CN110500291A - A kind of multiple ontology control method based on genetic algorithm - Google Patents
A kind of multiple ontology control method based on genetic algorithm Download PDFInfo
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
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Abstract
A kind of multiple ontology control method based on genetic algorithm, comprising the following steps: step 1. is directed to multiple ontology water system, establishes system pipe network characteristic curve governing equation；Flow and lift needed for step 2. acquisition system, establish pump head and power characteristic equation；Step 3. flow and lift demand according to needed for system defines initial population scale, calculates water pump operation parameter and determines individual chromosome structure；Step 4. analysis system bulk flow and power parameter establish flow and efficiency optimization objective function；Step 5. is based on genetic algorithm, carries out binary coding to individual chromosome, while the optimization of water pump system operating parameter is realized using fitness function and selection, variation, crossover operator；Step 6. determines water pump optimal operating parameter, carries out dynamic adjustment to the setup parameter of water pump controller.Flow and pressure needed for the present invention guarantees water system reduce system overall operation energy consumption.
Description
Technical field
The invention belongs to centrifugal pump method for controlling frequency conversion fields, and in particular to a kind of multiple ontology based on genetic algorithm
Control method is mainly used for quickly and effectively carrying out optimized control to the water pump operation parameter in multiple ontology water system,
Under the premise of the flow needed for guaranteeing water system and pressure, to promote water pump comprehensive operation efficiency, system fortune is further decreased
Row energy consumption.
Background technique
The control of water pump is a complicated engineering in multiple ontology water system, in order to reduce the operation of water system
Energy consumption is needed for different resistance of pipe system characteristics, and control water pump assembly provides required flow and lift, to meet user
The water demand of side.Water supply condensation technique mainly uses frequency conversion+industrial frequency control technology and full frequency conversion control technique at present, uses
Frequency conversion+power frequency control technology, existing main problem are that the flow of its output and lift need to be adjusted by valve
Section can generate biggish pressure drop when system deviates high-efficiency point operation at valve, and system operation energy consumption increases, system operation
Stability is poor, is unfavorable for energy conservation and environmental protection.With the application of the full converter technique of intelligence, by configuring frequency control for every water pump
Device realizes the automatic control of pump capacity and pressure, and still, current most of full frequency-conversion water supply systems are used to be calculated based on PID
The constant pressure control method of method (i.e. proportional-integral-differential algorithm), He Wanglin is in a kind of its patent " constant pressure water supply device "
(patent No.: 208533622 U of CN) and Zhang Heqing are in a kind of its patent " constant pressure water supply system " (patent No.: CN
208650145 U) in propose a kind of constant pressure water supply technology, which becomes by using PLC, frequency converter and pressure
Device is sent, realizes the frequency control of water pump, to guarantee the constant of outlet pressure, meets the needs of user side is to hydraulic pressure, however, working as
When the system-head curve of system changes, flow needed for system and pressure can also change, and full frequency conversion and unvarying pressure control side
Method is still run by the pressure initially set up, leads to the too high or too low problem of system pressure, and the flow that simultaneity factor provides can not yet
With actually required flow matches, the waste of the unstability and portion of energy that cause system to run.Sun Tian et al. is in its patent
A kind of base is proposed in " a kind of cooling method for controlling pump of parallel connection based on genetic algorithm " (patent No.: 106016605 A of CN)
In the cooling method for controlling pump of the air-conditioning system of genetic algorithm, this method is more by the working efficiency and statistics for calculating single pump
The system working efficiency of platform pump realizes that cooling pump group is in energy consumption minimum state using efficiency highest as goal of regulation and control.But
The control object of this method is general pump, cannot achieve the control to water pump operation frequency, and the control of pressure and flow then according to
Old to be adjusted using valve, system still has flow and hypertonia or too low problem, and system operation energy consumption is still larger.
Summary of the invention
The technical problem to be solved by the present invention is to there are following for the control method of existing multiple ontology water system
A few class disadvantages: 1) water pump easily deviates and runs under design conditions, and system is there are hypertonia, energy consumption are excessive, and with hydrodynamic
And vibration problem；2) initially setting Isobarically Control mode can not adapt to the system-head curve of real-time change, system easily occur pressure and
The too high or too low problem of flow.The multiple ontology control method based on genetic algorithm that the object of the present invention is to provide a kind of, for
Specific water supply pipe net system is based on flow and efficiency optimization objective function by flow and lift needed for computing system,
Water pump assembly optimal operating parameter is determined using genetic algorithm, with flow and pressure needed for guaranteeing water system, reduces system
Overall operation energy consumption.
The technical solution adopted by the present invention to solve the technical problems is:
A kind of multiple ontology control method based on genetic algorithm, comprising the following steps:
Step 1. is directed to multiple ontology water system, establishes system pipe network characteristic curve governing equation
Fig. 2 is multiple ontology water system, and whole system includes: frequency-variable controller D01, D02 and D03, water pump D04,
D05 and D06, pressurized tank D07, water inlet manifold D08, outfall sewer D09；Frequency-variable controller D01, D02 and D03 are respectively to water pump
D04, D05 and D06 are controlled, by the control of pump rotary speed, to realize the control of flow and lift；The work of whole system
Make mode are as follows: water passes through pressurized tank D07, is pressurized into water inlet manifold D08, then by water pump D04, D05 and D06 to it, increases
Water after pressure reaches user side by outfall sewer D09；For the normal operation for guaranteeing whole system, water pump D04, D05 and D06
Provided pressure needs to overcome the resistance of pipe system of system, while the flow provided will meet the needs of system；If water pump
The flow and lift of offer are excessively high, then generate biggish pressure drop when passing through valve, increase the operation energy consumption of system, conversely, working as water
When the flow and too low lift provided is provided, then the demand of user side is unable to satisfy, it may appear that the problems such as hydraulic pressure deficiency and water shortage；
The resistance of pipe system of water system include the pressure loss of particular flow rate lower pipeline, the pressure loss of pressurized tank and
The local pressure loss of control valve, wherein the pressure loss of pipeline is determined by the resistance coefficient of flow velocity and pipeline, control valve
Local pressure loss mainly determine that valve opening is bigger by the aperture of valve, resistance is smaller；In order to realize to multiple ontology
The intelligent control of system, needs exist for the pipe system performance curve equation for establishing system, and Fig. 3 is water system pipe system performance curve
Schematic diagram, shown in corresponding expression formula such as formula (1)；
Hr=kQr 2+H0 (1)
In formula, HrFor total (pumping) head needed for system, QrFor total flow needed for system, H0For the initial ductwork pressure of system, k
For resistance of pipe system characteristic coefficient；
Flow and lift needed for step 2. acquisition system, establish pump head and power characteristic equation
Use regimen condition based on user side obtains the flow and lift provided needed for water system, and value is respectively QrWith
Hr, in order to calculate the flow and power of water pump, need to establish the characteristic equation of water pump, Fig. 4 is difference corresponding to separate unit water pump
Frequency down-off-lift performance curve, Fig. 5 is different frequency down-off-power-performance curve corresponding to separate unit water pump, more
In Parallel pump scheme, used three water pumps, model is identical, it is therefore possible to use same group of characteristic equation is expressed,
The corresponding specific value of performance curve based on Fig. 4 and Fig. 5, the lift and power characteristic equation of available water pump, is adopted here
It is expressed with 3 order polynomial approximate equations, shown in calculation formula such as formula (2) and (3)；
H=a00+a10f+a01Q+a20f2+a11fQ+a02Q2+a21f2Q+a12fQ2+a03Q3+a30f3 (2)
P=b00+b10f+b01Q+b20f2+b11fQ+b02Q2+b21f2Q+b12fQ2+b03Q3+b30f3 (3)
In formula, Q is the output flow of water pump, and P is the input power of water pump driving motor, and f is the running frequency of water pump, H
For the output lift of water pump, a00To a30For the coefficient of lift characteristic equation, b00To b30For the coefficient of power characteristic equation；
By formula (2) and (3), lift and performance number under available different frequency and flow, to guarantee subsequent water
The calculating of pump operation parameter and the iterative solution of genetic algorithm；
Step 3. flow and lift demand according to needed for system defines initial population scale, calculates water pump operation parameter simultaneously
Determine individual chromosome structure
Based on flow Q needed for systemrWith required lift Hr, optimized by defining the scale of initial population to control
The convergence rate of solution and the diversity of population, usual population scale N are controlled between 20 to 200 (i.e. N=20~200), with
Afterwards by calculating the operating parameter of water pump, individual specimen needed for determining initial population；Fig. 6 is water pump operation parameter computation
Process, step include: the number of units that B01 defines water pump, and the corresponding water pump quantity of system is 3 here；B02 determines every at random
The running frequency of platform pump, according to frequency accidental function fi=Rand (0 ... fmax), determine the running frequency of specified water pump, fiIt is
The frequency of i platform water pump, fmaxFor the maximum value of frequency, i.e. 50Hz；B03 determines the lift of every pump at random, random according to lift
Function Hi=Rand (0 ... Hmax), determine the lift of specified water pump, HiFor the lift of i-th water pump, HmaxFor the maximum of lift
Value；B04 is based on the frequency f being calculated at randomiWith lift Hi, the flow of every pump is calculated according to formula (2)；B05 judges three
Whether platform pump calculates completion, completes if calculated, and enters in next step, and otherwise, return is calculated again；B06 calculates specific
Parallel water pump system total flow Q under operating parametersys, the flow Q based on the calculating of three water pumps1、Q2And Q3, pass through formula Qsys
=∑ (QI) obtain system total flow Qsys；B07 passes through comparison system total flow QsysWith flow Q needed for systemrAnd single pump
Lift HiWith lift H needed for systemrSize, to determine whether individual specimen calculated meets performance requirement；B08 is based on sentencing
Determine as a result, determining qualified individuals sample, concurrently sets the corresponding chromosome structure of individual specimen, composition includes: #1 water pump
Corresponding operating parameter (the f of D04#1, H#1, Q#1), the corresponding operating parameter (f of #2 water pump D05#2, H#2, Q#2), #3 water pump
Corresponding operating parameter (the f of D06#3, H#3, Q#3)；
Step 4. analysis system bulk flow and power parameter establish flow and efficiency optimization objective function
The system bulk flow Q being calculated by step 3sysAnd every water pump consumption that formula (3) is calculated
Power Pi, establish multiple ontology flow system flow and efficiency optimization objective function F (Q) and F (η), flow and efficiency goal function
Respectively as shown in formula (4) and (5):
F (Q)=Min (Δ Q)=Min (| Qsys-Qr|/Qr) (4)
In formula, Δ Q is the ratio of flow needed for the difference and system of flow needed for system actual flow and system, that is, is flowed
Measure flood rate, η be system gross efficiency, i.e., the sum of three water pump output powers and three water pump driving motor input powers it
The ratio of sum, ρ are the density of water, and g is acceleration of gravity；
Step 5. is based on genetic algorithm, carries out binary coding to individual chromosome, while using fitness function and choosing
It selects, make a variation, the optimization of crossover operator realization water pump system operating parameter
Genetic algorithm is made of coding, fitness function, genetic operator (selection intersects, variation) and operating parameter, whole
A solution procedure is as shown in fig. 7, specifically include following steps: C01 determines the initialization fortune of chromosome structure and every pump
Row parameter；C02 encodes individual chromosome structure, is encoded to the decimal system to binary conversion, due to the original decimal system
The format of numerical value is that decimal point retains one, in order to quickly and effectively carry out Binary Conversion, here by that will have decimal
Decimal value carries out integer processing multiplied by 10, and the decimal value of integer is finally carried out Binary Conversion, obtains
Efficient coding, each operating parameter uses 9 efficient codings, less than 9, is carried out in coding right-most position by mending " 0 "
It supplies；Three water pumps, every water pump include 3 frequency, lift and flow operating parameters, amount to 9 operating parameters, coding is total
A length of 81；C03 defines genetic algorithm the number of iterations n, and for EQUILIBRIUM CALCULATION FOR PROCESS time and precision, the number of iterations is set as n=
10000；C04 uses genetic operator: selection, intersects at variation, handles individual specimen, defines fitness function G first,
Fitness function reflects the distance between each chromosome and Optimum Solution chromosome, shown in the expression formula of G such as formula (6):
Fitness function is made of the inverse of system total efficiency and flow flood rate, and the numerical value which calculates is bigger, is said
Bright individual chromosome is closer to optimal solution chromosome；Then, by selection operator by the high individual inheritance of fitness to the next generation
Population；Moreover new individual is obtained by mutation operator, and when operation, needs to define aberration rate, and value range is 0.005~
0.01, Fig. 8 is individual chromosome mutation operator schematic diagram, and mutation operator is by the random function definitive variation position that uniformly makes a variation, so
Original gene is replaced by other allele afterwards, in fig. 8, " 1 " that makes a variation on position is substituted for " 0 ", to generate new
Body；Meanwhile new individual is obtained using crossover operator, and when operation, needs to define crossover probability, and value range is 0.4~
0.99, Fig. 9 is individual chromosome crossing operation schematic diagram, and crossing operation sets an intersection by single point crossing method at random
Point, when carrying out intersection, two individual part-structures after the point are interchangeable, and generate two new individuals, i.e., original
Body A and individual B is by after crossing operation, generating new individual A and new individual B；C05 is based on optimizing flow and efficiency mesh
Scalar functions, the individual specimen in population after solving to genetic algorithm is assessed, to obtain optimum solution；C06 determines iteration time
Whether number reaches setting value n=10000, if it exceeds then stopping iteration；C07 genetic algorithm optimization terminates, and obtains flow and overflows
Rate is minimum, the highest water pump optimal operating parameter solution of system total efficiency, and carries out Gray code to optimum solution, and converting thereof into can
The strong decimal system of the property read；C08 carries out Gray code operation to optimum solution, binary numeral is transformed into decimal value first, so
Numerical value is carried out reduction treatment, obtain final water pump operation parametric optimal solution divided by 10 afterwards；
Step 6. determines water pump optimal operating parameter, carries out dynamic adjustment to the setup parameter of water pump controller
Water pump optimal operating parameter is determined by step 5 for particular system pepeline characteristic, by 1# water pump D04,2# water
Pump the frequency values f in D05 and 3# water pump D06 operating parameter1#, f2#, f3#As setting value be written frequency-variable controller D01, D02 and
D03 carries out dynamic and intelligent adjustment to system, to guarantee flow and pressure needed for water system, promotes water pump integrated operation effect
Rate reduces system operation energy consumption.
The present invention is directed to the water system of different system-head curves, by introducing pump characteristics equation and genetic algorithm, with reality
Now to the adjust automatically of multiple ontology water system flow, lift and frequency, the flow needed for guaranteeing water system and pressure
Under the premise of, so that the overall operation efficiency of water pump assembly is optimal value, system operation energy consumption is greatly reduced.Therefore, this method
With important science and engineering application value.
Beneficial effects of the present invention are mainly manifested in: 1) being based on water system system-head curve equation and pump performance characteristic
Equation can rapidly and accurately obtain water pump operation parameter；2) it is calculated based on flow and efficiency optimization objective function and heredity
Method can be quickly found out system optimal operating parameter, realize the adjust automatically of water pump operation parameter, guarantee water system institute
Under the premise of needing flow and pressure, system overall operation energy consumption is reduced；3) compared with traditional general pump water system, based on something lost
The multiple ontology control system power saving rate of propagation algorithm reaches as high as 44%.
Detailed description of the invention
Fig. 1 is the multiple ontology control method flow chart based on genetic algorithm.
Fig. 2 is multiple ontology water system schematic diagram.
Fig. 3 is multiple ontology system pipe network characteristic curve schematic diagram.
Fig. 4 is different frequency down-off-lift performance curve schematic diagram corresponding to separate unit water pump.
Fig. 5 is different frequency down-off-power-performance curve synoptic diagram corresponding to separate unit water pump.
Fig. 6 is water pump operation parameter computation flow diagram.
Fig. 7 is genetic algorithm optimization flow diagram.
Fig. 8 is individual chromosome mutation operator schematic diagram.
Fig. 9 is individual chromosome crossing operation schematic diagram.
Specific embodiment
The invention will be further described below in conjunction with the accompanying drawings.
Referring to Fig.1~Fig. 9, a kind of multiple ontology control method based on genetic algorithm, comprising the following steps:
Step 1 establishes multiple ontology water system pipe system performance curve；
Flow Q needed for step 2 acquisition systemrWith lift Hr；
Step 3 establishes pump characteristics equation Hi=H (Qi,fi) and Pi=P (Qi,fi)；
Step 4 defines initial population scale；
Step 5 calculates water pump operation parameter；
Step 6 establishes flow, efficiency optimization objective function；
Step 7 is based on genetic algorithm and is iterated solution；
Step 8 determines water pump optimal operating parameter, carries out dynamic adjustment to the operating parameter of controller.
In the present embodiment, a kind of multiple ontology control method based on genetic algorithm, comprising the following steps:
Step 1. is directed to multiple ontology water system, establishes system pipe network characteristic curve governing equation
Fig. 2 is multiple ontology water system, and whole system includes: frequency-variable controller D01, D02 and D03, frequency-variable controller
Power be 2.2kW, tuning range be 10Hz to 50Hz, water pump D04, D05 and D06, the model of three water pumps is consistent, right
Running parameter under the 50Hz answered are as follows: metered flow 17m3/ h, rated head 23m, rated speed 3000r/min are specified
Power is 2.2kW, pressurized tank D07, water inlet manifold D08, outfall sewer D09；Frequency-variable controller D01, D02 and D03 are respectively to water
Pump D04, D05 and D06 are controlled, by the control of pump rotary speed, to realize the control of flow and lift；Whole system
Working method are as follows: water passes through pressurized tank D07, increases into water inlet manifold D08, then by water pump D04, D05 and D06 to it
Pressure, pressurized water reach user side by outfall sewer D09；For the normal operation for guaranteeing whole system, water pump D04, D05
Need to overcome the resistance of pipe system of system with pressure provided by D06, while the flow provided will meet the needs of system；If
The flow and lift that water pump provides are excessively high, then generate biggish pressure drop when passing through valve, increase the operation energy consumption of system, conversely,
When the flow and too low lift that water pump provides, then the demand of user side is unable to satisfy, it may appear that hydraulic pressure deficiency and water shortage etc. are asked
Topic；
The resistance of pipe system of water system include the pressure loss of particular flow rate lower pipeline, the pressure loss of pressurized tank and
The local pressure loss of control valve, wherein the pressure loss of pipeline is determined by the resistance coefficient of flow velocity and pipeline, control valve
Local pressure loss mainly determine that valve opening is bigger by the aperture of valve, resistance is smaller；In order to realize to multiple ontology
The intelligent control of system, needs exist for the pipe system performance curve equation for establishing system, and Fig. 3 is water system pipe system performance curve
Schematic diagram, shown in corresponding expression formula such as formula (1)；
Hr=kQr 2+H0 (1)
In formula, HrFor total (pumping) head needed for system, QrFor total flow needed for system, H0For the initial ductwork pressure of system, k
For resistance of pipe system characteristic coefficient；
The water system flow and pressure value are obtained by measurement, as flow QrWhen being 0, corresponding pressure Hr=H0=
0m, as flow QrFor 39m3When/h, corresponding pressure Hr=15m；Bring corresponding value into formula (1), available k=
0.009862, therefore formula (1) can be converted are as follows: Hr=0.009862Qr 2；
Flow and lift needed for step 2. acquisition system, establish pump head and power characteristic equation
Use regimen condition based on user side obtains the flow and lift provided needed for water system, and value is respectively Qr=
39m3/ h and Hr=15m needs to establish the characteristic equation of water pump to calculate the flow and power of water pump, and Fig. 4 is separate unit water pump
Corresponding different frequency down-off-lift performance curve, Fig. 5 are different frequency down-off-power corresponding to separate unit water pump
Performance curve, in multiple ontology system, used three water pumps, model is identical, it is therefore possible to use same group of characteristic
Equation is expressed, the corresponding specific value of the performance curve based on Fig. 4 and Fig. 5, the lift and power characteristic of available water pump
Equation is expressed using 3 order polynomial approximate equations here, shown in calculation formula such as formula (2) and (3)；
H=a00+a10f+a01Q+a20f2+a11fQ+a02Q2+a21f2Q+a12fQ2+a03Q3+a30f3 (2)
P=b00+b10f+b01Q+b20f2+b11fQ+b02Q2+b21f2Q+b12fQ2+b03Q3+b30f3 (3)
In formula, Q is the output flow of water pump, and P is the input power of water pump driving motor, and f is the running frequency of water pump, H
For the output lift of water pump, a00To a30It can by bringing the numerical value in Fig. 4 into formula (2) for the coefficient of lift characteristic equation
It is obtained with approximate calculation: a00=-1.049, a10=0.1002, a01=0.01198, a20=0.008444, a11=
0.0007731, a02=-0.02513, a21=-0.0001039, a12=0.0006579, a03=-0.0009518, a30=
3.158e-05；b00To b30It can be approximate by bringing the numerical value in Fig. 5 into formula (3) for the coefficient of power characteristic equation
It is calculated: b00=-0.04764, b10=0.004457, b01=0.0008245, b20=-0.0001343, b11=-
4.824e-05 b02=2.506e-06, b21=2.882e-05, b12=9.674e-06, b03=-5.365e-05, b30=
6.614e-06；
By formula (2) and (3), lift and performance number under available different frequency and flow, to guarantee subsequent water
The calculating of pump operation parameter and the iterative solution of genetic algorithm；
Step 3. flow and lift demand according to needed for system defines initial population scale, calculates water pump operation parameter simultaneously
Determine individual chromosome structure
Based on flow Q needed for systemr=39m3/ h and required lift Hr=15m, by the rule for defining initial population
Mould controls the convergence rate of optimization and the diversity of population, defines population scale N=100 here, then passes through meter
Calculate the operating parameter of water pump, individual specimen needed for determining initial population；Fig. 6 is water pump operation parameter computation process, step
It suddenly include: the number of units that B01 defines water pump, the corresponding water pump quantity of system is 3 here；B02 determines the operation of every pump at random
Frequency, according to frequency accidental function fi=Rand (0 ... fmax), determine the running frequency of specified water pump, fiFor i-th water pump
Frequency, fmaxFor the maximum value of frequency, i.e. 50Hz；B03 determines the lift of every pump at random, according to lift random function Hi=
Rand(0…Hmax), determine the lift of specified water pump, HiFor the lift of i-th water pump, HmaxFor the maximum value of lift；B04 base
In the frequency f being calculated at randomiWith lift Hi, the flow of every pump is calculated according to formula (2)；Whether B05 judges three pumps
It calculates and completes, completed if calculated, entered in next step, otherwise, return is calculated again；B06 calculates specific run ginseng
Parallel water pump system total flow Q under severalsys, the flow Q based on the calculating of three water pumps1、Q2And Q3, pass through formula Qsys=∑
(Qi) obtain system total flow Qsys；B07 passes through comparison system total flow QsysWith flow Q needed for systemrAnd separate unit pump lift
HiWith lift H needed for systemrSize, to determine whether individual specimen calculated meets performance requirement；B08 is based on determining knot
Fruit determines qualified individuals sample, concurrently sets the corresponding chromosome structure of individual specimen, composition includes: #1 water pump D04
Corresponding operating parameter (f#1, H#1, Q#1), the corresponding operating parameter (f of #2 water pump D05#2, H#2, Q#2), D06 pairs of #3 water pump
Operating parameter (the f answered#3, H#3, Q#3)；
Step 4. analysis system bulk flow and power parameter establish flow and efficiency optimization objective function
The system bulk flow Q being calculated by step 3sysAnd every water pump consumption that formula (3) is calculated
Power Pi, establish multiple ontology flow system flow and efficiency optimization objective function F (Q) and F (η), flow and efficiency goal function
Respectively as shown in formula (4) and (5):
F (Q)=Min (Δ Q)=Min (| Qsys-Qr|/Qr) (4)
In formula, Δ Q is the ratio of flow needed for the difference and system of flow needed for system actual flow and system, that is, is flowed
Measure flood rate, η be system gross efficiency, i.e., the sum of three water pump output powers and three water pump driving motor input powers it
The ratio of sum, ρ are the density of water, and g is acceleration of gravity；
Step 5. is based on genetic algorithm, carries out binary coding to individual chromosome, while using fitness function and choosing
It selects, make a variation, the optimization of crossover operator realization water pump system operating parameter
Genetic algorithm is made of coding, fitness function, genetic operator (selection intersects, variation) and operating parameter, whole
A solution procedure is as shown in fig. 7, specifically include following steps: C01 determines the initialization fortune of chromosome structure and every pump
Row parameter；C02 encodes individual chromosome structure, is encoded to the decimal system to binary conversion, due to the original decimal system
The format of numerical value is that decimal point retains one, in order to quickly and effectively carry out Binary Conversion, here by that will have decimal
Decimal value carries out integer processing multiplied by 10, and the decimal value of integer is finally carried out Binary Conversion, obtains
Efficient coding, each operating parameter uses 9 efficient codings, less than 9, is carried out in coding right-most position by mending " 0 "
It supplies；Three water pumps, every water pump include 3 frequency, lift and flow operating parameters, amount to 9 operating parameters, coding is total
A length of 81；C03 defines genetic algorithm the number of iterations n, and for EQUILIBRIUM CALCULATION FOR PROCESS time and precision, the number of iterations is set as n=
10000；C04 uses genetic operator: selection, intersects at variation, handles individual specimen, defines fitness function G first,
Fitness function reflects the distance between each chromosome and Optimum Solution chromosome, shown in the expression formula of G such as formula (6):
Fitness function is made of the inverse of system total efficiency and flow flood rate, and the numerical value which calculates is bigger, is said
Bright individual chromosome is closer to optimal solution chromosome；Then, by selection operator by the high individual inheritance of fitness to the next generation
Population；Moreover new individual is obtained by mutation operator, when operation, needs to define aberration rate, value 0.001, and Fig. 8 is a
Then Autosome mutation operator schematic diagram, mutation operator pass through other etc. by the random function definitive variation position that uniformly makes a variation
" 1 " that makes a variation on position is substituted for " 0 ", to generate new individual in fig. 8 by position gene replacement original gene；Meanwhile it using
Crossover operator obtains new individual, and when operation needs to define crossover probability, and value is taken as 0.5, Fig. 9 as individual chromosome intersection
Operation schematic diagram, crossing operation set a crosspoint by single point crossing method at random, carry out when intersecting, two after the point
The part-structure of individual is interchangeable, and generates two new individuals, i.e., original individual A and individual B pass through crossing operation
Afterwards, new individual A and new individual B is generated；C05 is based on optimizing flow and efficiency goal function, solves to genetic algorithm
The individual specimen in population afterwards is assessed, to obtain optimum solution；C06 determines whether the number of iterations reaches setting value n=
10000, if it exceeds then stopping iteration；C07 genetic algorithm optimization terminates, and obtains flow flood rate minimum, system total efficiency is most
High water pump optimal operating parameter solution, and Gray code is carried out to optimum solution, convert thereof into the readable strong decimal system；C08 pairs
Optimum solution carries out Gray code operation, and binary numeral is transformed into decimal value first, then carries out numerical value divided by 10
Reduction treatment obtains final water pump operation parametric optimal solution, and wherein the corresponding optimized operation parameter of 1# water pump D04 is (f#1=
39.9Hz H#1=15m, Q#1=13m3/ h), the corresponding optimized operation parameter (f of #2 water pump D05#2=39.9Hz, H#2=
15m, Q#2=13m3/ h), the corresponding optimized operation parameter (f of #3 water pump D06#3=39.9Hz, H#3=15m, Q#3=13m3/
h)；
Step 6. determines water pump optimal operating parameter, carries out dynamic adjustment to the setup parameter of water pump controller
Water pump optimal operating parameter is determined by step 5 for particular system pepeline characteristic, by 1# water pump D04,2# water
Pump the frequency values f in D05 and 3# water pump D06 operating parameter1#=39.9Hz, f2#=39.9Hz, f3#=39.9Hz is as setting
Value write-in frequency-variable controller D01, D02 and D03, when three water pumps work under corresponding optimized operation operating condition, consumed drive
Dynamic power input to machine is respectively as follows: P1#=0.866kW, P2#=0.866kW, P3#=0.866kW passes through formula (4) and formula
(5) available flow targets function F (Q)=0, efficiency goal function F (η)=0.61；When water pump uses power frequency operation,
Frequency values in 1# water pump D04,2# water pump D05 and 3# water pump D06 operating parameter are f1#=50Hz, f2#=50Hz, f3#=
50Hz, as flow system flow Qr=39m3/ h, is allocated by Principle of Average Allocation, then the flow of three water pumps is Q#1=Q#2=
Q#3=13m3/ h, according to the corresponding flow-lift curve of 50Hz, its available corresponding lift value is H#1=H#2=H#3=
25.5m, according to the corresponding flow-power curve of 50Hz, its available corresponding driving motor input power is P#1=P#2
=P#3=1.546kW；Compared with power frequency operation mode, single pump power after being solved using genetic algorithm optimization has dropped Δ P=
1.546-0.866=0.68kW, system saving electricity rate have reached 44%；Therefore, it is controlled using the multiple ontology based on genetic algorithm
Method carries out dynamic and intelligent adjustment to system operational parameters, can effectively ensure that flow and pressure needed for water system, promotes water
Comprehensive operation efficiency is pumped, system operation energy consumption is reduced.
Content described in this specification embodiment is only enumerating to the way of realization of inventive concept, guarantor of the invention
Shield range should not be construed as being limited to the specific forms stated in the embodiments, and protection scope of the present invention also forgives this field
Technical staff conceive according to the present invention it is conceivable that equivalent technologies mean.
Claims (5)
1. a kind of multiple ontology control method based on genetic algorithm, which is characterized in that the described method comprises the following steps:
Step 1. is directed to multiple ontology water system, establishes system pipe network characteristic curve governing equation
Multiple ontology water system includes frequency-variable controller D01, D02 and D03, water pump D04, D05 and D06, pressurized tank D07, into
Supply mains D08 and outfall sewer D09；Frequency-variable controller D01, D02 and D03 respectively control water pump D04, D05 and D06,
By the control of pump rotary speed, to realize the control of flow and lift；The working method of whole system are as follows: water passes through pressurized tank
D07 is pressurized it into water inlet manifold D08, then by water pump D04, D05 and D06, and pressurized water passes through outfall sewer
D09 reaches user side；For the normal operation for guaranteeing whole system, the needs of pressure provided by water pump D04, D05 and D06, which overcome, is
The resistance of pipe system of system, while the flow provided will meet the needs of system；
The resistance of pipe system of water system includes the pressure loss of particular flow rate lower pipeline, the pressure loss of pressurized tank and control valve
The local pressure loss of door, wherein the pressure loss of pipeline is determined by the resistance coefficient of flow velocity and pipeline, the part of control valve
The pressure loss mainly determines that valve opening is bigger by the aperture of valve, and resistance is smaller；In order to realize the intelligence to multiple ontology system
It can control, the pipe system performance curve equation of system is established, shown in expression formula such as formula (1)；
Hr=kQr 2+H0 (1)
In formula, HrFor total (pumping) head needed for system, QrFor total flow needed for system, H0For the initial ductwork pressure of system, k is pipe
Net characteristics resistance coefficient；
Flow and lift needed for step 2. acquisition system, establish pump head and power characteristic equation
Use regimen condition based on user side obtains the flow and lift provided needed for water system, and value is respectively QrAnd Hr, it is
The flow and power for calculating water pump, are needed to establish the characteristic equation of water pump, are expressed using 3 order polynomial approximate equations,
Shown in its calculation formula such as formula (2) and (3)；
H=a00+a10f+a01Q+a20f2+a11fQ+a02Q2+a21f2Q+a12fQ2+a03Q3+a30f3 (2)
P=b00+b10f+b01Q+b20f2+b11fQ+b02Q2+b21f2Q+b12fQ2+b03Q3+b30f3 (3)
In formula, Q is the output flow of water pump, and P is the input power of water pump driving motor, and f is the running frequency of water pump, and H is water
The output lift of pump, a00To a30For the coefficient of lift characteristic equation, b00To b30For the coefficient of power characteristic equation；
By formula (2) and (3), the lift and performance number under different frequency and flow are obtained, to guarantee subsequent water pump operation ginseng
The iterative solution of several calculating and genetic algorithm；
Step 3. flow and lift demand according to needed for system defines initial population scale, calculates water pump operation parameter and determination
Individual chromosome structure
Based on flow Q needed for systemrWith required lift Hr, optimization is controlled by defining the scale of initial population
Convergence rate and population diversity, population scale N control between 20 to 200, then by calculate water pump operation ginseng
Number, individual specimen needed for determining initial population；Water pump operation parameter computation process includes: the number of units that B01 defines water pump, this
In the corresponding water pump quantity of system be 3；B02 determines the running frequency of every pump at random, according to frequency accidental function fi=
Rand(0…fmax), determine the running frequency of specified water pump, fiFor the frequency of i-th water pump, fmaxFor the maximum value of frequency, i.e.,
50Hz；B03 determines the lift of every pump at random, according to lift random function Hi=Rand (0 ... Hmax), determine specified water pump
Lift, HiFor the lift of i-th water pump, HmaxFor the maximum value of lift；B04 is based on the frequency f being calculated at randomiAnd lift
Hi, the flow of every pump is calculated according to formula (2)；B05 judges whether three pumps calculate completion, completes, enters if calculated
In next step, otherwise, it returns and is calculated again；B06 calculates the parallel water pump system total flow Q under specific run parametersys, base
The flow Q that Yu Santai water pump calculates1、Q2And Q3, pass through formula Qsys=∑ (Qi) obtain system total flow Qsys；B07 passes through comparison
System total flow QsysWith flow Q needed for systemrAnd separate unit pump lift HiWith lift H needed for systemrSize, to determine
Whether the individual specimen of calculating meets performance requirement；B08 is based on judgement as a result, determining qualified individuals sample, concurrently sets individual
The corresponding chromosome structure of sample, composition includes: the corresponding operating parameter (f of #1 water pump D04#1, H#1, Q#1), #2 water pump
Corresponding operating parameter (the f of D05#2, H#2, Q#2), the corresponding operating parameter (f of #3 water pump D06#3, H#3, Q#3)；
Step 4. analysis system bulk flow and power parameter establish flow and efficiency optimization objective function
The system bulk flow Q being calculated by step 3sysAnd formula (3) be calculated every water pump consumption power
Pi, establish multiple ontology flow system flow and efficiency optimization objective function F (Q) and F (η), flow and efficiency goal function are respectively such as
Shown in formula (4) and (5):
F (Q)=Min (Δ Q)=Min (| Qsys-Qr|/Qr) (4)
In formula, Δ Q is the ratio of flow needed for the difference and system of flow needed for system actual flow and system, i.e. flow overflows
Rate, η are the gross efficiency of system, the i.e. ratio of the sum of three water pump output powers and the sum of three water pump driving motor input powers
Value, ρ are the density of water, and g is acceleration of gravity；
Step 5. is based on genetic algorithm, carries out binary coding to individual chromosome, while using fitness function and selection, becoming
Different, crossover operator realizes the optimization of water pump system operating parameter
Genetic algorithm is made of coding, fitness function, genetic operator (selection intersects, variation) and operating parameter, including following
Step: C01 determines the initialization operating parameter of chromosome structure and every pump；C02 encodes individual chromosome structure, compiles
Code is the decimal system to binary conversion, since the format of original decimal value is that decimal point retains one, in order to quickly have
The carry out Binary Conversion of effect passes through the decimal value that will have decimal multiplied by 10 here, carries out integer processing, finally will
The decimal value of integer carries out Binary Conversion, obtains efficient coding, and each operating parameter uses 9 efficient codings, no
9, foot, it is supplied in coding right-most position by mending " 0 "；Three water pumps, every water pump include frequency, lift and stream
3 operating parameters are measured, 9 operating parameters are amounted to, coding overall length is 81；C03 defines genetic algorithm the number of iterations n, in order to balance
It calculates the time and precision, the number of iterations is set as n=10000；C04 uses genetic operator: selection, intersects at variation, to individual sample
This is handled, and defines fitness function G first, and fitness function reflects between each chromosome and Optimum Solution chromosome
Distance, shown in the expression formula of G such as formula (6):
Fitness function is made of the inverse of system total efficiency and flow flood rate, and the numerical value which calculates is bigger, is illustrated a
Autosome is closer to optimal solution chromosome；Then, by selection operator by the high individual inheritance of fitness to next-generation population；
Moreover new individual is obtained by mutation operator, when operation, needs to define aberration rate, and value range is 0.005~0.01, becomes
Then xor is replaced original gene by other allele, will be made a variation by the random function definitive variation position that uniformly makes a variation
" 1 " on position is substituted for " 0 ", to generate new individual；Meanwhile new individual is obtained using crossover operator, it is fixed to need when operation
Adopted crossover probability, value range are that 0.4~0.99, Fig. 9 is individual chromosome crossing operation schematic diagram, and crossing operation passes through list
Point cross method sets a crosspoint at random, and when carrying out intersection, two individual part-structures after the point are interchangeable, and
Two new individuals, i.e., original individual A and individual B are generated by after crossing operation, generating new individual A and new individual B；
C05 is based on optimizing flow and efficiency goal function, and the individual specimen in population after solving to genetic algorithm is assessed, with
Obtain optimum solution；C06 determines whether the number of iterations reaches setting value n=10000, if it exceeds then stopping iteration；C07 heredity is calculated
Method optimization terminates, and it is minimum to obtain flow flood rate, the highest water pump optimal operating parameter solution of system total efficiency, and to optimum solution into
Row Gray code converts thereof into the readable strong decimal system；C08 carries out Gray code operation to optimum solution, first by binary number
Value is transformed into decimal value, then carries out reduction treatment, it is optimal to obtain final water pump operation parameter numerical value divided by 10
Solution；
Step 6. determines water pump optimal operating parameter, carries out dynamic adjustment to the setup parameter of water pump controller
Water pump optimal operating parameter is determined by step 5 for particular system pepeline characteristic, by 1# water pump D04,2# water pump D05
With the frequency values f in 3# water pump D06 operating parameter1#, f2#, f3#Frequency-variable controller D01, D02 and D03 is written as setting value, it is right
System carries out dynamic and intelligent adjustment, to guarantee flow and pressure needed for water system, promotes water pump comprehensive operation efficiency, reduces system
System operation energy consumption.
2. a kind of multiple ontology control method based on genetic algorithm as described in claim 1, it is characterised in that: the step
, it is specified that its water pump quantity for being included of multiple ontology system and frequency-variable controller quantity expand to 4 and 4 or more in 1.
3. a kind of multiple ontology control method based on genetic algorithm according to claim 1 or 2, it is characterised in that: institute
State in step 2, it is specified that pump head and power characteristic equation using 3 order polynomial approximate equations, if the polynomial equation
Precision be unable to satisfy requirement, indicated using 4 times and 4 times or more polynomial approximation equations.
4. a kind of multiple ontology control method based on genetic algorithm according to claim 1 or 2, it is characterised in that: institute
State in step 2, it is specified that three water pumps model it is identical, according to the requirement of real system, using the different water of bench-types No. 3
Pump or the combination forms such as 2 identical 1 differences, lift and power characteristic equation corresponding to every different model water pump need
It to be defined respectively.
5. a kind of multiple ontology control method based on genetic algorithm according to claim 1 or 2, it is characterised in that: institute
State in step 5, it is specified that the operating parameter decimal system turn scale involved in binary process, retain two or three-digit, with
The demand of different Model of pump operating parameters is adapted to, corresponding integer processing is then needed multiplied by 100 or 1000, while corresponding
The total length of chromosome coding is then increased.
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