CN114298598A - Urban high-reliability medium-voltage distribution network wiring mode comprehensive evaluation method - Google Patents

Urban high-reliability medium-voltage distribution network wiring mode comprehensive evaluation method Download PDF

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CN114298598A
CN114298598A CN202111671445.9A CN202111671445A CN114298598A CN 114298598 A CN114298598 A CN 114298598A CN 202111671445 A CN202111671445 A CN 202111671445A CN 114298598 A CN114298598 A CN 114298598A
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index
weight
reliability
distribution network
medium
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郭雪丽
龚正国
陈庆岩
王爽
秦亚东
王莹
王辉
杨冰
宋少
郑刚
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Nanyang Power Supply Co of State Grid Henan Electric Power Co Ltd
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Nanyang Power Supply Co of State Grid Henan Electric Power Co Ltd
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Abstract

The invention provides a comprehensive evaluation method for wiring modes of an urban high-reliability medium-voltage distribution network, which comprises the following steps of: s1: constructing a comprehensive evaluation index system of a high-reliability wiring mode of the medium-voltage distribution network; s2: determining the weight of each evaluation factor by adopting a decision experiment and evaluation experiment DEMATEL-network analysis method ANP-entropy-resisting weight method and an improved grey correlation degree method; s3: and constructing an index scoring function by using a polynomial difference method and calculating to obtain a comprehensive scoring result. The reasonable evaluation index system and the comprehensive evaluation method are constructed, the high-reliability wiring mode comprehensive planning effect of the medium-voltage distribution network can be objectively reflected, the design scheme is more reasonable, the development of the high-reliability distribution network is promoted, and the method has important application significance.

Description

Urban high-reliability medium-voltage distribution network wiring mode comprehensive evaluation method
Technical Field
The invention relates to the technical field of power systems, in particular to a comprehensive assessment method for wiring modes of an urban high-reliability medium-voltage distribution network.
Background
With the rapid acceleration of the urbanization process of China, high-reliability power supply areas such as new urban areas, economic development areas and the like are well-established. How to reasonably select the medium-voltage distribution network wiring mode becomes a key problem for planning and constructing a high-reliability area. The high-reliability power supply area is generally in the range of A + and A-type power supply areas specified in the power distribution network planning and design technical guide, a cable network double-ring type or single-ring type structure is recommended, but as the reliability requirements of power distribution network users are higher and higher, the traditional high-reliability wiring mode can not meet the requirements any more. Therefore, the construction scheme of a world first-class medium-voltage distribution network such as Singapore is used for reference, and the construction scheme becomes a preferred scheme for the grid transformation of a high-reliability demonstration area of a domestic city. However, as the permeability of the distributed power supply is gradually improved, the access of the conversion device also affects the reliability of the power distribution network, so that a novel wiring mode is developed on the basis of a conventional wiring mode to adapt to the future development trend of the power distribution network. In order to solve the problems that the medium-voltage distribution network wiring mode in a high-reliability area is various in evaluation index and has no unified standard in planning and designing, research is conducted on a high-reliability wiring mode comprehensive evaluation method of a medium-voltage distribution network.
The patent with the publication number of CN104156884B discloses an economical planning and evaluation information system for a wiring mode of a distribution network containing a microgrid, which comprises a database module, an input module, an analysis module, a planning and evaluation module and an output module which are sequentially connected; the input module acquires the wiring mode, the microgrid data and the power equipment data from the database module, and the analysis module analyzes and calculates cost data of each operation stage of the purchase stage cost of each wiring mode according to the data input by the input module and sends the cost data to the planning and evaluation module; the planning and evaluation module firstly plans the distributed power supply in the microgrid according to the received data to obtain the annual cost of the unit load of the microgrid, then carries out economic evaluation on the wiring mode containing the microgrid, and the output module outputs the planning and evaluation result.
Patent document CN112541252A discloses a method for optimizing a connection mode based on reliability evaluation and a system for implementing the method, wherein an evaluation model combining economy and reliability is established to effectively evaluate the connection mode, so as to obtain an optimal connection mode and effectively utilize resources. The optimization method specifically comprises the following steps: constructing a power supply model; step two: acquiring relevant data to be processed on a power distribution network line, and inputting the data into an evaluation system established for analyzing a wiring mode; step three: establishing a comprehensive evaluation model, and taking an evaluation result obtained by combining the economic value and the reliability value as a target evaluation value; step four: and determining a wiring mode.
Both methods can evaluate the wiring method, but both methods consider a single aspect and the evaluation is not comprehensive enough.
Disclosure of Invention
In view of the above, the invention provides a comprehensive evaluation method for a wiring mode of an urban high-reliability medium-voltage distribution network.
In order to solve the technical problems, the invention provides a comprehensive assessment method for a wiring mode of an urban high-reliability medium-voltage distribution network, which comprises the following steps:
s1: constructing a comprehensive evaluation index system of a high-reliability wiring mode of the medium-voltage distribution network;
s2: determining the weight of each evaluation factor by adopting a decision experiment and evaluation experiment DEMATEL-network analysis method ANP-entropy-resisting weight method and an improved grey correlation degree method;
s3: and constructing an index scoring function by using a polynomial difference method and calculating to obtain a comprehensive scoring result.
Further, in the step S1, a comprehensive evaluation index system of the high-reliability wiring mode of the medium-voltage distribution network is constructed according to 4 criteria of reliability, economy, technology and adaptability;
(1) reliability index
The power distribution network power supply reliability index is a basis for measuring the power distribution network reliability level, the index not only needs to objectively reflect the overall power supply reliability level of the system, but also needs to be beneficial to finding out weak links existing in the power distribution network so as to take corresponding enhancement measures, including average power supply availability ASAI, system average power failure frequency SAIFI and system average power failure duration SAIDI 3 indexes;
(2) index of economic efficiency
The economic indexes mainly reflect the economic characteristics of different medium-voltage wiring modes, and comprise 2 indexes of annual investment cost and annual power failure loss of unit load;
(3) technical index
The technical indexes mainly reflect the technical characteristics of a medium-voltage wiring mode, and comprise 2 indexes of voltage deviation and line loss rate;
(4) adaptive index
The adaptability indexes mainly reflect the adaptability degree of the medium-voltage wiring mode to the future development of the power grid in the planning area, and comprise 3 indexes of operation difficulty degree, grid frame expansibility and new load access difficulty degree.
Further, the step S2 specifically includes: a) selecting an evaluation method; b) determining each criterion weight; c) determining index weight of each layer; d) and calculating the comprehensive weight.
Further, the step S3 specifically includes: 1) determining a scoring standard; 2) establishing a scoring function of each index; 3) calculating index scores of all levels; 4) and calculating a comprehensive score.
Further, the step S2 adopts a DEMATEL method to screen the main elements of the complex system, thereby simplifying the system structure analysis process; meanwhile, the network analysis method ANP method can fully consider the mutual influence and domination relation among elements, thereby solving the problem of actual decision; determining subjective weights of 4 criteria by using a DEMATEL-based network analysis method;
assuming that the network layer of the ANP has n criteria, which are respectively represented by C1, C2,. cndot.,. Cn, dependence relationships exist among the criteria, and yji represents the importance degree of the criteria Cj (j ≠ i) to Ci; sequentially taking Ci (i-1, 2, n) as a criterion, and comparing Ci with other index values except the index values per se pairwise to obtain a corresponding weight matrix; according to the characteristic root method, the weight vector under the criterion of Ci is obtained
Figure BDA0003453114740000031
Figure BDA0003453114740000032
The weight matrix is:
Figure BDA0003453114740000033
under each criterion layer, the criterion has no influence relationship on the criterion layer, namely, the diagonal element of the matrix is 0, and a direct influence matrix is obtained, namely:
Figure BDA0003453114740000034
for direct influence matrix WdAnd solving a comprehensive influence matrix W of the limit, namely:
Figure BDA0003453114740000035
each row of elements of the matrix tends to a certain stable value, and finally, the non-zero stable value of each row is the subjective weight value of each corresponding element, so that the subjective weight set is as follows:
Ws=(Wsi|1≤i≤n) (4)。
further, in step S2, the entropy weight method:
the inverse entropy is defined as:
Figure BDA0003453114740000041
in the formula: p is a radical ofjFor the probability of occurrence of each state, 1. ltoreq. pjN is less than or equal to n
Figure BDA0003453114740000042
The characteristics of the entropy values are different, namely the difference of indexes is in direct proportion to the entropy values and the weight coefficients;
the steps of determining the index weight by the entropy weight method are as follows: assuming that there are m evaluation objects, n evaluation indexes, and an index evaluation matrix X ═ Xij) n x m, wherein xij(i-1, 2, n, j-1, 2, m) is an index value; determining the inverse entropy of each index as:
Figure BDA0003453114740000043
in the formula
Figure BDA0003453114740000044
H is obtained from the formula (6)iPerforming weight normalization to obtain objective weight woiNamely:
Figure BDA0003453114740000045
the set of objective weights is then:
Wo=(Woi|1≤i≤n) (8)。
further, in step S2, the DEMATEL-ANP-inverse entropy weight method combines the weights:
the relative importance degree of the subjective and objective weights is different according to different criteria; let the relative importance of the subjective weight and the objective weight be expressed as alphaiAnd betaiFinally, combining the basic thought of the matrix estimation theory, the important coefficient alpha of the subjective and objective weights of each criterion is calculatediAnd betaiNamely:
Figure BDA0003453114740000046
and finally, calculating the combination weight by using the obtained subjective weight set, objective weight set and relative importance coefficients of the subjective weight and the objective weight, namely:
Figure BDA0003453114740000047
further, in step S2, according to the improved gray correlation method, weights of the indexes in the index layer are solved, and the weights are multiplied by weight values of the indexes in the criterion layer, so as to obtain weight values of the indexes in the high-reliability connection mode of the medium-voltage distribution network; the calculation steps are as follows:
determining an initial weight value; m experts are provided to make experience judgment on the n evaluation index weights of the determined target, and the judgment data is formed as follows:
Figure BDA0003453114740000051
determining a reference sequence; selecting the maximum weight value from each column of X as a reference weight value, wherein the reference data column is as follows:
X0=[x01,x02,…,x0n] (12)
find each index sequence x1,x2,…,xnWith reference data x0The distance between, i.e.:
Figure BDA0003453114740000052
solving the weight of each index, namely:
Figure BDA0003453114740000053
fourthly, solving the normalized weight of each index, namely:
according to
Figure BDA0003453114740000054
Will be provided with
Figure BDA0003453114740000055
Normalization processing can obtain an index weight vector, where ω is (ω)1,ω2,...,ωm)T
Further, in the step S3, a percentile system is adopted, and a fuzzy membership method is combined to provide a score standard of each index of the high-reliability wiring mode of the medium-voltage distribution network; in the 4 criteria, reliability, economy and technical indexes are all quantitative calculable indexes; the adaptability index is difficult to quantitatively calculate, needs qualitative treatment and can be evaluated by a fuzzy statistical method.
Further, in the step S3, each index distribution is analyzed and calculated by a pyhon software to obtain each index quantile, and further, a scoring function of the high-reliability wiring mode index system of the medium-voltage distribution network is obtained.
At present, the comprehensive evaluation methods for the medium-voltage distribution network mainly comprise the following steps: the entropy weight analytic hierarchy process has the core idea that a clear hierarchical structure is established to decompose complex problems, can quantify and integrate each index on the basis of effectively processing the internal relation and mutual independence among all evaluation indexes, has stronger integrity and flexibility, and is a key technology for analyzing complex problems and establishing an evaluation system in evaluation; the fishbone diagram analysis method, also called causal analysis method, arranges the problem characteristics and the affected factors into layers according to the correlation, and marks the graph of the important factors, and is an analysis method for looking at the nature through the phenomenon; the Delphi method is a method capable of fully integrating expert knowledge, experience and information in a certain field, also called an expert scoring method, and inquires expert opinions in an anonymous mode for many times, so that decision opinions tend to be consistent through communication and circular feedback of information, and finally a collective judgment result with high accuracy is obtained. The method has three obvious characteristics of anonymity, multiple feedback and statistical property of results, is very suitable for analyzing and judging complex systems, and can be applied to various links of comprehensive evaluation such as screening of evaluation indexes, establishment of an index system, setting of index weight, determination of evaluation standards and the like; the fuzzy comprehensive evaluation method is an analysis method which is based on a fuzzy set theory, carries out quantitative processing on various fuzzy information in analysis and evaluation and carries out state judgment. It uses membership degree to describe the intermediate degree of difference, and is a description of ambiguity by using accurate mathematical language. The evaluation method can reasonably quantify the qualitative index, so that the problems of uncertainty of original data in comprehensive evaluation, ambiguity of evaluation standards and the like are better solved.
The evaluation current situation of various comprehensive evaluation analysis methods aiming at the power distribution network is as follows:
(1) the comprehensive evaluation is carried out on the power distribution network by combining an entropy weight analytic hierarchy process, but an evaluation system of a wiring mode is not established independently;
(2) an analytic hierarchy process based on Delphi method correction is used for setting all levels of index weights of an evaluation system, a high-voltage distribution network planning evaluation index system and a comprehensive evaluation model are researched, and the targeted comprehensive evaluation of a medium-voltage distribution network connection mode is not realized;
(3) the typical power supply mode of an important power user is evaluated based on an analytic hierarchy process and expert experience, but a comprehensive evaluation system is large in structure and is not evaluated aiming at a specific wiring mode.
The current situation of comprehensive evaluation of the power grid wiring mode is as follows:
the existing comprehensive evaluation of the power grid connection mode only evaluates a typical power supply model of the current medium-voltage power distribution system, but the comprehensive evaluation result is only simple analysis and an effective comprehensive scoring system is not established;
(1) the existing comprehensive evaluation system of the power distribution network connection mode comprehensively considers factors such as safety, reliability and economy of the power distribution network connection mode, comprehensively evaluates the power distribution network connection mode according to weighted average of index values, but does not aim at a high-reliability power supply area, and the connection mode also belongs to traditional connection mode analysis.
(2) Reliability calculation, economic calculation of a whole life cycle and electrical analysis are carried out on a common typical wiring mode in the planning area, the theoretical optimal wiring mode of different power supply areas of the planning area is determined through comprehensive evaluation, and the influence of the wiring mode on the urban development adaptability is not considered in evaluation indexes.
Compared with the related technology, the urban high-reliability medium-voltage distribution network wiring mode comprehensive evaluation method provided by the invention has the following beneficial effects: based on the current situation and existing problems of the comprehensive evaluation system, the comprehensive evaluation index system of the high-reliability connection mode of the medium-voltage distribution network is constructed according to 4 criteria of reliability, economy, technology and adaptability, the weights of all evaluation factors are determined by adopting a decision making experiment and an evaluation experiment (DECINTAL MAKING AND evaluation laboratory, DEMATEL) method, a network analysis method (ANP), an anti-entropy weight method and an improved grey correlation method, and finally, an index scoring function is constructed by utilizing a polynomial difference method and a comprehensive scoring result is obtained through calculation. A reasonable evaluation index system and a comprehensive evaluation method are constructed, the high-reliability wiring mode comprehensive planning effect of the medium-voltage distribution network can be objectively reflected, the design scheme is more reasonable, the development of the high-reliability distribution network is promoted, and the method has important application significance.
Drawings
FIG. 1 is a flow chart of the comprehensive evaluation method of the present invention;
FIG. 2 is a pyhon computational weight display diagram of the present invention;
FIG. 3 is a fuzzy distribution diagram of a trapezoidal or semi-trapezoidal distribution of the present invention.
Detailed Description
The invention is further described with reference to the following figures and embodiments.
Examples
Referring to fig. 1-3, the present embodiment provides a method for comprehensively evaluating a wiring pattern of an urban high-reliability medium-voltage distribution network.
Firstly, carrying out typical high-reliability wiring mode analysis on medium-voltage distribution network
The high-reliability wiring mode of the traditional medium-voltage distribution network, such as a single-ring network and a double-ring network, is analyzed. On the basis, a petal-shaped wiring mode which is currently used as a main net rack transformation scheme is analyzed by combining the research result of the construction condition of a high-reliability demonstration area of a domestic 'first-class distribution network'. Meanwhile, in view of the influence of the distributed power supply on the reliability of the power distribution network, a three-way simultaneous supply wiring mode with a flexible direct-current loop is analyzed. Through analyzing the 4 typical high-reliability wiring modes of the medium-voltage distribution network, a theoretical basis is provided for establishing a reasonable comprehensive evaluation system.
Second, high-reliability wiring mode evaluation index system for constructing medium-voltage distribution network
(1) Reliability index
The power distribution network power supply reliability index is a basis for measuring the power distribution network reliability level, and the index not only needs to objectively reflect the overall power supply reliability level of the system, but also needs to be beneficial to finding out weak links existing in the power distribution network so as to take corresponding enhancement measures, including 3 indexes of average power supply availability (ASAI), system average power failure frequency (SAIFI) and system average power failure duration (SAIDI).
(2) Index of economic efficiency
The economic indexes mainly reflect the economic characteristics of different medium-voltage wiring modes, including 2 indexes of annual investment cost and annual power failure loss of unit load.
(3) Technical index
The technical indexes mainly reflect the technical characteristics of the medium-voltage wiring mode, and comprise 2 indexes of voltage deviation and line loss rate.
(4) Adaptive index
When selecting the medium voltage distribution network connection mode, the actual operation condition of the power grid in the planned area needs to be considered, and meanwhile, a space needs to be reserved for future grid expansion. Considering the requirement of a high-reliability power supply area of a city on the future development of a power distribution network and the access influence of a distributed power supply, the adaptability of the high-reliability power supply area to the city development should be combined when a medium-voltage power distribution network wiring mode is planned. The adaptability indexes mainly reflect the adaptability degree of the medium-voltage wiring mode to the future development of the power grid in the planning area, and comprise 3 indexes of operation difficulty degree, grid frame expansibility and new load access difficulty degree.
In the above 4 dimensional indexes, reliability, economy and technical indexes are all quantitative calculable indexes, but adaptive indexes are difficult to quantitatively calculate and need qualitative processing, and evaluation processing can be performed by a fuzzy statistical method.
Third, determining a high-reliability wiring mode comprehensive evaluation method of the medium-voltage distribution network
In a high-reliability wiring mode evaluation index system of a medium-voltage distribution network, the relationship among 4 criteria of reliability, economy, technology and adaptability is complex and ambiguous, in view of the fact that the embodiment adopts a DEMATEL-ANP-entropy-resisting weight method to comprehensively consider subjective and objective information, the weight of each criterion layer is calculated, then each index weight in the criterion is solved by using an improved grey correlation degree method, and finally, the comprehensive scores of different wiring modes can be calculated according to the index weights, so that a decision maker can provide a selection judgment basis.
(1) DEMATEL-ANP method
The DEMATEL method is adopted to screen the main elements of the complex system and simplify the analysis process of the system structure. Meanwhile, the network analysis method ANP method can fully consider the mutual influence and domination relation among elements, so that the actual decision problem is solved. The ANP constructs a judgment matrix by pairwise comparison of the dominated elements, and by using a DEMATEL method for reference, the construction method of the judgment matrix is improved by using the element influence relationship, so that the subjective estimation of the influence degree of the elements on the ANP can be avoided, and the problem that the direct influence and the indirect influence are not uniform when the judgment matrix is constructed can be solved. Subjective weights for 4 criteria were determined using a DEMATEL-based network analysis.
Suppose that the network layer of the ANP has n criteria, which are respectively represented by C1, C2, ·, Cn, and there is a dependency relationship between the criteria, and yji represents the importance degree of the criteria Cj (j ≠ i) to Ci. And sequentially taking Ci (i-1, 2, n) as a criterion, and comparing Ci with other index values except the index values per se in pairs to obtain corresponding weight matrixes. According to the characteristicsRoot method, obtaining weight vector with Ci as criterion
Figure BDA0003453114740000091
Figure BDA0003453114740000092
The weight matrix is:
Figure BDA0003453114740000093
under each criterion layer, the criterion has no influence relationship on the criterion layer, namely, the diagonal element of the matrix is 0, and a direct influence matrix is obtained, namely:
Figure BDA0003453114740000094
for direct influence matrix WdAnd solving a comprehensive influence matrix W of the limit, namely:
Figure BDA0003453114740000095
each row of elements of the matrix tends to a certain stable value, and finally, the non-zero stable value of each row is the subjective weight value of each corresponding element, so that the subjective weight set is as follows:
Ws=(Wsi|1≤i≤n) (4)
(2) entropy weight method
The entropy weight method is a comprehensive evaluation method which can be used for multiple objects and multiple indexes, the evaluation result is mainly based on objective data, the subjective influence is hardly caused, and the interference of human factors can be avoided to a great extent. In order to avoid the extreme case that the index is too small during weight distribution due to high sensitivity of the index difference degree in the entropy weight method, the entropy weight method is selected to determine the objective weight in the embodiment. The inverse entropy is defined as:
Figure BDA0003453114740000096
in the formula: p is a radical ofjFor the probability of occurrence of each state, 1. ltoreq. pjN is less than or equal to n
Figure BDA0003453114740000101
The characteristic of the entropy value is different from that of the entropy value, namely, the difference of the indexes is in direct proportion to both the entropy value and the weight coefficient.
The steps of determining the index weight by the inverse entropy weight method are as follows. Assuming that there are m evaluation objects, n evaluation indexes, and an index evaluation matrix X ═ Xij) n x m, wherein xij(i-1, 2, n, j-1, 2, m) is an index value. Determining the inverse entropy of each index as:
Figure BDA0003453114740000102
in the formula
Figure BDA0003453114740000103
H is obtained from the formula (6)iPerforming weight normalization to obtain woiNamely:
Figure BDA0003453114740000104
the set of objective weights is then:
Wo=(Woi|1≤i≤n) (8)
(3) DEMATEL-ANP-inverse entropy weight method combined weight
The relative importance of subjective and objective weights varies according to criteria. Let the relative importance of the subjective weight and the objective weight be expressed as alphaiAnd betaiFinally, combining the basic thought of the matrix estimation theory, the important coefficient alpha of the subjective and objective weights of each criterion is calculatediAnd betaiNamely:
Figure BDA0003453114740000105
and finally, calculating the combination weight by using the obtained subjective weight set, objective weight set and relative importance coefficients of the subjective weight and the objective weight, namely:
Figure BDA0003453114740000106
(4) method for improving grey correlation
The improved grey correlation method fully combines subjective information of expert experience judgment values and a scientific and simple mathematical model, overcomes the defect that the traditional grey correlation analysis method is easily influenced by resolution coefficient values in the calculation process, and ensures that the obtained index weight can fully reflect objective degree and also can reflect subjective degree to a certain degree. According to the improved grey correlation method, the weight of each index in the index layer is solved, and the weight is multiplied by the weight of each index in the criterion layer, so that the weight of each index in the high-reliability wiring mode of the medium-voltage distribution network can be obtained. The calculation procedure is as follows.
Determining an initial weight value. M experts are provided to make experience judgment on the n evaluation index weights of the determined target, and the judgment data is formed as follows:
Figure BDA0003453114740000111
determining a reference sequence. Selecting the maximum weight value from each X column as a reference weight value to form a reference data column
X0=[x01,x02,…,x0n] (12)
Find each index sequence x1,x2,…,xnWith reference data x0The distance between, i.e.:
Figure BDA0003453114740000112
(iii) weighting each index, i.e.
Figure BDA0003453114740000113
Fourthly, solving the normalized weight of each index, namely:
according to
Figure BDA0003453114740000114
Will be provided with
Figure BDA0003453114740000115
Normalization processing can obtain an index weight vector, where ω is (ω)1,ω2,...,ωm)T
Calculating the comprehensive scores of different wiring modes according to the index weight.
High-reliability wiring mode comprehensive evaluation of medium-voltage distribution network
The high-reliability wiring mode comprehensive evaluation method of the medium-voltage distribution network is implemented by the following process shown in fig. 1, wherein the standard layer weight of an evaluation system is determined firstly, then each index weight of the evaluation system is determined, finally an index system scoring function is established, and a comprehensive score result can be calculated by combining the index weights.
(1) Criterion layer weight determination
Through investigating and researching the wiring mode of the medium-voltage distribution network in the domestic 5 reliable power supply demonstration areas, the mutual direct influence degree among macro demand indexes is empirically judged, and C is used1、C2、C3、C4Respectively representing 4 criteria layer indexes of reliability, economy, technicality and adaptability, constructing a judgment matrix by introducing a 1-9 ratio scaling method, and obtaining the relative weight of each factor. When two judgment matrixes are constructed, the elements of the upper level are compared with the elements of the same level in pairs by taking the elements of the upper level as a reference, the relative importance degree of the elements is determined according to a pre-selected evaluation scale, and finally, a quantitative judgment matrix is established according to the relative importance degree. The evaluation scale is shown in table 1 below.
TABLE 1 judge matrix evaluation scale table
Assessment scale Means of
1 The i factor is as important as the j factor
3 The i factor is slightly more important than the j factor
5 The i factor is more important than the j factor
7 The i factor is significantly more important than the j factor
9 The i factor is extremely important than the j factor
2、4、6、8 The comparison results of the i element and the j element are between the above results
Reciprocal of the The j element to i element comparison result is the inverse of the i element to j element comparison result
The decision matrix representation is determined according to the rating scale as shown in table 2 below.
TABLE 2 judgment matrix example Table
A (general purpose) B1 (index level) B2 Bn
B1 a11 a12 a1n
B2 a21 a22 a2n
Bn an1 an1 ann
Subjective weight determination:
according to experience, 4 criterion layer indexes of the time are sorted according to importance degree, C1>C4>C2=C3
A decision matrix was constructed and its weights calculated by pyhon software analysis, as shown in figure 2.
And (3) determining subjective weight:
ws=[0.5579 0.0963 0.0963 0.2495]T (15)
calculating objective weight:
when objective weight is determined, an inverse entropy weight method is adopted for calculation, and initial weight experience scores of macroscopic demand indexes of medium-voltage distribution network wiring modes in 5 reliable power supply demonstration areas during planning are referred through investigation results to finally obtain an initial judgment matrix X shown in a formula (16). It can be known from observation that each row element of the matrix X represents a weight opinion set aiming at a certain index when each demonstration area is planned, each column element represents a weight opinion set aiming at all indexes when each demonstration area is planned, and the sum of the column elements is 1.
Figure BDA0003453114740000121
Calculating according to the formulas (6) to (8), and obtaining the objective weight vector of each index of the normalized criterion layer as follows:
w0=[0.2494 0.2511 0.2501 0.2493]T (17)
on the basis of knowing the main and objective weight vectors of each criterion layer index, the final combination weight vector of each index can be obtained according to the combination weight calculation method of the formula (10)
wi=[0.2927 0.2256 0.225 0.2567]T (18)
The weight calculation result shows that the more basic requirements are, the larger the index weight value is, the larger the evaluation influence on the cable mode is, and meanwhile, the rationality of the requirement hierarchical structure is verified. The final combination weight effectively integrates subjective information and objective information of the index, and plays a role in optimizing the index weight.
(2) Determination of each index weight of index system
The importance of each index of a wiring mode of the medium-voltage distribution network is understood when 5 reliable power supply demonstration areas are planned, and relevant weights are given to each index, as shown in the following table 3.
TABLE 3 weight tables for each index of each exemplary zone
Figure BDA0003453114740000131
According to the improved grey correlation method, the weights of all indexes in the index layer are solved, and the weights are multiplied by the weight values of all indexes in the criterion layer, so that the weight values of all indexes in the high-reliability wiring mode of the medium-voltage distribution network are obtained, and the weight values are shown in table 4.
Table 4 high-reliability wiring mode comprehensive evaluation index system weight calculation table for medium-voltage distribution network
Figure BDA0003453114740000132
Figure BDA0003453114740000141
(3) Determining each index scoring standard of index system
Qualitative descriptions of indicators must be converted into normative quantitative data through quantization, which is determined by different underlying indicators based on different meaning and purpose designs. In addition, quantified quantitative data often has different dimensions and orders of magnitude, and needs to be normalized before comparison or integration can be performed. The raw data are converted into a normalized format for direct comparison by using a certain scaling system, namely index score standard.
The score scale is divided into a percent system, a ten system and a five system. According to the embodiment, the scoring standard of each index of the high-reliability wiring mode of the medium-voltage distribution network is given by adopting a percentile system and combining a fuzzy membership method.
Qualitative index
Selecting fuzzy statistical method to determine the membership degree of qualitative index, specifically inviting m experts (for example, m is 10), respectively evaluating each index according to the comment grades in a given comment set, determining the grade of each index, then counting the evaluation results of all experts to obtain the index U considered by the index in m expertsijUnder comment VijNumber m of expertsijBased thereon, the corresponding degree of membership r is calculatedij
Figure BDA0003453114740000142
In the formula, mijIndicates as an index UijUnder comment VijThe number of experts; m is the total number of all experts participating in the evaluation.
Thereby obtaining a qualitative index UiSingle factor fuzzy comprehensive evaluation Ri=(ri1,ri2,ri3)。
The comment set V is a set of evaluation levels, where V is { V ═ V }jJ is 1,2, …, m, which is actually a division of the evaluated object change interval. Where vj represents the jth evaluation level, and m is the number of evaluation levels. The specific rating may be described in an appropriate language according to the evaluation content, for example, the evaluation economic benefit index may be described by V ═ good, medium, or poor;
according to the existing comment set, the numerical result is defined, i.e. the comment set is represented by the value B. For example, { good, medium, and bad } is numerically expressed as B ═ 95, 60, and 40 };
thus, the overall evaluation score for the qualitative index:
F=Ri·B (20)
② calculation of membership of quantitative index
And the membership function of the quantitative index is calculated by adopting a fuzzy distribution method. Among the objective things, the most common is the case of a real number R as a domain, and the membership functions of the fuzzy sets on the real number set R are usually called fuzzy distributions. When the membership function of the objective fuzzy phenomenon in question is similar to a given fuzzy distribution, the fuzzy distribution can be selected as the solved membership function, and then the parameters which are in line with the reality are determined through priori knowledge or data experiments, so that the specific membership function is obtained.
Membership functions of quantitative indexes can be generally divided into benefit type, cost type and moderate type, and respectively correspond to extremely large indexes, extremely small indexes and intermediate indexes. The ultra-large index is an index with a larger value, the ultra-small index is an index with a smaller value, and the intermediate index is an index with a value in a certain fixed interval.
Common fuzzy distributions and graphs corresponding to the three types of indexes include rectangular distribution or semi-rectangular distribution, trapezoidal distribution or semi-trapezoidal distribution, gaussian distribution or semi-gaussian distribution, cauchy distribution or semi-cauchy distribution and the like, and the fuzzy distribution of trapezoidal distribution or semi-trapezoidal distribution is selected in this chapter, and a specific graph is shown in fig. 3. In the figure, aiFor the index factor to be investigated, SiDenotes aiIn [0, 1 ]]In (b) is aiDegree of membership to a certain decision comment.
Membership functions based on trapezoidal distribution or semi-trapezoidal distribution are respectively defined as:
A. very large scale index
Such indexes are mainly benefit type indexes, and the larger the index value is, the better the evaluation result of a certain aspect of the evaluated object is. The membership function can be obtained by the following formula:
Figure BDA0003453114740000151
B. very small index
Such an index is mainly a cost-based index, and a smaller index value indicates a better evaluation result in a certain aspect of an object to be evaluated. The membership function can be obtained by the following formula:
Figure BDA0003453114740000152
C. intermediate type index
The indexes are also called interval type indexes, the optimal value of the indexes is in a certain fixed interval, and the membership function can be obtained by the following formula:
Figure BDA0003453114740000161
when determining the membership degree of the quantitative index, firstly, judging which model is adopted according to the property of the index, and then determining the specific value of each parameter in the membership function according to the specific numerical value of the quantitative index. Because the dimensions, values and the like of different indexes have obvious differences, the specific values of all parameters in the quantitative index membership function have no unified standard and need to be determined by combining the actual conditions of all the indexes.
Analysis and calculation are carried out on the distribution of each index in each demonstration area through the pyhon software to obtain each index quantile, and further a scoring function of a high-reliability wiring mode index system of the medium-voltage distribution network is obtained and calculated as shown in the following table 5.
TABLE 5 Scoring standards for respective indices of respective demonstration areas
Figure BDA0003453114740000162
Fifth, example application
And selecting a high-reliability typical area of a developed city for comprehensive evaluation and verification. The design of 4 transformation schemes of wiring modes is respectively a single-ring net structure a, a double-ring net structure b, a petal-shaped structure c and a three-way co-supply structure d containing a flexible direct-closing ring.
And building a reliability calculation model in the DIgsilent according to the current engineering situation data. The operation time of tripping off and isolating the fault line according to the interconnection switches on two sides of the fault line is considered according to 30min, and the operation time of switching on and switching off the ring network switch at the line breaking point is considered according to 1 h; calculating the economic index by combining the data of collecting capital and the economic index calculation formula; calculating the technical index of the index system by BPA calculation software; and (4) scoring the adaptive indexes according to expert evaluation, and calculating the index scores by combining a qualitative index evaluation mode. The specific index calculation results are shown in table 6 below.
TABLE 6 various index values of developed cities under different medium-voltage distribution network wiring modes
Figure BDA0003453114740000171
Combining the weights of the indexes and the scoring criteria, the scores are calculated as shown in table 7 below:
TABLE 7 comprehensive evaluation table for different medium-voltage distribution network wiring modes in a developed city
Layer of criteria Single ring net structure Double-ring net structure Petal type structure Three-way co-supply structure containing flexible direct-closing loop
Reliability of 68.79 87.01 89.71 83.65
Economy of use 79.54 85.43 75.22 78.82
Technical characteristics 82.1 80.1 75.43 74.1
Adaptability 74.86205 73.8572 83.25855 89.14765
Composite score 75.77 81.72 81.57 81.82
According to the comprehensive evaluation result, the comprehensive scores of the cable double-ring network, the petal-shaped wiring mode and the three-way same supply wiring mode with the flexible direct-closing ring are similar, and compared with the cable single-ring network, the cable double-ring network has the advantages of being outstanding in reliability and adaptability. Although the three-way same-supply wiring mode containing the flexible direct closing ring has the defects of high investment, operation and maintenance cost, immature equipment, high failure rate and the like, and has no obvious advantages in the aspects of economy and technology, the flexible direct closing ring technology has more beneficial and more beneficial effects on the reliability of the system than disadvantages, and has relatively high adaptability score for urban development, so that the comprehensive score is slightly higher, the evaluation result conforms to the actual situation of regional high-reliability transformation engineering, and the feasibility and the effectiveness of an evaluation system are verified.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (10)

1. The comprehensive assessment method for the wiring mode of the urban high-reliability medium-voltage distribution network is characterized by comprising the following steps:
s1: constructing a comprehensive evaluation index system of a high-reliability wiring mode of the medium-voltage distribution network;
s2: determining the weight of each evaluation factor by adopting a decision experiment and evaluation experiment DEMATEL-network analysis method ANP-entropy-resisting weight method and an improved grey correlation degree method;
s3: and constructing an index scoring function by using a polynomial difference method and calculating to obtain a comprehensive scoring result.
2. The urban high-reliability medium-voltage distribution network wiring mode comprehensive evaluation method according to claim 1, wherein in the step S1, a comprehensive evaluation index system of the high-reliability wiring mode of the medium-voltage distribution network is constructed according to 4 criteria of reliability, economy, technology and adaptability;
(1) reliability index
The power distribution network power supply reliability index is a basis for measuring the power distribution network reliability level, the index not only needs to objectively reflect the overall power supply reliability level of the system, but also needs to be beneficial to finding out weak links existing in the power distribution network so as to take corresponding enhancement measures, including average power supply availability ASAI, system average power failure frequency SAIFI and system average power failure duration SAIDI 3 indexes;
(2) index of economic efficiency
The economic indexes mainly reflect the economic characteristics of different medium-voltage wiring modes, and comprise 2 indexes of annual investment cost and annual power failure loss of unit load;
(3) technical index
The technical indexes mainly reflect the technical characteristics of a medium-voltage wiring mode, and comprise 2 indexes of voltage deviation and line loss rate;
(4) adaptive index
The adaptability indexes mainly reflect the adaptability degree of the medium-voltage wiring mode to the future development of the power grid in the planning area, and comprise 3 indexes of operation difficulty degree, grid frame expansibility and new load access difficulty degree.
3. The comprehensive evaluation method for the wiring mode of the urban high-reliability medium-voltage distribution network according to claim 2, wherein the step S2 specifically comprises: a) selecting an evaluation method; b) determining each criterion weight; c) determining index weight of each layer; d) and calculating the comprehensive weight.
4. The comprehensive urban high-reliability medium-voltage distribution network connection mode evaluation method according to claim 3, wherein the step S3 specifically comprises: 1) determining a scoring standard; 2) establishing a scoring function of each index; 3) calculating index scores of all levels; 4) and calculating a comprehensive score.
5. The comprehensive urban high-reliability medium-voltage distribution network wiring mode evaluation method according to claim 5, wherein the step S2 is implemented by adopting a DEMATEL method to screen main elements of a complex system and simplify a system structure analysis process; meanwhile, the network analysis method ANP method can fully consider the mutual influence and domination relation among elements, thereby solving the problem of actual decision; determining subjective weights of 4 criteria by using a DEMATEL-based network analysis method;
assuming that the network layer of the ANP has n criteria, which are respectively represented by C1, C2,. cndot.,. Cn, dependence relationships exist among the criteria, and yji represents the importance degree of the criteria Cj (j ≠ i) to Ci; sequentially taking Ci (i-1, 2, n) as a criterion, and comparing Ci with other index values except the index values per se pairwise to obtain a corresponding weight matrix; according to the characteristic root method, the weight vector under the criterion of Ci is obtained
Figure FDA0003453114730000021
Figure FDA0003453114730000022
The weight matrix is:
Figure FDA0003453114730000023
under each criterion layer, the criterion has no influence relationship on the criterion layer, namely, the diagonal element of the matrix is 0, and a direct influence matrix is obtained, namely:
Figure FDA0003453114730000024
for direct influence matrix WdAnd solving a comprehensive influence matrix W of the limit, namely:
Figure FDA0003453114730000025
each row of elements of the matrix tends to a certain stable value, and finally, the non-zero stable value of each row is the subjective weight value of each corresponding element, so that the subjective weight set is as follows:
Ws=(Wsi|1≤i≤n) (4)。
6. the comprehensive assessment method for wiring patterns of urban high-reliability medium-voltage distribution networks according to claim 5, wherein in step S2, the entropy weight method:
the inverse entropy is defined as:
Figure FDA0003453114730000031
in the formula: p is a radical ofjFor the probability of occurrence of each state, 1. ltoreq. pjN is less than or equal to n
Figure FDA0003453114730000032
The characteristics of the entropy values are different, namely the difference of indexes is in direct proportion to the entropy values and the weight coefficients;
the steps of determining the index weight by the entropy weight method are as follows: assuming that there are m evaluation objects, n evaluation indexes, and an index evaluation matrix X ═ Xij) n x m, wherein xij(i-1, 2, n, j-1, 2, m) is an index value; determining the inverse entropy of each index as:
Figure FDA0003453114730000033
in the formula
Figure FDA0003453114730000034
H is obtained from the formula (6)iPerforming weight normalization to obtain objective weight woiNamely:
Figure FDA0003453114730000035
the set of objective weights is then:
Wo=(Woi|1≤i≤n) (8)。
7. the comprehensive evaluation method for the wiring mode of the urban high-reliability medium-voltage distribution network according to claim 6, wherein in the step S2, DEMATEL-ANP-inverse entropy weight method is used for combining weights:
the relative importance degree of the subjective and objective weights is different according to different criteria; let the relative importance of the subjective weight and the objective weight be expressed as alphaiAnd betaiFinally, combining the basic thought of the matrix estimation theory, the important coefficient alpha of the subjective and objective weights of each criterion is calculatediAnd betaiNamely:
Figure FDA0003453114730000036
and finally, calculating the combination weight by using the obtained subjective weight set, objective weight set and relative importance coefficients of the subjective weight and the objective weight, namely:
Figure FDA0003453114730000037
8. the comprehensive assessment method for wiring modes of urban high-reliability medium-voltage distribution networks according to claim 7, wherein in step S2, the weights of the indicators in the index layer are solved according to an improved gray correlation method, and multiplied by the weight values of the indicators in the criterion layer, so as to obtain the weight values of the indicators in the high-reliability wiring modes of the medium-voltage distribution networks; the calculation steps are as follows:
determining an initial weight value; m experts are provided to make experience judgment on the n evaluation index weights of the determined target, and the judgment data is formed as follows:
Figure FDA0003453114730000041
determining a reference sequence; selecting the maximum weight value from each column of X as a reference weight value, wherein the reference data column is as follows:
X0=[x01,x02,…,x0n] (12)
find each index sequence x1,x2,…,xnWith reference data x0The distance between, i.e.:
Figure FDA0003453114730000042
solving the weight of each index, namely:
Figure FDA0003453114730000043
fourthly, solving the normalized weight of each index, namely:
according to
Figure FDA0003453114730000044
Will be provided with
Figure FDA0003453114730000045
Normalization processing can obtain an index weight vector, where ω is (ω)1,ω2,...,ωm)T
9. The comprehensive assessment method for the wiring mode of the urban high-reliability medium-voltage distribution network according to claim 8, wherein in the step S3, a percentage system is adopted, and a fuzzy membership method is combined to give a score standard of each index of the high-reliability wiring mode of the medium-voltage distribution network; in the 4 criteria, reliability, economy and technical indexes are all quantitative calculable indexes; the adaptability index is difficult to quantitatively calculate, needs qualitative treatment and can be evaluated by a fuzzy statistical method.
10. The comprehensive assessment method for the wiring mode of the urban high-reliability medium-voltage distribution network according to claim 9, wherein in the step S3, each index distribution is analyzed and calculated through a pyhon software to obtain each index quantile point, and further obtain a scoring function of the high-reliability wiring mode index system of the medium-voltage distribution network.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115175274A (en) * 2022-07-13 2022-10-11 国网山西省电力公司信息通信分公司 Intelligent power distribution-oriented 5G heterogeneous wireless network access selection method

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115175274A (en) * 2022-07-13 2022-10-11 国网山西省电力公司信息通信分公司 Intelligent power distribution-oriented 5G heterogeneous wireless network access selection method

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