Disclosure of Invention
The invention aims to provide a method for realizing comprehensive energy efficiency evaluation of a rail transit energy management system, which integrates various influencing factors of the rail transit energy management system, establishes a set of complete comprehensive energy efficiency evaluation index system of the rail transit energy management system, constructs a target judgment matrix through multi-round difference comparison, performs fuzzification processing, determines the coefficient of a base layer index relative to a target layer by combining an improved entropy method, keeps the objective data information and the flexibility on the basis, avoids the influence of insufficient objective information and subjective randomness, improves a traditional numerical value standardization processing method, and can reflect the mutual influence between the original data difference and each index at the same time.
In order to achieve the above purpose, the solution of the invention is:
a method for realizing comprehensive energy efficiency evaluation of a rail transit energy management system comprises the following steps:
step 1, analyzing the operation characteristics and energy consumption composition of rail transit, and performing type division on line stations;
step 2, establishing a four-level rail transit energy management system comprehensive energy efficiency evaluation index system which is respectively a target layer, a system layer, a subentry layer and a base layer from top to bottom;
step 3, constructing a target judgment matrix based on an analytic hierarchy process;
step 4, fuzzifying the target judgment matrix, and calculating the coefficient of the system layer evaluation index relative to the target layer and the coefficient of the subentry layer evaluation index relative to the system layer;
step 5, based on the historical statistical data of the rail transit energy management system, calculating the basic layer evaluation index values of all stations of the line by adopting an improved standardization method;
step 6, calculating the coefficient of the evaluation index of the basic layer relative to the item layer by adopting an improved entropy method;
and 7, calculating a comprehensive energy efficiency evaluation value of the evaluation index of the target layer so as to determine comprehensive energy efficiency sequencing of each station.
After the scheme is adopted, the invention has the following beneficial effects:
(1) the method comprises the steps of fully considering different types of station positioning differences and operation conditions of the rail transit energy management system, comprehensively analyzing influences of water resources, electric energy quality, energy consumption equipment operation time, station passenger flow, station environment differences and the like on electric energy consumption, establishing a comprehensive energy efficiency evaluation index system with four levels from top to bottom, and more comprehensively reflecting the operation conditions of the rail transit energy management system;
(2) through multi-round difference comparison, a target judgment matrix is constructed, and ambiguity processing is performed, so that the reliability and flexibility of the judgment matrix are improved; the traditional entropy method is improved, so that the sensitivity to abnormal data is reduced, meanwhile, the condition that the importance of important evaluation indexes is insufficient is avoided, and the accuracy and the objectivity of index coefficients are enhanced; the evaluation indexes of the base layers are subjected to standardized processing, so that the difference of the variation degree of the evaluation indexes of the base layers in the original data can be reflected, and the mutual influence among the indexes can be effectively reflected;
(3) the fuzzy analytic hierarchy process and the objective analytic process are combined to determine the evaluation index coefficients of each layer, the influence of insufficient objective information and subjective randomness is effectively reduced, the reliability of the coefficients is guaranteed, meanwhile, the flexibility is high, the engineering field requirements of different regions can be met, and the comprehensive energy efficiency evaluation sequencing of the rail transit energy management system has high reliability and practicability.
Detailed Description
The technical solution and the advantages of the present invention will be described in detail with reference to the accompanying drawings.
As shown in fig. 1, the invention provides a method for implementing comprehensive energy efficiency evaluation of a rail transit energy management system, which includes the following steps:
step 1, analyzing the operation characteristics and energy consumption composition of rail transit, and performing type division on line stations;
according to the comprehensive energy efficiency system and the actual operation condition of the stations, the line stations are divided into four types, namely transfer underground stations, transfer elevated stations, common underground stations and common elevated stations.
Compared with underground station ventilation equipment, the elevated station has less ventilation equipment and low power consumption, and does not need to consider environmental indexes and energy consumption indexes of a ventilation system; the transfer station is larger than the passenger flow of a common station, and the electric energy consumption is more than that of a non-transfer station of the same type.
Step 2, establishing a four-level rail transit energy management system comprehensive energy efficiency evaluation index system, namely a target layer, a system layer, a subentry layer and a basic layer;
establishing a four-level index system according to the characteristics of the rail transit industry and the relation among all systems, wherein the highest layer is a target layer, and only one evaluation index is available, namely a comprehensive energy efficiency evaluation value; the target layer comprises six system layer evaluation indexes which are respectively power consumption, water resource consumption, power quality, equipment state, environment state and passenger flow, and the passenger flow does not contain the evaluation indexes of the subentry layer; according to the type of electric equipment, dividing the electric energy consumption into five evaluation indexes of a subentry layer, wherein the five evaluation indexes of the subentry layer are ventilation electricity utilization, illumination electricity utilization, power electricity utilization, special electricity utilization and loss variation respectively; dividing water resource consumption into two evaluation indexes of a subentry layer, wherein the two evaluation indexes of the subentry layer are water for a water chiller and special water for the water chiller respectively; dividing the power quality into three evaluation indexes of a hierarchy of items, wherein the three evaluation indexes of the hierarchy of items are respectively voltage quality, frequency quality and waveform quality; dividing the operation of equipment into three evaluation indexes of a subentry layer, wherein the three evaluation indexes of the subentry layer are respectively ventilation equipment, lighting equipment and power equipment; dividing the environmental state into three subentry layer evaluation indexes, wherein the three subentry layer evaluation indexes are temperature, humidity and carbon dioxide concentration respectively; each item layer evaluation index comprises a plurality of specific calculation evaluation indexes, namely the basic layer evaluation index.
In the division process of the comprehensive energy efficiency evaluation index system structure, the evaluation indexes of the different item layers contained in the same system layer evaluation index or the evaluation indexes of the basic layers contained in the same evaluation index have the same attribute, the evaluation indexes of the different system layers are different, the evaluation indexes of the same attribute cannot be overlapped, and the number of the evaluation indexes of the basic layers contained in each evaluation index of the different item layers is not less than 2, as shown in fig. 2.
Step 3, constructing a target judgment matrix based on an analytic hierarchy process;
multiple experts in the industry adopt an analytic hierarchy process to evaluate the subentry layer contained in the index of each system layer respectively under the condition of non-interferenceAnd comparing the evaluation indexes and all system layer evaluation indexes pairwise according to the importance degrees, constructing a consistency judgment matrix, comparing the differences of the judgment matrixes, if the differences are large, reconstructing the judgment matrixes by the experts, and when the differences meet the requirements, solving the average value of the corresponding elements of the judgment matrixes as the corresponding elements of a target judgment matrix A, wherein: a ═ a
kt)
n×n,
k is 1,2 … n, t is 1,2 … n, n is the number of evaluation indexes of the hierarchy level belonging to the same system level evaluation index or the number of evaluation indexes of all the system levels.
When an expert constructs a judgment matrix, the scaling method shown in the table 1 is adopted, and compared with the traditional 1-9 scaling method, the method has higher order retention, consistency, uniformity and fitting performance.
TABLE 1 significance Scale of significance table
The experts are not easy to select too many and not suitable to select too few, usually 6-10 are suitable, too few has greater subjectivity, too many is not beneficial to convergence, and the reliability of the judgment matrix is ensured through difference comparison and averaging processing of the judgment matrix.
Step 4, fuzzifying the target judgment matrix, and calculating the coefficient of the system layer evaluation index relative to the target layer and the coefficient of the subentry layer evaluation index relative to the system layer;
blurring a target decision matrix into
Wherein:
when in use
When the temperature of the water is higher than the set temperature,
i.e. a real number,
the larger the size, the higher the ambiguity, and the method can be used for self-defining determination within the allowable range
And
the value of (2) can be adapted to the requirements of different regions.
The k-th evaluation index is relative to the real coefficient gamma of the previous levelk;
Wherein the content of the first and second substances,
is a matrix
The k-th row of elements in the unit feature vector,
is a matrix
The k-th row of elements in the unit feature vector,
is a matrix
Line k elements in unit feature vector, b
tIs a matrix
Reciprocal of the sum of the elements of column t, c
tIs a matrix
Reciprocal of the sum of the elements of column t, d
tIs a matrix
The reciprocal of the sum of the elements in column t.
Using varying coefficients pl、pm、puAnd the coefficient is determined by the normalized feature vector element corresponding to the index, and compared with the existing coefficient determining method, the method ensures the reliability and increases the flexibility.
Calculating the coefficient xi of the evaluation indexes of the six system layers relative to the target layer according to the methodeWherein E is 1,2 … E, E is the total number of system layer evaluation indexes, and the passenger flow coefficient is recorded as ξ; a 6-order blur matrix is constructed, E ═ 6; respectively calculating coefficients phi of the evaluation indexes of the item layers relative to the system layers contained in the evaluation indexes of each system layerrWherein R is 1,2 … R, and R is the number of the hierarchy evaluation indexes contained in the system level evaluation index; at the moment, a 5-order fuzzy matrix is constructed relative to the system layer electric energy consumption evaluation index, wherein R is 5; constructing a 2-order fuzzy matrix relative to the system layer water resource consumption evaluation index, wherein R is 2; constructing a 3-order fuzzy matrix relative to the system layer power quality evaluation index, wherein R is 3; constructing a 3-order fuzzy matrix relative to the system layer equipment state evaluation index, wherein R is 3; constructing a 3-order fuzzy matrix relative to the system layer environment state evaluation index, wherein R is 3; finally, the coefficient of all the evaluation indexes of the sub-item layers relative to the system layer is recorded as etaf,f=1,2…F,F=16。
Step 5, based on the historical statistical data of the rail transit energy management system, calculating the basic layer evaluation index value z of each station of the line by adopting an improved standardization methodijAnd system layer evaluation index passenger flow standardized value zj;
Wherein: mu.siEvaluating the mean, σ, of the indices for the ith base layeriEvaluating the standard deviation, x, of the index for the ith base layerimaxEvaluating the maximum value, x, of the index for the ith base layerimaxThe minimum value of the evaluation indexes of the ith base layer is a proportionality coefficient, epsilon (0,1), i is 1,2, …, B, B is the total number of the evaluation indexes of the base layer, j is 1,2, …, D, D is the number of stations, and the sample is the selected line station; for negative evaluation index, the calculated normalized value z is usedijAnd converting the result into a forward evaluation index after negation.
The evaluation index values of each base layer after standardization processing are adopted to eliminate the influence of dimension difference of the evaluation index of the base layer, so that the evaluation indexes of the standardized base layers have comparability, the difference of the variation degree of the evaluation index of each base layer in original data can be reflected, and the mutual influence among the indexes can be effectively reflected.
The normalized value z of the passenger flow at the jth station is calculated by adopting the methodj。
Step 6, calculating a coefficient omega of the evaluation index i of the base layer relative to the subentry layer by adopting an improved entropy methodi。
And (3) base layer evaluation index relatizing treatment:
the specific gravity of the ith basic layer evaluation index under the jth station is as follows:
entropy of the ith base layer evaluation index:
the coefficient α of the i-th base layer evaluation index with respect to the hierarchy layeriComprises the following steps:
calculating the coefficient omega of the evaluation index i of the base layer relative to the item layeri:
ωi=ραi+(1-ρ)βi
Wherein:
ρ is a proportionality coefficient, ρ ∈ (0, 1).
The traditional entropy method is improved, the data information of the evaluation index of the basic layer is fully utilized, the sensitivity to abnormal data is reduced, meanwhile, the condition that the important evaluation index is inadequately emphasized is avoided, and the accuracy and the objectivity of the index coefficient of the basic layer are enhanced.
Step 7, calculating a comprehensive energy efficiency evaluation value of the evaluation index of the target layer so as to determine comprehensive energy efficiency sequencing of each station:
wherein, VjFor the comprehensive energy efficiency evaluation value of the jth station, the system layer evaluation index e comprises a sub-layer evaluation index f, and the sub-layer evaluation index f comprises a base layer evaluation index i.
And the rail transit energy management system automatically calculates the comprehensive energy efficiency evaluation value of each station, and performs longitudinal and transverse sequencing on the comprehensive energy efficiency of each station according to the comprehensive energy efficiency evaluation value.
The coefficient calculated by the method considers subjective ambiguity judgment and objective data information at the same time, effectively reduces the influence caused by man-made random interference and possible insufficient data information, and has higher reliability and rationality.
The comprehensive energy efficiency evaluation value of the stations of the same type is larger, the ranking is more advanced, the operation mode is more reasonable and economical, the construction of an energy management system of the stations can be effectively promoted, and a reference decision is provided for energy-saving management; by comparing comprehensive energy efficiency evaluation values of different types of stations, energy consumption influence factors can be further excavated, the rail transit energy management system is sound, and reasonable construction of new lines is facilitated.
In summary, the invention establishes a set of complete comprehensive energy efficiency evaluation index system in the rail transit energy management industry, avoids one-sidedness simply based on energy consumption, improves the reliability of a target judgment matrix through multi-round difference comparison, combines objective analysis and optimized fuzzy judgment to jointly determine a coefficient, considers the fuzziness of artificial judgment on the basis of data information preservation, can avoid the randomness of the artificial judgment and the insufficient data of the objective analysis, optimizes the traditional data standardization method, and meets the engineering requirements of different types of rail transit lines.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the protection scope of the present invention.