in the initial indicator set and the sum of the variances of the indicators in the optimized indicator set, including:

[0015] The ratio of the sum of the variances of each indicator in the optimized indicator set to the sum of the variances of each indicator in the initial indicator set is taken as the information contribution rate of the optimized indicator set.

[0016] In a possible implementation, the rationality of the optimization indicator set is verified according to the information contribution rate of the optimization indicator set, and the rationality verification result is obtained, including:

[0017] If the information contribution rate of the optimization indicator set is greater than or equal to the preset contribution rate, the rationality verification result is determined to be a passed verification; otherwise, the rationality verification result is determined to be a failed verification.

[0018] In a possible implementation, determining the target weight of each indicator in the initial indicator set includes:

[0019] Using the analytic hierarchy process, determine the first weight of each indicator in the initial indicator set;

[0020] The principal component analysis method is used to determine the second weight of each indicator in the initial indicator set;

[0021] The average of the first weight and the second weight of each indicator in the initial indicator set is used as the target weight of each indicator in the initial indicator set.

[0022] In a possible implementation, the initial indicator set is optimized according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set, including:

[0023] Sort the indicators in the initial indicator set in descending order according to the target weight to obtain a sorted initial indicator set;

[0024] The preset proportion of indicators that are ranked at the back of the sorted initial indicator set are eliminated to obtain the optimized indicator set.

[0025] In a possible implementation, the initial indicator set includes an indicator set at a physical level, an indicator set at an operation level, and an indicator set at an information level.

[0026] In a possible implementation, the physical level indicator set includes line N-1 pass rate, line standard wiring rate, average equipment operation life, new energy consumption rate, backup power supply guarantee rate, and main section N-2 pass rate;

[0027] The set of indicators at the operation level includes voltage qualification rate, power supply reliability rate, line overload rate, user-side flexible resource ratio, energy storage and new energy capacity ratio, and equipment utilization rate;

[0028] The set of indicators at the information level includes smart terminal coverage, distribution automation self-healing rate, smart switch standard coverage, power supply dispatchability rate, energy storage shareability rate and communication performance adaptation index.

[0029] In a possible implementation, after obtaining the rationality verification result, the security risk assessment index screening method applicable to the new distribution network also includes:

[0030] If the rationality verification result is that the verification fails, the initial indicator set is readjusted to obtain a new initial indicator set, and based on the new initial indicator set, the process jumps to the step of determining the target weight of each indicator in the initial indicator set and continues to execute.

[0031] In a second aspect, an embodiment of the present invention provides a security risk assessment index screening device applicable to a new distribution network, comprising:

[0032] An acquisition module, used for acquiring an initial indicator set for safety risk assessment of a new distribution network;

[0033] An optimization module is used to determine the target weight of each indicator in the initial indicator set, and optimize the initial indicator set according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set;

[0034] A rationality verification module is used to determine the information contribution rate of the optimization indicator set, and to verify the rationality of the optimization indicator set according to the information contribution rate of the optimization indicator set to obtain a rationality verification result;

[0035] The processing module is used to use the optimized indicator set as the safety risk evaluation system of the new distribution network if the rationality verification result is verified to be passed.

[0036] The embodiment of the present invention provides a method and device for screening safety risk assessment indicators suitable for a new distribution network. The method obtains an initial indicator set for performing safety risk assessment on the new distribution network, optimizes the initial indicator set according to the target weight of each indicator in the initial indicator set, obtains an optimized indicator set, and performs rationality verification on the optimized indicator set according to the information contribution rate of the optimized indicator set to obtain a rationality verification result. Finally, if the rationality verification result is a passed verification, the optimized indicator set is used as a safety risk assessment system for the new distribution network, so that the safety risk assessment system for the new distribution network can be scientifically and quantitatively selected, so that the indicator for performing safety risk assessment on the new distribution network is no longer single and is suitable for the new distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 It is a flow chart of a method for screening safety risk assessment indicators applicable to a new type of distribution network provided by an embodiment of the present invention;

[0039] Figure 2 It is a flow chart of a method for screening safety risk assessment indicators applicable to a new type of distribution network provided by another embodiment of the present invention;

[0040] Figure 3 It is a structural schematic diagram of a security risk assessment index screening device applicable to a new type of power distribution network provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0042] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0043] Figure 1 The implementation flow chart of the method for screening security risk assessment indicators applicable to a new distribution network provided by the embodiment of the present invention is described in detail as follows:

[0044] Step 101, obtaining an initial indicator set for performing safety risk assessment on a new distribution network.

[0045] The new distribution network refers to the introduction of modern information technology and intelligent control technology on the basis of the traditional distribution network to achieve efficient, safe, reliable and sustainable development of the power system. The core of the new distribution network is the intelligent power system, which realizes efficient dispatching, optimal configuration and intelligent control of electricity through the application of information technology, thereby improving the economic benefits and reliability of the power system.

[0046] The initial indicator set may include multiple indicators for conducting safety risk assessment on the new distribution network.

[0047] The initial indicator set may include an indicator set at the physical level, an indicator set at the operation level, and an indicator set at the information level.

[0048] In some possible implementation methods, the Delphi method can be used to extract safety risk assessment indicators of the new distribution network based on the three perspectives of physics, operation, and information, and to construct a new distribution network safety risk assessment system of target layer-criterion layer-indicator layer to form an initial indicator set.

[0049] For the power system, physical security is the material basis of power system security, operational security is the condition for the normal operation of the power system, and although information security is not directly reflected in the power system security, the information security and controllability of the new power system is an important guarantee for physical and operational security. Physical security, operational security, and information security are all indispensable and jointly maintain the security of the power system. Based on this, the embodiment of the present application starts from the three perspectives of physical, information, and operational levels to determine the initial indicator set.

[0050] Among them, the target layer refers to the new distribution network security risk assessment system. The criterion layer refers to the physical layer, operation layer and information layer. The indicator layer refers to the specific indicators contained in the physical layer, operation layer and information layer.

[0051] In some embodiments, the physical level indicator set includes line N-1 pass rate, line standard wiring rate, average operation life of equipment, new energy consumption rate, backup power supply guarantee rate, and main section N-2 pass rate;

[0052] The set of indicators at the operation level includes voltage qualification rate, power supply reliability rate, line overload rate, user-side flexible resource ratio, energy storage and new energy capacity ratio, and equipment utilization rate;

[0053] The set of indicators at the information level includes smart terminal coverage, distribution automation self-healing rate, smart switch standard coverage, power supply dispatchability rate, energy storage shareability rate and communication performance adaptation index.

[0054] Step 102, determining the target weight of each indicator in the initial indicator set, and optimizing the initial indicator set according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set.

[0055] The target weight of each indicator in the initial indicator set can be used to indicate the importance of each indicator. The larger the target weight, the higher the importance.

[0056] The embodiment of the present application can optimize and screen each indicator in the initial indicator set according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set. The optimized indicator set is an indicator set after the initial indicator set is screened.

[0057] Step 103, determining the information contribution rate of the optimization index set, and performing rationality verification on the optimization index set according to the information contribution rate of the optimization index set to obtain a rationality verification result.

[0058] The information contribution rate of the optimized indicator set can be used to indicate the proportion of valuable information provided by the optimized indicator set to the total information provided by the initial indicator set.

[0059] The embodiment of the present application can perform rationality verification on the optimization index set according to the information contribution rate of the optimization index set to obtain a rationality verification result, wherein the rationality verification result includes verification passed or verification failed.

[0060] Step 104: If the rationality verification result is passed, the optimized indicator set is used as the safety risk evaluation system of the new distribution network.

[0061] If the rationality verification result is passed, it means that the valuable information provided by the current optimization index set can effectively evaluate the safety risk of the new distribution network. At this time, the optimization index set can be used as the safety risk evaluation system of the emerging distribution network. Subsequently, the safety risk of the new distribution network can be evaluated based on the safety risk evaluation system of the new distribution network.

[0062] The embodiment of the present application obtains an initial indicator set for conducting safety risk assessment on the new distribution network, optimizes the initial indicator set according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set, and verifies the rationality of the optimized indicator set according to the information contribution rate of the optimized indicator set to obtain a rationality verification result. Finally, if the rationality verification result is a passed verification, the optimized indicator set is used as the safety risk assessment system of the new distribution network, so that the safety risk assessment system of the new distribution network can be scientifically and quantitatively selected, so that the indicators for conducting safety risk assessment on the new distribution network are no longer single and are applicable to the new distribution network. Furthermore, based on the safety risk assessment system applicable to the new distribution network, the safety risk assessment of the new distribution network is conducted, so that the weak links of the new distribution network can be found, and support can be provided for the planning and development of the new distribution network, so that the new distribution network can be constructed and renovated in a targeted manner, making the development of the new distribution network safer and more reliable.

[0063] In some embodiments, in step 103, determining the information contribution rate of the optimization indicator set includes:

[0064] Obtain the indicator data set corresponding to each indicator in the initial indicator set;

[0065] Based on the indicator data set corresponding to each indicator in the initial indicator set, the sum of the variances of each indicator in the initial indicator set and the sum of the variances of each indicator in the optimized indicator set are calculated;

[0066] Based on the sum of the variances of the indicators in the initial indicator set and the sum of the variances of the indicators in the optimized indicator set, the information contribution rate of the optimized indicator set is determined.

[0067] In this embodiment, the indicator data corresponding to each indicator in the initial indicator set in different years can be calculated respectively to obtain the indicator data set corresponding to each indicator in the initial indicator set. Among them, the indicator data set corresponding to each indicator in the initial indicator set can be directly obtained from the power system, planning reports, etc., or can be calculated by relevant formulas based on the basic data required to calculate the indicator data set corresponding to each indicator in the initial indicator set.

[0068] For each indicator in the initial indicator set, the variance of the indicator is calculated based on the indicator data set corresponding to the indicator.

[0069] The variances of the various indicators in the initial indicator set are added together to obtain the sum of the variances of the various indicators in the initial indicator set, and the variances of the various indicators in the optimized indicator set are added together to obtain the sum of the variances of the various indicators in the optimized indicator set.

[0070] The information contribution rate of the embodiment of the present application reflects the information content through the variance of the index, and realizes the rationality verification of the optimization index set. Afterwards, the information contribution rate of the optimization index set can be calculated based on the sum of the variances of each index in the initial index set and the sum of the variances of each index in the optimization index set.

[0071] Variance is a statistic that measures the degree of data dispersion, which reflects the degree of variation of data around its mean. The larger the variance, the higher the degree of data dispersion, that is, the greater the difference between the data; the smaller the variance, the lower the degree of data dispersion, that is, the smaller the difference between the data. Therefore, variance can be used to measure the stability or consistency of data, thereby reflecting the information content of indicators and calculating the information contribution rate.

[0072] In some embodiments, the information contribution rate of the optimized indicator set is determined based on the sum of the variances of the indicators in the initial indicator set and the sum of the variances of the indicators in the optimized indicator set, including:

[0073] The ratio of the sum of the variances of each indicator in the optimized indicator set to the sum of the variances of each indicator in the initial indicator set is taken as the information contribution rate of the optimized indicator set.

[0074] The sum of the variances of the indicators in the optimized indicator set is ratioed to the sum of the variances of the indicators in the initial indicator set. This ratio can reflect the percentage of the information content of the optimized indicator set to the data information content of the initial indicator set. Based on this, the rationality of the optimized indicator set is verified.

[0075] In some embodiments, in step 103, the rationality of the optimization indicator set is verified according to the information contribution rate of the optimization indicator set to obtain a rationality verification result, including:

[0076] If the information contribution rate of the optimization indicator set is greater than or equal to the preset contribution rate, the rationality verification result is determined to be a passed verification; otherwise, the rationality verification result is determined to be a failed verification.

[0077] The preset contribution rate is a relatively high value, for example, 90% or 95%, and so on.

[0078] In this embodiment, if the information contribution rate of the optimization indicator set is greater than or equal to the preset contribution rate, the rationality verification result of the optimization indicator set is determined to be passed; if the information contribution rate of the optimization indicator set is less than the preset contribution rate, the rationality verification result of the optimization indicator set is determined to be failed.

[0079] The information contribution rate of the optimized indicator set indicates the degree to which the optimized indicator set reflects the original information related to the initial indicator set. Therefore, when its value is greater than or equal to the preset contribution rate, it is considered to have passed the rationality verification.

[0080] In some embodiments, in step 102, determining the target weight of each indicator in the initial indicator set includes:

[0081] Using the analytic hierarchy process, determine the first weight of each indicator in the initial indicator set;

[0082] The principal component analysis method is used to determine the second weight of each indicator in the initial indicator set;

[0083] The average of the first weight and the second weight of each indicator in the initial indicator set is used as the target weight of each indicator in the initial indicator set.

[0084] This embodiment adopts two methods to calculate the weight of each indicator in the initial indicator set respectively, and then adopts the average value of the weights of the two as the target weight of each indicator in the initial indicator set, which can avoid the bias of determining the weight by a single method and improve the accuracy of determining the importance of each indicator.

[0085] In some possible implementations, the above-mentioned use of the analytic hierarchy process to determine the first weight of each indicator in the initial indicator set may include the following steps:

[0086] 1) Establish a hierarchical structure model;

[0087] When using AHP to analyze decision-making problems, we must first organize and hierarchize the problems and construct a hierarchical structure model. These levels can generally be divided into three categories: the highest level (target level), the middle level (criteria level), and the lowest level (indicator level). The number of levels in the hierarchical structure is related to the complexity of the problem and the degree of detail required for analysis. Generally, the number of levels is not affected, and the elements dominated by each element in each level generally do not exceed 9.

[0088] 2) Construct all judgment matrices in each level;

[0089] The weight of each criterion in the target layer is not necessarily the same in the target measurement. In the minds of decision makers, they each occupy a certain proportion. The numbers 1 to 9 and their reciprocals are used as scales to define the judgment matrix A = (a ij ) n×n .

[0090] Table 1 Judgment matrix scale definition

[0091]

[0092]

[0093] 3) Hierarchical sorting

[0094] 3.1) Hierarchical single sorting

[0095] That is, for a factor of the previous level in the corresponding model calculated according to the constructed judgment matrix, the weights of all factors related to it at this level are calculated; at the same time, in order to ensure that the conclusion of the hierarchical analysis is basically reasonable, the judgment matrix must also be tested for consistency, and the negative average CI of the remaining characteristic roots other than the maximum eigenvalue of the judgment matrix is ​​introduced:

[0096]

[0097] Among them, λ max is the maximum value of the judgment matrix, n is the dimension of the judgment matrix; when CI = 0, the judgment matrix has complete consistency and the test ends; when CI ≠ 0, the random consistency ratio CR calculation is required:

[0098]

[0099] Among them, RI is the average random consistency index of the judgment matrix, and its value is shown in Table 2. If CR < 0.1, it is considered that the consistency of the judgment matrix is ​​acceptable, and the hierarchical single sorting result can reflect the relative importance of the factors at this level to the factors at the previous level; if CR < 0.1 is not satisfied, the values ​​of the elements of the judgment matrix need to be adjusted until a satisfactory consistency position is achieved.

[0100] Table 2 Average random consistency index RI

[0101]

[0102] 3.2) Total ranking of levels

[0103] That is, the weight values ​​of all factors relative to the target layer are calculated using the results of single sorting of all layers in the same layer and the weights of all factors in the previous layer; the consistency ratio of the total sorting of the layer is defined as:

[0104]

[0105] Among them, a n is the weight value of the nth factor in the previous level. When CR < 0.1, the result of the total hierarchical ranking is considered satisfactory.

[0106] Principal component analysis is a classic dimensionality reduction statistical method used to reduce the complexity of a data set while minimizing information loss. It uses an orthogonal transformation to transform the observed values ​​of a set of variables into values ​​represented by a set of linearly unrelated variables (called principal components). The number of principal components is at most min(n, p)-1, where n represents the number of observations and p represents the number of original variables.

[0107] In some possible implementations, the principal component analysis method is used to determine the second weight of each indicator in the initial indicator set, which may include the following steps:

[0108] Step 1: Standardization of indicator data

[0109] Collect p-dimensional random vector x=(x1,x2,…,x p ) T , n samples x i =(x i1 ,x i2 ,…,x ip ) T , i=1,2,…,n,n>p, construct a sample matrix, perform the following standardized transformation on the sample matrix, and obtain the standardized matrix Z.

[0110]

[0111] Step 2: Determine the correlation between indicators

[0112] Find the correlation coefficient matrix R for the standardized Z:

[0113]

[0114] Step 3: Determine the number of principal components m

[0115] The following formula is used to solve the p characteristic roots of the sample correlation coefficient matrix R:

[0116] |R-λI p |=0

[0117] The following formula is used to determine the principal component, so that the utilization rate of information reaches more than 85%:

[0118]

[0119] For each λ, the following formula is used j , (j=1,2,…,m) solve and get the unit eigenvector :

[0120] Rb=λ j b

[0121] Step 4: Establish the principal component expression

[0122] The standardized indicator variables are converted into principal components using the following formula:

[0123]

[0124] Step 5: Comprehensive evaluation of principal components

[0125] The m principal components are weighted and summed to obtain the final evaluation value, where the weight is the variance contribution rate of each principal component.

[0126] In some embodiments, in step 102, the initial indicator set is optimized according to the target weight of each indicator in the initial indicator set to obtain the optimized indicator set, including:

[0127] Sort the indicators in the initial indicator set in descending order according to the target weight to obtain a sorted initial indicator set;

[0128] The preset proportion of indicators that are ranked at the back of the sorted initial indicator set are eliminated to obtain the optimized indicator set.

[0129] The preset ratio can be set according to actual needs, for example, it can be 10% or 20%, and so on.

[0130] In this embodiment, the target weights may be sorted in descending order, and a preset proportion of indicators in the rear of the sorted initial indicator set may be removed to obtain an optimized indicator set.

[0131] In another embodiment, the target weights may be sorted in ascending order, and a preset proportion of indicators in the front of the sorted initial indicator set may be removed to obtain an optimized indicator set.

[0132] In another embodiment, the indicators whose target weights are less than the preset weights in the initial indicator set can be eliminated to obtain the optimized indicator set. The preset weights can be set according to actual needs and are not specifically limited here.

[0133] In some embodiments, after obtaining the rationality verification result, the above-mentioned security risk assessment index screening method applicable to the new distribution network may further include:

[0134] If the rationality verification result is that the verification fails, the initial indicator set is readjusted to obtain a new initial indicator set, and based on the new initial indicator set, the process jumps to the step of determining the target weight of each indicator in the initial indicator set and continues to execute.

[0135] If the rationality verification result is that the verification failed, it means that the current optimization index set does not meet the requirements. At this time, the initial index set needs to be readjusted to obtain the adjusted initial index set, that is, the new initial index set, and based on the new initial index set, jump to step 102 to continue execution. That is, determine the target weight of each indicator in the new initial index set, and optimize the new initial index set according to the target weight of each indicator in the new initial index set to obtain a new optimization index set; determine the information contribution rate of the new optimization index set, and perform rationality verification on the new optimization index set according to the information contribution rate of the new optimization index set to obtain a rationality verification result; if the rationality verification result is that the verification passed, the new optimization index set is used as the safety risk assessment system of the new distribution network; if the rationality verification result is still that the verification failed, adjust the initial index set again until the rationality verification result is that the verification passed.

[0136] Among them, the initial indicator set can be adjusted through further research, by adding high-frequency indicators and related special indicators recognized by domestic and foreign authoritative organizations on the basis of the original initial indicators, and then using the Delphi method again to finally form a new initial indicator set.

[0137] In one embodiment, see Figure 2 The above-mentioned method for screening security risk assessment indicators applicable to the new distribution network may include the following steps:

[0138] The security risk assessment indicators suitable for the new distribution network are determined from the physical perspective, operational perspective and information perspective, and the Delphi method is used to determine the initial indicator set.

[0139] The first weight of each indicator in the initial indicator set is determined by using the hierarchical analysis method; the second weight of each indicator in the initial indicator set is determined by using the principal component analysis method; the average of the first weight and the second weight of each indicator is taken as the target weight of each indicator;

[0140] Eliminate the indicators with smaller target weights to obtain the optimized indicator set;

[0141] The information contribution rate method is used to judge the rationality of the indicators of the optimization indicator set;

[0142] If the rationality of the indicators of the optimization indicator set is verified, the optimization indicator set will be used as the safety risk evaluation system of the new distribution network;

[0143] If the indicator rationality verification of the optimized indicator set fails, the initial indicator set is readjusted and the indicator screening is performed again until the safety risk assessment system of the new distribution network is obtained.

[0144] The specific explanations of each step in the embodiments of the present application can be referred to the description in the aforementioned embodiments and will not be repeated here.

[0145] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0146] The following is an embodiment of the device of the present invention. For details not described in detail, reference may be made to the corresponding method embodiments described above.

[0147] Figure 3 The schematic diagram of the structure of the security risk assessment index screening device applicable to the novel power distribution network provided by the embodiment of the present invention is shown. For the convenience of explanation, only the part related to the embodiment of the present invention is shown, which is described in detail as follows:

[0148] like Figure 3 As shown, the safety risk assessment index screening device 20 suitable for the new distribution network includes: an acquisition module 21, an optimization module 22, a rationality verification module 23 and a processing module 24.

[0149] An acquisition module 21 is used to acquire an initial indicator set for performing a safety risk assessment on a new distribution network;

[0150] The optimization module 22 is used to determine the target weight of each indicator in the initial indicator set, and optimize the initial indicator set according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set;

[0151] A rationality verification module 23 is used to determine the information contribution rate of the optimization index set, and perform rationality verification on the optimization index set according to the information contribution rate of the optimization index set to obtain a rationality verification result;

[0152] The processing module 24 is used to use the optimized indicator set as the safety risk evaluation system of the new distribution network if the rationality verification result is passed.

[0153] In a possible implementation, in the rationality verification module 23, determining the information contribution rate of the optimization indicator set includes:

[0154] Obtain the indicator data set corresponding to each indicator in the initial indicator set;

[0155] Based on the indicator data set corresponding to each indicator in the initial indicator set, the sum of the variances of each indicator in the initial indicator set and the sum of the variances of each indicator in the optimized indicator set are calculated;

[0156] Based on the sum of the variances of the indicators in the initial indicator set and the sum of the variances of the indicators in the optimized indicator set, the information contribution rate of the optimized indicator set is determined.

[0157] In a possible implementation, in the rationality verification module 23, based on the sum of the variances of the indicators in the initial indicator set and the sum of the variances of the indicators in the optimized indicator set, the information contribution rate of the optimized indicator set is determined, including:

[0158] The ratio of the sum of the variances of each indicator in the optimized indicator set to the sum of the variances of each indicator in the initial indicator set is taken as the information contribution rate of the optimized indicator set.

[0159] In a possible implementation, in the rationality verification module 23, the rationality of the optimization indicator set is verified according to the information contribution rate of the optimization indicator set to obtain a rationality verification result, including:

[0160] If the information contribution rate of the optimization indicator set is greater than or equal to the preset contribution rate, the rationality verification result is determined to be a passed verification; otherwise, the rationality verification result is determined to be a failed verification.

[0161] In a possible implementation, in the optimization module 22, the target weight of each indicator in the initial indicator set is determined, including:

[0162] Using the analytic hierarchy process, determine the first weight of each indicator in the initial indicator set;

[0163] The principal component analysis method is used to determine the second weight of each indicator in the initial indicator set;

[0164] The average of the first weight and the second weight of each indicator in the initial indicator set is used as the target weight of each indicator in the initial indicator set.

[0165] In a possible implementation, in the optimization module 22, the initial indicator set is optimized according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set, including:

[0166] Sort the indicators in the initial indicator set in descending order according to the target weight to obtain a sorted initial indicator set;

[0167] The preset proportion of indicators that are ranked at the back of the sorted initial indicator set are eliminated to obtain the optimized indicator set.

[0168] In a possible implementation, the initial indicator set includes an indicator set at a physical level, an indicator set at an operation level, and an indicator set at an information level.

[0169] In a possible implementation, the physical level indicator set includes line N-1 pass rate, line standard wiring rate, average equipment operation life, new energy consumption rate, backup power supply guarantee rate, and main section N-2 pass rate;

[0170] The set of indicators at the operation level includes voltage qualification rate, power supply reliability rate, line overload rate, user-side flexible resource ratio, energy storage and new energy capacity ratio, and equipment utilization rate;

[0171] The set of indicators at the information level includes smart terminal coverage, distribution automation self-healing rate, smart switch standard coverage, power supply dispatchability rate, energy storage shareability rate and communication performance adaptation index.

[0172] In a possible implementation, the processing module 24 is further configured to:

[0173] If the rationality verification result is that the verification fails, the initial indicator set is readjusted to obtain a new initial indicator set, and based on the new initial indicator set, the process jumps to the step of determining the target weight of each indicator in the initial indicator set and continues to execute.

[0174] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0175] Those of ordinary skill in the art will appreciate that the templates, units, and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0176] If the module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, it can implement the steps of the above-mentioned various security risk assessment index screening method embodiments applicable to the new distribution network. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium.

[0177] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for screening safety risk assessment indicators for a new distribution network, characterized in that: include: Obtaining an initial set of indicators for security risk assessment of new distribution networks; Determining a target weight of each indicator in the initial indicator set, and optimizing the initial indicator set according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set; Determining the information contribution rate of the optimization index set, and performing rationality verification on the optimization index set according to the information contribution rate of the optimization index set to obtain a rationality verification result; If the rationality verification result is verified to be passed, the optimization indicator set is used as the safety risk evaluation system of the new distribution network.

2. The method for screening safety risk assessment indicators applicable to a new distribution network according to claim 1, characterized in that: Determining the information contribution rate of the optimization indicator set includes: Obtaining an indicator data set corresponding to each indicator in the initial indicator set; Based on the indicator data set corresponding to each indicator in the initial indicator set, the sum of the variances of each indicator in the initial indicator set and the sum of the variances of each indicator in the optimized indicator set are calculated; Based on the sum of the variances of the indicators in the initial indicator set and the sum of the variances of the indicators in the optimized indicator set, the information contribution rate of the optimized indicator set is determined.

3. The method for screening safety risk assessment indicators applicable to a new distribution network according to claim 2 is characterized in that: The determining the information contribution rate of the optimized indicator set based on the sum of the variances of the indicators in the initial indicator set and the sum of the variances of the indicators in the optimized indicator set includes: The ratio of the sum of the variances of the various indicators in the optimization indicator set to the sum of the variances of the various indicators in the initial indicator set is taken as the information contribution rate of the optimization indicator set.

4. The method for screening safety risk assessment indicators applicable to a new distribution network according to claim 1, characterized in that: The rationality verification of the optimization index set is performed according to the information contribution rate of the optimization index set to obtain a rationality verification result, including: If the information contribution rate of the optimization indicator set is greater than or equal to the preset contribution rate, the rationality verification result is determined to be a passed verification; otherwise, the rationality verification result is determined to be a failed verification.

5. The method for screening safety risk assessment indicators applicable to a new distribution network according to claim 1, characterized in that: Determining the target weight of each indicator in the initial indicator set includes: Using the hierarchical analysis method, determine the first weight of each indicator in the initial indicator set; Using principal component analysis, determine the second weight of each indicator in the initial indicator set; The average value of the first weight and the second weight of each indicator in the initial indicator set is used as the target weight of each indicator in the initial indicator set.

6. The method for screening safety risk assessment indicators applicable to a new distribution network according to claim 1, characterized in that: The step of optimizing the initial indicator set according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set includes: Sorting the indicators in the initial indicator set in descending order according to the target weight to obtain a sorted initial indicator set; The indicators of a preset proportion ranked at the back of the sorted initial indicator set are removed to obtain an optimized indicator set.

7. The method for screening safety risk assessment indicators applicable to a new distribution network according to claim 1, characterized in that: The initial indicator set includes an indicator set at the physical level, an indicator set at the operation level, and an indicator set at the information level.

8. The method for screening safety risk assessment indicators applicable to a new distribution network according to claim 7, characterized in that: The physical level indicator set includes line N-1 pass rate, line standard wiring rate, average operation life of equipment, new energy consumption rate, backup power supply guarantee rate and main section N-2 pass rate; The indicator set at the operation level includes voltage qualification rate, power supply reliability rate, line overload rate, user-side flexible resource ratio, energy storage and new energy capacity ratio, and equipment utilization rate; The information-level indicator set includes smart terminal coverage, distribution automation self-healing rate, smart switch standard coverage, power supply dispatchability rate, energy storage shareability rate and communication performance adaptation index.

9. The method for screening safety risk assessment indicators applicable to a new distribution network according to any one of claims 1 to 8, characterized in that: After obtaining the rationality verification result, the security risk assessment index screening method applicable to the new distribution network further includes: If the rationality verification result is that the verification fails, the initial indicator set is readjusted to obtain a new initial indicator set, and based on the new initial indicator set, the process jumps to the step of determining the target weight of each indicator in the initial indicator set to continue execution.

10. A safety risk assessment index screening device suitable for a new type of distribution network, characterized in that: include: An acquisition module, used for acquiring an initial indicator set for safety risk assessment of a new distribution network; An optimization module, used to determine the target weight of each indicator in the initial indicator set, and optimize the initial indicator set according to the target weight of each indicator in the initial indicator set to obtain an optimized indicator set; A rationality verification module, used to determine the information contribution rate of the optimization index set, and perform rationality verification on the optimization index set according to the information contribution rate of the optimization index set to obtain a rationality verification result; A processing module is used to use the optimization indicator set as the safety risk evaluation system of the new distribution network if the rationality verification result is verified to be passed.

Images