CN104036433A - Method for evaluating running management level of power distribution network - Google Patents

Method for evaluating running management level of power distribution network Download PDF

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CN104036433A
CN104036433A CN201410286980.6A CN201410286980A CN104036433A CN 104036433 A CN104036433 A CN 104036433A CN 201410286980 A CN201410286980 A CN 201410286980A CN 104036433 A CN104036433 A CN 104036433A
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China
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mrow
msubsup
distribution network
msub
power distribution
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林弘宇
王伟
张景超
马建伟
陈上吉
孙芊
王磊
李珊珊
韩菲
雷显荣
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Tianjin University
State Grid Corp of China SGCC
State Grid Henan Electric Power Co Ltd
Electric Power Research Institute of State Grid Henan Electric Power Co Ltd
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Tianjin University
State Grid Corp of China SGCC
State Grid Henan Electric Power Co Ltd
Electric Power Research Institute of State Grid Henan Electric Power Co Ltd
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Publication of CN104036433A publication Critical patent/CN104036433A/en
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Abstract

The invention discloses a method for evaluating the running management level of a power distribution network. The method comprises the following steps of: A, analysing factors influencing power distribution network effect indexes and the like, and determining the index with the maximum influence on the power supply reliability of the power distribution network; B, determining a calculation formula for each index in the step A; C, evaluating each index weight of the index system in the step A through mathematical calculation by virtue of a triangular fuzzy analytic hierarchy method; D, obtaining each index weight by virtue of the resolution in the step C. According to the method, by scientifically and accurately evaluating the running management level of the power distribution network, establishment for the comprehensive index system of the power distribution network is enriched, and the safe and stable running of the power distribution network in China is promoted.

Description

Power distribution network operation management level evaluation method
Technical Field
The invention relates to the field of power distribution systems, in particular to a method for evaluating the operation management level of a power distribution network.
Background
In recent years, the research and construction of smart grids has risen globally. Around the strategic target of 'strong intelligent power grid construction' proposed by the national power grid company, a large amount of intelligent power grid test point engineering construction is developed in various parts of China, wherein mature test point projects comprise an intelligent substation, power distribution automation, a power utilization information acquisition system and the like.
As an important component of a power grid, the intellectualization of a power distribution network becomes a new trend of future power grid development, and plays a significant role in realizing the overall goal of smart power grid construction. Therefore, the evaluation on the intelligent power distribution network is very significant. At present, no scientific method for evaluating the operation management level of the power distribution network exists.
Disclosure of Invention
The invention aims to provide a method for evaluating the operation management level of a power distribution network, which can scientifically and accurately evaluate the operation management level of the power distribution network, enrich the establishment of a comprehensive index system of the power distribution network and be beneficial to the safe and stable operation of the power distribution network in China.
The invention adopts the following technical scheme:
a power distribution network operation management level evaluation method comprises the following steps:
a: analyzing factors influencing the effect indexes of the power distribution network, determining the effect indexes related to the operation management level as the power distribution network power supply reliability, and determining the index with the maximum influence of the operation management level of the power distribution network on the power distribution network power supply reliability;
the indexes of the operation management level, which have the greatest influence on the power supply reliability of the power distribution network, are the data integrity of the power distribution network of the PMS, the major defect elimination rate, the temporary power failure proportion, the live working rate and the power failure operation time-based power restoration rate;
b: respectively determining a calculation formula of each index in the step A;
the distribution network data integrity of the PMS system refers to the proportion of distribution network equipment in the production information management system to the total number of all distribution network equipment in the regional operation and maintenance range, and the calculation formula of the distribution network data integrity of the PMS system is
In the above formula, the pole-mounted switch equipment comprises a circuit breaker, a load switch, an isolating switch and a fuse, the number of the distribution network overhead line, the cable line, the pole-mounted transformer, the pole-mounted switch equipment, the switch station, the box transformer and the ring main unit is 0.15, 0.15 and 0.1 respectively;
the major defect elimination rate refers to the proportion of successful major defect item number in time, namely the proportion of the major defect number in the total major defects in the same time period in time, and is used for reflecting the capability of eliminating serious hidden dangers, and the calculation formula of the major defect elimination rate is
The temporary power failure proportion is the proportion of the temporary power failure time to the total power failure time, the temporary power failure proportion is the proportion of the temporary power failure time in one year to the total power failure time in one year and is used for reflecting the rationality of the maintenance plan formulation, and the calculation formula of the temporary power failure proportion is
The hot-line work rate is a ratio of hot-line work items in the year to all the implemented items, and reflects a range of hot-line work development. The live working refers to various operations performed on a live power device or in proximity to a live part, particularly any part of a worker's body or all operations performed using a tool, a device or an instrument to enter a defined live working area, and includes the following items: firstly, pole cutters, lightning arresters, sectional and linear cross arms and fuse sets are exchanged in an electrified way; secondly, standing and adjusting the pole in an electrified way; thirdly, removing and building the pile head and the cable tail wire on the fuse wire in an electrified way; fourthly, loading switch blades are additionally arranged on the loaded sections in a segmented mode; charged water washing;
the calculation formula of the live working rate is
The power failure operation is the time-based power recovery rate, which means that the proportion of the power supply times to the total power failure operation times can be timely recovered in a specified time in the power failure operation so as to reflect the efficiency of the power failure operation. The calculation formula of the power failure operation power recovery rate according to time is
C: and (3) respectively calculating each index weight of the index system in the step A through mathematical calculation by utilizing a triangular fuzzy analytic hierarchy process, wherein the weight calculation by utilizing the triangular fuzzy analytic hierarchy process comprises the following implementation steps:
c1: firstly, establishing a hierarchical structure;
establishing a hierarchical structure according to different decision factor importance, determining a final target as a highest layer, wherein each influence factor, then an influence sub-factor layer and finally a lowest layer formed by various schemes are arranged below the highest layer;
c2: constructing a triangular fuzzy judgment matrix;
for a certain factor of the k-1 th layer, all n's are present for the k-th layer associated therewithkWhen the factors are compared pairwise, a triangular fuzzy number is adopted for quantitative representation, namely a fuzzy judgment matrixElement alpha in (1)ij=(lij,mij,uij) Is one in mijA closed interval of median, wherein i and j are the ith and jth factors of the k layer, lij、UijIs sequentially aijLower and upper limits of the values. m isijThe value of (A) is an integer of 1-9 adopted in the comparison and judgment of the traditional AHP method, and the meaning is as follows:
scale value Significance of scale
1 The former being as important as the latter
3 The former being slightly more important than the latter
5 The former being of considerable importance over the latter
7 The former being more important than the latter
9 The former being of extreme importance than the latter
2、4、6、8 Intermediate value representing the above-mentioned adjacent judgment
C3: calculating a comprehensive fuzzy degree value;
according to the formula:obtaining a comprehensive triangular fuzzy number judgment matrix of the k layer, wherein, <math> <mrow> <msubsup> <mi>&alpha;</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>=</mo> <mrow> <mo>(</mo> <msubsup> <mi>l</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>,</mo> <msubsup> <mi>m</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>,</mo> <msubsup> <mi>u</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> <mi>t</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>T</mi> <mo>,</mo> </mrow> </math> representing the fuzzy number given by the ith expert to the ith factor and the jth factor of the kth layer;is that(T ═ 1,2, …, T) average;
then according to the formula: <math> <mrow> <msubsup> <mi>S</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msubsup> <mi>M</mi> <mi>ij</mi> <mi>k</mi> </msubsup> <mo>&CircleTimes;</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>n</mi> <mi>k</mi> </msub> </munderover> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>n</mi> <mi>k</mi> </msub> </munderover> <msubsup> <mi>M</mi> <mi>ij</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> </mrow> </math> the value of the comprehensive degree of ambiguity is obtained,the integrated fuzzy degree value of the ith element of the kth layer;
c4: calculating hierarchical weights
First using the formulaThe calculation is carried out in such a way that,
to obtain <math> <mrow> <mi>V</mi> <mrow> <mo>(</mo> <msubsup> <mi>S</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>S</mi> <mi>j</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>&NotEqual;</mo> <mi>j</mi> <mo>;</mo> </mrow> </math> Wherein V representsDegree of likelihood;
<math> <mrow> <msubsup> <mi>P</mi> <mi>ih</mi> <mi>k</mi> </msubsup> <mrow> <mo>(</mo> <msubsup> <mi>A</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mo>=</mo> <mi>min</mi> <mi>V</mi> <mrow> <mo>(</mo> <msubsup> <mi>S</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>S</mi> <mi>j</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>&NotEqual;</mo> <mi>j</mi> <mo>;</mo> </mrow> </math> wherein,representing the weight of each factor at the k-th layer to the h-th factor at the k-1 layer,representing the ith factor on the kth layer;
then toNormalization is performed, and the weight of the kth layer to the h factor of the k-1 layer can be obtained, namely:
P h = ( P 1 h k , P 2 h k , . . . , P nh k ) T ;
c5: composite total weight
After the weights of the respective layers are found, the ranking weight vector of the k-1 layer to the total target is known as:
then the composite ordering W of the global elements on the k-th layer to the overall targetkComprises the following steps:
<math> <mrow> <msup> <mi>W</mi> <mi>k</mi> </msup> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>n</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> </munderover> <msubsup> <mi>P</mi> <mi>ij</mi> <mi>k</mi> </msubsup> <msubsup> <mi>W</mi> <mi>j</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> </mrow> </math> wherein WkIs the total weight;
d: and D, respectively obtaining the weight of each index through the solution in the step C, wherein the weight is shown in the following table:
e: and evaluating the operation management level of the power distribution network, wherein the specific steps of evaluating the operation management level of the power distribution network are as follows:
e1: looking up an industry standard, converting the marked value into a percentile system value according to the marked value of the power distribution network in an ideal state, and making a scoring standard;
e2: b, respectively calculating corresponding index numerical values according to each index calculation formula in the step B by collecting original data of the power distribution network to be evaluated;
e3: according to the index values calculated in the step E2, various indexes of the operation management level of the power distribution network are evaluated by referring to the scoring standard formulated in the step 1; and D, obtaining a weighted value of the operation management level by using the index weights obtained in the step D and combining the index numerical value calculated in the step E2, namely evaluating the operation management level of the power distribution network.
The invention selects the effect index associated with the operation management level by analyzing the factors influencing the effect index of the power distribution network: the power supply reliability of the power distribution network is analyzed, and the relation between the power supply reliability and the power grid operation management level is analyzed, so that a specific characteristic index system for evaluating the power distribution network operation management level is established; then, respectively calculating the weight of each index of the index system through mathematical calculation by utilizing a triangular fuzzy analytic hierarchy process, and finally evaluating each index of the operation management level of the power distribution network through each index numerical value obtained through calculation and looking up the established scoring standard; and evaluating the operation management level of the power distribution network by combining each index weight. The invention scientifically and accurately evaluates the operation management level of the power distribution network, enriches the establishment of a comprehensive index system of the power distribution network and is beneficial to the safe and stable operation of the power distribution network in China.
Drawings
FIG. 1 is a schematic flow chart of the present invention.
Detailed Description
As shown in fig. 1, the method for evaluating the operation management level of the power distribution network according to the present invention includes the following steps:
a: analyzing the factors influencing the effect indexes of the power distribution network, determining the effect indexes associated with the operation management level as the power distribution network power supply reliability, and determining the indexes with the maximum influence of the operation management level of the power distribution network on the power distribution network power supply reliability:
the influence of the operation management level of the power distribution network on the power supply reliability of the power distribution network is as follows:
if the operation management level of the power distribution network is high, firstly, the hidden trouble of equipment can be reduced, and the frequency of fault occurrence is reduced; secondly, the fault can be repaired in time, and the power failure time is reduced; thirdly, the power failure frequency caused by live working can be reduced, and power supply can be timely recovered according to the specified time during power failure operation.
Therefore, the indexes of the PMS system which have the greatest influence on the power supply reliability of the power distribution network include the distribution network data integrity, the major defect elimination rate, the temporary power failure proportion, the live working rate and the power failure operation time-based power restoration rate, and are shown in table 1:
TABLE 1
B: respectively determining a calculation formula of each index in the step A, wherein the statistical time span of all the indexes is one year;
the distribution network data integrity of the PMS system refers to the proportion of distribution network equipment in the production information management system to the total number of all distribution network equipment in the regional operation and maintenance range, and the calculation formula of the distribution network data integrity of the PMS system is
In the above formula, the pole-mounted switch equipment comprises a circuit breaker, a load switch, an isolating switch and a fuse, the number of the distribution network overhead line, the cable line, the pole-mounted transformer, the pole-mounted switch equipment, the switch station, the box transformer and the ring main unit is 0.15, 0.15 and 0.1 respectively;
the major defect elimination rate refers to the proportion of successful major defect item number in time, namely the proportion of the major defect number in the total major defects in the same time period in time, and is used for reflecting the capability of eliminating serious hidden dangers, and the calculation formula of the major defect elimination rate is
The temporary power failure proportion is the proportion of the temporary power failure time to the total power failure time, the temporary power failure proportion is the proportion of the temporary power failure time in one year to the total power failure time in one year and is used for reflecting the rationality of the maintenance plan formulation, and the calculation formula of the temporary power failure proportion is
The hot-line work rate is a ratio of hot-line work items in the year to all the implemented items, and reflects a range of hot-line work development. The live working refers to various operations performed on a live power device or in proximity to a live part, particularly any part of a worker's body or all operations performed using a tool, a device or an instrument to enter a defined live working area, and includes the following items: firstly, pole cutters, lightning arresters, sectional and linear cross arms and fuse sets are exchanged in an electrified way; secondly, standing and adjusting the pole in an electrified way; thirdly, removing and building the pile head and the cable tail wire on the fuse wire in an electrified way; fourthly, loading switch blades are additionally arranged on the loaded sections in a segmented mode; charged water washing;
the calculation formula of the live working rate is
The power failure operation is the time-based power recovery rate, which means that the proportion of the power supply times to the total power failure operation times can be timely recovered in a specified time in the power failure operation so as to reflect the efficiency of the power failure operation. The calculation formula of the power failure operation power recovery rate according to time is
C: the weights of all indexes of the index system in the step A are respectively obtained through mathematical calculation by utilizing a triangular fuzzy analytic hierarchy process, the triangular fuzzy analytic hierarchy process belongs to the prior art in the field, and details are not repeated here, and the implementation steps of obtaining the weights by the triangular fuzzy analytic hierarchy process are explained below:
c1: firstly, establishing a hierarchical structure; and establishing a hierarchical structure according to different decision factor importance, determining the final target as a highest layer, wherein each influence factor, then an influence sub-factor layer and finally a lowest layer formed by various schemes are arranged below the highest layer.
C2: constructing a triangular fuzzy judgment matrix;
for a certain factor of the k-1 th layer, all n's are present for the k-th layer associated therewithkWhen the factors are compared pairwise, a triangular fuzzy number is adopted for quantitative representation, namely a fuzzy judgment matrixElement alpha in (1)ij=(lij,mij,uij) Is one in mijA closed interval of median, wherein i and j are the ith and jth factors of the k layer, lij、UijIs sequentially aijLower and upper limits of the values. m isijThe value of (A) is an integer of 1-9 adopted in the comparison and judgment of the traditional AHP method, and the meaning is shown in a table 2:
scale value Significance of scale
1 The former being as important as the latter
3 The former being slightly more important than the latter
5 The former being of considerable importance over the latter
7 The former being more important than the latter
9 The former being of extreme importance than the latter
2、4、6、8 Intermediate value representing the above-mentioned adjacent judgment
TABLE 2 Scale of comparative decision matrices
C3: calculating a comprehensive fuzzy degree value;
according to the formula:
<math> <mrow> <msubsup> <mi>M</mi> <mi>ij</mi> <mi>k</mi> </msubsup> <mo>=</mo> <mfrac> <mn>1</mn> <mi>T</mi> </mfrac> <mrow> <mo>(</mo> <msubsup> <mi>&alpha;</mi> <mi>ij</mi> <mn>1</mn> </msubsup> <mo>&CirclePlus;</mo> <msubsup> <mi>&alpha;</mi> <mi>ij</mi> <mn>2</mn> </msubsup> <mo>&CirclePlus;</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>&CirclePlus;</mo> <msubsup> <mi>&alpha;</mi> <mi>ij</mi> <mi>T</mi> </msubsup> <mo>)</mo> </mrow> </mrow> </math>
obtaining a comprehensive triangular fuzzy number judgment matrix of the k layer, wherein, <math> <mrow> <msubsup> <mi>&alpha;</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>=</mo> <mrow> <mo>(</mo> <msubsup> <mi>l</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>,</mo> <msubsup> <mi>m</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>,</mo> <msubsup> <mi>u</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> <mi>t</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>T</mi> <mo>,</mo> </mrow> </math> representing the fuzzy number given by the ith expert to the ith factor and the jth factor of the kth layer;is that(T is 1,2, …, T).
Then according to the formula:
<math> <mrow> <msubsup> <mi>S</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msubsup> <mi>M</mi> <mi>ij</mi> <mi>k</mi> </msubsup> <mo>&CircleTimes;</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>n</mi> <mi>k</mi> </msub> </munderover> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>n</mi> <mi>k</mi> </msub> </munderover> <msubsup> <mi>M</mi> <mi>ij</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> </mrow> </math>
the value of the comprehensive degree of ambiguity is obtained,is the integrated ambiguity value of the ith element of the kth layer.
C4: calculating hierarchical weights
First using the formulaThe calculation is carried out in such a way that,
to obtain <math> <mrow> <mi>V</mi> <mrow> <mo>(</mo> <msubsup> <mi>S</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>S</mi> <mi>j</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>&NotEqual;</mo> <mi>j</mi> <mo>;</mo> </mrow> </math>
Wherein V representsDegree of likelihood.
<math> <mrow> <msubsup> <mi>P</mi> <mi>ih</mi> <mi>k</mi> </msubsup> <mrow> <mo>(</mo> <msubsup> <mi>A</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mo>=</mo> <mi>min</mi> <mi>V</mi> <mrow> <mo>(</mo> <msubsup> <mi>S</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>S</mi> <mi>j</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>&NotEqual;</mo> <mi>j</mi> <mo>;</mo> </mrow> </math>
Wherein,representing the weight of each factor at the k-th layer to the h-th factor at the k-1 layer,indicating the ith factor on the kth layer.
Then toNormalization is performed, and the weight of the kth layer to the h factor of the k-1 layer can be obtained, namely:
P h = ( P 1 h k , P 2 h k , . . . , P nh k ) T ;
c5: composite total weight
After the weights of the respective layers are found, the ranking weight vector of the k-1 layer to the total target is known as:
then the composite ordering W of the global elements on the k-th layer to the overall targetkComprises the following steps:
<math> <mrow> <msup> <mi>W</mi> <mi>k</mi> </msup> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>n</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> </munderover> <msubsup> <mi>P</mi> <mi>ij</mi> <mi>k</mi> </msubsup> <msubsup> <mi>W</mi> <mi>j</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>10</mn> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </math> wherein WkIs the total weight;
d: through the solution in the step C, the weights of all indexes are respectively obtained, and the weights are shown in a table 3;
TABLE 3
E: evaluating the operation management level of the power distribution network; the specific steps of the evaluation of the operation management level of the power distribution network are as follows:
e1: looking up an industry standard, converting the index marking value into a percentile system value according to the index marking value in the ideal state of the power distribution network, and making a scoring standard;
the scoring standard is a standardized format which can be directly compared and is obtained by converting various original data through a certain scale system; the scoring scale can be in percent, ten and five points. In this embodiment, a percentile system is used, and a higher score indicates better performance.
The index scoring standard is set up with the types and ideal values of main reference indexes, the index types are divided into positive indexes, negative indexes and intermediate value indexes, the positive indexes mean that the higher the value of the index is, the better the negative index is, the lower the value is, and the intermediate value indexes mean that a certain value or interval with the value in the middle is the best.
In the process of evaluating the power distribution network, a reasonable range of index values needs to be determined. When a certain parameter is within the reasonable range, the parameter of the power grid or the system operation state represented by the parameter basically meets the requirement from the aspect; otherwise, it is not. The reasonable range of the index is the ideal value of the index.
By searching for relevant industry standards of the power distribution network, the index type and ideal value of the operation management level evaluation system (shown in table 4) and the scoring standard of the operation management level evaluation system (shown in table 5) are worked out:
index type and ideal value of operation management level evaluation system
TABLE 4
Scoring standard for running management level evaluation system
TABLE 5
E2: b, respectively calculating corresponding index numerical values according to each index calculation formula in the step B by collecting original data of the power distribution network to be evaluated;
e3: according to the index values calculated in the step E2, various indexes of the operation management level of the power distribution network are evaluated by referring to the scoring standard formulated in the step 1; and D, obtaining a weighted value of the operation management level by using the index weights obtained in the step D and combining the index numerical value calculated in the step E2, namely evaluating the operation management level of the power distribution network.
For example, the method is used for evaluating the operation management level of a certain distribution network, and the raw data and the calculation result are shown in table 6. And (3) calculating to obtain the distribution network data integrity index value of the PMS system to be 89.45% (233552/261094), wherein the score can be found to be 69.80 by looking up the score standard, and the PMS system data integrity of the distribution network is better and the score is higher. Meanwhile, the scores of the indexes are multiplied by the respective weight values, and then the scores are summed to obtain the score 67.71(69.80 × 0.20+100 × 0.25+32.61 × 0.15+23.09 × 0.20+96.18 × 0.20) of the operation management level of the power distribution network, wherein the evaluation score belongs to a qualified level, which indicates that the operation management level of the power distribution network is good, and the sub-indexes with larger influences are the temporary power failure proportion and the hot-line operation rate and need to be greatly improved.
TABLE 6 evaluation of management level of operation

Claims (1)

1. A power distribution network operation management level evaluation method is characterized by comprising the following steps:
a: analyzing factors influencing the effect indexes of the power distribution network, determining the effect indexes related to the operation management level as the power distribution network power supply reliability, and determining the index with the maximum influence of the operation management level of the power distribution network on the power distribution network power supply reliability;
the indexes of the operation management level, which have the greatest influence on the power supply reliability of the power distribution network, are the data integrity of the power distribution network of the PMS, the major defect elimination rate, the temporary power failure proportion, the live working rate and the power failure operation time-based power restoration rate;
b: respectively determining a calculation formula of each index in the step A;
the distribution network data integrity of the PMS system refers to the proportion of distribution network equipment in the production information management system to the total number of all distribution network equipment in the regional operation and maintenance range, and the calculation formula of the distribution network data integrity of the PMS system is
In the above formula, the pole-mounted switch equipment comprises a circuit breaker, a load switch, an isolating switch and a fuse, the number of the distribution network overhead line, the cable line, the pole-mounted transformer, the pole-mounted switch equipment, the switch station, the box transformer and the ring main unit is 0.15, 0.15 and 0.1 respectively;
the major defect elimination rate refers to the proportion of successful major defect item number in time, namely the proportion of the major defect number in the total major defects in the same time period in time, and is used for reflecting the capability of eliminating serious hidden dangers, and the calculation formula of the major defect elimination rate is
The temporary power failure proportion is the proportion of the temporary power failure time to the total power failure time, the temporary power failure proportion is the proportion of the temporary power failure time in one year to the total power failure time in one year and is used for reflecting the rationality of the maintenance plan formulation, and the calculation formula of the temporary power failure proportion is
The hot-line work rate is a ratio of hot-line work items in the year to all the implemented items, and reflects a range of hot-line work development. The live working refers to various operations performed on a live power device or in proximity to a live part, particularly any part of a worker's body or all operations performed using a tool, a device or an instrument to enter a defined live working area, and includes the following items: firstly, pole cutters, lightning arresters, sectional and linear cross arms and fuse sets are exchanged in an electrified way; secondly, standing and adjusting the pole in an electrified way; thirdly, removing and building the pile head and the cable tail wire on the fuse wire in an electrified way; fourthly, loading switch blades are additionally arranged on the loaded sections in a segmented mode; charged water washing;
the calculation formula of the live working rate is
The power failure operation is the time-based power recovery rate, which means that the proportion of the power supply times to the total power failure operation times can be timely recovered in a specified time in the power failure operation so as to reflect the efficiency of the power failure operation. The calculation formula of the power failure operation power recovery rate according to time is
C: and (3) respectively calculating each index weight of the index system in the step A through mathematical calculation by utilizing a triangular fuzzy analytic hierarchy process, wherein the weight calculation by utilizing the triangular fuzzy analytic hierarchy process comprises the following implementation steps:
c1: firstly, establishing a hierarchical structure;
establishing a hierarchical structure according to different decision factor importance, determining a final target as a highest layer, wherein each influence factor, then an influence sub-factor layer and finally a lowest layer formed by various schemes are arranged below the highest layer;
c2: constructing a triangular fuzzy judgment matrix;
for a certain factor of the k-1 layer, when all the nk factors of the k layer related to the certain factor are compared pairwise, a triangular fuzzy number is adopted for quantitative representation, namely a fuzzy judgment matrixElement alpha in (1)ij=(lij,mij,uij) Is one in mijA closed interval of median, wherein i and j are the ith and jth factors of the k layer, lij、UijIs sequentially aijLower and upper limits of the values. m isijThe value of (A) is an integer of 1-9 adopted in the comparison and judgment of the traditional AHP method, and the meaning is as follows:
scale value Significance of scale 1 The former being as important as the latter 3 The former being slightly more important than the latter 5 The former being of considerable importance over the latter
7 The former being more important than the latter 9 The former being compared with the latterOf extreme importance 2、4、6、8 Intermediate value representing the above-mentioned adjacent judgment
C3: calculating a comprehensive fuzzy degree value;
according to the formula:obtaining a comprehensive triangular fuzzy number judgment matrix of the k layer, wherein, <math> <mrow> <msubsup> <mi>&alpha;</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>=</mo> <mrow> <mo>(</mo> <msubsup> <mi>l</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>,</mo> <msubsup> <mi>m</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>,</mo> <msubsup> <mi>u</mi> <mi>ij</mi> <mi>t</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> <mi>t</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>T</mi> <mo>,</mo> </mrow> </math> representing the fuzzy number given by the ith expert to the ith factor and the jth factor of the kth layer;is that(T ═ 1,2, …, T) average;
then according to the formula: <math> <mrow> <msubsup> <mi>S</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msubsup> <mi>M</mi> <mi>ij</mi> <mi>k</mi> </msubsup> <mo>&CircleTimes;</mo> <msup> <mrow> <mo>(</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>n</mi> <mi>k</mi> </msub> </munderover> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>n</mi> <mi>k</mi> </msub> </munderover> <msubsup> <mi>M</mi> <mi>ij</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> </mrow> </math> the value of the comprehensive degree of ambiguity is obtained,the integrated fuzzy degree value of the ith element of the kth layer;
c4: calculating hierarchical weights
First using the formulaThe calculation is carried out in such a way that,
to obtain <math> <mrow> <mi>V</mi> <mrow> <mo>(</mo> <msubsup> <mi>S</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>S</mi> <mi>j</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>&NotEqual;</mo> <mi>j</mi> <mo>;</mo> </mrow> </math> Wherein V representsDegree of likelihood;
<math> <mrow> <msubsup> <mi>P</mi> <mi>ih</mi> <mi>k</mi> </msubsup> <mrow> <mo>(</mo> <msubsup> <mi>A</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mo>=</mo> <mi>min</mi> <mi>V</mi> <mrow> <mo>(</mo> <msubsup> <mi>S</mi> <mi>i</mi> <mi>k</mi> </msubsup> <mo>&GreaterEqual;</mo> <msubsup> <mi>S</mi> <mi>j</mi> <mi>k</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>&NotEqual;</mo> <mi>j</mi> <mo>;</mo> </mrow> </math> wherein,representing the weight of each factor at the k-th layer to the h-th factor at the k-1 layer,representing the ith factor on the kth layer;
then toNormalization is performed, and the weight of the kth layer to the h factor of the k-1 layer can be obtained, namely:
P h = ( P 1 h k , P 2 h k , . . . , P nh k ) T ;
c5: composite total weight
After the weights of the respective layers are found, the ranking weight vector of the k-1 layer to the total target is known as:
then the composite ordering W of the global elements on the k-th layer to the overall targetkComprises the following steps:
<math> <mrow> <msup> <mi>W</mi> <mi>k</mi> </msup> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <msub> <mi>n</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> </munderover> <msubsup> <mi>P</mi> <mi>ij</mi> <mi>k</mi> </msubsup> <msubsup> <mi>W</mi> <mi>j</mi> <mrow> <mi>k</mi> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <msub> <mi>n</mi> <mi>k</mi> </msub> <mo>,</mo> </mrow> </math> wherein WkIs the total weight;
d: and D, respectively obtaining the weight of each index through the solution in the step C, wherein the weight is shown in the following table:
e: and evaluating the operation management level of the power distribution network, wherein the specific steps of evaluating the operation management level of the power distribution network are as follows:
e1: looking up an industry standard, converting the marked value into a percentile system value according to the marked value of the power distribution network in an ideal state, and making a scoring standard;
e2: b, respectively calculating corresponding index numerical values according to each index calculation formula in the step B by collecting original data of the power distribution network to be evaluated;
e3: according to the index values calculated in the step E2, various indexes of the operation management level of the power distribution network are evaluated by referring to the scoring standard formulated in the step 1; and D, obtaining a weighted value of the operation management level by using the index weights obtained in the step D and combining the index numerical value calculated in the step E2, namely evaluating the operation management level of the power distribution network.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104408549A (en) * 2014-10-31 2015-03-11 国家电网公司 Running state evaluation method of urban distribution network
CN107767047A (en) * 2017-10-19 2018-03-06 国电南瑞科技股份有限公司 A kind of power distribution network regulates and controls integral system operation conditions evaluation method
CN107767067A (en) * 2017-10-31 2018-03-06 国网福建省电力有限公司 Power distribution network management and running evaluation index system construction method based on big data

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102063657A (en) * 2010-12-23 2011-05-18 中国电力科学研究院 Operating level and power supplying capability evaluation method for urban electric distribution network
CN102968668A (en) * 2012-12-03 2013-03-13 黑龙江省电力科学研究院 Urban power distribution network evaluation system and method
CN103530817A (en) * 2013-10-10 2014-01-22 国家电网公司 Distributed photovoltaic grid-connected adaptability evaluation method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102063657A (en) * 2010-12-23 2011-05-18 中国电力科学研究院 Operating level and power supplying capability evaluation method for urban electric distribution network
CN102968668A (en) * 2012-12-03 2013-03-13 黑龙江省电力科学研究院 Urban power distribution network evaluation system and method
CN103530817A (en) * 2013-10-10 2014-01-22 国家电网公司 Distributed photovoltaic grid-connected adaptability evaluation method

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
孙岩: ""配电网综合评价方法及应用"", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 *
张峰: ""PMS系统在配网工作中的实践"", 《经济发展方式转变与自主创新——第十二届中国科学技术协会年会》 *
张超: ""配电网规划后评估方法和实用软件研究"", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》 *
韩震焘: ""城市配电网综合评价体系研究"", 《万方学位论文》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104408549A (en) * 2014-10-31 2015-03-11 国家电网公司 Running state evaluation method of urban distribution network
CN107767047A (en) * 2017-10-19 2018-03-06 国电南瑞科技股份有限公司 A kind of power distribution network regulates and controls integral system operation conditions evaluation method
CN107767067A (en) * 2017-10-31 2018-03-06 国网福建省电力有限公司 Power distribution network management and running evaluation index system construction method based on big data

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