CN107906810A - A kind of energy saving group control method of salt water cooling system of more handpiece Water Chilling Units cooperations - Google Patents
A kind of energy saving group control method of salt water cooling system of more handpiece Water Chilling Units cooperations Download PDFInfo
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- CN107906810A CN107906810A CN201711074632.2A CN201711074632A CN107906810A CN 107906810 A CN107906810 A CN 107906810A CN 201711074632 A CN201711074632 A CN 201711074632A CN 107906810 A CN107906810 A CN 107906810A
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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
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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
- F25B2500/00—Problems to be solved
- F25B2500/18—Optimization, e.g. high integration of refrigeration components
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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
- F25B2500/00—Problems to be solved
- F25B2500/19—Calculation of parameters
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Abstract
The present invention provides a kind of energy saving group control method of salt water cooling system of more handpiece Water Chilling Units cooperations.The present invention uses improvement short annealing algorithm that under each cooling condition demand, distribution, lifting system overall performance index are optimized to the refrigeration work consumption of handpiece Water Chilling Units to ship cooling system.The foundation of target equation has considered the energy-saving effect of chilled water pump temperature difference control variable-flow measure, and the delivery requirements of freezing water are met by chilled water pump frequency control, while reduces energy loss meaningless in transmitting procedure.By the dynamic property index of adaptive polo placement separate unit handpiece Water Chilling Units, the accuracy of target equation is improved.
Description
Technical field
A kind of energy saving group control method of salt water cooling system of more handpiece Water Chilling Units cooperations of the present invention, belongs to intelligent ship
With seawater cooling means technical field.
Background technology
As the most common concentration methods for cooling of ship, indirect-cooling freon handpiece Water Chilling Units respectively with seawater and fresh water into
Row heat exchange reduces temperature in cabin, sees Fig. 1.But since the indoor refrigeration duty in cabin fluctuates very big, the configuration of separate unit handpiece Water Chilling Units
(unit presses maximum refrigeration duty type selecting) when system loading off-design is worth excessive (low cooling condition), cooling system is in low
Efficiency is run.Therefore, double handpiece Water Chilling Units configurations are carried out for high load capacity operating mode, running on the lower load so that system is in most of work
The developing direction that all there is higher operational efficiency to be current ship salt water cooling system under condition, is shown in Fig. 2.Conventional multicomputer control
System strategy to be used with refrigeration duty to control the start-stop of handpiece Water Chilling Units, and general workload demand is close to a unit full power cold
Just consider to load new unit during output.But the optimum performance index of separate unit handpiece Water Chilling Units is when being not commonly present at full capacity,
Therefore there is multicomputer to share the energy saving space that workload demand independently undertakes compared with single fighter more power saving.
1984, R.J.Hankner, et al. in its " HVAC system dynamics and energy use in
The output of the average method control handpiece Water Chilling Units such as use, i.e. separate unit cooling-water machine are proposed in the research of buildings-Part I "
Group is contributed is multiplied by rate of load condensate equal to total refrigeration duty demand, and rate of load condensate refers to that the capacity of every handpiece Water Chilling Units and each capacity are total
The business of sum, the control strategy is simple and practicable, but it is optimal to reach efficiency.
2004, Y.Yao, et al. in its " Optimal operationof a large cooling system
In the research of based on an empirical model ", considered chilled water pump energy-saving and frequency-variable operation, propose with
System performance index (SCOP) value maximizes target in order to control, so as to draw the optimal control policy of handpiece Water Chilling Units.But the plan
Slightly decision process is complicated, and the QUADRATIC PROGRAMMING METHOD FOR of use is not easy to restrain in low- load conditions.
2008, poplar led to clear wait and passes through in the research of its " the Energy Saving Control strategy based on handpiece Water Chilling Units optimal control "
Multicomputer load test, explores more handpiece Water Chilling Units under different demands operating mode based on the load(ing) point that unit COP is optimal, but
Be and be not explicitly described cooling system whether reach entirety can be optimal.
Existing invention (200810182566.5) marine central air conditioner refrigerating device proposes a kind of ship central air-conditioning system
Device for cooling, refrigeration performance is stable its purpose is to provide among, erosion-resisting marine central air conditioner refrigerating device, is not directed to
How optimization system efficiency.
A kind of existing central air-conditioning freezing unit group control method of invention (201210125509.X) proposes to control by heat
The algorithm of this pair of of handpiece Water Chilling Units team control, effectively make handpiece Water Chilling Units operate in it is more economical it is energy saving in the state of, reach extension and set
Standby service life and the purpose for reducing energy consumption.In its algorithm and not yet explicitly handpiece Water Chilling Units open the division condition of number of units, i.e. overall design is born
Lotus 0%, 20%, 38%, 55%, 70%, is determined by which kind of mode.Therefore, so division can cause handpiece Water Chilling Units to operate in
The saying of more economical energy saving state lacks foundation.
Existing invention (201510819296.4) a kind of computer room group control device and its controlling party based on global association optimization
Method proposes a kind of computer room group control device based on global association optimization, including central group control device, pump control unit, cold
But tower control device, handpiece Water Chilling Units communication device and air-treatment unit control device；The pump control unit, cooling tower
Control device, handpiece Water Chilling Units communication device and air-treatment unit control device are connected with central group control device；The center
Industrial computer, industrial switch and central processing unit built in group control device；First controller built in the pump control unit
With the first intelligent electric meter；Second controller and the second intelligent electric meter built in the cooling tower control device；The air processing machine
3rd controller and the 3rd intelligent electric meter built in group control device；Building energy agreement built in the handpiece Water Chilling Units communication device
Gateway；Handpiece Water Chilling Units communication device connects handpiece Water Chilling Units control device, and handpiece Water Chilling Units control device includes the 4th controller.Its
Core is to propose the framework and composition of group control system, does not describe how to be associated the concrete measure of optimization.
The group control method and system of a kind of handpiece Water Chilling Units of existing invention (201610013560.X) propose offer of the present invention
The group control method and system of a kind of handpiece Water Chilling Units, wherein the described method includes：It is corresponding to gather currently running handpiece Water Chilling Units
Cooling load；The cooling load of collection is contrasted with cooling load set in advance；When the refrigeration duty of collection
Amount with the cooling load set in advance meet preset condition when, the currently running handpiece Water Chilling Units are loaded or
It is to propose the framework and composition of group control system that person's off-load, which operates its core, does not describe the generation method of preset condition.
The control method and device of existing invention (20161010953.4) air-conditioning group control system disclose a kind of air-conditioning system
System and its control method and device.The air-conditioning system includes multiple air-conditioner hosts, and the control method of the air-conditioning system includes：Meter
Calculate the energy consumption power needed for air-conditioning system；Energy consumption power according to needed for air-conditioning system determines to need air-conditioner host to be started
Quantity；Multiple air-conditioner hosts of control quantification are opened at the same time.The invention does not describe it and carries out more air-conditioner host increasings, subtracts machine
During team control, the incidence relation between the definite method of load threshold and energy saving performance.
Looked back based on document above, the difficult point of the Optimization of Energy Saving technology of multicomputer team control at present is：1. handpiece Water Chilling Units performance
Index changes with the operation time limit, needs the performance index under continuous updating sub-load just to carry out power excellent
Change distribution.2. the energy consumption of cooling system not only includes handpiece Water Chilling Units refrigeration electricity consumption, also include the transmission energy damage of conveying chilled water
Consumption.Combined influence of the pump variable frequency operation to system power dissipation is considered as in optimal control decision-making.3. in Optimal Decision-making, by
Cover multiple and different energy consumption systems at the same time in target equation, also have different constraints, therefore solve optimal power point
Timing is easily absorbed in local optimum or iterative process restrains slow or not convergent situation.
The content of the invention
The purpose of the present invention is：Reduce cooling system entirety energy consumption, lifting system operational efficiency.
In order to achieve the above object, the technical scheme is that providing a kind of sea of more handpiece Water Chilling Units cooperations
The energy saving group control method of water cooling system, it is characterised in that comprise the following steps：
Step 1: establish system performance index SCOP target equations
In formula, n1、n2The respectively total number of handpiece Water Chilling Units and chilled water pump, PChiller, iFor the use of i-th handpiece Water Chilling Units
Electrical power, COPiFor the dynamic property index of i-th handpiece Water Chilling Units, C is chilled water specific heat capacity, and Δ t is supply backwater temperature difference, G0, i
For the metered flow of i-th chilled water pump, P0, iFor the rated power of i-th chilled water pump；
Step 2: the dynamic property index of adaptive polo placement separate unit handpiece Water Chilling Units, wherein, the dynamic of i-th handpiece Water Chilling Units
Performance index COPiIt is expressed as：
COPi=ai+bi·Ri+ci·Ri 2
In formula, RiFor the part load ratio of i-th handpiece Water Chilling Units, linear coefficient ai, bi, ciUsing following formula adaptively more
Newly：
Step 3: determine electrical power constraints, the refrigeration work consumption constraints of system performance index SCOP target equations
And the conservation of energy, wherein：
Electrical power constraints is：
min(PChiller, i)≤PChiller, i≤max(PChiller, i)
min(PPump, i)≤PPump, i≤max(PPump, i)
In formula, PPump, iFor the electric power of i-th chilled water pump；
Refrigeration work consumption constraints is：
min(QChiller, i)≤QChiller, i≤max(QChiller, i)
In formula, QChiller, iFor the refrigeration work consumption of i-th handpiece Water Chilling Units；
The conservation of energy：
QloadFor bearing power；
Step 4: maximization solution is carried out to system performance index SCOP targets equation using fast simulated annealing algorithm,
Determine optimal handpiece Water Chilling Units power distribution；
Step 5: the chilled-water flow of each handpiece Water Chilling Units is calculated, wherein, the chilled-water flow Q of i-th handpiece Water Chilling Unitsi
=C × Δ T × PChiller, i×COPi。
Preferably, the step 4 includes process one and process two, wherein：
Process one is to use higher initial temperature, and Disturbance Model makees global quick global optimizing, includes the following steps：
The random global perturbation equation of step 1.1, foundation, generates new RANDOM SOLUTION；
Step 1.2, by newly-generated RANDOM SOLUTION substitute into energy equation, if energy value declines new explanation be accepted as working as
Optimal solution under preceding state, according to Boltzmann-Gibbs distribution acceptance probabilities and Metropolis criterions if energy rises
Determine whether to receive new explanation as the optimal solution under current state；
If step 1.3, new explanation are rejected, return to step 1.1；
If step 1.4, new explanation are received, Current Temperatures are updated according to annealing scheme formula one, annealing scheme formula one is：
In formula, T and T0It is Current Temperatures and initial temperature respectively；α is temperature decline coefficient；J is
Iterations；
Process two is to use relatively low initial temperature, and Disturbance Model makees local slow optimizing, includes the following steps：
Step 2.1, foundation Random Local perturbation equation, generate new RANDOM SOLUTION；
Step 2.2, by newly-generated RANDOM SOLUTION substitute into energy equation, if energy value declines new explanation be accepted as working as
Optimal solution under preceding state, it is accurate according to Boltzmann-Gibbs distribution acceptance probabilities and Metropolis if energy rises
Then, M criterions are hereinafter referred to as, determine whether to receive new explanation as the optimal solution under current state；
If step 2.3, new explanation are rejected, return to step 2.1；
If step 2.4, new explanation are received, Current Temperatures are updated according to annealing scheme formula two, annealing scheme formula two is：
In formula, k0For the iterations of process one；β is the temperature rise factor.
Preferably, further include：
Step 6: the rotating speed of each handpiece Water Chilling Units is calculated, wherein, the rotating speed of i-th handpiece Water Chilling UnitsFormula
In, QI, 0For the specified chilled-water flow of i-th handpiece Water Chilling Units, nI, 0For the rated speed of i-th handpiece Water Chilling Units.
The present invention, which uses, improves short annealing algorithm to ship cooling system under each cooling condition demand, to cooling-water machine
The refrigeration work consumption of group optimizes distribution, lifting system overall performance index (SCOP).The foundation of target equation considers
The energy-saving effect of chilled water pump temperature difference control variable-flow measure, passes through chilled water pump frequency control and meets the defeated of freezing water
Demand is sent, while reduces energy loss meaningless in transmitting procedure.Pass through the dynamic of adaptive polo placement separate unit handpiece Water Chilling Units
Energy index, improves the accuracy of target equation.In optimization process, improvement fast simulated annealing algorithm is employed, passes through sublevel
Duan Youhua ring layouts, realize the initial global optimizing of optimization, optimize the preferable optimization process of later stage local optimizing, break away from
The problem of conventional algorithm is easily absorbed in local optimization when underload interest rate optimizes, improves the optimization efficiency of simulated annealing.
These designs are effective to solve the difficult point realized at present in multicomputer team control Optimization of Energy Saving.
Brief description of the drawings
Fig. 1 is single fighter salt water cooling system Organization Chart；
Fig. 2 is multicomputer salt water cooling system chilled water system Organization Chart；
Fig. 3 is short annealing compared with improving the annealing temperature curve of short annealing algorithm；
Fig. 4 is the optimization process for improving fast simulated annealing algorithm；
Fig. 5 is COP curves under 50RT, 20RT handpiece Water Chilling Units different load rate；
Fig. 6 is SCOP optimization process of the cooling system under demand operating mode 45RT；
Fig. 7 is performance index contrast before and after system optimization.
Embodiment
To become apparent the present invention, hereby with preferred embodiment, and attached drawing is coordinated to be described in detail below.
The present invention provides a kind of energy saving group control method of salt water cooling system of more handpiece Water Chilling Units cooperations, including with
Lower step：
Step 1: establish system performance index SCOP target equations
In formula, n1、n2The respectively total number of handpiece Water Chilling Units and chilled water pump, PChiller, iFor the use of i-th handpiece Water Chilling Units
Electrical power, COPiFor the dynamic property index of i-th handpiece Water Chilling Units, C is chilled water specific heat capacity, and Δ t is supply backwater temperature difference, G0, i
For the metered flow of i-th chilled water pump, P0, iFor the rated power of i-th chilled water pump.
The derivation of above-mentioned formula is：
System performance index is the index for characterizing salt water cooling system efficiency, and it is total with system that it is defined as cooling system power
The business of electric power：
In formula, SCOP be cooling system overall performance index, QChiller, iFor the refrigeration work consumption of i-th handpiece Water Chilling Units,
PChiller, iFor the electric power of i-th handpiece Water Chilling Units, PPump, iFor the electric power of i-th chilled water pump.Under normal circumstances,
Handpiece Water Chilling Units are corresponded with chilled water pump and configured, so n1=n2.If the refrigeration work consumption separate unit performance of handpiece Water Chilling Units is referred to
Mark COPiSubstitute, then formula (1) can transform to：
Under a certain cooling condition, refrigeration duty Q is determined, the supply backwater temperature difference of variable flow system is constant, then chilled-water flow
Determined by following formula：
G is chilled-water flow in formula, and Q is refrigeration duty, and C is chilled water specific heat capacity, and Δ T is supply backwater temperature difference.According to water pump
Similar law, the electric power of water pump can try to achieve by following formula：
G in formula0For the metered flow of water pump, P0For its rated power.After formula (4) is substituted into formula (2), target equation (2)
It can transform to：
Step 2: the dynamic property index of adaptive polo placement separate unit handpiece Water Chilling Units.From formula (5) can with inference, system
Separate unit performance index COPs of the performance index SCOP with the sharing of load of each handpiece Water Chilling Units and under the sharing of load is related.Due to
Handpiece Water Chilling Units performance index (COP) changes with the operation time limit, therefore can optimize in preceding, need carrying out systematic entirety
Adaptive polo placement is carried out to the performance index of separate unit handpiece Water Chilling Units.
The dynamic property index COP of i-th handpiece Water Chilling UnitsiIt is expressed as：
COPi=ai+bi·Ri+ci·Ri 2
In formula, RiFor the part load ratio of i-th handpiece Water Chilling Units, linear coefficient ai, bi, ciUsing following formula adaptively more
Newly：
The above method can obtain the COP values of unit in system operation by part load ratio R in real time, so as to more preferable
Unit COP-R relations in ground renewal target equation, if R matrixes are irreversible, can use least square recurrence method to obtain COP-
R relational expressions.
Step 3: determine electrical power constraints, the refrigeration work consumption constraints of system performance index SCOP target equations
And the conservation of energy, wherein：
Electrical power constraints is：
min(PChiller, i)≤PChiller, i≤max(PChiller, i)
min(PPump, i)≤PPump, i≤max(PPump, i)
In formula, PPump, iFor the electric power of i-th chilled water pump；
Refrigeration work consumption constraints is：
min(QChiller, i)≤QChiller, i≤max(QChiller, i)
In formula, QChiller, iFor the refrigeration work consumption of i-th handpiece Water Chilling Units；
The conservation of energy：
QloadFor bearing power；
Step 4: maximization solution is carried out to system performance index SCOP targets equation using fast simulated annealing algorithm,
Determine optimal handpiece Water Chilling Units power distribution.
Defined according to step 3, by maximizing formula (5) system can be made to realize maximum on the premise of refrigeration requirement is met
Energy-saving effect.Convergent situation is not easy in order to avoid under underload rate, optimization process is absorbed in, it is quick using improving herein
Simulated annealing carries out maximization solution to formula (5).
Improved fast simulated annealing algorithm can be divided into quick global annealing optimizing and the annealing optimizing two of slow local
Process, is shown in Fig. 3.
Step 4 includes process one and process two, wherein：
Process one is to use higher initial temperature, and Disturbance Model makees global quick global optimizing, includes the following steps：
The random global perturbation equation of step 1.1, foundation, generates new RANDOM SOLUTION：
X=min (X)+r (max (X)-min (X))
In formula, X is the codomain section of disaggregation；Random numbers of the r between 0 and 1, obedience are uniformly distributed；X for it is newly-generated with
Machine solution.
Step 1.2, by newly-generated RANDOM SOLUTION substitute into energy equation, if energy value declines new explanation be accepted as working as
Optimal solution under preceding state, according to Boltzmann-Gibbs distribution acceptance probabilities and Metropolis criterions if energy rises
Determine whether to receive new explanation as the optimal solution under current state；
If step 1.3, new explanation are rejected, return to step 1.1；
If step 1.4, new explanation are received, Current Temperatures are updated according to annealing scheme formula one, annealing scheme formula one is：
In formula, T and T0It is Current Temperatures and initial temperature respectively；α is temperature decline coefficient；J is
Iterations；
Process two is to use relatively low initial temperature, and Disturbance Model makees local slow optimizing, includes the following steps：
Step 2.1, foundation Random Local perturbation equation, generate new RANDOM SOLUTION：
xj=xj-1+(r-0.5)(max(X)-min(X))/L(j)
In formula, X is the codomain section of disaggregation；Random numbers of the r between 0 and 1, obedience are uniformly distributed；xjFor it is newly-generated with
Machine solution；xj-1For the RANDOM SOLUTION of last grey iterative generation；L (j) is search restriction factor, with iterations j positive correlations.
Step 2.2, by newly-generated RANDOM SOLUTION substitute into energy equation, if energy value declines new explanation be accepted as working as
Optimal solution under preceding state, it is accurate according to Boltzmann-Gibbs distribution acceptance probabilities and Metropolis if energy rises
Then, M criterions are hereinafter referred to as, determine whether to receive new explanation as the optimal solution under current state；
If step 2.3, new explanation are rejected, return to step 2.1；
If step 2.4, new explanation are received, Current Temperatures are updated according to annealing scheme formula two, annealing scheme formula two is：
In formula, k0For the iterations of process one；β is the temperature rise factor.
Improved short annealing algorithm changes the single perturbation scheme of short annealing algorithm, different annealing schemes
It is engaged with perturbation mode, forms the initial global optimizing of optimization, is optimized the preferable Optimization Progress of later stage local optimizing, solve
Local optimum is easily absorbed in during solution optimal power allocation or iterative process convergence is slow or not convergent difficult point.Fig. 4 is described
Improve the implementation procedure of annealing algorithm.
Step 5: the chilled-water flow of each handpiece Water Chilling Units is calculated, wherein, the chilled-water flow Q of i-th handpiece Water Chilling Unitsi
=C × Δ T × PChiller, i×COPi；
Step 6: the rotating speed of each handpiece Water Chilling Units is calculated, wherein, the rotating speed of i-th handpiece Water Chilling UnitsFormula
In, QI, 0For the specified chilled-water flow of i-th handpiece Water Chilling Units, nI, 0For the rated speed of i-th handpiece Water Chilling Units.
The present invention, which uses, improves short annealing algorithm to ship cooling system under each cooling condition demand, to cooling-water machine
The refrigeration work consumption of group optimizes distribution, lifting system overall performance index (SCOP).The foundation of target equation considers
The energy-saving effect of chilled water pump temperature difference control variable-flow measure, passes through chilled water pump frequency control and meets the defeated of freezing water
Demand is sent, while reduces energy loss meaningless in transmitting procedure.Pass through the dynamic of adaptive polo placement separate unit handpiece Water Chilling Units
Energy index, improves the accuracy of target equation.In optimization process, improvement fast simulated annealing algorithm is employed, passes through sublevel
Duan Youhua ring layouts, realize the initial global optimizing of optimization, optimize the preferable optimization process of later stage local optimizing, break away from
The problem of conventional algorithm is easily absorbed in local optimization when underload interest rate optimizes, improves the optimization efficiency of simulated annealing.
These designs are effective to solve the difficult point realized at present in multicomputer team control Optimization of Energy Saving.
The present invention is further illustrated below in conjunction with specific data：
It is each one of 50RT and 20RT handpiece Water Chilling Units to meet ship in high and low refrigeration that certain example, which is equipped with rated cooling capacity,
Demand under operating mode, the coefficient of performance is shown in Fig. 5 under its sub-load.The refrigeration work consumption that intervals of power is 10% can be achieved in each unit
Adjust.50RT units are equipped with the chilled water pump one that rated power is 5kw, its metered flow is 120T/h, and 20RT units are equipped with
Rated power is the chilled water pump one of 2kw, its metered flow is 60T/h.
Based on above-mentioned it is assumed that bringing parameter into formula (5), then formula (5) can be reduced to：
In formula, Q1、Q2、P1、P2、Q1, N、Q2, N50RT units, the operation refrigeration work consumption of 20RT units, operation are corresponded to respectively
Electric power and specified refrigeration work consumption.P3, N、P4, NThe respectively rated power of 10kw, 5kw water pump.
The Q under a certain system conditiond, target equation can be abbreviated as：
Wherein Q1+Q2≈Q.The optimization of target equation is regarded as in the case where meeting duty requirements freezing to two handpiece Water Chilling Units
The optimal dispatching of power.
Fig. 6 is described in the case of demand operating mode 45RT, the power optimization process of cooling system.In iteration mistake early period
Cheng Zhong, global perturbation equation generate RANDOM SOLUTION.In the case where temperature is higher, non-optimal solution also has greater probability satisfaction
Metropolis criterions and received, so optimization initial stage system performance index fluctuating range it is larger.In iteration mistake
The middle and later periods of journey, RANDOM SOLUTION are generated by local perturbation equation.Due to the rapid decrease of temperature, non-optimal solution meets
The probability of Metropolis criterions is gradually reduced as 0, so phase after optimization, SCOP convergences, the power distribution of system reach most
It is excellent.
Before and after Fig. 7 describes optimization, the contrast of the system performance index under different cooling condition demands.Before optimization, it is
System employs conventional fully loaded increasing machine strategy, after 20RT units are fully loaded with, opens 50RT units, and chilled water pump constant flow is transported
OK.After optimization, system distributes each cold output power according to optimum results, due to the general unit performance of large sized unit (COP)
It is high compared to small-load generators, so also preferentially opening large sized unit under small operating mode.Since chilled water pump is by constant temperature difference control
Variable-flow operation processed, so the power consumption of water pump is determined by cold.Under small operating mode, the energy consumption accounting that water pump is saved is larger, therefore
System performance index differential is larger before and after optimization.In the case of big operating mode, since two-shipper group is gradually fully loaded with, chilled water pump is becoming
Power consumption difference under flow and constant flow is gradually reduced, so the system performance exponential curve before and after optimization also gradually closes up.
When cooling condition is 5RT, after optimization SCOP lifting 2.36, be lifted under all part load conditions it is highest.It is each after optimization
Under load condition, SCOP averagely lifts 0.88.
Table 1 enumerates the different increase and decrease machine strategy of system before and after optimization.Mutually more conventional increase and decrease mechanism degree, after optimization
When refrigeration duty changes, the power adjustment of unit is more frequent.In order to avoid refrigeration duty short-term fluctuation make it that system is frequent
Loading, unloading unit, because carrying out smooth treatment to measurement load data in real time, reduce shadow of the load disturbance to system stability
Ring.Many documents have a detailed description this, repeat no more.
Table 1 optimizes front and rear system increase and decrease machine strategy contrast
Claims (3)
1. a kind of energy saving group control method of salt water cooling system of more handpiece Water Chilling Units cooperations, it is characterised in that including following step
Suddenly：
Step 1: establish system performance index SCOP target equations
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</msub>
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<msub>
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<mi>i</mi>
</msub>
</mrow>
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<mi>C</mi>
<mo>&times;</mo>
<mi>&Delta;</mi>
<mi>T</mi>
<mo>&times;</mo>
<msub>
<mi>G</mi>
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In formula, n1、n2The respectively total number of handpiece Water Chilling Units and chilled water pump, PChiller, iElectric work is used for i-th handpiece Water Chilling Units
Rate, COPiFor the dynamic property index of i-th handpiece Water Chilling Units, C is chilled water specific heat capacity, and Δ t is supply backwater temperature difference, G0, iFor i-th
The metered flow of platform chilled water pump, P0, iFor the rated power of i-th chilled water pump；
Step 2: the dynamic property index of adaptive polo placement separate unit handpiece Water Chilling Units, wherein, the dynamic property of i-th handpiece Water Chilling Units
Index COPiIt is expressed as：
COPi=ai+bi·Ri+ci·Ri 2
In formula, RiFor the part load ratio of i-th handpiece Water Chilling Units, linear coefficient ai, bi, ciUsing following formula adaptive updates：
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Step 3: determine electrical power constraints, refrigeration work consumption constraints and the energy of system performance index SCOP target equations
Conservation is measured, wherein：
Electrical power constraints is：
min(PChiller, i)≤PChiller, i≤max(PChiller, i)
min(PPump, i)≤PPump, i≤max(PPump, i)
In formula, PMmp, iFor the electric power of i-th chilled water pump；
Refrigeration work consumption constraints is：
min(QChiller, i)≤QChiller, i≤max(QChiller, i)
In formula, QChiller, iFor the refrigeration work consumption of i-th handpiece Water Chilling Units；
The conservation of energy：
QloadFor bearing power；
Step 4: carrying out maximization solution to system performance index SCOP targets equation using fast simulated annealing algorithm, determine
Optimal handpiece Water Chilling Units power distribution；
Step 5: the chilled-water flow of each handpiece Water Chilling Units is calculated, wherein, the chilled-water flow Q of i-th handpiece Water Chilling Unitsi=C ×
ΔT×PChiller, i×COPi。
2. a kind of energy saving group control method of salt water cooling system of more handpiece Water Chilling Units cooperations as claimed in claim 1, it is special
Sign is that the step 4 includes process one and process two, wherein：
Process one is to use higher initial temperature, and Disturbance Model makees global quick global optimizing, includes the following steps：
The random global perturbation equation of step 1.1, foundation, generates new RANDOM SOLUTION；
Step 1.2, by newly-generated RANDOM SOLUTION substitute into energy equation, if energy value declines new explanation be accepted as current state
Under optimal solution, if energy rise if according to Boltzmann-Gibbs distribution acceptance probability and Metropolis criterions judge is
It is no to receive new explanation as the optimal solution under current state；
If step 1.3, new explanation are rejected, return to step 1.1；
If step 1.4, new explanation are received, Current Temperatures are updated according to annealing scheme formula one, annealing scheme formula one is：
In formula, T and T0It is Current Temperatures and initial temperature respectively；α is temperature decline coefficient；J is iteration time
Number；
Process two is to use relatively low initial temperature, and Disturbance Model makees local slow optimizing, includes the following steps：
Step 2.1, foundation Random Local perturbation equation, generate new RANDOM SOLUTION；
Step 2.2, by newly-generated RANDOM SOLUTION substitute into energy equation, if energy value declines new explanation be accepted as current state
Under optimal solution, according to Boltzmann-Gibbs distribution acceptance probabilities and Metropolis criterions if energy rises, below letter
Claim M criterions, determine whether to receive new explanation as the optimal solution under current state；
If step 2.3, new explanation are rejected, return to step 2.1；
If step 2.4, new explanation are received, Current Temperatures are updated according to annealing scheme formula two, annealing scheme formula two is：
In formula, k0For the iterations of process one；β is the temperature rise factor.
3. a kind of energy saving group control method of salt water cooling system of more handpiece Water Chilling Units cooperations as claimed in claim 1, it is special
Sign is, further includes：
Step 6: the rotating speed of each handpiece Water Chilling Units is calculated, wherein, the rotating speed of i-th handpiece Water Chilling UnitsIn formula, QI, 0
For the specified chilled-water flow of i-th handpiece Water Chilling Units, nI, 0For the rated speed of i-th handpiece Water Chilling Units.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109838876A (en) * | 2019-02-19 | 2019-06-04 | 陈娟 | Central air-conditioning freezing computer room team control management system |
| CN111664553A (en) * | 2020-06-08 | 2020-09-15 | 中国工商银行股份有限公司 | Water chilling unit operation control method and system, electronic equipment and storage medium |
| CN112572752A (en) * | 2020-11-27 | 2021-03-30 | 沪东中华造船(集团)有限公司 | Frequency conversion energy-saving method for marine seawater cooling pump |
| CN116258022A (en) * | 2023-05-11 | 2023-06-13 | 上海能誉科技股份有限公司 | Annual energy consumption analog simulation calculation method and system for high-efficiency refrigeration station house |
| CN116822709A (en) * | 2023-05-22 | 2023-09-29 | 深圳市中电电力技术股份有限公司 | Parallel water chilling unit load distribution optimization method, system and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040011066A1 (en) * | 2002-07-19 | 2004-01-22 | Hitachi Plant Engineering & Construction Co., Ltd. | Air conditioning plant and control method thereof |
| CN1570500A (en) * | 2004-05-14 | 2005-01-26 | 杜勇 | Energy conservation operation control method for water-cooled central air-conditioning systems |
| KR100802159B1 (en) * | 2006-08-29 | 2008-02-11 | 바스코리아 주식회사 | Fan coil unit controller for optimally controlling the indoor temperature and the system for controlling the fan coil units |
| CN105546757A (en) * | 2016-01-05 | 2016-05-04 | 珠海格力电器股份有限公司 | Group control method and system for water chilling units |
| CN107131704A (en) * | 2017-06-24 | 2017-09-05 | 济南金孚瑞冷却技术有限公司 | A kind of SMART FLUID cooling system |
-
2017
- 2017-11-03 CN CN201711074632.2A patent/CN107906810A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040011066A1 (en) * | 2002-07-19 | 2004-01-22 | Hitachi Plant Engineering & Construction Co., Ltd. | Air conditioning plant and control method thereof |
| CN1570500A (en) * | 2004-05-14 | 2005-01-26 | 杜勇 | Energy conservation operation control method for water-cooled central air-conditioning systems |
| KR100802159B1 (en) * | 2006-08-29 | 2008-02-11 | 바스코리아 주식회사 | Fan coil unit controller for optimally controlling the indoor temperature and the system for controlling the fan coil units |
| CN105546757A (en) * | 2016-01-05 | 2016-05-04 | 珠海格力电器股份有限公司 | Group control method and system for water chilling units |
| CN107131704A (en) * | 2017-06-24 | 2017-09-05 | 济南金孚瑞冷却技术有限公司 | A kind of SMART FLUID cooling system |
Non-Patent Citations (1)
| Title |
|---|
| 张怀亮: "基于进化策略的艇用冷水机组群控优化节能技术", 《电机与控制应用》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109838876A (en) * | 2019-02-19 | 2019-06-04 | 陈娟 | Central air-conditioning freezing computer room team control management system |
| CN111664553A (en) * | 2020-06-08 | 2020-09-15 | 中国工商银行股份有限公司 | Water chilling unit operation control method and system, electronic equipment and storage medium |
| CN112572752A (en) * | 2020-11-27 | 2021-03-30 | 沪东中华造船(集团)有限公司 | Frequency conversion energy-saving method for marine seawater cooling pump |
| CN116258022A (en) * | 2023-05-11 | 2023-06-13 | 上海能誉科技股份有限公司 | Annual energy consumption analog simulation calculation method and system for high-efficiency refrigeration station house |
| CN116822709A (en) * | 2023-05-22 | 2023-09-29 | 深圳市中电电力技术股份有限公司 | Parallel water chilling unit load distribution optimization method, system and storage medium |
| CN116822709B (en) * | 2023-05-22 | 2024-03-22 | 深圳市中电电力技术股份有限公司 | Parallel water chilling unit load distribution optimization method, system and storage medium |
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