CN109146274A - A kind of plant gas synthetical condition assessment method based on entropy weight - Google Patents
A kind of plant gas synthetical condition assessment method based on entropy weight Download PDFInfo
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Abstract
The plant gas synthetical condition assessment method based on entropy weight that the present invention relates to a kind of, it is characterised in that the following steps are included: 1) determining the evaluation indexes at different levels of reflection plant gas production management situation, construct plant gas production management System of Comprehensive Evaluation；2) the plant gas production management System of Comprehensive Evaluation based on foundation establishes plant gas comprehensive evaluation model in conjunction with entropy assessment and Principal Component Analysis, the first class index evaluation of estimate and comprehensive evaluation value of the unit sample that obtains participating in evaluation and electing；3) according to the first class index evaluation of estimate and comprehensive evaluation value of the unit sample that respectively participates in evaluation and electing being calculated, the comprehensive state of different stage plant gas is assessed.The present invention can be widely applied to plant gas synthetical condition assessment field.
Description
Technical field
The present invention relates to plant gas synthetical condition assessment fields, comprehensive especially with regard to a kind of plant gas based on entropy weight
Conjunction state appraisal procedure.
Background technique
In recent years, since plant gas has, the short construction period, high reliablity, pollution environment is few and energy conversion efficiency is high
The features such as, to realize energy structure optimizing and peaking demand of power grid, China's plant gas installed capacity rapid development.Although combustion gas
Power station environment disposal of pollutants is few, but high Gas Prices make plant gas benefit unsatisfactory；Meanwhile with national ring
The tightening year by year of protective policy is polluted in border, also proposed severe challenge to plant gas pollutant emission.
Power Plant comprehensive evaluation analysis research and development is rapid, and analytical effect is significant, but there are also one there is also some defects
Fixed improved space.First, index system foundation is not comprehensive, current Power Plant comprehensive evaluation index is mostly with economy, ring
Index based on guarantor property and reliability, without being related to the index system of safety, equipment management etc..And equipment management refers to
Mark is the guarantee of Power Plant economic security operation, is that electric power enterprise realizes industry competition, it is essential to strengthen core competitiveness
Index system；Second, comprehensive evaluation analysis thinking focuses on impact analysis of the first class index weight to evaluation result more, to second level
Small Indicators weight considers the impact analysis of evaluation result insufficient；In addition, existing analytic hierarchy process (AHP), Field Using Fuzzy Comprehensive Assessment etc.
Method determines that weight is mostly artificial subjective weights, and human factor is affected, and it is true still to pass through subjective weights when index is less
Determine weight, but index increases, index discrimination hour, subjective weights implement difficulty increase, it is also difficult to accomplish objective and accurate；
Third, currently, evaluation method and system to the economy of fired power generating unit, safety and reliability have had very much, but for
The comprehensive index system of plant gas is established and appraisal procedure, especially regardless of grade, the overall merit of classifying type does not compare also
It is few.In China electric power development face it is various under the new situation, for improve plant gas overall merit accurate reasonability, enhancing
Competitiveness is produced, productivity effect is maximized, Optimization of Energy Saving consumption reduction establishes a set of rationally effective Gas Generator Set overall evaluation system
It is extremely urgent.
Summary of the invention
In view of the above-mentioned problems, the object of the present invention is to provide a kind of plant gas synthetical condition assessment side based on entropy weight
Method, this method is succinct effective, objective reasonable, overall merit can be carried out to plant gas entirety operation state, to examine combustion gas
The performance of power plant's indices.
To achieve the above object, the present invention takes following technical scheme: a kind of plant gas comprehensive state based on entropy weight
Appraisal procedure, comprising the following steps: 1) determine the evaluation indexes at different levels of reflection plant gas production management situation, building combustion gas electricity
Factory's production management System of Comprehensive Evaluation；2) the plant gas production management System of Comprehensive Evaluation based on foundation, in conjunction with
Entropy assessment and Principal Component Analysis establish plant gas comprehensive evaluation model, the first class index evaluation for the unit sample that obtains participating in evaluation and electing
Value and comprehensive evaluation value；3) right according to the first class index evaluation of estimate and comprehensive evaluation value of the unit sample that respectively participates in evaluation and electing being calculated
The comprehensive state of different stage plant gas is assessed.
In the step 1), the plant gas production management System of Comprehensive Evaluation includes that first class index and second level refer to
Mark, the first class index includes safety and environmental protection index, major economic indicators, reliability index, main operating index and equipment pipe
Index is managed, each first class index respectively includes several two-level index.
In the step 2), the plant gas production management System of Comprehensive Evaluation based on foundation, in conjunction with entropy assessment and
Principal Component Analysis establishes plant gas comprehensive evaluation model, the first class index evaluation of estimate and synthesis of the unit sample that obtains participating in evaluation and electing
The method of evaluation of estimate, comprising the following steps: the 2.1) power of each two-level index in System of Comprehensive Evaluation is determined by entropy assessment
Weight, and be calculated each first class index evaluation of estimate according to two-level index weighted value forms and participates in evaluation and electing the one of unit sample for evaluating
Grade index entropy assessment evaluations matrix；2.2) obtained first class index entropy assessment evaluations matrix is led using Principal Component Analysis
Constituent analysis extracts principal component according to variance contribution ratio, and the comprehensive evaluation value for the unit sample that participates in evaluation and electing is calculated.
In the step 2.1), the construction method of the first class index entropy assessment evaluations matrix, comprising the following steps:
2.1.1) the two-level index type and quantity for being included according to each first class index, and the institute for the unit sample that respectively participates in evaluation and electing
There is two-level index value, constructs first class index decision matrix Ak；
In formula: k is first class index serial number, and k=1,2 ..., p, p are the number of first class index；aijFor i-th of machine that participates in evaluation and electing
J-th of two-level index value of group, and i=1,2 ..., n, n are the unit sample number that participates in evaluation and electing, and j=1,2 ..., m, m is k-th of level-one
The two-level index number that index is included；
2.1.2) different according to the attribute of two-level index, to each first class index matrix AkIn two-level index standardized
Change, each first class index decision matrix R after being standardizedk；
Wherein, to the calculation formula of positive generic attribute two-level index standardization are as follows:
The calculation formula standardized to negative generic attribute two-level index are as follows:
In formula, aijFor i-th of unit that participates in evaluation and electing j-th of two-level index value,Be positive jth in generic attribute index
The minimum value of a two-level index,Be positive the maximum value of j-th of two-level index in generic attribute index,For
The maximum value of j-th of two-level index in negative generic attribute index,Be negative in generic attribute index j-th of two-level index
Minimum value；
First class index decision matrix R after standardizationkAre as follows:
2.1.3 the first class index decision matrix R after each standardization) is calculated using Information EntropykIn, the information of each two-level index
Entropy EjAnd its errored message degree dj；
Respectively participate in evaluation and electing the comentropy E of each two-level index in unit samplejCalculation formula are as follows:
In formula: j=1,2 ..., m, k=1/ln (n) are constant related with the unit sample number that participates in evaluation and electing；rijMeet 0≤rij
≤ 1 HeAnd work as rijWhen=0, r is enabledijln(rij)=0；
The errored message degree d of each two-level indexjCalculation formula are as follows:
dj=1-Ej；
2.1.4) according to the errored message degree of each two-level index, the weight w of each two-level index is calculatedj:
In formula:
2.1.5) according to the weight of each two-level index and each first class index decision matrix, each first class index is calculated
Evaluation of estimate Zi,k:
In formula: 0≤Zi,k≤1；
2.1.6) according to the evaluation of estimate of each first class index, the first class index entropy for evaluating the unit sample comprehensive state that participates in evaluation and electing is constituted
Power method evaluations matrix Zn,p:
In the step 2.2), using Principal Component Analysis to obtained first class index entropy assessment evaluations matrix carry out it is main at
Analysis extracts principal component, and the method that the comprehensive evaluation value for the unit sample that participates in evaluation and electing is calculated according to variance contribution ratio, including
Following steps:
2.2.1) to first class index entropy assessment evaluations matrix Zn,pPrincipal component analysis is carried out, the n unit samples that participate in evaluation and electing are obtained
Principal component；
2.2.2) according to the principal component of n unit sample is obtained, the comprehensive evaluation value F for the unit sample that respectively participates in evaluation and electing is calculatedi；
The step 2.2.1) in, principal component analysis is carried out to first class index entropy assessment evaluations matrix, obtains the n machines that participate in evaluation and electing
The method of the principal component of group sample, comprising the following steps:
1. first class index entropy assessment evaluations matrix Zn,pCorrelation matrix R；
2. calculating the m characteristic root of correlation matrix R:
λ1≥λ2≥λ3≥…≥λm≥0；
Its character pair vector:
ej=(l1j,l2j,…,lmj), j=1,2 ..., m；
In formula, ejFor the feature vector of j-th of index, lmjFor element in feature vector；
3. calculating variance contribution ratio according to the characteristic root of correlation matrix R:
4. descending sort is carried out to variance contribution ratio, when the accumulative variance contribution ratio of preceding p index is met threshold condition,
As the principal component for the unit sample that participates in evaluation and electing；
If the accumulative variance contribution ratio of a index of preceding p (p≤m) meets:
The then principal component of the n unit samples that participate in evaluation and electing are as follows:
Mi,j=Zn,p×[e1e2…em]′；
In formula, [e1e2…em] ' for preceding m feature vector forms matrix.
The invention adopts the above technical scheme, which has the following advantages: 1, the present invention is from safety and environmental protection index, main
Economic indicator, reliability index, main operating index, the big first class index domain of equipment management index five are to plant gas production management
Index is constructed and is analyzed, and five big first class index include the respectively different sub- indexs of second level again.It is special from index concept to index
Point carries out comprehensive refinement analysis to each index, provides support for the bidding assessment work of going deep into of plant gas.2, of the invention
Index weights are determined by entropy assessment according to correlation between achievement data, rejecting artificial subjective factor influences, it is ensured that is evaluating
Index increase, index discrimination hour, subjective weights implement difficulty increase, it is difficult to when accomplishing objective and accurate, guarantee evaluation
Result fairness reasonability.3, the plant gas of different type, different stage is placed on identical platform and compares evaluation by the present invention,
It carries out objectively evaluating comparative analysis using power plant's actual operation level of control data, from first class index ranking and overall merit ranking
Two aspects ensure that evaluation fairness to plant gas overall merit, be that corporate decision maker's production and operation management and power plant transport
Administrative staff's enhancing efficiency by relying on tapping internal latent power provides guidance and help.Therefore, the present invention can be widely applied to plant gas synthetical condition assessment neck
Domain.
Detailed description of the invention
Fig. 1 is the method for the present invention flow chart.
Specific embodiment
The present invention is described in detail below with reference to the accompanying drawings and embodiments.
As shown in Figure 1, a kind of plant gas synthetical condition assessment method based on entropy weight provided by the invention, including it is following
Step:
1) evaluation indexes at different levels of reflection plant gas production management situation are determined, building plant gas production management is comprehensive
Assessment indicator system.
The present invention refers to from safety and environmental protection index, major economic indicators, reliability index, main operating index, equipment management
Mark five big first class index domains plant gas production management index is constructed and analyzed, five big first class index include again respectively not
The same sub- index of second level.From index concept to index feature, comprehensive refinement analysis is carried out to each index.Each index is introduced such as
Under:
1. safety and environmental protection index
Safety and environmental protection index includes 10 related two-level index, and being respectively as follows: prevents power generation major accident measure plan
Completion rate (just), general environment liability for polution event (negative), employee's occupational health physical examination rate (just), SO 2 from fume discharge are dense
Spend (negative), flue gas nitrogen oxide concentration of emission (negative), quantity of wastewater effluent (negative), noise of equipment maximum value (negative), factory outside noise
(negative), power plant's one kind number of faults and two class number of faults (negative) of power plant.Wherein, the positive and negative Criterion Attribute for respectively referring to each evaluation index
It is positive or negative.
2. major economic indicators
Major economic indicators include 16 two-level index, are respectively as follows: generated energy (just), average load (just), rate of load condensate
(just), specific yield production and operation cost (negative), sale of electricity fixed cost per unit (negative), per capita administration fee (negative), power generation mark coal
Consume (negative), coal consumption of power supply (negative), power generation heat consumption rate (negative), power generation gas consumption rate (negative), comprehensive station service power consumption rate (negative), direct station-service
Electric rate (negative), heat supply standard coal consumption (cogeneration of heat and power) (negative), hotspot stress (cogeneration of heat and power) (just), heating demand (cogeneration of heat and power)
(just), integrated heat efficiency (cogeneration of heat and power) (just).
3. reliability index
Reliability index mainly includes 9 two-level index, is respectively as follows: abnormal few generated energy (negative), generation schedule completion rate
(just), gas-to electricity hourage (just), unplanned outage number (negative), unit tripping number (negative), unplanned outage hourage
(negative), planned outage hourage (negative), unit equivalent available factor (just), generating equipment equivalent available factor (just).
4. main operating index
Main operating index includes 14 two-level index, is respectively as follows: HPFH use rate, make-up water percentage (just), power generation consumption fresh water
Rate (negative), waste heat boiler exhaust gas temperature (negative), Steam-water Quality qualification rate (just), oil and gas quality qualification rate (just), desalination aquatic products water
Rate (just), specific consumption of feed-water pump (negative), water circulating pump power consumption (negative), condenser terminal difference (negative), feed temperature (just), hot-well depression
Spend (negative), protective system in heat power device devoting rate (just), relay protection movement accuracy (just).
5. equipment management index
Equipment management index mainly includes some Small Indicators in maintenance and management process, perfect equipment management index body
Scientific, the standardization that system can carry out equipment management for power plant provide foundation, promote to improve Plant engineering modernization level with
Equipment management benefit.Equipment management index domain shares 17 related two-level index, including key equipment availability (just), key are set
Utilization rate (just) when standby serviceability rate (just), key equipment platform, the maintenance and repair budget degree of deviation (negative), scheduled overhaul implementation rate (just), outside
Committee maintenance cost ratio (negative), maintenance personal's ratio (negative), maintenance cost intensity (negative), service material expense ratio (negative), part warehouse
Deposit the rate of capital turnover (just), service material consumption costs (negative), inventory's service material (negative), unit generated energy maintenance cost
The maintenance cost (negative) of (negative), unit output value, the maintenance cost (negative) of unit profit, elimination of equipment defect rate (just), elimination of equipment defect and
When rate (just).
2) the plant gas production management System of Comprehensive Evaluation based on foundation, in conjunction with entropy assessment and principal component analysis
Method establishes plant gas production management comprehensive evaluation model, and the first class index evaluation of estimate and synthesis for the unit sample that obtains participating in evaluation and electing are commented
Value.
2.1) weight of each two-level index in System of Comprehensive Evaluation is determined by entropy assessment, and is weighed according to two-level index
Each first class index evaluation of estimate is calculated in weight values, and forms the first class index entropy assessment evaluation square for evaluating the unit sample that participates in evaluation and electing
Battle array.
The construction method of first class index entropy assessment evaluations matrix, comprising the following steps:
2.1.1) the two-level index type and quantity for being included according to each first class index, and the institute for the unit sample that respectively participates in evaluation and electing
There is two-level index value, constructs first class index decision matrix Ak:
In formula: k is first class index serial number, and k=1,2 ..., p, p are the number of first class index；aijFor i-th of machine that participates in evaluation and electing
J-th of two-level index value of group, and i=1,2 ..., n, n are the unit sample number that participates in evaluation and electing, and j=1,2 ..., m, m is k-th of level-one
The two-level index number that index is included.
2.1.2) to each first class index matrix AkIn positive generic attribute index and negative generic attribute index standardize, obtain
Each first class index decision matrix R after standardizationk。
According to professional knowledge and Analysis on Mechanism it is found that positive generic attribute indexAttribute value is bigger, and unit performance is got over
It is excellent；Negative generic attribute indexAttribute value is smaller, and unit performance is more excellent.Unit performance is evaluated for each ATTRIBUTE INDEX
Consistency makes each attribute being consistent property in comentropy, and two class indexs are carried out standardization processing.
Positive generic attribute index standardization:
Negative generic attribute index standardization:
In formula, aijFor i-th of unit that participates in evaluation and electing j-th of two-level index value,Be positive jth in generic attribute index
The minimum value of a two-level index,Be positive the maximum value of j-th of two-level index in generic attribute index,For
The maximum value of j-th of two-level index in negative generic attribute index,Be negative in generic attribute index j-th of two-level index
Minimum value.
Each first class index decision matrix R according to each ATTRIBUTE INDEX value after standardization, after being standardizedkAre as follows:
2.1.3 the first class index decision matrix R after each planningization) is calculated using Information EntropykIn, the information of each two-level index
Entropy EjAnd its errored message degree dj。
Entropy assessment is a kind of objective making decision method that index weights are determined according to evaluation index matrix.Comentropy, which reflects, is
The chaos degree of disorder of system, entropy is bigger, shows that the degree of disorder of system is bigger, information value degree is smaller；On the contrary, entropy is smaller,
The degree of disorder of system is smaller, and information value degree is bigger.Its calculation formula is:
In formula: X represents different state x1,x2,...,xn, P (xi) represent different xiThe probability of (i=1,2 ..., n), 0≤
P(xi)≤1 andAs P (xiWhen)=0,0log0=0.
The index weights of two-level index, for indicating in evaluation procedure, to the important of the not ipsilateral for being evaluated object
Degree it is rationed, weight is bigger, then influence of the index to first class index is bigger, to power plant evaluation contribution it is bigger.This
In invention, the comentropy E of each two-level index in the unit sample that respectively participates in evaluation and electingjCalculation formula are as follows:
In formula: j=1,2 ..., m, k=1/ln (n) are constant related with the unit sample number that participates in evaluation and electing, it is therefore an objective to make Fj∈
[0,1]；rijMeet 0≤rij≤ 1 HeAnd work as rij, it is specified that r when=0ijln(rij)=0.
According to the comentropy of each two-level index, the errored message degree d of each two-level index is obtainedjCalculation formula are as follows:
dj=1-Ej
2.1.4) according to the errored message degree of each two-level index, the weight of each two-level index is calculated.
The weight of certain index refers to relative importance of the index in the overall evaluation.Weight is indicated in evaluation procedure
In, to the rationed of the significance level of the not ipsilateral for being evaluated object, to effect of each evaluation index in overall assessment
It distinguishes.The weight of each two-level index are as follows:
In formula:Weight wjIt is bigger, j pairs of the ATTRIBUTE INDEX in m ATTRIBUTE INDEX
The influence of first class index k is bigger, bigger to the contribution of unit evaluation.
2.1.5) according to the weight of each two-level index and each first class index decision matrix, each first class index is calculated
Evaluation of estimate:
In formula: 0≤Zi,k≤ 1, first class index value Zi,kBigger, the performance of the first class index is got in the unit sample that shows to participate in evaluation and electing
It is excellent.
2.1.6) according to the evaluation of estimate of each first class index, the first class index entropy for evaluating the unit sample comprehensive state that participates in evaluation and electing is constituted
Power method evaluations matrix Zn,p:
2.2) principal component analysis is carried out to obtained first class index entropy assessment evaluations matrix using Principal Component Analysis, according to
Variance contribution ratio extracts principal component, and the comprehensive evaluation value for the unit sample that participates in evaluation and electing is calculated.
Principal Component Analysis is a kind of important statistical method of multiple attribute synthetical evaluation, for how studying by several
A principal component expresses the internal structure between multiple variables, and dimensionality reduction thought can convert high dimensional data to low-dimensional data processing
It is simple, direct to make data processing problem for analysis, therefore principal component analytical method is answered extensively in the evaluation analysis of various fields
With.In overall merit, principal component change direction can be determined by calculating variance size, thus obtain the power of principal component
Weight, gained weight are the variance contribution ratio as corresponding principal component.The information that principal component is reflected is more, and corresponding weight is got over
Greatly.
The method that power plant's comprehensive evaluation value is calculated according to first class index entropy assessment evaluations matrix, comprising the following steps:
2.2.1) to first class index entropy assessment evaluations matrix Zn,pPrincipal component analysis is carried out, the n unit samples that participate in evaluation and electing are obtained
Principal component；
The method that principal component analysis is carried out to first class index entropy assessment evaluations matrix, comprising the following steps:
1. first class index entropy assessment evaluations matrix Zn,pCorrelation matrix R；
2. calculating the m characteristic root of correlation matrix R:
λ1≥λ2≥λ3≥…≥λm≥0
Its character pair vector:
ej=(l1j,l2j,…,lmj), j=1,2 ..., m
In formula, ejFor the feature vector of j-th of index, lmjFor element in feature vector.
3. calculating variance contribution ratio according to the characteristic root of correlation matrix R:
4. descending sort is carried out to variance contribution ratio, when the accumulative variance contribution ratio of preceding p index is met threshold condition,
As the principal component for the unit sample that participates in evaluation and electing.
If the accumulative variance contribution ratio of a index of preceding p (p≤m) meets:
Then think that this p principal component can integrate and embody m index, i.e., the principal component of n unit sample are as follows:
Mi,j=Zn,p×[e1e2…em]′
In formula, [e1e2…em] ' for preceding m feature vector forms matrix.
2.2.2) according to the principal component of n unit sample is obtained, the comprehensive evaluation value F for the unit sample that respectively participates in evaluation and electing is calculatedi；
3) according to the unit sample that respectively participates in evaluation and electing that is calculated and metrics evaluation value and first class index comprehensive evaluation value, it is right
The comprehensive state of different stage plant gas is assessed.
According to the first class index evaluation of estimate and comprehensive evaluation value of the unit that respectively participates in evaluation and electing, the level-one for the unit sample that respectively participated in evaluation and electing
Metrics evaluation ranking and comprehensive evaluation value ranking, and then the comprehensive state of different stage plant gas is assessed.
Embodiment one
1, evaluation object
The present embodiment chooses 6 plant gas operational management achievement datas in certain enterprise May in 2017 as evaluation object,
It is 1-6 by plant gas number, wherein No. 1 power plant is F grade of pure condensate base lotus, for for F grades of hot radical lotus, No. 3 power plant are for No. 2 power plant
E grades of pure condensate base lotus, No. 4 power plant are E grades of pure condensate peak regulation, and No. 5 power plant are for F grades of hot radical lotus, and No. 6 power plant are F grades of pure condensate peak regulation.Institute
Having modeling achievement data is power plant's operation management index of correlation data that each power plant reports group, and examines that data are errorless.
2, plant gas data sample is chosen
According to the plant gas production management System of Comprehensive Evaluation of foundation, evaluation index data are chosen.
1. safety and environmental protection index: flue gas nitrogen oxide concentration of emission (A1), quantity of wastewater effluent (A2), noise of equipment maximum value
(A3), factory outside noise (in the daytime) (A4), factory outside noise (night) (A5), each index specific value are as shown in table 1 below.
1 safety and environmental protection index of table
In safety and environmental protection index, due to shortage of data or achievement data it is identical and reject index: prevent power generation weight
Major break down measure completion rate of the plan, general environment liability for polution event, employee's occupational health physical examination rate, SO 2 from fume discharge
Two class number of faults of concentration, power plant's one kind number of faults and power plant.
2. reliability index: generation schedule completion rate (B1), unit equivalent available factor (EAF) (B2), gas-to electricity are small
When number (B3), unplanned outage number (B4), unit tripping number (B5), unplanned outage hourage (B6), planned outage it is small
When number (B7), each index specific value is as shown in table 2 below.
2 reliability index of table
In reliability index, due to shortage of data or achievement data is identical and the index rejected: abnormal few generated energy, power generation
Equipment equivalent available factor.
3. equipment management index: being utilized when key equipment availability (C1), Perfectness ratio of critical equipments (C2), key equipment platform
Rate (C3), elimination of equipment defect promptness rate (C4), elimination of equipment defect rate (C5), the Parts Inventory rate of capital turnover (C6), maintenance personal's ratio
(C7), service material consumption costs (C8), inventory's service material (C9), each index specific value are as shown in table 3 below.
3 equipment management index of table
In equipment management index, due to shortage of data or achievement data is identical and the index rejected: outer committee's maintenance cost ratio,
The maintenance and repair budget degree of deviation, unit generated energy maintenance cost, the maintenance cost of unit output value, the maintenance cost of unit profit.
4. major economic indicators: generated energy (D1), average load (D2), rate of load condensate (D3), the specific yield production and operation at
This (D4), consumption of standard coal for power generation (D5), coal consumption of power supply (D6), power generation heat consumption rate (D7), power generation gas consumption rate (D8), comprehensive station service
Rate (D9), auxiliary power consumption rate of power plant (D10), each index specific value are as shown in table 4 below.
4 major economic indicators of table
In major economic indicators, due to shortage of data or achievement data it is identical and reject index: sale of electricity unit is fixed into
This, administration fee, heat supply standard coal consumption (cogeneration of heat and power), hotspot stress (cogeneration of heat and power), heating demand (cogeneration of heat and power), comprehensive per capita
It closes the thermal efficiency (cogeneration of heat and power).
5. main operating index: Steam-water Quality qualification rate (E1), oil, gas quality qualification rate (E2), demineralized water producing water ratio
(E3), make-up water percentage (E4), power generation consumption fresh water rate (E5), waste heat boiler exhaust gas temperature (E6), each index specific value such as the following table 5 institute
Show.
The main operating index of table 5
In main operating index, due to shortage of data or achievement data is identical and the index rejected: HPFH use rate, water supply
Pump unit consumption, water circulating pump power consumption, condenser terminal difference, feed temperature, condensate undercooling, protective system in heat power device devoting rate, relay
Protection act accuracy.
3, plant gas overall merit
Selected plant gas index is commented according to the entropy assessment Application of principal component analysis on evaluation model of foundation
Valence, program operation result are as follows:
1. each two-level index weight:
Weight w 1:0.12066,0.22114,0.24531,0.21082,0.20205；
Weight w 2:0.18443,0.22313,0.09606,0.10978,0.15927,0.10978,0.11755；
Weight w 3:0.062252,0.062252,0.10717,0.086266,0.060545,0.21132,0.13485,
0.15358,0.12176；
Weight w 4:0.12829,0.17021,0.19326,0.053765,0.077757,0.076905,0.078228,
0.054742,0.075502,0.091347；
Weight w 5:0.1863,0.045143,0.14294,0.30416,0.24369,0.077762.
2. first class index matrix
Two-level index matrix z=
0.2778 0.4969 1.9668 3.7129 0.6012
0.2452 0.8828 2.2019 3.4789 0.3183
0.1807 0.9481 1.1982 0.4229 0.5716
0.4691 1.1356 1.3420 0.5205 0.4566
0.3367 1.0917 1.4925 2.0235 0.9668
0.3196 1.1789 1.0192 1.7435 0.7411
M=6
N=5
Level-one evaluation index ranking: Leveltwoevaluationsort=
4 5 6 1 2 3
6 4 5 3 2 1
2 1 5 4 3 6
1 2 5 6 4 3
5 6 1 4 3 2
Comprehensive evaluation value:
F=1.9100 1.8453 0.3042 0.3361 0.8946 0.6087
Overall merit ranking: Leveloneevaluationsort=
1 2 5 6 4 3
The evaluation index calculated result of the obtained unit sample that participates in evaluation and electing is as shown in table 6 below:
Table 6 participates in evaluation and electing unit evaluation index calculated result
Note: 1~w5 of weight w be respectively safety and environmental protection index, reliability index, equipment management index, major economic indicators,
Two-level index weight in main operating index.
4 interpretations of result
4.1, entropy assessment first class index interpretation of result:
4.1.1, from the point of view of by safety and environmental protection index, 5 indexs evaluated are negative generic attribute index, the smaller electricity of index
Factory is more excellent.Power plant safety environmental protection index ranking is 4,5,6,1,2,3.It (is indicated in evaluation procedure, to quilt by index weights
The significance level of the not ipsilateral of evaluation object it is rationed, weight is bigger, then influence of the index to two-level index is bigger,
It is bigger to the contribution of power plant's evaluation) it is found that denitrification concentration of emission weighted value is smaller outer, other index weights compared with
Greatly, noise of equipment maximum value weighted value is maximum (contribution of the index in safety and environmental protection metrics evaluation is larger), passes through index number
According to it is found that although No. 4 electric power factory equipment noise maximum values are not minimum, the numbers of its nitrous oxides concentration and factory outside noise (in the daytime)
Value is all minimum, therefore it ranks the first in safety and environmental protection metrics evaluation, and No. 5 electric power factory equipment noise maximum values are optimal, but with 4
Number power plant's value is not much different, and not as good as No. 5 flue gas nitrogen oxide concentration, factory outside noise (night) value power plant, therefore it is number two；
Although No. 6 power plant's quantity of wastewater effluent are zero, other index values are not optimal in below average grade, and ranking is not as good as No. 4, No. 5
(one index of explanation is in optimal or differs greatly with other power plant's index orders of magnitude, can't generate to final appraisal results
Decisive role).Although No. 2, No. 3 power plant factory outside noise (in the daytime) index value minimum, other index values are unsatisfactory, especially
It is quantity of wastewater effluent, and the order of magnitude differs larger with other power plant.No. 3 electric power factory equipment noise maximum values are highest, although sewage
Discharge amount is smaller, but other index values are all larger, therefore its is the last.
4.1.2, from reliability index angle analysis, generation schedule completion rate, unit equivalent available factor, gas-to electricity are small
When number be positive generic attribute index, index value more high-power station is more excellent；Other generic attribute indexs that are negative, index value more small power plant are more excellent.
Maximum by unit equivalent available factor weighted value known to index weights, gas-to electricity hourage takes second place, unit tripping number the
Three.No. 6 power plant in addition to generation schedule completion rate, gas-to electricity hourage numerical value be not it is optimal, other index values be it is optimal,
And generation schedule completion rate index value is preferable, therefore its reliability is best；Although No. 4 Power Plant equivalent available factors are not most
It is excellent, but its generation schedule completion rate and unit tripping number be it is optimal, other than planned outage hourage numerical value is undesirable,
His index value, therefore its reliability is taken second place.Although No. 1 power plant is preferable in gas-to electricity hourage numerical value, other indexs are equal
Undesirable, especially unit equivalent available factor, generation schedule completion rate and unit tripping number, unplanned outage hourage refer to
Mark is worst, therefore its reliability ranking is worst.
4.1.3, equipment management index analysis, Parts Inventory rate of capital turnover weighted value is maximum known to weighted value result,
Service material consumption costs takes second place, and maintenance personal's ratio, inventory's service material weight are subsequent.No. 1, No. 2 Parts Inventory fund weeks
Rate of rotation index value is optimal, and the order of magnitude differs larger with other power plant, and No. 2 power plant are in maintenance personal's ratio, inventory's service material etc.
Index value is preferable, therefore its equipment management index is optimal.No. 6 power plant's Parts Inventory rate of capital turnover index values are poor, other refer to
It marks and pessimistic, if elimination of equipment defect promptness rate, elimination of equipment defect rate, especially inventory's service material index value are worst, with other electricity
Factory's difference order of magnitude is very big, and equipment management index ranking is worst.
4.1.4, major economic indicators are analyzed, and generated energy, average load, rate of load condensate are positive generic attribute index, and index value is got over
High-power station is more excellent；Other indexs are negative generic attribute index, and index value more small power plant is more excellent.By weighted value result it is found that rate of load condensate
Weighted value it is maximum, it is maximum to the contribution of evaluation result.Rate of load condensate is to measure the index of electricity consumption balance degree, from economical operation
Angle considers that rate of load condensate shows that the utilization rate of electrical equipment is higher, be conducive to wastage reducing and energy saving closer to 1.Index value is bigger, table
Bright production smoothing, the rate of utilization of equipment's capacity is high, and it is more excellent that index value gets over high-power station's (unit).Average load weighted value takes second place, power generation
Measure weighted value third.Although by each power plant's index value it is found that No. 1 power plant load rate be not it is optimal, relative to other power plant's numbers
Magnitude difference is larger, and average load, generated energy are optimal；Other index values also are located at preferential ranks, therefore its main economic
Index is optimal；No. 2 power plant take second place relative to No. 1 economy of power plant index, but due to other power plant, major economic indicators ranking
Second.And No. 3 power plant's average loads, rate of load condensate, specific yield production and operation cost, power generation gas consumption rate and auxiliary power consumption rate of power plant are equal
For worst-case value, and other index values are also pessimistic, and major economic indicators are worst.Pass through the investigation and analysis to Power Plant situation
It is found that though No. 6 power plant are F grades of units, since unit is dedicated for peak regulation, operating condition is influenced quite greatly by power grid transfer,
Therefore relative to other F grades of base lotus unit, there are fluctuations in economy, occupy the 4th；No. 3 power plant and No. 4 power plant are E grades
Gas turbine, since combustion chambers burn temperature is lower, power generation gas consumption is significantly higher, and then the specific yield production and operation is at high cost,
There is opposite disadvantage in itself on Technical Economy.On the other hand, as can be seen from the results, thermal power plant unit in May (No. 2, No. 5 electricity
Factory) economy be lower than pure condensate unit (No. 1 power plant), tally with the actual situation, it was demonstrated that the real-time effectiveness of model.
4.1.5, mainly operating index is analyzed, and Steam-water Quality qualification rate, oil gas quality qualification rate, demineralized water producing water ratio are positive
Generic attribute index, index value more high-power station are more excellent；Other generic attribute indexs that are negative, index value more small power plant are more excellent.By each power plant
Index value is it is found that Steam-water Quality qualification rate, oil gas quality qualification rate index value are not much different, and evaluation result is substantially by other indexs
It determines.By index value weighted value it is found that the weighted value of make-up water percentage is maximum, power generation consumption fresh water rate weighted value takes second place, and Zhuhai electric power is mended
Water rate, power generation consumption fresh water rate index value are optimal, and other index values are preferable, therefore its main operating index is optimal.No. 6 power plant
Make-up water percentage, power generation consumption fresh water rate, Steam-water Quality qualification rate, waste heat boiler target exhaust gas temperature are slightly worse compared with Zhuhai electric power, only remove
Salt water producing water ratio is due to No. 5 power plant, therefore its main operating index is number two.And No. 2 power plant's demineralized water producing water ratio indexs are 0,
It is larger that the order of magnitude is differed compared with other power plant；And its power generation consumption fresh water rate index is worst, make-up water percentage index is simultaneously pessimistic, so that
Its main operating index ranking is worst.
4.2, principal component comprehensive evaluation result is analyzed:
By principal component calculated result it is found that power plant's overall merit ranking is 1,2,5,6,4,3.By evaluation result it is found that 1
Although number, the evaluation ranking of No. 2 power plant's safety and environmental protections, reliability and main operating index it is unsatisfactory, its equipment management, master
Want the ranking of economic indicator optimal, and other opposite power plant of economic index evaluation are larger, economic index is in principal component analysis
Contribution rate is larger in the process, so that the two power plant occupy first place in overall merit ranking.This also illustrates to comment in power plant's synthesis
Economic indicator plays leading role in valence.Although No. 6 power plant's reliabilities are optimal, it is too late in economy as variable load plant
Other F grades of power plant, and show in terms of equipment management it is poor so that its ranking in F grades of power plant rearward.
The various embodiments described above are merely to illustrate the present invention, wherein the structure of each component, connection type and manufacture craft etc. are all
It can be varied, all equivalents and improvement carried out based on the technical solution of the present invention should not exclude
Except protection scope of the present invention.
Claims (6)
1. a kind of plant gas synthetical condition assessment method based on entropy weight, it is characterised in that the following steps are included:
1) evaluation indexes at different levels for determining reflection plant gas production management situation, construct plant gas production management overall merit
Index system；
2) the plant gas production management System of Comprehensive Evaluation based on foundation is built in conjunction with entropy assessment and Principal Component Analysis
Vertical plant gas comprehensive evaluation model, the first class index evaluation of estimate and comprehensive evaluation value of the unit sample that obtains participating in evaluation and electing；
3) according to the first class index evaluation of estimate and comprehensive evaluation value of the unit sample that respectively participates in evaluation and electing being calculated, to different stage combustion gas
The comprehensive state of power plant is assessed.
2. a kind of plant gas synthetical condition assessment method based on entropy weight as described in claim 1, it is characterised in that: described
In step 1), the plant gas production management System of Comprehensive Evaluation includes first class index and two-level index, the level-one
Index includes safety and environmental protection index, major economic indicators, reliability index, main operating index and equipment management index, each institute
It states first class index and respectively includes several two-level index.
3. a kind of plant gas synthetical condition assessment method based on entropy weight as claimed in claim 2, it is characterised in that: described
In step 2), the plant gas production management System of Comprehensive Evaluation based on foundation, in conjunction with entropy assessment and Principal Component Analysis,
Plant gas comprehensive evaluation model is established, the method for the first class index evaluation of estimate and comprehensive evaluation value of the unit sample that obtains participating in evaluation and electing,
The following steps are included:
2.1) weight of each two-level index in System of Comprehensive Evaluation is determined by entropy assessment, and according to two-level index weighted value
Each first class index evaluation of estimate is calculated, forms the first class index entropy assessment evaluations matrix for evaluating the unit sample that participates in evaluation and electing；
2.2) principal component analysis is carried out to obtained first class index entropy assessment evaluations matrix using Principal Component Analysis, according to variance
Contribution rate extracts principal component, and the comprehensive evaluation value for the unit sample that participates in evaluation and electing is calculated.
4. a kind of plant gas synthetical condition assessment method based on entropy weight as claimed in claim 3, it is characterised in that: described
In step 2.1), the construction method of the first class index entropy assessment evaluations matrix, comprising the following steps:
2.1.1) the two-level index type and quantity for being included according to each first class index, and the unit sample that respectively participates in evaluation and electing all two
Grade index value, constructs first class index decision matrix Ak；
In formula: k is first class index serial number, and k=1,2 ..., p, p are the number of first class index；aijFor i-th of unit that participates in evaluation and electing
J-th of two-level index value, and i=1,2 ..., n, n are the unit sample number that participates in evaluation and electing, and j=1,2 ..., m, m is k-th of first class index
The two-level index number for being included；
2.1.2) different according to the attribute of two-level index, to each first class index matrix AkIn two-level index standardize, obtain
Each first class index decision matrix R after standardizationk；
Wherein, to the calculation formula of positive generic attribute two-level index standardization are as follows:
The calculation formula standardized to negative generic attribute two-level index are as follows:
In formula, aijFor i-th of unit that participates in evaluation and electing j-th of two-level index value,It is positive in generic attribute index j-th two
The minimum value of grade index,Be positive the maximum value of j-th of two-level index in generic attribute index,Be negative class
The maximum value of j-th of two-level index in ATTRIBUTE INDEX,Be negative the minimum of j-th of two-level index in generic attribute index
Value；
First class index decision matrix R after standardizationkAre as follows:
2.1.3 the first class index decision matrix R after each standardization) is calculated using Information EntropykIn each two-level index comentropy EjAnd
Its errored message degree dj；
Respectively participate in evaluation and electing the comentropy E of each two-level index in unit samplejCalculation formula are as follows:
In formula: j=1,2 ..., m, k=1/ln (n) are constant related with the unit sample number that participates in evaluation and electing；rijMeet 0≤rij≤ 1 HeAnd work as rijWhen=0, r is enabledijln(rij)=0；
The errored message degree d of each two-level indexjCalculation formula are as follows:
dj=1-Ej；
2.1.4) according to the errored message degree of each two-level index, the weight w of each two-level index is calculatedj:
In formula:
2.1.5) according to the weight of each two-level index and each first class index decision matrix, the evaluation of each first class index is calculated
Value Zi,k:
In formula: 0≤Zi,k≤1；
2.1.6) according to the evaluation of estimate of each first class index, the first class index entropy assessment for evaluating the unit sample comprehensive state that participates in evaluation and electing is constituted
Evaluations matrix Zn,p:
5. a kind of plant gas synthetical condition assessment method based on entropy weight as claimed in claim 3, it is characterised in that: described
In step 2.2), principal component analysis is carried out to obtained first class index entropy assessment evaluations matrix using Principal Component Analysis, according to
Variance contribution ratio extracts principal component, and the method that the comprehensive evaluation value for the unit sample that participates in evaluation and electing is calculated, comprising the following steps:
2.2.1) to first class index entropy assessment evaluations matrix Zn,pCarry out principal component analysis, obtain n participate in evaluation and electing unit samples it is main at
Point；
2.2.2) according to the principal component of n unit sample is obtained, the comprehensive evaluation value F for the unit sample that respectively participates in evaluation and electing is calculatedi；
6. a kind of plant gas synthetical condition assessment method based on entropy weight as claimed in claim 5, it is characterised in that: described
Step 2.2.1) in, principal component analysis is carried out to first class index entropy assessment evaluations matrix, obtain n participate in evaluation and electing unit samples it is main at
The method divided, comprising the following steps:
1. first class index entropy assessment evaluations matrix Zn,pCorrelation matrix R；
2. calculating the m characteristic root of correlation matrix R:
λ1≥λ2≥λ3≥…≥λm≥0；
Its character pair vector:
ej=(l1j,l2j,…,lmj), j=1,2 ..., m；
In formula, ejFor the feature vector of j-th of index, lmjFor element in feature vector；
3. calculating variance contribution ratio according to the characteristic root of correlation matrix R:
4. descending sort is carried out to variance contribution ratio, when the accumulative variance contribution ratio of preceding p index is met threshold condition, by it
Principal component as the unit sample that participates in evaluation and electing；
If the accumulative variance contribution ratio of a index of preceding p (p≤m) meets:
The then principal component of the n unit samples that participate in evaluation and electing are as follows:
Mi,j=Zn,p×[e1e2…em]′；
In formula, [e1e2…em] ' for preceding m feature vector forms matrix.
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