CN109063919A - The optimization method of fluid heating snow-melting system operating parameter based on multiple objective programming - Google Patents
The optimization method of fluid heating snow-melting system operating parameter based on multiple objective programming Download PDFInfo
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Abstract
基于多目标规划的流体加热融雪系统运行参数的优化方法，本发明涉及流体加热融雪系统运行参数的优化方法。本发明为了解决现有技术无法计算系统融雪效果和运行成本以及无法确定最优运行参数的问题。本发明包括：一：建立流体加热融雪系统融雪效果数据库；二：计算某一工况条件下流体加热融雪系统融雪效果；三：根据传递热流密度q得到单位面积路体范围内流体加热融雪系统运行费用M；四：对M进行评价；五：采用多目标规划的方法建立流体加热融雪系统运行策略的优化模型；六：得到某一工况条件下流体加热融雪系统最优运行参数；七：重复步骤六，得到全工况条件下流体加热融雪系统运行参数的控制图。本发明用于交通运输工程领域。
The invention relates to a method for optimizing the operating parameters of a fluid heating and snow melting system based on multi-objective programming. The invention aims to solve the problems that the prior art cannot calculate the snow melting effect and operating cost of the system and cannot determine the optimal operating parameters. The present invention includes: 1: establishing a snow melting effect database of the fluid heating snow melting system; 2: calculating the snow melting effect of the fluid heating snow melting system under a certain working condition; Cost M; 4: Evaluate M; 5: Use multi-objective programming to establish an optimization model for the operation strategy of the fluid heating and snow melting system; 6: Obtain the optimal operating parameters of the fluid heating and snow melting system under a certain working condition; 7: Repeat In step six, the control chart of the operating parameters of the fluid heating snow melting system under all working conditions is obtained. The invention is used in the field of transportation engineering.
Description
Technical field
The present invention relates to Communication and Transportation Engineering fields, and in particular to the optimization side of fluid heating snow-melting system operating parameter
Method.
Background technique
In the northern area of China, the snow melt problem under Snowfall seriously restricts the places such as road, bridge and airport
Safe and highly efficient operation.Currently used deicing mode such as spreads deicing salt, snow removing vehicle or artificial snow removing and embodies one
Fixed limitation, spreading deicing salt on environment and building structures has certain harm, and its service performance is affected by environment
Factor is larger；Snow removal with machine and artificial snow removing need road occupying to work, and have influenced the normal operation on road and bridge or airport, and
Efficiency of cleaning snow is low, along with snowfall generally require repeatedly remove the snow repeatedly.In view of the above problems, scholar has developed stream
Body heats pavement snow melting system, and the system is with its good snow melt applicability, system controllability and measurability, heat energy source popularity, each
Snow removing sensibility place has broad application prospects.
The outer scholar of Current Domestic is concentrated mainly on test observation and theoretical modeling point for the research of fluid heating system
Analysis aspect, conducts extensive research system heat transfer mechanism and the parameter for influencing service ability, but in system snow melt strategy
The research of aspect is less；The construction and operation of system are determined by the experience of design (use) person mostly at present, are lacked theoretical
Basis, this increases the blindness of initial stage design and later period operation to a certain extent, significantly impacts the reality of this technology
Using effect；Meanwhile the research at this stage about system snow melt effect and snow melt cost is more deficient, runs snow melt for system
The calculating prediction of ability and Optimal Operation Strategies all lacks scientific and systematicness, constrains this technology to a certain extent
Practical implementation.
Summary of the invention
The purpose of the present invention is to solve the prior arts can not computing system snow melt effect and operating cost and can not
The problem of determining optimized operation parameter, and propose the optimization side of the fluid heating snow-melting system operating parameter based on multiple objective programming
Method.
Based on multiple objective programming fluid heating snow-melting system operating parameter optimization method the following steps are included:
Step 1: fluid heating snow-melting system snow melt effect data library is established；
Step 2: snow-melting system snow melt effect data library is heated according to the fluid that step 1 is established, calculates a certain operating condition item
Fluid heats snow-melting system snow melt effect F under part, and the working condition includes environment temperature, intensity of solar radiation, wind speed and drop
Avenge rate；
Step 3: the governing equation by establishing transmitting heat flow density calculates transmitting heat flow density q, according to transmitting hot-fluid
Density q obtains fluid within the scope of the body of unit area road and heats snow-melting system operating cost M；
Step 4: determining economic index R, flows within the scope of the unit area road body obtained according to economic index R to step 3
Body heating snow-melting system operating cost M is evaluated；
Step 5: according to step 2 and step 4, fluid heating snow-melting system fortune is established using the method for multiple objective programming
The Optimized model of row strategy；
Step 6: the Optimized model for the fluid heating snow-melting system operation reserve that step 5 is established is solved, is obtained
Fluid heats snow-melting system optimized operation parameter under a certain working condition, and the fluid heating snow-melting system operating parameter is fluid
Heat the preheating time t of snow-melting systemyrWith fluid temperature (F.T.) Tf；
Step 7: repeating step 6, obtains fluid heating snow-melting system optimized operation parameter set under the conditions of full working scope
It closes, obtains the control figure of fluid heating snow-melting system operating parameter under the conditions of full working scope according to optimized operation parameter sets.
For more intuitively output system optimisation strategy, optimisation strategy control figure is depicted according to multi-state the trial result
Spectrum adjusts the operation reserve of system for system operator in due course for different running environment conditions.
The invention has the benefit that
The present invention lacks science for the prediction of current fluid heating pavement snow melting system snow melt effect and operating cost,
And in actual operation, there is great blindness in the selection of system running policy, proposes a kind of pre- fluid measured and adds
The method of hot pavement snow melting system snow melt effect and operating cost, and propose system optimized operation strategy.
For problem of the prior art, the present invention is based on independently developed fluid heating road face snow-melting system simulation model realities
Show the calculating of system operation snow melt effect, and proposed the evaluation method of system economical operation benefit, realizes operating cost
Prediction system optimized operation strategy is proposed based on snow melt effect and economic benefit Bi-Objective Optimization Method.
The invention has the following advantages that
1) based on the tentative calculation of simulation model, the building in multi-state tactful snow melt effect data library entirely is realized, this method can
Quickly to calculate and export the system snow melt effect under specific operation condition and specific run strategy.
2) it is based on regression analysis, establishes the governing equation of system operation transmitting heat flow density, and by physical analysis, is taken off
The inherent physical link of transmitting heat flow density and system consumption heat, and the fortune of the transform mode computing system by electricity price are shown
Row cost.
3) evaluation method of system operation cost is proposed, it can be more different in specific running environment for user
Economic cost caused by strategy.
4) it is based on multi-objective planning method, establishes the Optimized model of system running policy, and proposes system operation plan
The slightly evaluation method of goodness.
5) it is based on intelligent Genetic Algorithm, realizes the solution of strategy optimization model, and propose under different service conditions most
Excellent system running policy.
6) output of optimisation strategy is realized by the way of optimisation strategy control figure, it is easy to use intuitive, for being
System manager adjusts operation reserve in due course.
The present invention can quickly and accurately export the snow melt effect of fluid heating system, and computing system economical operation takes
With, propose for both optimize after system optimal operating parameter, make system run economic cost control lower
Level, while ensure that the snow melt effect of system, make the operation of system and control that there is higher science.
Detailed description of the invention
Fig. 1 is snow melt effect output surface chart under the conditions of operating condition one；
Fig. 2 is snow melt effect output surface chart under the conditions of operating condition two；
Fig. 3 is snow melt effect output surface chart under the conditions of operating condition three；
Fig. 4 is fitness surface chart under the conditions of operating condition one；
Fig. 5 is fitness surface chart under the conditions of operating condition two；
Fig. 6 is fitness surface chart under the conditions of operating condition three；
Fig. 7 is environment temperature 263K, considers the fluid temperature (F.T.) control figure that ratio is 60:40；
Fig. 8 is environment temperature 263K, considers the preheating time control figure that ratio is 60:40.
It is 0.2mm/h, 0.4mm/h, 0.6mm/h, 0.8mm/h, 1.0mm/h that a-e, which has respectively represented snowfall rate, in figure
Curve.
Specific embodiment
Specific embodiment 1: the optimization method of the fluid heating snow-melting system operating parameter based on multiple objective programming includes
Following steps:
Step 1: fluid heating snow-melting system snow melt effect data library is established；
Step 2: snow-melting system snow melt effect data library is heated according to the fluid that step 1 is established, calculates a certain operating condition item
Fluid heats snow-melting system snow melt effect F under part, and the working condition includes environment temperature, intensity of solar radiation, wind speed and drop
Avenge rate；
Step 3: the governing equation by establishing transmitting heat flow density calculates transmitting heat flow density q, according to transmitting hot-fluid
Density q obtains fluid within the scope of the body of unit area road and heats snow-melting system operating cost M；
Step 4: determining economic index R, flows within the scope of the unit area road body obtained according to economic index R to step 3
Body heating snow-melting system operating cost M is evaluated；
Step 5: according to step 2 and step 4, fluid heating snow-melting system fortune is established using the method for multiple objective programming
The Optimized model of row strategy；
Step 6: the Optimized model for the fluid heating snow-melting system operation reserve that step 5 is established is solved, is obtained
Fluid heats snow-melting system optimized operation parameter under a certain working condition, and the fluid heating snow-melting system operating parameter is fluid
Heat the preheating time t of snow-melting systemyrWith fluid temperature (F.T.) Tf；
Step 7: repeating step 6, obtains fluid heating snow-melting system optimized operation parameter set under the conditions of full working scope
It closes, obtains the control figure of fluid heating snow-melting system operating parameter under the conditions of full working scope according to optimized operation parameter sets.
For more intuitively output system optimisation strategy, optimisation strategy control figure is depicted according to multi-state the trial result
Spectrum adjusts the operation reserve of system for system operator in due course for different running environment conditions.
The invention discloses a kind of biobjective scheduling operation reserves for fluid heating road face snow-melting system, are related to
The evaluation of system snow melt effect, the evaluation of economical operation benefit, the evaluation of tactful goodness and the proposition of optimisation strategy, it can be achieved that
System proposes to meet snow melt demand and possesses the Optimal Operation Strategies of reasonable economic benefit under the conditions of multi-state.
Specific embodiment 2: the present embodiment is different from the first embodiment in that: stream is established in the step 1
The detailed process in body heating snow-melting system snow melt effect data library are as follows:
4 environmental parameters and 2 operating parameters are subjected to constant gradient according to local climate condition and choose tentative calculation value, form 6
The snow melt effect tentative calculation grid of dimension, using independently developed fluid heating pavement snow melting system simulation calculation software (dbase:
Fluid heats pavement snow melting system Thaw performance simulation software；Software abbreviation: Thaw performance software for calculation；Registration number:
Simulation and forecast 2018SR439618) is carried out to the operating status of fluid heating snow-melting system, obtains different working conditions and fluid
Heat snow-melting system operating parameter under road surface snow thickness data, use target without snow rate be 100% without avenge the time
Index than (target is without snow time ratio) as evaluation fluid heating snow-melting system snow melt effect, carries out the calculating of snow melt effect；
4 environmental parameters are environment temperature, intensity of solar radiation, wind speed and snowfall rate, and 2 operating parameters are preheating time tyr
With fluid temperature (F.T.) Tf；
Shown in calculating such as formula (1) without snow time ratio:
Wherein W is target without snow time ratio (%), tmeltIt is road table without snow duration (h), tsnowfallFor snowfall duration (h)；
The full working scope fluid of final 6 dimension of building heats snow-melting system snow melt effect data library.
The gradient selection of Beijing Airport parameter is shown in Table 1.
1 snow melt effect responsive parameter gradient value of table
Other steps and parameter are same as the specific embodiment one.
Specific embodiment 3: the present embodiment is different from the first and the second embodiment in that: root in the step 2
Snow-melting system snow melt effect data library is heated according to the fluid that step 1 is established, fluid under a certain working condition is calculated and heats snow melt system
The detailed process of system snow melt effect F are as follows:
Snow-melting system snow melt effect data library is heated according to the fluid that step 1 is established, carries out certain using linear interpolation function
The calculating of the snow melt effect of one working condition and system operational parameters.Pavement snow melting system simulation calculation software is heated in fluid
In, need to input the thermodynamic parameter and system Construction geometric parameter of road body structure, the value of parameter need to be according to studying
The actual set of system is determined.Snow melt effect under certain environmental conditions is as shown in Figure 1-Figure 3.
Other steps and parameter are the same as one or two specific embodiments.
Specific embodiment 4: unlike one of present embodiment and specific embodiment one to three: the step 3
In by establish transmitting heat flow density governing equation, calculate transmitting heat flow density q, according to transmitting heat flow density q obtain unit
The detailed process of fluid heating snow-melting system operating cost M within the scope of the body of area road are as follows:
Using independently developed fluid heating pavement snow melting system simulation calculation software to the fortune of fluid heating snow-melting system
Row state carries out simulation and forecast, obtains the transmitting heat flow density q versus time curve that road is transferred to by fluid；It is based on
This, the responsive parameter to economic benefit include environment temperature, intensity of solar radiation, 3 environmental parameters of wind speed, fluid temperature (F.T.) and
Preheating time, 2 policing parameters carried out parametric regression analysis, the governing equation of transmitting heat flow density were established, for Beijing Airport
Heat flow density governing equation such as formula (2) shown in:
Wherein p1And p2For the corrected parameter of intensity of solar radiation, t is system operation time, and k is wind speed correction factor,
Tamb is environment temperature；
When intensity of solar radiation is 0W/m2When:
When intensity of solar radiation is 50W/m2When:
When intensity of solar radiation is 100W/m2When:
When intensity of solar radiation is 200W/m2When:
Heat flow density is converted to by formula (3) and formula (4) operating cost of system；
Q=∫ qd (S) d (t) (3)
M=Q/ μ × m (4)
Wherein Q is the heat (J) consumed in system operation, and S is heat transfer area (m2), μ is converting heat efficiency, and m is to work as
Ground electricity price (member/degree).
Thereby establish the economic model of system operation.
Other steps and parameter are identical as one of specific embodiment one to three.
Specific embodiment 5: unlike one of present embodiment and specific embodiment one to four: the step 4
Middle determining economic index R, fluid heats snow-melting system within the scope of the unit area road body obtained according to economic index R to step 3
The detailed process that operating cost M is evaluated are as follows:
Economic index R is determined using formula (5):
R(Tf,tyr)=100- (M (Tf,tyr)-Mmin)/(Mmax-Mmin)×100 (5)
Wherein MmaxFor economic cost maximum value in all operating parameters, MminIt is minimum for economic cost in all operating parameters
Value；
Using economic index as the index of evaluation system economical operation benefit, when systematic running cost reaches minimum value
Economic index R (Tf, tyr)=100, when systematic running cost reaches maximum value, R (Tf, tyr)=0.
Other steps and parameter are identical as one of specific embodiment one to four.
Specific embodiment 6: unlike one of present embodiment and specific embodiment one to five: the step 5
It is middle according to step 2 and step 4, the optimization mould of fluid heating snow-melting system operation reserve is established using the method for multiple objective programming
The detailed process of type are as follows:
Calculating based on front snow melt effect and operating cost establishes system running policy using the method for multiple objective programming
Optimized model, as shown in formula (6):
MaxO=w1F(Tf,tyr)+w2R(Tf,tyr)
s.t.0≤tyr≤6
293≤Tf≤323 (6)
Wherein O is the fitness value for evaluating operating parameter, w1And w2To run snow melt effect and fortune to system in operating parameter
Row cost considers ratio, and F is that system runs snow melt effect.
In model, it is contemplated that the economic benefit of system operation will control within 6h, it is contemplated that Lu Tijie preheating time
Temperature second inner force inside structure, by fluid temperature (F.T.) control between 293-323K (20-50 DEG C).
The model proposes the index of evaluation system operation reserve goodness: fitness value, and the fitness value that model calculates is got over
Greatly, the goodness for characterizing the operation reserve is higher.
Other steps and parameter are identical as one of specific embodiment one to five.
Specific embodiment 7: unlike one of present embodiment and specific embodiment one to six: the step 6
In to step 5 establish fluid heating snow-melting system operation reserve Optimized model solve, obtain under a certain working condition
Fluid heating snow-melting system optimized operation parameter obtains detailed process are as follows:
It is solved using Optimized model of the genetic algorithm to the fluid heating snow-melting system operation reserve that step 5 is established,
Genetic manipulation includes gene intersection and genetic mutation in genetic algorithm, using the random method for generating operation point；Genetic algorithm
Selection mode uses tournament method.
Other steps and parameter are identical as one of specific embodiment one to five.
Beneficial effects of the present invention are verified using following embodiment:
Embodiment one:
For calculating operating condition Parameter Conditions as shown in Table 2.
2 strategy optimization model of table solves working condition
Such as Fig. 4-Fig. 6, the optimisation strategy under the conditions of operating condition three is exported, can be searched excellent under corresponding working condition
It is as shown in Figure 7 and Figure 8 to change policy control figure.Ratio w1, w2 and different environment temperatures are considered for different operations, is drawn altogether
30 policy control figures are made, respectively output optimization fluid temperature (F.T.) and optimization preheating time, Fig. 7 and Fig. 8 show only wherein two
Width.Its interpreting blueprints mode is to stress ratio according to environment temperature and strategy to find corresponding policy control figure, is sought in figure indsole coordinate
Corresponding intensity of solar radiation is looked for, extends meet at corresponding wind speed oblique line then up, then horizontal direction extension meets at snowfall
Rate curve is upwardly extended in point of intersection, obtains the Optimal Operation Strategies under the working condition.
The present invention can also have other various embodiments, without deviating from the spirit and substance of the present invention, this field
Technical staff makes various corresponding changes and modifications in accordance with the present invention, but these corresponding changes and modifications all should belong to
The protection scope of the appended claims of the present invention.
Claims (7)
1. the optimization method of the fluid heating snow-melting system operating parameter based on multiple objective programming, it is characterised in that: the fluid
Heat snow-melting system operating parameter optimization method the following steps are included:
Step 1: fluid heating snow-melting system snow melt effect data library is established；
Step 2: snow-melting system snow melt effect data library is heated according to the fluid that step 1 is established, is calculated under a certain working condition
Fluid heats snow-melting system snow melt effect F, and the working condition includes environment temperature, intensity of solar radiation, wind speed and snowfall speed
Rate；
Step 3: the governing equation by establishing transmitting heat flow density calculates transmitting heat flow density q, according to transmitting heat flow density q
It obtains fluid within the scope of the body of unit area road and heats snow-melting system operating cost M；
Step 4: determining economic index R, and fluid adds within the scope of the unit area road body obtained according to economic index R to step 3
Hot snow-melting system operating cost M is evaluated；
Step 5: according to step 2 and step 4, fluid heating snow-melting system operation plan is established using the method for multiple objective programming
Optimized model slightly；
Step 6: the Optimized model for the fluid heating snow-melting system operation reserve that step 5 is established is solved, is obtained a certain
Fluid heats snow-melting system optimized operation parameter under working condition, and the fluid heating snow-melting system operating parameter is fluid heating
The preheating time t of snow-melting systemyrWith fluid temperature (F.T.) Tf；
Step 7: repeating step 6, obtains fluid heating snow-melting system optimized operation parameter sets under the conditions of full working scope, root
The control figure of fluid heating snow-melting system operating parameter under the conditions of full working scope is obtained according to optimized operation parameter sets.
2. the optimization method of the fluid heating snow-melting system operating parameter based on multiple objective programming according to claim 1,
It is characterized in that: establishing the detailed process in fluid heating snow-melting system snow melt effect data library in the step 1 are as follows:
4 environmental parameters and 2 operating parameters are subjected to constant gradient according to local climate condition and choose tentative calculation value, form 6 dimensions
Snow melt effect tentative calculation grid, the operation using fluid heating pavement snow melting system simulation calculation software to fluid heating snow-melting system
State carries out simulation and forecast, and the road surface snow deposit obtained under different working conditions and fluid heating snow-melting system operating parameter is thick
Degree evidence uses target without snow rate for 100% finger without the snow time than heating snow-melting system snow melt effect as evaluation fluid
Mark carries out the calculating of snow melt effect；4 environmental parameters be environment temperature, intensity of solar radiation, wind speed and snowfall rate, 2
A operating parameter is preheating time tyrWith fluid temperature (F.T.) Tf；
Shown in calculating such as formula (1) without snow time ratio:
Wherein W is target without snow time ratio, tmeltIt is road table without snow duration, tsnowfallFor snowfall duration；
The full working scope fluid of final 6 dimension of building heats snow-melting system snow melt effect data library.
3. the optimization method of the fluid heating snow-melting system operating parameter according to claim 1 or claim 2 based on multiple objective programming,
It is characterized by: heating snow-melting system snow melt effect data library according to the fluid that step 1 is established in the step 2, certain is calculated
The detailed process of fluid heating snow-melting system snow melt effect F under one working condition are as follows:
Snow-melting system snow melt effect data library is heated according to the fluid that step 1 is established, carries out a certain work using linear interpolation function
The calculating of the snow melt effect of condition condition and system operational parameters.
4. the optimization method of the fluid heating snow-melting system operating parameter based on multiple objective programming according to claim 3,
It is characterized in that: by establishing the governing equation of transmitting heat flow density in the step 3, transmitting heat flow density q is calculated, according to biography
It passs heat flow density q and obtains the detailed process of fluid heating snow-melting system operating cost M within the scope of the body of unit area road are as follows:
It is simulated using operating status of the fluid heating pavement snow melting system simulation calculation software to fluid heating snow-melting system
Prediction, obtains the transmitting heat flow density q versus time curve that road is transferred to by fluid；To environment temperature, solar radiation
Intensity, wind speed, fluid temperature (F.T.) and preheating time carry out parametric regression analysis, the governing equation of transmitting heat flow density are established, such as formula
(2) shown in:
Wherein p1And p2For the corrected parameter of intensity of solar radiation, t is system operation time, and k is wind speed correction factor, and Tamb is
Environment temperature；
When intensity of solar radiation is 0W/m2When:
When intensity of solar radiation is 50W/m2When:
When intensity of solar radiation is 100W/m2When:
When intensity of solar radiation is 200W/m2When:
Heat flow density is converted to by formula (3) and formula (4) operating cost of system；
Q=∫ qd (S) d (t) (3)
M=Q/ μ × m (4)
Wherein Q is the heat consumed in system operation, and S is heat transfer area, and μ is converting heat efficiency, and m is local electricity price.
5. the optimization method of the fluid heating snow-melting system operating parameter based on multiple objective programming according to claim 4,
It is characterized in that: determining economic index R, the unit area Lu Tifan obtained according to economic index R to step 3 in the step 4
Enclose the detailed process that interior fluid heating snow-melting system operating cost M is evaluated are as follows:
Economic index R is determined using formula (5):
R(Tf,tyr)=100- (M (Tf,tyr)-Mmin)/(Mmax-Mmin)×100
Wherein MmaxFor economic cost maximum value in all operating parameters, MminFor economic cost minimum value in all operating parameters；
Economy using economic index as the index of evaluation system economical operation benefit, when systematic running cost reaches minimum value
Index R (Tf, tyr)=100, when systematic running cost reaches maximum value, R (Tf, tyr)=0.
6. the optimization method of the fluid heating snow-melting system operating parameter based on multiple objective programming according to claim 5,
It is characterized in that: according to step 2 and step 4 in the step 5, fluid heating snow melt being established using the method for multiple objective programming
The detailed process of the Optimized model of system running policy are as follows:
The Optimized model that system running policy is established using the method for multiple objective programming, as shown in formula (6):
MaxO=w1F(Tf,tyr)+w2R(Tf,tyr)
s.t.0≤tyr≤6
293≤Tf≤323 (6)
Wherein O is the fitness value for evaluating operating parameter, w1And w2For in operating parameter to system run snow melt effect and operation at
This considers ratio, and F is that system runs snow melt effect.
7. the optimization method of the fluid heating snow-melting system operating parameter based on multiple objective programming according to claim 6,
Be characterized in that: the Optimized model for the fluid heating snow-melting system operation reserve established in the step 6 to step 5 is asked
Solution obtains fluid heating snow-melting system optimized operation parameter under a certain working condition and obtains detailed process are as follows:
It is solved using Optimized model of the genetic algorithm to the fluid heating snow-melting system operation reserve that step 5 is established, heredity
Genetic manipulation includes gene intersection and genetic mutation in algorithm, using the random method for generating operation point；Genetic algorithm selection
Mode uses tournament method.
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