CN115409309A - Method for evaluating bearing capacity of distributed renewable energy accessed to power distribution network based on variable weight theory - Google Patents

Method for evaluating bearing capacity of distributed renewable energy accessed to power distribution network based on variable weight theory Download PDF

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CN115409309A
CN115409309A CN202111528751.7A CN202111528751A CN115409309A CN 115409309 A CN115409309 A CN 115409309A CN 202111528751 A CN202111528751 A CN 202111528751A CN 115409309 A CN115409309 A CN 115409309A
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汪鹏
王波
马恒瑞
马富齐
王红霞
张嘉欣
张迎晨
李怡凡
冯磊
王雷雄
朱成亮
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State Grid Hubei Electric Power Co Ltd
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Abstract

The invention discloses a method for evaluating the bearing capacity of a distributed renewable energy source accessed to a power distribution network based on a variable weight theory, which comprises the following steps: (1) Determining the alternative object set is to determine the operation and planning objects of the existing power grid; (2) determining each evaluation index of the index set; (3) the score of the index is calculated according to each index; (4) determining the weight of each index; (5) The comprehensive score value of the scheme is calculated, and the method has the advantages that: the project provides a comprehensive evaluation method for the bearing capacity of a power distribution network of a distributed power supply, the method establishes a novel index system for comprehensive evaluation of the power distribution network from the aspects of safety and reliability, power quality, operation economy, flexibility and the like, then calculates index weights by using a multilevel fuzzy comprehensive evaluation algorithm based on a variable weight theory, and comprehensively evaluates the bearing capacity of the power distribution network after the high-proportion distributed power supply is accessed.

Description

Method for evaluating bearing capacity of distributed renewable energy accessed to power distribution network based on variable weight theory
Technical Field
The invention relates to the technical field of distributed renewable energy access power distribution networks, in particular to the technical field of a method for evaluating the bearing capacity of a distributed renewable energy access power distribution network.
Background
The environmental protection pressure is increased day by day due to the large consumption of fossil energy, and under the call of energy conservation and emission reduction, distributed renewable energy is used as novel energy, and is rapidly developed at home and abroad due to the characteristics of small pollution, flexible power generation mode and the like. At present, renewable energy development is extensive, the problem of coordination between renewable energy development and power grid planning is relatively little considered, and the health sustainable development of middle-term and long-term renewable energy is adversely affected. With the access of a large amount of wind power and photovoltaic power generation to the power distribution network, the load type of the power distribution network also changes, and the load demand increases. But the planning of the original distribution network does not consider the influence of the access of a large number of distributed power sources. If the distributed photovoltaic access scale exceeds the actual bearing capacity of the power distribution network, the problems of transformer and line overload, line voltage deviation out-of-limit, harmonic exceeding, protection failure and the like can be caused, and the safe and stable operation of the power grid is influenced. Therefore, a scientific and systematic comprehensive evaluation system is expected to be established, and the influence effect of the distributed power supply on the power distribution network is accurately analyzed.
Disclosure of Invention
In order to solve the technical problems, the invention provides a distributed renewable energy access power distribution network bearing capacity evaluation method based on a variable weight theory, relevant research of renewable energy bearing capacity improvement technology research and application considering comprehensive energy services is developed, the influence of renewable energy access to a power grid is analyzed according to the actual conditions of a power supply side and a load side of the power grid, and the bearing capacity of the power grid on renewable energy is improved.
The technical solution adopted by the invention to solve the technical problems is as follows:
a distributed renewable energy access power distribution network bearing capacity evaluation method based on a variable weight theory comprises the following steps:
(1) Determining the alternative object set is to determine the operation and planning objects of the existing power grid, and different object divisions can use A = { A = according to different permeabilities of the distributed power supply 1 ,A 2 ,K,A i ,K,A n Denotes, n is the number of objects;
(2) Determining each evaluation index of the index set, wherein each index is represented by X = { X = 1 ,X 2 ,K,X i ,K,X n Denotes, n is the number of evaluation indexes;
(3) The scoring of the indexes is that all indexes of the object i are calculated according to the calculation method of each index, each evaluation index is subjected to dimensionless processing by using a power efficiency coefficient method, and the formula is as follows:
Figure BDA0003409952380000021
in the formula x ij Is the score value of the jth index of object i; x ij ' is the actual calculated value of the jth index of the object i; m is a group of j ，m j A satisfactory value and an impermissible value of the index j, respectively; c and d are constants, and are usually c =60, d =40;
(4) Determining weights of indices
According to the established index system, each factor of the index layer is compared in pairs and specific values are obtained, and for the case of n factors, the following comparison matrix a is formed:
Figure BDA0003409952380000031
in the formula a ij Is the importance of factor i relative to factor j, the values of which are shown in the following table:
comparing the scaled meanings of matrix A
Figure BDA0003409952380000032
And calculating the index weight according to a geometric mean method:
Figure BDA0003409952380000033
then, the weights of the indexes of the object i are determined again according to the weight-variable theory, and W is used i ＝{W i1 ,W i2 ,K,W im Represents;
(5) Calculating a composite score value for a solution
And (3) the comprehensive score value of the object i is equal to the weight of each index calculated in the step (4) multiplied by the score of each index calculated by the efficacy coefficient method in the step (3), and the calculation formula is as follows:
Figure BDA0003409952380000041
(6) Determining comprehensive evaluation result by maximum membership principle
The result evaluation grade is determined by adopting a scoring method in percentage, and the project adopts 5-grade evaluation, as shown in the table:
comparing the scaled meanings of matrix A
Grade 1 (great difference) 2 (poor) 3 (middle) 4 (Liang) 5 (you)
Score value [0,20] [20,40] [40,60] [60,80] [80-100]
。
The technical effect achieved by adopting the technical scheme is as follows: the project provides a comprehensive evaluation method for the bearing capacity of a power distribution network of a distributed power supply, the method establishes a novel index system for comprehensive evaluation of the power distribution network from the aspects of safety and reliability, power quality, operation economy, flexibility and the like, then calculates index weights by using a multilevel fuzzy comprehensive evaluation algorithm based on a variable weight theory, and comprehensively evaluates the bearing capacity of the power distribution network after the high-proportion distributed power supply is accessed.
Detailed Description
1. Distributed renewable energy access power distribution network bearing capacity index system
1.1 short-circuit Current check
And the short-circuit current check is based on the principle that the short-circuit current of each bus node of the system does not exceed the cut-off current limit value of the corresponding circuit breaker after the distributed power supply is connected.
The check object should include all devices within the evaluation range through which a short-circuit current is likely to flow.
And calculating the bus short-circuit current of the system according to the current situation of the short-circuit current in the maximum operation mode of the system in the evaluation range and the capacity of the distributed power supply to be checked by taking GB/T15544 and DL/T5729 as the basis.
The short-circuit current should be checked according to the following formula
I XZ ＜I m
In the formula I XZ For short-circuit current of system bus, I m The minimum of the open current limits of the corresponding circuit breakers on all the equipment and feeders connected to the bus should be chosen for the allowable short circuit current limit.
1.2 Voltage offset checking
The voltage deviation checking should take the principle of reactive power in-situ balance and the principle that the voltage of the power grid is not out of limit after the distributed power supply is connected.
The checking object comprises a 10 kV-220 kV voltage grade bus of a 35 kV-220 kV transformer substation.
The maximum positive voltage deviation and the maximum negative voltage deviation of the evaluation area are respectively calculated according to the highest operating voltage and the lowest operating voltage of the power grid in the evaluation period and combined with the voltage limit value given by GB/T12325, and are respectively expressed as delta UH and delta UL.
According to the capacity of the distributed power supply to be checked and the requirement of GB/T33593, the maximum positive and negative voltage deviations of the area caused by the access of the newly-added distributed power supply are calculated according to the following formula and are respectively expressed as delta U H And δ U L 。
Figure BDA0003409952380000061
In the formula, Q max The maximum reactive positive and negative values, U, calculated according to the required value of GB/T33593 on the power factor of the grid-connected point of different types of distributed power supplies N Is the rated voltage, R, of the bus in this region L 、X L The resistive and reactive components of the network impedance are negligible in high-voltage networks.
The voltage deviation should be checked according to the following formula
ΔU H ＞δU H Or Δ U L ＜δU L
1.3 harmonic checking
The harmonic wave checking is based on the principle that the harmonic wave current value and the inter-harmonic wave voltage content rate of a distributed power supply access power grid node in the system are not out of limit.
The check object should include all nodes that are likely to be affected by the harmonic currents and inter-harmonic voltages provided by the distributed power supply.
The harmonic current should be checked as follows
I xz,h ＞I h
In the formula I xz,h Is the h-th harmonic current value, I h The h-th harmonic current limit specified for GB/T14549.
The voltage content rate of each subharmonic of the check node should not exceed the GB/T24337 regulation limit.
1.4 Power grid bearing Capacity grading
And the power grid bearing capacity evaluation grade is determined in a partition and layering mode according to the calculation and analysis result. The evaluation grades can be divided into green, yellow and red from low to high.
When the evaluation grade is determined, the local part of the power grid is subject to the overall condition, and when the evaluation grade of the next-level power grid is lower than that of the previous-level power grid, the evaluation grade is subject to the previous-level power grid.
The evaluation area short circuit current, voltage deviation or harmonic check does not pass, and the corresponding evaluation grade is red.
The evaluation region transmits electricity back to the 220kV and above power grid due to the distributed power supply, and the evaluation grade of the region is red.
The evaluation rating should comply with the provisions of the following table
Assessing rating
Figure BDA0003409952380000071
2. Safety and reliability calculation index
2.1 Medium Voltage line "N-1" pass Rate
The verification passing rate of the medium-voltage line N-1 refers to that all loads of the line can be transferred to other lines for power supply after a transformer substation is shut down in a maximum load operation mode, the proportion of the line is used for reflecting the conversion of the loads of the medium-voltage line into the power supply in the maximum load operation mode, and the calculation formula is as follows:
Figure BDA0003409952380000081
in the formula n t Is the number of the transferable lines; n is l Is the total number of medium voltage lines in the area.
2.2 short circuit Capacity
After the distributed power supply is connected to the grid, short-circuit current can be provided for a short-circuit point, and when the capacity of the distributed power supply reaches a certain degree, the overcurrent protection device cannot act correctly. The short-circuit capacity is that when a three-phase short circuit occurs to a feeder line, the short-circuit current calculated in the maximum operation mode is multiplied by the voltage of a short-circuit point, the apparent power value is taken, the capability of the feeder line to deal with the fault is reflected, and the calculation formula is as follows:
Figure BDA0003409952380000082
in the formula
Figure BDA0003409952380000083
Is the short circuit current in the maximum operating mode;
Figure BDA0003409952380000084
the short-circuit current injected to the short-circuit point by the ith distributed power supply; u shape f The short-circuit point voltage. If the fault point of the power grid can be safely removed, normal power supply of other loads is guaranteed, and the short-circuit capacity is smaller than the cutoff capacity of the feeder circuit breaker.
2.3SAIFI, SAIDI and ASAI
The distribution network is divided into blocks according to the switch positions through the configuration condition and the automation degree of the switch devices in the distribution network, the influence of the fault of any element in the same block on the load point is completely the same, and the equivalent fault rate lambda of the block s is s And average equivalent repair time gamma s The following:
Figure BDA0003409952380000091
Figure BDA0003409952380000092
in the formula of i Is the failure rate of the ith element of block s; m is the total number of elements of the block s; gamma ray i Is the repair time of the ith element of block s. The average annual outage time for block s is:
U s ＝γ s λ s
system reliability Index System Average Power off Frequency SAIFI (System Average Interruption Frequency Index), system Average outage Duration SAIDI (System Average Interruption Duration Index), and Average Power supply Availability ASAI (Average Service Availability Index) calculation formulas are as follows:
Figure BDA0003409952380000093
Figure BDA0003409952380000094
Figure BDA0003409952380000095
in the formula N s The number of users of the block s.
3. Calculation index of operation economy index
3.1 line loss Rate
The line loss rate is the percentage of the active power loss of the feeder line to the input power of the initial end of the feeder line, and the calculation formula of the line loss rate is as follows:
Figure BDA0003409952380000101
in the formula, L and T are a branch and a distribution set respectively; i is i Is the current amplitude of the ith branch; I.C. A j Is the current amplitude of the jth distribution branch; r is i Is the resistance of the ith branch; r is j Is the resistance of the jth transformer branch; p l max Is the supply power value of the line.
3.2 line maximum load rate, distribution transformer maximum load rate
The maximum load rate of the line and the distribution transformer refers to the ratio of the maximum load of the line and the distribution transformer to the maximum transmission active power of the line and the distribution transformer, and the calculation formula is as follows:
Figure BDA0003409952380000102
in the formula P i max Is the maximum value of the ith load;
Figure BDA0003409952380000103
is the power factor of the ith load; n is the total number of loads on the line or transformer; and S is the maximum transmission active power allowed by the line and the distribution transformer.
3.3 average load factor of line and distribution transformer
The average load rate of the line and the distribution transformer refers to the average value of the load rates of the feeder line and the distribution transformer in the annual period, and the calculation formula is as follows:
Figure BDA0003409952380000104
in the formula P ave Is the average load.
4. Theory of variable weight
The variable weight theory solves the problem that the scores of all indexes deviate from normal values, namely the scores of the indexes are too high or too low, the influence of abnormal indexes on an evaluation result is reduced by reducing the weight, and a variable weight calculation formula of a balance function is introduced:
Figure BDA0003409952380000111
in the formula w j 、w′ j The weights before and after the weight change are respectively; x is the number of j Is the score for index j; m is the number of indexes; t is an element of (0, 1)]Are equalization coefficients. The evaluation of the prior weight-variable theory is that the equalization coefficient T is considered to be constant, and the variation condition of the equalization coefficient T under different degrees of deviation of the index from the normal value is not considered, so that the evaluation effect is influenced.
For this purpose, for object (recipe) A j Score x of jth index of (1) ij The method for calculating the equalization coefficient T used in this project is as follows:
Figure BDA0003409952380000112
it should be noted that the above formula is only qualitative guarantee x ij The more deviated from the mean value of each index, T ij The closer to 0; on the contrary, if x ij The closer to the mean value of each index, T ij The closer to 1; that is, the above formula is given T ij But not T ij A quantitative calculation of (a), which can only represent one trend.
5. Comprehensive evaluation method based on variable weight theory
A single-layer fuzzy comprehensive evaluation step based on a variable weight theory:
(1) The determination of the alternative object (scheme) set is to determine the existing power grid operation and planning object (scheme), and different scheme partitions can use A = { A ] according to different permeabilities of the distributed power supply 1 ,A 2 ,K,A i ,K,A n Denotes, n is the number of objects (solutions);
(2)determining each evaluation index of the index set, wherein each index is X = { X = 1 ,X 2 ,K,X i ,K,X n Denotes, m is the number of evaluation indexes;
(3) The scoring of the index is performed by calculating all indexes of an object (scheme) i according to a calculation method of each index, and performing dimensionless processing on each evaluation index by using a power efficiency coefficient method, wherein the formula is as follows:
Figure BDA0003409952380000121
in the formula x ij Is the score value of the jth index of object (scenario) i; x is the number of ij Is the actual calculated value of the jth index for object (solution) i; m is a group of j ，m j A satisfactory value and an impermissible value of the index j, respectively; c, d are constants, typically c =60, d =40;
(4) Determining weights of indices
According to the established index system, each factor of the index layer is compared in pairs and specific values are obtained using the method of table 1, and for the case where there are n factors, the following comparison matrix a is formed:
Figure BDA0003409952380000122
in the formula a ij Is the importance of factor i relative to factor j, the values of which are shown in the table:
comparing the scaled meanings of matrix A
Figure BDA0003409952380000131
And calculating the index weight according to a geometric mean method (root method), as shown in the formula:
Figure BDA0003409952380000132
then according to the variable weight theory of section 3.1The weights of the indices of the object (solution) i are redetermined, using W i ＝{W i1 ,W i2 ,K,W im Represents;
(5) Calculating a composite score value for a solution
The comprehensive score value of the object (scheme) i is equal to the weight of each index calculated in the step (4) multiplied by the score of each index calculated by the efficacy coefficient method in the step (3), and the calculation formula is as follows:
Figure BDA0003409952380000133
(6) Determining fuzzy comprehensive evaluation result by maximum membership principle
The result evaluation grade is determined by adopting a scoring method of percentage system, and the project adopts 5-grade evaluation, as shown in the table:
comparing the scaled meanings of matrix A
Grade 1 (great difference) 2 (poor) 3 (middle) 4 (Liang) 5 (you)
Score value [0,20] [20,40] [40,60] [60,80] [80-100]
6. Example analysis of empirical evidence
6.1 overview of the Neizhou grid
The Chazhou city is located in the north of Hubei province, wuhan city in the middle of Dongcheng province, xiyan, beijing Xinyang, nanda Chazhou city, and the total soil area of the Chazhou city is 9636 square kilometers. By 2019, the daily population of the whole city is 258 thousands of people, and the operation range comprises the city district, the Zeng City district (county level), the free county and the Guangshi city. Mineral products, photovoltaic, wind power, tourism and other resources of the city of the Nippon nationality are rich, and in 2010-2019, the economic development quality, speed and benefit of the city of the Nippon nationality are better than, faster than and higher than the average level of the whole provinces of the nation.
In the intersection zone of the Yangtze river basin and the Huai river basin in the Neizhou city, the terrain mainly takes the plain and the hills as main parts, the water energy resource is not abundant, and the wind power and photovoltaic resources are abundant. By the end of 2019, the total installed capacity of the Nizhou power grid reaches 2486.306MW. The city in Neizhou has 7 small hydropower stations with installed capacity of 13.3MW, wherein the number of the small hydropower stations is 1000kW and more than that of the built-in small hydropower stations. The built small hydropower stations are all radial-flow type hydropower stations with extremely small storage capacity, and generally can only participate in power generation in rich water seasons with abundant incoming water, and in dry water seasons, because of water shortage, the hydropower stations are basically in a shutdown state and can generate no power. The built-in network-connected garbage power station 1 is a 10kV Baichuan garbage power station with the installed capacity of 2MW. The built-up online wind power station has 15 seats and installed capacity of 1216.4MW. The installed photovoltaic capacity of the built-in online photovoltaic power station is 1231.606MW, wherein the installed photovoltaic capacity of the centralized photovoltaic power station is 20kV and above, and the installed photovoltaic capacity of the integrated photovoltaic power station is 1050MW. And the installed capacity of distributed photovoltaic of 10kV and below is 181.606MW.
6.2 example base information
6.2.1 evaluation of boundary conditions
6.2.2 load case
The maximum load of the major network of the state in 2020 is 103.79 ten thousand kilowatts (8 months and 5 days), which is increased by 1.56 percent compared with the maximum load (102.2) in 2019; in 2020, the maximum daily power supply amount of a main network is 1929 ten thousand kWh, which is increased by 3.4% compared with the maximum daily power supply amount (1864) in 2019; in 2020, the maximum output of new energy is 157 ten thousand watts (8 months and 15 days), which is increased by 16.30 percent compared with the maximum output (135) in 2019.
6.2.3 Power Condition
In the intersection region of the Yangtze river basin and the Huai river basin in the Yangzhou city, the terrain mainly takes plains and hills as main parts, the water energy resources are not abundant, and the wind power and photovoltaic resources are abundant. By the end of 2019, the total installed capacity of the Nizhou power grid reaches 2486.306MW.
The city of Neizhou has 7 small hydropower stations with installed capacity of 13.29MW, wherein the small hydropower stations have built-in network capacity of 1000kW and more. The built small hydropower stations are all radial-flow type hydropower stations with extremely small storage capacity, and generally can only participate in power generation in rich water seasons with abundant incoming water, and in dry water seasons, because of water shortage, the hydropower stations are basically in a shutdown state and can generate no power.
General meter for small hydropower station in the Dizhou province
Figure BDA0003409952380000151
Figure BDA0003409952380000161
The grid connection of the Nizhou power grid is established as a garbage power station 1 of the online, a 10kV Baichuan garbage power station and the installed capacity of 2MW. The onboard power grid of the Neizhou is built into 15 wind power plants with installed capacity of 1216.4MW.
Existing wind power installation summary table of Cizhou
Figure BDA0003409952380000162
Figure BDA0003409952380000171
Installed photovoltaic capacity 1231.606MW of built-in online grid of the grid-connected of the Naviu power grid, wherein 20 centralized photovoltaic power stations of 35kV and above have capacity 1050MW. And the installed capacity of distributed photovoltaic of 10kV and below is 181.606MW.
Existing centralized photovoltaic power station summary table of Pouzhou
Figure BDA0003409952380000172
Figure BDA0003409952380000181
Existing distributed photovoltaic power station summary table of the Poison
Figure BDA0003409952380000182
Figure BDA0003409952380000191
6.3 Heat stability assessment index score
Scoring according to the indices in the table:
when lambda is less than or equal to 0, 100 is taken;
when lambda is more than 0 and less than or equal to 80 percent, taking the fraction as (0.8-lambda/0.8) × 100;
when lambda is greater than 80%, 0 is taken.
Evaluation index of thermal stability
Figure BDA0003409952380000192
Figure BDA0003409952380000201
6.4 short-circuit Current check index Scoring
Scoring according to the indices in the table:
when I is XZ ＜I m Taking the score as (I) m -I XZ )/I m *100；
When I is XZ ＞I m Taking 0;
short-circuit current checking and evaluating index
Belonging to the area Name of bus Short-circuit current limit (kA) I m I XZ Score of
All over the world 220kV varied 220kV #1 mother plant with state 80 13.90 82.63
All over the world 220kV Zaizhou Dazhuan 220kV #2 80 13.90 82.63
All over the world 110kV #4 mother-child changing 220kV along with state 40 8.65 78.38
Anywhere in the world 220kV 110kV #5 mother varied with state 40 8.68 78.30
Anywhere in the world 220kV Alzhou to 10kV #7 mother 20 34.44 0
Anywhere in the world 220kV 10kV #8 mother-house 20 34.44 0
All over the world 220kV 10kV 9 mother-house 20 36.24 0
Anywhere in the world 220kV 10 # mother-house changed from 10kV to-10 kV 20 36.24 0
6.5 Voltage deviation check indicator score
Scoring according to the indices in the table:
when Δ U is measured H ＞δU H When the score is (Δ U) H -δU H )/ΔU H *100；
When Δ U L ＜δU L When the fraction is (delta U) L -ΔU L )/ΔU L *100。
Voltage positive deviation checking and evaluating index
Figure BDA0003409952380000202
Figure BDA0003409952380000211
Negative voltage deviation checking and evaluating indicator
Figure BDA0003409952380000212
6.6 harmonic check index score
By taking 100, not by taking 0.
Harmonic checking index
Figure BDA0003409952380000213
Figure BDA0003409952380000221
6.7 Grading result of each index of 220kV change along with state
Index scoring results
Figure BDA0003409952380000231
6.8 index weight calculation and comprehensive scoring
Referring to DL/T + 2041-2019 and related documents, a comparison matrix of indexes DL/T + 2041-2019 is shown in the table.
Index comparison matrix of < DL/T + 2041-2019 >
Index class Evaluation of thermal stability Short circuit current check Voltage deviation checking Harmonic checking index
Evaluation of thermal stability 1 1/5 1/5 1/3
Short circuit current check 5 1 1 1
Voltage deviation checking 5 1 1 1
Harmonic checking index 3 1 1 1
Combining the index calculation result and the variable weight theory in the previous section, the index weight coefficient of DL/T + 2041-2019 before variable weight is calculated as follows:
W＝(0.07 0.32 0.32 0.28) T
the equalization coefficient matrix T can be found according to equation (3.2):
T＝(0.93 0.89 0.95 0.93) T
further, according to a formula, index weight coefficients of DL/T + 2041-2019 after variable weights are obtained are as follows:
W′＝(0.07 0.28 0.36 0.28) T
and finally, obtaining a comprehensive score value of 90.72 according to a formula.

Claims (1)

1. A distributed renewable energy source access power distribution network bearing capacity evaluation method based on a variable weight theory is characterized by comprising the following steps:
(1) Determining the alternative object set is to determine the operation and planning objects of the existing power grid, and different object divisions can use A = { A = according to different permeabilities of the distributed power supply 1 ,A 2 ,K,A i ,K,A n Denotes, n is the number of objects;
(2) Determining each evaluation index of the index set, wherein each index is X = { X = 1 ,X 2 ,K,X i ,K,X n Denotes, n is the number of evaluation indexes;
(3) The scoring of the indexes is that all indexes of the object i are calculated according to the calculation method of each index, each evaluation index is subjected to dimensionless processing by using a power efficiency coefficient method, and the formula is as follows:
Figure FDA0003409952370000011
in the formula x ij Is the score value of the jth index of object i; x ij ' is the actual calculated value of the jth index of the object i; m is a group of j ，m j A satisfactory value and an impermissible value of the index j, respectively; c, d are both constants, typically c =60,d＝40；
(4) Determining weights of indices
According to the established index system, each factor of the index layer is compared in pairs and specific values are obtained, and for the case of n factors, the following comparison matrix a is formed:
Figure FDA0003409952370000012
in the formula a ij Is the importance of factor i relative to factor j, the values of which are shown in the following table:
comparing the scaled meanings of matrix A
Figure FDA0003409952370000021
And calculating the index weight according to a geometric mean method:
Figure FDA0003409952370000022
then, the weights of the indexes of the object i are determined again according to the weight-changing theory, and W is used i ＝{W i1 ,W i2 ,K,W im Denotes a (j) };
(5) Calculating a composite score value for a solution
And (3) the comprehensive score value of the object i is equal to the weight of each index calculated in the step (4) multiplied by the score of each index calculated by the efficacy coefficient method in the step (3), and the calculation formula is as follows:
Figure FDA0003409952370000031
(6) Determining comprehensive evaluation result by maximum membership principle
The result evaluation grade is determined by adopting a scoring method of percentage system, and the project adopts 5-grade evaluation, as shown in the table:
comparing the scaled meanings of matrix A
Grade 1 (great difference) 2 (poor) 3 (middle) 4 (Liang) 5 (you) Score value [0,20] [20,40] [40,60] [60,80] [80-100]
。
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