CN106766450A - Refrigeration heat pump system least energy consumption optimal control device and control method - Google Patents
Refrigeration heat pump system least energy consumption optimal control device and control method Download PDFInfo
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- CN106766450A CN106766450A CN201710148833.6A CN201710148833A CN106766450A CN 106766450 A CN106766450 A CN 106766450A CN 201710148833 A CN201710148833 A CN 201710148833A CN 106766450 A CN106766450 A CN 106766450A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F25—REFRIGERATION OR COOLING; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS; MANUFACTURE OR STORAGE OF ICE; LIQUEFACTION SOLIDIFICATION OF GASES
- F25B—REFRIGERATION MACHINES, PLANTS OR SYSTEMS; COMBINED HEATING AND REFRIGERATION SYSTEMS; HEAT PUMP SYSTEMS
- F25B49/00—Arrangement or mounting of control or safety devices
- F25B49/02—Arrangement or mounting of control or safety devices for compression type machines, plants or systems
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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Abstract
The present invention provides a kind of refrigeration heat pump system least energy consumption optimal control device, and the control device receives the least energy consumption optimal control signal, and controls refrigeration heat pump system according to the least energy consumption optimal control.Also provide a kind of control method of utilization refrigeration heat pump system least energy consumption optimal control device simultaneously.Effect of the present invention can be achieved on the least energy consumption optimal control of refrigeration heat pump system, to reach the saving energy consumption under different cooling conditions.The method makes the change of the good following condition of refrigeration heat pump system and is adjusted, relatively conventional unity loop control, and energy-saving effect is up to more than 18% during 100% workload demand.
Description
Technical field
The present invention is a kind of refrigeration heat pump system least energy consumption optimal control device and control method, belongs to air-conditioning system excellent
Change control field.
Background technology
With the continuous improvement of living standard, requirement of the people to indoor comfort is improved constantly, and causes air conditioning energy consumption fast
Speed increases.According to data, the ratio of social commodities total energy consumption shared by building energy consumption rises to 25% from 10% in 1978
Left and right, and will continue to increase, and it is finally reached 35% or so.And about 60%-70% is in public building summer power load
Central air conditioner system is consumed in, wherein 50%-60% freezes for refrigeration unit, 20%-30% is used for chilled water pump with cooling
The transmission ＆ distribution of water pump, it is seen that reduce operation of air conditioning systems energy consumption, be necessary to building energy conservation.
At present, substantial amounts of computer simulation technique is applied to the performance simulation of refrigeration system, the optimization design of product and control
Analysis of strategies processed, and the foundation of Mathematical Modeling is the core of analog simulation.Traditional refrigeration system component Mathematical Modeling must be set up
It is, based on stable state, not consider influence of the working state of system to single part, does not consider system in whole cyclic process
Homeostasis energy problem.
Conventional refrigerating method has three kinds, i.e. steam compression type, steam-sprayed and absorption refrigeration, above-mentioned refrigeration side at present
Formula directly consumes electric energy or heat energy.Analyzed by theoretical refrigeration cycle and actual consumption draw compression-type refrigeration mode have compared with
Specific energy consumption refrigerating capacity high, but there is a problem of that sub-load efficiency is relatively low.Classical refrigeration system unity loop control structure,
As shown in Figure 1.In conventional refrigeration control, compressor, chilled water system, four loops of cooling water system and electric expansion valve
Operating point setting value rule of thumb given by operating personnel, no longer change with power condition changing afterwards, this control mode is not
The input of system can automatically be changed under variable working condition, it is impossible to Dynamic Matching system variation and workload demand, it is impossible to realize effective
Saving energy consumption.The control of cooling load controller 2 compressor 3 in Fig. 1, condensing pressure controller 4 control cooling water pump and condenser
6, degree of superheat controller 12 control electric expansion valve 7 and evaporator 9, the control chilled water pump of chilled water pump controller 13, refrigeration are negative
Lotus measurement 10 determines workload demand, and end load 11 determines end load, and cooling tower 5 uses fixed-frequency control, traditional refrigeration heat
Pump monitoring system control strategy is the unity loop control for not adding optimization, and circuit controls operating point setting value is by operating personnel according to warp
Setting is tested, optimization is not added, operating point setting value can not follow the change of cooling condition, it is impossible to realize least energy consumption control, energy-conservation
Effect is poor.
The content of the invention
It is an object of the invention to provide a kind of refrigeration heat pump system least energy consumption optimal control device and control method, to solve
Certainly refrigeration heat pump system problems of energy consumption under variable working condition.
To achieve the above object, the present invention provides a kind of refrigeration heat pump system least energy consumption optimal control device, the device
It is connected with refrigeration heat pump system, wherein：The device includes compressor variable frequency device, cooling water pump frequency converter, chilled water pump frequency conversion
Device, set point optimal controller, the compressor of the compressor variable frequency device output end connection refrigeration heat pump system, cooling water pump become
The cooling water pump of frequency device output end connection refrigeration heat pump system, chilled water pump inverter output terminal connect the cold of refrigeration heat pump system
Freeze water pump；The set point optimal controller includes hardware module KMD5831 building controllers and control software WinControl,
Set point optimal controller receives refrigeration heat pump system working state signal, and control letter is obtained through WinControl program calculations
Number, control signal output forms refrigeration heat pump system least energy consumption optimal control device to the compressor variable frequency device..
Also provide a kind of control method of utilization refrigeration heat pump system least energy consumption optimal control device simultaneously.
Effect of the invention is：
First, the setpoint control device that the refrigeration system total energy consumption model according to exploitation is set up has considered system as a whole
The inside shape of compressor frequency, chilled water pump frequency, cooling water pump frequency, four input variables of electronic expansion valve opening and system
The contact of state variable evaporating pressure, condensing pressure and the degree of superheat, exists than more comprehensively have studied in refrigeration system energy saving optimizing
Part Dead Core Problems.
Second, least energy consumption optimization control scheme is devised using heterarchical architecture, the method has well adapted to system
The power conservation requirement that cooling system runs under variable working condition, compared to conventional control, with tracking performance is good, dynamic control precision ±
Within 5%.
3rd, optimization aim is solved using the pattern search algorithm for combining exterior penalty function, effectively solve
The derivative calculations problem of non-linear power dissipation obj ectives function.
4th, in refrigeration system variable working condition, using the method for model parameter self adaptation, each control loop of on-line optimization sets
Definite value, actual control result shows that the method makes the change of the good following condition of refrigeration heat pump system and is adjusted, relatively
Conventional single-loop is controlled, and energy-saving effect is up to more than 18% during 100% workload demand.
Brief description of the drawings
Fig. 1 conventional refrigeration unity loop control structure charts；
Fig. 2 inventive refrigeration system optimal control overall plan figures；
Fig. 3 inventive refrigeration system hierarchy optimization control schematic diagrams；
Fig. 4 inventive refrigeration system model parameter adaptive structure figures；
Fig. 5 refrigeration heat pump system least energy consumption control flow charts of the present invention；
The flow chart of the pattern search method of Fig. 6 combination exterior penalty functions；
Fig. 7 inventive refrigeration system set-point optimization control structure figures.
In figure：
1. the condensing pressure controller 5. of 2. cooling load controller of set point optimal controller, 3. compressor 4. is cooled down
The cooling load of 9. evaporator of tower 6. condenser, 7. expansion valve, 8. evaporating pressure controller 10. measures 11. end loads
The adaptation layer of 12. evaporator superheat controller, 13. chilled water pump controller, 14. dynamic controller, 15. refrigeration unit 16.
The model parameter self adaptation 22. of 20. energy consumption function evaluation of the dynamic control of 17. optimization layer 18. 19. optimal controller of layer 21. is joined
Number self adaptation 23. linear dynamic estimates the chilled water pump 28. of 24. steady-state model, 25. LPF, 26. cooling water pump 27.
The chilled water pump frequency converter of 29. cooling water pump frequency converter of compressor variable frequency device 30.
Specific embodiment
Refrigeration heat pump system least energy consumption optimal control device of the invention and control method are illustrated with reference to accompanying drawing.
Refrigeration heat pump system least energy consumption optimal control device of the invention, the device is connected with refrigeration heat pump system,
The device includes compressor variable frequency device 28, cooling water pump frequency converter 29, chilled water pump frequency converter 30, set point optimal controller 1,
The compressor 3 of the output end of the compressor variable frequency device 28 connection refrigeration heat pump system, the connection of the output end of cooling water pump frequency converter 29
The cooling water pump 26 of refrigeration heat pump system, chilled water pump frequency converter 30) output end connect refrigeration heat pump system chilled water pump 27；
The set point optimal controller 1 includes hardware module KMD5831 building controllers and control software WinControl, set point
Optimal controller 1 receives refrigeration heat pump system working state signal, and control signal is obtained through WinControl program calculations, controls
Signal output forms refrigeration heat pump system least energy consumption optimal control device to the compressor variable frequency device 28.
The control method of utilization refrigeration heat pump system least energy consumption optimal control device of the invention, the control method is logical
WinControl softwares are crossed using hierarchy optimization control, the hierarchy optimization control includes adaptation layer 16, optimization layer 17 and moves
State key-course 18, realizes that refrigeration heat pump system least energy consumption is controlled by refrigeration heat pump system least energy consumption optimal control device,
Comprise the following steps：
1) refrigeration heat pump system is set up by WinControl software programmings in set point optimal controller 1 and compresses function
Consumption model：
In formula, Wk- energy consumption of compressor (kW) Qe- evaporator capacity (kW)
hci- condenser inlet enthalpy (kJ/kg) hco- condensator outlet enthalpy (kJ/kg)
heo- evaporator outlet enthalpy (kJ/kg) Pe- evaporating pressure (kPa)
Pc- condensing pressure (kPa)
Cooling water pump energy consumption model：
In formula, mclw- cooling water mass flow (kg/s) ma- cooling tower MAF (kg/s)
cp,w- cooling water specific heat capacity (kJ/kg DEG C) Tclwo- cooling water outlet temperature (DEG C)
Tamb- outside air temperature (DEG C) Qclw- cooling tower load (kW)
a1、a2、a3- the fitting coefficient relevant with cooling tower structure
Chilled water pump energy consumption model：
In formula, k2,chw, k2,choThe coefficient of relationship of-chilled water mass flow and frequency
Te- evaporator refrigerant temperature (DEG C) Tchwi- chilled water return water temperature (DEG C)
αe- refrigerant and chilled water heat exchange coefficient me- heat exchange index
fchw- chilled water pump frequency (Hz)
Combination builds refrigeration heat pump system entirety energy consumption model；
2) 20 are evaluated according to the least energy consumption of the overall energy consumption model and adaptation layer 16, in set point optimal controller
Least energy consumption model and determination constraints realization are set up by WinControl software programmings in 1；
Least energy consumption model：
In formula, Wk- energy consumption of compressor (kW) Wchw- chilled water pump energy consumption (kW)
Wclw- cooling water pump energy consumption (kW)
Constraints is：State variable is limited：Exss+bx≤0
Control signal is limited：Fuss(xss,vss)+bu≤0
Refrigerating capacity is limited：Qe=Qe,o
The degree of superheat is limited：Tsh=Tsh,min(Qe)
Wherein, xss=[Pe Pc Tsh]TIt is state variable, TshIt is the degree of superheat,
bx=[- Pc,max Pe,min 0]T, Pc,maxIt is condensing pressure maximum, Pe,minIt is evaporating pressure minimum value, uss=
[fk fclw fchw]T, fkIt is compressor frequency, fclwIt is cooling water water pump frequency, fchwIt is chilled water pump frequency,It is system disturbance, bu=[0-fclw,max 0 -fchw,max 0 -fk,max]T, fclw,maxIt is cooling
Pump working frequency maxima, fchw,maxIt is chilled water pump working frequency maximum, fk,maxIt is compressor operating frequency maxima,
Qe,oIt is refrigeration demand, Tsh,min(Qe) it is minimum superheat,
3) according to the model self-adapted control 21 of adaptation layer 16, pass through in set point optimal controller 1
WinControl software programmings complete the parameter adaptive control of the least energy consumption model.
4) according to the optimal controller 19 of optimization layer 17, WinControl softwares are passed through in set point optimal controller 1
The exterior penalty function that the least energy consumption model is set up in programming completes conversion of the least energy consumption from constrained optimization to unconstrained optimization,
And solve the state magnitude under least energy consumption value and least energy consumption according to pattern search algorithm.
5) according to dynamic control layer 18, the state magnitude under the least energy consumption is used as dynamic control 18 dynamic controller of layer
14 input.
6) compressor that the output signal of the dynamic controller 14 is accessed in above-mentioned least energy consumption optimal control device becomes
Frequency device 28, cooling water pump frequency converter 29, chilled water pump frequency converter 30 and electric expansion valve 7.
7) the least energy consumption optimal control device outputs signals to refrigeration unit 15, so as to complete least energy consumption optimization control
System.
When the refrigeration heat pump system working conditions change, model parameter self adaptation 21 is by self-adaptative adjustment least energy consumption function
Evaluate 20 coefficient.The least energy consumption function evaluates the 20 least energy consumption function models for building and refrigeration heat pump system quantity of state
It is related.
The optimal controller 19 of the optimization layer 17 is using the pattern search algorithm for combining exterior penalty function.
Described least energy consumption model is the least energy consumption model based on mechanism, and compressor conservation of energy side is respectively adopted
Journey, cooling water system energy conservation equation, chilled water system energy conservation equation derive energy consumption of compressor model, cooling water pump
Energy consumption model and chilled water pump energy consumption model.
What refrigeration heat pump system least energy consumption optimal control device of the invention and control method function were realized in：
Fig. 2 is inventive refrigeration system optimal control overall plan figure, including set point optimal controller 1, dynamic control
Device 14 and refrigeration unit 15.
Fig. 3 is inventive refrigeration system hierarchy optimization control schematic diagram, and it includes adaptation layer 16, optimization layer 17 and dynamic
Key-course 18, the adaptation layer 16 realizes that its input is working state of system amount, control with model parameter adaptive control 21
Semaphore, its output feeding optimization layer 17, the optimization layer 17 includes that least energy consumption function evaluates 20 and optimal controller 19, from
The output of adaptation layer 16 and control signal amount are sent to least energy consumption function and evaluate in 20, and least energy consumption model and determination are set up in completion
Constraints, least energy consumption function evaluates the input of 20 output as optimal controller 19, and optimal controller 19 completes minimum
The solution of state magnitude under power consumption values and least energy consumption, the output end of optimal controller 19 connection dynamic control layer 18, the dynamic
Key-course 18 includes dynamic controller 14, and the input signal of dynamic controller 14 is output and the actual working state of optimization layer 17
The difference of amount, the output signal of dynamic controller 14 is respectively connected to compressor variable frequency device 28, expansion valve 7, cooling water pump frequency converter 29
With chilled water pump frequency converter 30.
Fig. 4 is inventive refrigeration system model parameter adaptive structure figure, is typical model parameter adaptive control, real
Existing model parameter self adaptation, model parameter can change with the change of working condition in overcoming refrigeration system energy consumption model
Problem, it includes the reference model of refrigeration unit 15, and parameter adaptive 22, linear dynamic estimates 23, steady-state model 24, LPF
25, because model is based on steady-state model 24, parameter adaptive 22 is only only at steady state accurately, in dynamic situation most
Significant dynamic process is formed by the heat conductive wall of evaporator, and this dynamic process is simulated with a LPF 25, in order to adapt to
The disturbance of system under dynamic situation, estimates that 23 are used for adaptation layer by linear dynamic.
Fig. 5 is refrigeration heat pump system least energy consumption control flow chart of the present invention, is comprised the following steps：
Step 501：Start；
Step 502：In set point optimal controller 1 overall energy consumption model is set up with WinControl software programmings；
Overall energy consumption model includes setting up respectively using compressor energy conservation equation, cooling water system conservation of energy side
Energy consumption of compressor model, cooling water pump energy consumption model, chilled water pump energy consumption mould that journey, chilled water system energy conservation equation are derived
Type.
1) consider compressor frequency and system internal state variable evaporating pressure, condensing pressure and contacting for the degree of superheat and
The Calculation Method of Energy Consumption of generation.
The mass flow of compressor unit interval：
mk=nkηvolVkρki(Pe) (1)
In formula, ρki--- the density of gaseous refrigerant, kg/m3
ηvol--- the volume efficiency of compressor
Vk--- theoretical displacement, m3/h
nk--- compressor rotary speed, rpm
Wherein compressor rotary speed and frequency relation formula：
The actual outlet enthalpy of compressor：
In formula, hkois--- the adiabatic outlet enthalpy of compressor, kJ/kg
ηk--- compressor adiabatic efficiency
Due to compressor outlet enthalpy and condenser inlet enthalpy, evaporator outlet enthalpy and suction port of compressor enthalpy change
Less, substituted with evaporator outlet and condenser inlet enthalpy respectively.Formula (3) is changed into formula (4).
Evaporator capacity：
Qe=mk(heo(Pe)-hei(pe))=mk(heo(Pe)-hco(pc)) (5)
Enter in view of expansion valve, to export enthalpy constant, and condensator outlet enthalpy is equal to expansion valve inlet enthalpy, expansion
Valve outlet enthalpy is equal to evaporator inlet enthalpy, therefore condensator outlet enthalpy is equal with evaporator inlet enthalpy.Compressor does
The ratio such as formula (6) of work(and evaporator capacity.
Derive compressor work equation is：
2) consider cooling water frequency and system internal state variable evaporating pressure, condensing pressure and contacting for the degree of superheat and
The Calculation Method of Energy Consumption of generation.
Cooling water pump does work：
Wclw=k1,clw(fclw)3+k1,clo (8)
In formula, fclw--- cooling water pump incoming frequency, Hz
Cooling water flow and frequency relation：
mclw=k2,clwfclw+k2,clo (9)
Condenser heat exchange coefficient：
In formula, αc--- refrigerant and cooling water heat exchange coefficient
mc--- heat exchange index, value 0.4-0.84
Cooling water leaving water temperature：
Cold in-water temperature Tclwi, asked for by cooling tower heat balance equation (12).
In formula, Qclw- cooling tower load, kW
ma、mclw- cooling tower air, cooling water mass flow, kg/s
a1、a2、a3- fitting coefficient, it is relevant with cooling tower structure
TambThe temperature of-outdoor air, DEG C
Refrigerant and cooling water energy balance equation on condenser tube wall
mk(hci(Pe,Pc)-hco(Pc))=mclwcp,w(Tclwo-Tclwi) (13)
Arrangement can be obtained
mk(hci(Pe,Pc)-hco(Pc))-mclwcp,w(Tclwo-Tclwi)=0 (14)
Bringing formula (8)-(12) into formula (14) can obtain, condenser energy conservation equation formula
Include the implicit function relation of cooling water flow and state variable in formula (15), different conditions are obtained by equation solution
Flow m under variableclw, and then can obtain corresponding cooling water pump power consumption Wclw。
3) consider chilled water frequency and system internal state variable evaporating pressure, condensing pressure and contacting for the degree of superheat and
The Calculation Method of Energy Consumption of generation.
Chilled water pump does work：
Wchw=k1,chw(fchw)3+k1,cho (16)
In formula, fchw--- chilled water pump incoming frequency, Hz
Freezing water and frequency relation：
mchw=k2,chwfchw+k2,cho (17)
Evaporator heat exchange coefficient：
In formula, αe--- refrigerant and chilled water heat exchange coefficient, kJ/ (kgK)
me--- heat exchange index, value 0.4-0.84
Freezing supply water temperature：
In formula, Tchwi--- chilled water return water temperature
Refrigerant and chilled water energy balance equation on evaporator tube wall：
Qe-mchwcp,w(Tchwo-Tchwi)=0 (20)
Bringing formula (16)-(19) into formula (20) can obtain energy conservation equation formula on evaporator：
Include chilled water frequency f in formula (21)chwWith the nonlinear function of state variable, obtained by equation solution
Frequency f under to different conditions variablechw, and then can obtain corresponding chilled water pump power consumption Wchw。
Step 503：Least energy consumption model is set up with WinControl software programmings in set point optimal controller 1, really
Cover half type constraints；
Comprehensive compressor power consumption, cooling water circulating pump power consumption, chilled water circulating pump power consumption, set up refrigeration system total energy consumption mould
Type, builds energy optimization object function such as formula (22).
Qualifications are as follows：
State variable is limited：Exss+bx≤0
Control signal is limited：Fuss(xss,vss)+bu≤0
Refrigerating capacity is limited：Qe=Qe,o
The degree of superheat is limited：Tsh=Tsh,min(Qe)
W in the modelkIt is compressor power consumption, WclwIt is cooling water pump power consumption, WchwIt is chilled water pump power consumption；xss=[Pe
Pc Tsh]TAs state variable, wherein PeIt is evaporating pressure, PcIt is condensing pressure, TshIt is evaporator superheat, condensing pressure Pc
With evaporating pressure PeIt is free variable, degree of superheat TshSetting value (minimum thermal stability degree) according to refrigerating capacity QeModify and
Setting；uss=[fk fclw fchw]TIt is control variables, wherein fkIt is compressor incoming frequency, fclwFor cooling water pump incoming frequency,
fchwIt is chilled water pump incoming frequency；System disturbance, wherein outdoor environment temperature TambIt is system
Major disturbances, TwFor system water supplement temperature,For relative humidity, v are outdoor wind speed, neglected herein because the influence to system is smaller
Slightly；QeIt is the refrigerating capacity requirement of system.
Step 504：With WinControl softwares according to model parameter as shown in Figure 4 in set point optimal controller 1
The self-adaptative adjustment of self-adaptation control method programming realization least energy consumption parameter；
Fig. 4 is typical model parameter adaptive control figure, including the reference model of refrigeration unit 15, parameter adaptive 22,
Linear dynamic estimates 23, steady-state model 24, LPF 25, because model is that, based on limit steady-state model 24, parameter is certainly
Adapt to 22 be only only at steady state it is accurate, in dynamic situation most significant dynamic process by evaporator heat conductive wall shape
Into this dynamic process is simulated with a LPF 25, in order to adapt to the disturbance of system under dynamic situation, linear dynamic is estimated
Meter 23 is used for adaptation layer.
Step 505：According to exterior penalty function formula 23, WinControl software programmings are used in set point optimal controller 1
Realize that least energy consumption Constrainedization arrives the conversion without about fasciculation；
Least energy consumption of the use exterior penalty function of 17 optimal controller of optimization layer as shown in Figure 3 19 to belt restraining in step 503
Optimization is converted into unconfined optimization, such as formula (23).
Q in formulass=Qe-Qe,o, condenser heat rejection amount is affected by the external environment, and surrounding environment is must take into consideration in optimization problem
The change of temperature.
Step 506：Solved with WinControl software programming implementation patterns searching algorithm in set point optimal controller 1
State value under least energy consumption value and least energy consumption；
Fig. 6 is the flow chart of the pattern search algorithm for combining exterior penalty function, realizes the solution to formula (23), and search procedure is every
An iteration is all alternately to move axially and motion of defect modes, and the purpose of axial movement is the favourable side that search function value declines
To the purpose of motion of defect modes is to accelerate to move along beneficial direction, and the amount occurred in flow chart includes：State variable：X=[Pe
Pc]T, penalty function：F(xss, τ), penalty factor：τ, step-length δ0, contraction factor α, τ initial value can be no longer after choosing larger desired value
It is adjusted, therefore penalty function is changed into F (x) and is optimized just for state variable x, pattern search process includes following step
Suddenly：
Step 601：Start；
Step 602：Given initial state value, initializing constraint, randomly selects evaporating pressure and condensing pressure state becomes
The initial point x of amount0=(Pe0,Pc0), step-length δ0=1, contraction factor α=0.75, penalty factor τ=5000, it is allowed to error ε>0, k=
0, j=1；
Step 604：：Assignment, by xk(k=1,2...) value is assigned to y and is just moved axially；
Step 604：：Penalty function is calculated, penalty function F (y+ δ are calculatedkej) and F (y)；
Step 605：：Penalty function compares, and judges F (y+ δkej)<Whether F (y) sets up；
Step 606：：If F (y+ δkej)<F (y) sets up, and continues forward lookup；
Step 607：：If F (y+ δkej)<F (y) is invalid, judges F (y- δkej)<Whether F (y) sets up, if not into
It is vertical directly to judge whether that search is finished；
Step 608：：If F (y- δkej)<F (y) sets up, and continues reverse search；
Step 609：：Judge whether whether axial movement finishes；
Step 6010：：If axial movement is not finished, continue to move axially；
Step 6011：：If moved axially successfully, pattern search, pattern search basic point x are carried outk+1=y；
Step 6012：：Penalty function compares, and judges F (xk+1)<F(xk) whether set up；
Step 6013：：If F (xk+1)<F(xk) set up, motion of defect modes, 31~step 41 of repeat step；
Step 6014：：If F (xk+1)<F(xk) invalid, judge δk<Whether ε sets up；
Step 6015：：If δk<ε is invalid, judges xk+1=xkWhether set up；
Step 6016：：If xk+1=xkSet up, change step-length 31~step 43 of repeat step；
Step 6017：：If xk+1=xkInvalid, step-length is constant, xk+1=xk, 31~step 43 of repeat step；
Step 6018：：Iteration terminates, and obtains optimal solution；
Step 6019：Terminate.
Step 507：State value under the least energy consumption that will be solved in set point optimal controller 1 sends into dynamic controller
14；
State value under the least energy consumption that above-mentioned pattern search is tried to achieve dynamically is controlled as the reference input of dynamic controller 14
Device processed 14 includes condensing pressure PID controller 4, evaporating pressure PID controller 8, evaporator superheat PID controller 12 and freezing
Water pump P ID controllers 13.
Step 508：The output signal of the dynamic controller 14 accesses the pressure in above-mentioned least energy consumption optimal control device
Contracting machine frequency converter 28, cooling water pump frequency converter 29, chilled water pump frequency converter 30 and electric expansion valve 7；
Step 509：The least energy consumption optimal control device controls to freeze according to the output signal of the dynamic controller 14
Compressor 3 in heat pump, electric expansion valve 7, cooling water pump 26 and chilled water pump 27, realize least energy consumption optimal control.
Step 5010：Terminate.
Black lines mark section sets point optimal controller 1 completes adaptation layer 16 in Fig. 3, optimization layer 17 in Fig. 7
Function, realizes the solution of quantity of state under foundation, least energy consumption value and the least energy consumption of least energy consumption model, and exports least energy consumption
To loop control unit, black lines mark part cooling load controller 2 outputs signals to compressor variable frequency device 28 to control signal
Control compressor 3, condensing pressure controller 4 output signals to the control cooling water pump 26 of cooling water pump frequency converter 29 and condenser 6,
Evaporating pressure controller 8 outputs signals to chilled water pump frequency converter 30 control chilled water pump 27 and evaporator 9, evaporator superheat
The output signal of controller 12 controls electric expansion valve 7, and black mark part combines outer layer set-point optimization and internal layer is dynamically controlled
System, cooling load measurement 10 determines workload demand, and end load 11 determines end load, and cooling tower 5 uses fixed-frequency control, and this is most
Small energy consumption optimization control method can realize the least energy consumption to refrigeration heat pump system with reference to the refrigerating heat pump optimal control device
Optimal control, realizes the purpose of saving energy consumption.
Claims (6)
1. a kind of refrigeration heat pump system least energy consumption optimal control device, the device is connected with refrigeration heat pump system, its feature
It is：The device includes compressor variable frequency device (28), cooling water pump frequency converter (29), chilled water pump frequency converter (30), set point most
Excellent controller (1), the compressor (3) of compressor variable frequency device (28) the output end connection refrigeration heat pump system, cooling water pump become
The cooling water pump (26) of frequency device (29) output end connection refrigeration heat pump system, chilled water pump frequency converter (30) output end connection refrigeration
The chilled water pump (27) of heat pump；The set point optimal controller (1) including hardware module KMD5831 building controllers and
Control software WinControl, set point optimal controller (1) receives refrigeration heat pump system working state signal, warp
WinControl program calculations obtain control signal, and control signal output forms refrigeration heat to the compressor variable frequency device (28)
Pumping system least energy consumption optimal control device.
2. a kind of control method of utilization refrigeration heat pump system least energy consumption optimal control device, the control method is to pass through
WinControl softwares using hierarchy optimization control, the hierarchy optimization control include adaptation layer (16), optimization layer (17) and
Dynamic control layer (18), refrigeration heat pump system least energy consumption control is realized by refrigeration heat pump system least energy consumption optimal control device
System, comprises the following steps：
1) refrigeration heat pump system energy consumption of compressor is set up by WinControl software programmings in set point optimal controller (1)
Model：
In formula, Wk- energy consumption of compressor (kW) Qe- evaporator capacity (kW)
hci- condenser inlet enthalpy (kJ/kg) hco- condensator outlet enthalpy (kJ/kg)
heo- evaporator outlet enthalpy (kJ/kg) Pe- evaporating pressure (kPa)
Pc- condensing pressure (kPa)
Cooling water pump energy consumption model：
In formula, mclw- cooling water mass flow (kg/s) ma- cooling tower MAF (kg/s)
cp,w- cooling water specific heat capacity (kJ/kg DEG C) Tclwo- cooling water outlet temperature (DEG C)
Tamb- outside air temperature (DEG C) Qclw- cooling tower load (kW)
a1、a2、a3- the fitting coefficient relevant with cooling tower structure
Chilled water pump energy consumption model：
In formula, k2,chw, k2,choThe coefficient of relationship of-chilled water mass flow and frequency
Te- evaporator refrigerant temperature (DEG C) Tchwi- chilled water return water temperature (DEG C)
αe- refrigerant and chilled water heat exchange coefficient me- heat exchange index
fchw- chilled water pump frequency (Hz)
Combination builds refrigeration heat pump system entirety energy consumption model；
2) according to the least energy consumption evaluation (20) of the overall energy consumption model and adaptation layer (16), in set point optimal controller
(1) least energy consumption model and determination constraints realization are set up by WinControl software programmings in；
Least energy consumption model：
In formula, Wk- energy consumption of compressor (kW) Wchw- chilled water pump energy consumption (kW)
Wclw- cooling water pump energy consumption (kW)
Constraints is：State variable is limited：Exss+bx≤0
Control signal is limited：Fuss(xss,vss)+bu≤0
Refrigerating capacity is limited：Qe=Qe,o
The degree of superheat is limited：Tsh=Tsh,min(Qe)
Wherein, xss=[Pe Pc Tsh]TIt is state variable, TshIt is the degree of superheat,
bx=[- Pc,max Pe,min 0]T, Pc,maxIt is condensing pressure maximum, Pe,minIt is evaporating pressure minimum value, uss=[fk fclw
fchw]T, fkIt is compressor frequency, fclwIt is cooling water water pump frequency, fchwIt is chilled water pump frequency,It is system disturbance, bu=[0-fclw,max 0 -fchw,max 0 -fk,max]T, fclw,maxIt is cooling
Pump working frequency maxima, fchw,maxIt is chilled water pump working frequency maximum, fk,maxIt is compressor operating frequency maxima,
Qe,oIt is refrigeration demand, Tsh,min(Qe) it is minimum superheat,
3) according to the model self-adapted control (21) of adaptation layer (16), pass through in set point optimal controller (1)
WinControl software programmings complete the parameter adaptive control of the least energy consumption model；
4) it is soft by WinControl in set point optimal controller (1) according to the optimal controller (19) of optimization layer (17)
The exterior penalty function that the least energy consumption model is set up in part programming completes least energy consumption turning from constrained optimization to unconstrained optimization
Change, and the state magnitude under least energy consumption value and least energy consumption is solved according to pattern search algorithm；
5) according to dynamic control layer (18), the state magnitude under the least energy consumption is used as dynamic control layer (18) dynamic controller
(14) input；
6) output signal of the dynamic controller (14) accesses the compressor variable frequency in above-mentioned least energy consumption optimal control device
Device (28), cooling water pump frequency converter (29), chilled water pump frequency converter (30) and electric expansion valve (7)；
7) the least energy consumption optimal control device outputs signals to refrigeration unit (15), so as to complete least energy consumption optimization control
System.
3. refrigeration heat pump system least energy consumption optimal control method according to claim 2, it is characterized in that：When the refrigeration
During heat pump working conditions change, model parameter self adaptation (21) is evaluated the coefficient of (20) by self-adaptative adjustment least energy consumption function.
4. refrigeration heat pump system least energy consumption optimal control method according to claim 2, it is characterized in that：The minimum energy
The least energy consumption function model that consumption function evaluation (20) builds is related to refrigeration heat pump system quantity of state.
5. refrigeration heat pump system least energy consumption optimal control method according to claim 2, it is characterized in that：The optimization layer
(17) optimal controller (19) is using the pattern search algorithm for combining exterior penalty function.
6. refrigeration heat pump system least energy consumption optimal control method according to claim 2, it is characterized in that：Described minimum
Energy consumption model is the least energy consumption model based on mechanism, compressor energy conservation equation, cooling water system energy is respectively adopted and keeps
Permanent equation, chilled water system energy conservation equation derive energy consumption of compressor model, cooling water pump energy consumption model and chilled water pump
Energy consumption model.
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| CN107906760A (en) * | 2017-10-27 | 2018-04-13 | 顺德职业技术学院 | Frequency conversion heat pump water heater compressor frequency dynamic optimization method |
| CN108089440A (en) * | 2017-12-06 | 2018-05-29 | 北京百度网讯科技有限公司 | Energy-saving control method and device |
| CN109916090A (en) * | 2018-11-29 | 2019-06-21 | 青岛经济技术开发区海尔热水器有限公司 | Heat pump water heater control method and heat pump water heater |
| CN110388706A (en) * | 2019-07-22 | 2019-10-29 | 上海电力大学 | Refrigerating pump operation optimization configuration method of central air-conditioning chilled water secondary pump system |
| CN110793240A (en) * | 2019-10-10 | 2020-02-14 | 青岛新欧亚能源有限公司 | Large-scale air source heat pump low-energy consumption operation system and control method |
| CN113032935A (en) * | 2021-03-12 | 2021-06-25 | 西南石油大学 | Large parallel natural gas pipe network optimization operation model and solving method |
| CN115013943A (en) * | 2022-01-12 | 2022-09-06 | 武汉舒适易佰科技有限公司 | Intelligent air conditioner control system |
| CN118168109A (en) * | 2024-04-02 | 2024-06-11 | 广州施杰节能科技有限公司 | Efficient operation control method and system for chiller |
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| CN107490319A (en) * | 2017-07-06 | 2017-12-19 | 扬州大学 | Cooling tower half adjusts the annual determination method for becoming angle and optimizing operating scheme of blower fan |
| CN107906760A (en) * | 2017-10-27 | 2018-04-13 | 顺德职业技术学院 | Frequency conversion heat pump water heater compressor frequency dynamic optimization method |
| CN108089440A (en) * | 2017-12-06 | 2018-05-29 | 北京百度网讯科技有限公司 | Energy-saving control method and device |
| CN109916090A (en) * | 2018-11-29 | 2019-06-21 | 青岛经济技术开发区海尔热水器有限公司 | Heat pump water heater control method and heat pump water heater |
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| CN110793240A (en) * | 2019-10-10 | 2020-02-14 | 青岛新欧亚能源有限公司 | Large-scale air source heat pump low-energy consumption operation system and control method |
| CN113032935A (en) * | 2021-03-12 | 2021-06-25 | 西南石油大学 | Large parallel natural gas pipe network optimization operation model and solving method |
| CN115013943A (en) * | 2022-01-12 | 2022-09-06 | 武汉舒适易佰科技有限公司 | Intelligent air conditioner control system |
| CN118168109A (en) * | 2024-04-02 | 2024-06-11 | 广州施杰节能科技有限公司 | Efficient operation control method and system for chiller |
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