CN1255653C - Method for fuzzy expected controlling cold water system of central air conditioner - Google Patents
Method for fuzzy expected controlling cold water system of central air conditioner Download PDFInfo
- Publication number
- CN1255653C CN1255653C CN 200410040667 CN200410040667A CN1255653C CN 1255653 C CN1255653 C CN 1255653C CN 200410040667 CN200410040667 CN 200410040667 CN 200410040667 A CN200410040667 A CN 200410040667A CN 1255653 C CN1255653 C CN 1255653C
- Authority
- CN
- China
- Prior art keywords
- water
- fuzzy
- chilled water
- period
- control unit
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 129
- 238000000034 method Methods 0.000 title claims abstract description 21
- 239000000498 cooling water Substances 0.000 claims abstract description 16
- 238000012937 correction Methods 0.000 claims abstract description 16
- 238000012545 processing Methods 0.000 claims abstract description 7
- 238000004378 air conditioning Methods 0.000 claims description 15
- 230000008014 freezing Effects 0.000 claims description 9
- 238000007710 freezing Methods 0.000 claims description 9
- 230000009467 reduction Effects 0.000 claims description 8
- 230000008859 change Effects 0.000 claims description 7
- 238000006243 chemical reaction Methods 0.000 claims description 6
- JEGUKCSWCFPDGT-UHFFFAOYSA-N h2o hydrate Chemical compound O.O JEGUKCSWCFPDGT-UHFFFAOYSA-N 0.000 claims description 5
- 238000004891 communication Methods 0.000 claims description 4
- 238000005259 measurement Methods 0.000 claims description 4
- 238000005457 optimization Methods 0.000 claims description 3
- 238000009434 installation Methods 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 abstract description 4
- 238000005057 refrigeration Methods 0.000 abstract description 2
- 239000008400 supply water Substances 0.000 abstract 1
- 230000000694 effects Effects 0.000 description 7
- 238000005096 rolling process Methods 0.000 description 5
- 238000013459 approach Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 3
- 238000010276 construction Methods 0.000 description 2
- 241000606643 Anaplasma centrale Species 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000009931 harmful effect Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 230000035772 mutation Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
- 239000003643 water by type Substances 0.000 description 1
Images
Landscapes
- Air Conditioning Control Device (AREA)
Abstract
The present invention discloses a fuzzy anticipation control method and a device of a cooling water system of a central air conditioner, which belongs to the technology for controlling the energy saving of the air conditioner. The present invention aims to provide an energy-saving control method and a device of the central air conditioner. The method comprises operation parameter collection, data processing, optimized correction value prediction, fuzzy reasoning, and control variable output and control. By collecting the operation parameters of the temperature, the temperature difference, the flow rate, the pressure difference, etc. of supply water and return water of the cooling water system, the average values of corresponding operation parameters for n periods are computed. According to the variation trend of the average values, optimized correction values are predicted, and then, optimizing control quantity can be obtained through the fuzzy reasoning; the rotation speed of a refrigeration water pump is controlled through a frequency converter. The device comprises a fuzzy controller, the frequency converter, a water temperature sensor, a flow meter, a pressure difference sensor of water flows, and an intelligent control unit, wherein the sensor and the flow meter are connected with the intelligent control unit; the water pump is connected with the intelligent control unit through the frequency converter; the intelligent control unit is connected with the fuzzy controller.
Description
Technical field: the present invention relates to a kind of energy-saving control method of air conditioning water system, relate in particular to the fuzzy expection of a kind of freezing water system of central air conditioner control method; The invention still further relates to a kind of device of realizing this method.
Background technology: central air conditioner system is widely adopted in modern heavy construction, is one of facility of energy consumption maximum in the modern building.Increasingly serious along with the world energy sources supply and demand, people more and more pay attention to the exploitation and the application of central air conditioner system energy-conserving control technology.
In recent years, in order to reduce the energy waste of central air conditioner system, people begin to adopt universal frequency converter to control the chilled water pump of air-conditioning system.Control method commonly used has PID or PI control, and its control parameter is the temperature or the pressure of chilled water, i.e. constant difference or constant-pressure drop control; Control is according to being the operational parameter value in the current a certain moment, and control mode is for following control.This PID or PI control based on mathematical models, principle is simple, easy to use, cost is lower, also can reach certain energy-saving effect, but its limitation is:
A. central air-conditioning be a kind of time lag, the time become, the very strong complication system of coupling between non-linear, many reference amounts and parameter, be difficult for obtaining more accurate Mathematical Modeling, approximate or coarse model is difficult to achieve effective control;
During B.PID regulates, proportionality coefficient K
P, integration time constant T
IWith derivative time constant T
d, can not follow the variation of controlled parameter and adjust automatically in case after selected, if the people does not go to regulate, it is changeless etc. most important engineering parameter.That is to say, after engineering parameter is adjusted, just remove to tackle various operating condition, therefore can not reach best energy-saving effect with same kind of parameter.Its analysis of causes is as follows:
Central air conditioner system realizes the process of refrigeration, with chilled water as carrying cold medium in the realization that constantly circulates between air conditioner refrigerating device evaporimeter and the end equipments such as fan coil, air-conditioning unit.Because heavy construction air-conditioning area is big, water-system pipeline by air complex structure, path length, the water yield of possessing of chilled water system reaches hundreds of m
3, cause its thermal capacity and thermal inertia very big, be a typical big inertia system; On the other hand, be tens of minutes owing to finish a chilled water circulation required time, so it is again a Large-lag System.For this big inertia, large time delay and have dynamic mutation and highly nonlinear system, the maximum difficult point of control is to control the uncertainty and the height mutability of effect.Mainly show as: after control instruction is sent, response that water cycle period does not finish as yet or controlled parameter also is not able to do in time, variation may just take place again in system running environment or part throttle characteristics; After energy-saving control device collects new variation, can send new control instruction again, thereby cause the disorderly or vibration of system's operation, the chilled water return water temperature is fluctuateed in a big way, the long-time stable state that all can not reach setting is difficult to obtain desired control effect.
Summary of the invention: in order to overcome the deficiency that existing PID or PI energy-conserving control technology exist, the present invention aims to provide the fuzzy expection of a kind of freezing water system of central air conditioner control method; This method can effectively solve owing to chilled water system self characteristics such as intrinsic big inertia, large time delay cause the difficult problem of the disorderly or vibration of system's operation, realize the accurate control of chilled water return water temperature, thereby both can realize accurate control to air conditioning terminal service quality, can excavate the delivery energy saving space of chilled water system again to greatest extent, reach best energy-saving effect.The present invention also aims to provide a kind of device of realizing this method.
Technical scheme of the present invention comprises that correction valve prediction, fuzzy reasoning are handled, optimized to operational factor collection, data, controlled quentity controlled variable is exported and control; By collection to chilled water system supply and return water temperature, the temperature difference, flow, four operational factors of pressure reduction, calculate the n cycle mean value of corresponding operational factor, predict its optimization correction value according to the variation tendency of this mean value, then by the fuzzy reasoning controlled quentity controlled variable that is optimized, and, chilled-water flow is carried out corresponding adjusting by Frequency Converter Control chilled water pump rotating speed;
Concrete grammar is as follows:
1. operational factor collection is gathered the supply and return water temperature of chilled water system, the flow in the water supply line, these four operational factors of current pressure reduction between the confession water return pipeline by the cooling-water temperature sensor that is installed in central air conditioner system low-temperature receiver side, flowmeter and current differential pressure pickup;
2. data are handled, and intelligent control unit the air conditioning terminal k period according to the above-mentioned data computation of being gathered, i.e. required refrigerating capacity of current period:
Q
k＝λ·w·ΔT
In the formula, Q
k---k period, the i.e. required refrigerating capacity of air conditioning terminal of current period;
λ---with relevant constants such as chilled water specific heat, density;
W---chilled-water flow collection value;
Δ T---the temperature difference collection value between chilled water confession, the backwater;
Calculate the mean value of above-mentioned four operational factors of chilled water in nearest n chilled water cycle period simultaneously; Described mean value is the addition gained and that get divided by the number n in the cycle one by one value of the value of relevant parameters in nearest n chilled water cycle period; Its formula is:
In the formula,
---certain parameter k period, i.e. the n cycle mean value of current period;
x
i---certain parameter is in the value in i cycle;
N---the number of chilled water cycle period, n is 〉=5 integer;
Intelligent control unit is with required refrigerating capacity Q
kDynamically update and send to fuzzy controller with the n cycle mean value of described four operational factors;
3. optimize correction valve prediction, fuzzy controller calculates it and optimizes correction value---deviation E according to the n cycle mean value of Δ T
kAnd deviation variation rate
In the formula, E
k---k period, the i.e. temperature difference deviation of chilled water system of current period;
---k period, i.e. the n cycle mean temperature difference value of chilled water system of current period;
Δ T
0---the temperature difference setting value of chilled water system;
In the formula,
Period, the i.e. rate of change of the chilled water system temperature difference deviation of current period:
E
K-1---the temperature difference deviation of the preceding 1 period chilled water system of k;
4. fuzzy reasoning, fuzzy controller is optimized correction value, i.e. deviation E with temperature difference T
kAnd deviation variation rate
Carry out the A/D conversion and make Fuzzy processing, obtain fuzzy control quantity u through fuzzy reasoning again
k, this fuzzy control quantity is carried out sharpening processing and D/A conversion, the controlled quentity controlled variable that is optimized U
kAnd pass to intelligent control unit;
Deviation E
k, deviation variation rate
With optimal control amount u
kFuzzy subset's domain get:
Control law is expressed as:
In the formula, α, β ∈ (0,1)
5. the output of controlled quentity controlled variable and control, intelligent control unit is with optimal control amount U
kConvert the control signal of frequency converter to, regulate chilled water water circulating pump rotating speed to change the flow of chilled water system by frequency converter.
In order to realize said method, device of the present invention comprises fuzzy controller, frequency converter, cooling-water temperature sensor, flowmeter, current differential pressure pickup and the intelligent control unit that is made of control processor circuit, memory circuitry, network communication interface circuit, simulated measurement input circuit, analogue quantity output circuit and power circuit; The current differential pressure pickup is installed at two ends at by-passing valve, in the water side of secondary water pump flowmeter is installed, and flowmeter is installed on bypass pipe, and cooling-water temperature sensor, backwater end installation cooling-water temperature sensor are installed in the chilled water water side of air conditioner refrigerating unit; Current differential pressure pickup, flowmeter, cooling-water temperature sensor are connected with intelligent control unit by order wire respectively; No. one time water pump is connected with intelligent control unit respectively with order wire by frequency converter with the secondary water pump, and by-passing valve is connected with intelligent control unit by order wire; Intelligent control unit is connected with fuzzy controller by order wire respectively.
Compared with the prior art, the operational parameter value addition of continuous n the chilled water cycle period that the present invention will collect draws corresponding mean value, has reflected the mean parameter in some cycles.Because the parameter of institute's statistical computation so the mean parameter that calculates also is a dynamic parameter, can reflect the variation of process along with process moves preferably; On the other hand, owing to gathered the parameter value in n cycle, because of its accumulated time is far longer than the time in 1 cycle, so can eliminate the harmful effect of system's inertia and hysteresis preferably.
The present invention has significant effect and practical significance for the stability and the adaptive capacity of the energy-conservation and raising system operation that realizes freezing water system of central air conditioner.
Description of drawings:
Fig. 1 is the fuzzy expection of a freezing water system of central air conditioner control device schematic diagram;
Fig. 2 is the circuit diagram of intelligent control unit;
Fig. 3 is a chilled water return water temperature variation diagram in the prior art;
Fig. 4 is a chilled water return water temperature variation diagram of the present invention.
In the accompanying drawing: No. 10 water pumps of fuzzy controller 1 intelligent control unit, 2,3 frequency converter 4 by-passing valves, 5 current differential pressure pickup 6 flowmeters, 7,13 secondary water pump 8 cooling-water temperature sensors, 9,11 air conditioner refrigerating units 12 control processor circuits 14 memory circuitries 15 network communication interface circuit 16 simulated measurement input circuits 17 analogue quantity output circuits 18 power circuits 19
The specific embodiment: the invention will be further described below in conjunction with accompanying drawing and specific embodiment:
The fuzzy expection of freezing water system of central air conditioner provided by the present invention control method is achieved in that
1. operational factor collection, when the air conditioning terminal load variations, the operational factors such as current pressure reduction between the supply and return water temperature in the chilled water system, water supply flow and the confession water return pipeline are gathered by the cooling-water temperature sensor, flowmeter and the differential pressure pickup that are installed in the chilled water system.
2. data are handled, and intelligent control unit the air conditioning terminal k period, promptly current required refrigerating capacity according to the data computation of being gathered:
Q
k＝λ·w·ΔT
In the formula, Q
k---k period, the required refrigerating capacity of promptly current air conditioning terminal;
λ---with relevant constants such as chilled water specific heat, density:
W---chilled-water flow collection value;
Δ T---the temperature difference collection value between chilled water confession, the backwater:
Calculate the mean values of operational factor in nearest n chilled water cycle period such as the chilled water temperature difference, pressure reduction or flow simultaneously.Described mean value is the addition gained and that get divided by the number n in the cycle one by one value of the value of relevant parameters in nearest n chilled water cycle period: its mathematical formulae is:
In the formula,
---the n cycle mean value of certain parameter k period (promptly current);
x
i---certain parameter is in the value in i cycle;
N---the number of chilled water cycle period, n is 〉=5 integer;
Can obtain the relevant operational factor of chilled water with said method, as: n cycle mean values such as the temperature difference, pressure reduction or flow.As time goes on, these n cycle mean values also will be along with change.Therefore be also referred to as n cycle moving average; Certainly, also it can be indicated in respectively with time is on the figure of abscissa or in the form, obtains the Moving Average or the rolling average table of relevant parameter.Intelligent control unit is with required refrigerating capacity Q
kDynamically update and send to fuzzy controller with the n cycle moving average of relevant operational factor.
8. optimize correction valve prediction, at required refrigerating capacity Q
kUnder the situation about determining,, can regulate, promptly be optimized correction the operational factor of chilled water system in order to seek the maximum energy-saving running status.Because the required refrigerating capacity Q of air conditioning terminal
kBe the function of flow w and temperature difference T: Q
0=f (w, Δ T) therefore, can realize the energy-saving run of chilled water system by the reasonable adjusting to flow W and temperature difference T; Simultaneously, in order to realize accurate control, can realize: for this reason, choose Δ T as the control parameter by control temperature difference T to the chilled water return water temperature.Fuzzy controller calculates its optimization correction value, that is: deviation E according to the n cycle moving average of Δ T
kAnd deviation variation rate
In the formula, E
k---k period, the i.e. temperature difference deviation of current chilled water system;
---k period, i.e. the n cycle rolling average temperature approach of current chilled water system;
Δ T
0---the temperature difference setting value of chilled water system.
In the formula,
Period, the rate of change of promptly current chilled water system temperature difference deviation;
E
K-1---the temperature difference deviation of the preceding 1 period chilled water system of k.
Work as E
k＞0, the expression k period, promptly the n cycle rolling average temperature approach of current chilled water system is greater than setting value;
Work as E
k＜0, the expression k period, promptly the n cycle rolling average temperature approach of current chilled water system is less than setting value:
Work as E
k=0, the expression k period, promptly the n cycle rolling average temperature approach of current chilled water system equals setting value;
The time length of described period is got the several times in the sampling period or the cycle of system operational parameters.
4. fuzzy reasoning, fuzzy controller is optimized correction value, i.e. deviation E with temperature difference T
kAnd deviation variation rate
Carry out A/D conversion and Fuzzy processing, obtain fuzzy control quantity u through fuzzy reasoning again
k, this fuzzy control quantity is carried out sharpening processing and D/A conversion, the controlled quentity controlled variable that is optimized U
kAnd pass to intelligent control unit.In order to realize the self-adjusting of fuzzy control rule in the fuzzy controller, system is provided with two and adjusts factor-alpha and β, can be implemented under the different conditions deviation E in the control law
kAnd deviation variation rate
The adjustment of weighting degree.As deviation E
kHour, system is near stable state, and the main task of controller is to reduce overshoot to make system stable as early as possible; Just require deviation variation rate in the control law
Effect big, promptly to deviation variation rate
Weighting more greatly, control law is adjusted by α; As deviation E
kWhen big, the main task of controller is to eliminate deviation, at this moment deviation E
kWeighting in control law should be adjusted by β greatly, can eliminate deviation as early as possible.
Deviation E
k, deviation variation rate
With optimal control amount u
kFuzzy subset's domain get:
Control law is expressed as:
In the formula, α, β ∈ (0,1)
5. the output of controlled quentity controlled variable and control is with optimal control amount U
kConvert the control signal of frequency converter to, regulate chilled water water circulating pump rotating speed to change the flow of chilled water system, to satisfy the required refrigerating capacity Q of air conditioning terminal by frequency converter
kNeeds, realize the accurate control of chilled water return water temperature simultaneously, make chilled water system be in optimum capacity dispensing duty all the time, realize energy-saving and cost-reducing purpose.
The principle of device of the fuzzy expection of realization freezing water system of central air conditioner provided by the present invention control method is shown in Fig. 1～2, current differential pressure pickup 6 is installed at two ends at by-passing valve 5, flowmeter 7 is installed in water side at secondary water pump 8, flowmeter 13 is installed on bypass pipe, cooling-water temperature sensor 9,11 is installed respectively at the water side and the backwater end of air conditioner refrigerating unit 10 chilled waters.The sensor is used to gather operational factors such as water temperature, flow, pressure reduction.Current differential pressure pickup 6, flowmeter 7 and 13, cooling-water temperature sensor 9 are connected with intelligent control unit 2 by order wire respectively with 11; No. one time water pump 12, secondary water pump 8 are connected with intelligent control unit 3 respectively with order wire by frequency converter 4, and by-passing valve 5 is connected with intelligent control unit 3 by order wire. Intelligent control unit 2,3 is connected with fuzzy controller 1 respectively by order wire. Intelligent control unit 2,3 constitutes by control processor circuit 14, memory circuitry 15, network communication interface circuit 16, simulated measurement input circuit 17, analogue quantity output circuit 18 and power circuit 19.
As shown in Figure 3, Figure 4, the present invention can realize the accurate control to the chilled water return water temperature, and the return water temperature fluctuations amplitude of chilled water is less; And PID or PI controlling party rule can not realize the accurate control to the chilled water return water temperature, and the return water temperature fluctuations amplitude of chilled water is bigger.
Claims (2)
1, the fuzzy expection of a kind of freezing water system of central air conditioner control method comprises that correction valve prediction, fuzzy reasoning are handled, optimized to operational factor collection, data, controlled quentity controlled variable is exported and control; It is characterized in that: by collection chilled water system supply and return water temperature, the temperature difference, flow, four operational factors of pressure reduction, calculate the n cycle mean value of corresponding operational factor, predict its optimization correction value according to the variation tendency of this mean value, then by the fuzzy reasoning controlled quentity controlled variable that is optimized, and, chilled-water flow is carried out corresponding adjusting by Frequency Converter Control chilled water pump rotating speed; Concrete grammar is as follows:
1. operational factor collection is gathered the supply and return water temperature of chilled water system, the flow in the water supply line, these four operational factors of current pressure reduction between the confession water return pipeline by the cooling-water temperature sensor that is installed in central air conditioner system low-temperature receiver side, flowmeter and current differential pressure pickup;
2. data are handled, and intelligent control unit the air conditioning terminal k period according to the above-mentioned data computation of being gathered, i.e. required refrigerating capacity of current period:
Q
k＝λ·w·ΔT
In the formula, Q
k---k period, the i.e. required refrigerating capacity of air conditioning terminal of current period;
λ---with relevant constants such as chilled water specific heat, density;
W---chilled-water flow collection value;
Δ T---the temperature difference collection value between chilled water confession, the backwater;
Calculate the mean value of above-mentioned four operational factors of chilled water in nearest n chilled water cycle period simultaneously; Described mean value is the addition gained and that get divided by the number n in the cycle one by one value of the value of relevant parameters in nearest n chilled water cycle period; Its formula is:
In the formula,
---certain parameter k period, i.e. the n cycle mean value of current period;
x
i---certain parameter is in the value in i cycle;
N---the number of chilled water cycle period, n is 〉=5 integer;
Intelligent control unit is with required refrigerating capacity Q
kDynamically update and send to fuzzy controller with the n cycle mean value of described four operational factors;
3. optimize correction valve prediction, fuzzy controller calculates it and optimizes correction value---deviation E according to the n cycle mean value of Δ T
kAnd deviation variation rate
In the formula, E
k---k period, the i.e. temperature difference deviation of chilled water system of current period;
---k period, i.e. the n cycle mean temperature difference value of chilled water system of current period;
Δ T
0---the temperature difference setting value of chilled water system;
In the formula,
---k period, the i.e. rate of change of the chilled water system temperature difference deviation of current period;
E
K-1---the temperature difference deviation of the preceding 1 period chilled water system of k;
4. fuzzy reasoning, fuzzy controller is optimized correction value, i.e. deviation E with temperature difference T
kAnd deviation variation rate
Carry out the A/D conversion and make Fuzzy processing, obtain fuzzy control quantity u through fuzzy reasoning again
k, this fuzzy control quantity is carried out sharpening processing and D/A conversion, the controlled quentity controlled variable that is optimized U
kAnd pass to intelligent control unit;
Deviation E
k, deviation variation rate
With optimal control amount u
kFuzzy subset's domain get:
Control law is expressed as:
In the formula, α, β ∈ (0,1)
5. the output of controlled quentity controlled variable and control, intelligent control unit is with optimal control amount U
kConvert the control signal of frequency converter to, regulate chilled water water circulating pump rotating speed to change the flow of chilled water system by frequency converter.
2, a kind of device of realizing the fuzzy expection of the described freezing water system of central air conditioner of claim 1 control method comprises fuzzy controller, frequency converter, cooling-water temperature sensor, flowmeter, current differential pressure pickup and the intelligent control unit that is made of control processor circuit, memory circuitry, network communication interface circuit, simulated measurement input circuit, analogue quantity output circuit and power circuit; It is characterized in that: current differential pressure pickups (6) are installed at the two ends at by-passing valve (5), flowmeter (7) is installed in water side at secondary water pump (8), flowmeter (13) is installed on bypass pipe, cooling-water temperature sensor (9), backwater end installation cooling-water temperature sensor (11) are installed in the chilled water water side of air conditioner refrigerating unit (10); Current differential pressure pickup (6), flowmeter (7) and (13), cooling-water temperature sensor (9) are connected with intelligent control unit (2) by order wire respectively with (11); A water pump (12) is connected with intelligent control unit (3) respectively with order wire by frequency converter (4) with secondary water pump (8), and by-passing valve (5) is connected with intelligent control unit (3) by order wire; Intelligent control unit (2), (3) are connected with fuzzy controller (1) by order wire respectively.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200410040667 CN1255653C (en) | 2004-09-09 | 2004-09-09 | Method for fuzzy expected controlling cold water system of central air conditioner |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 200410040667 CN1255653C (en) | 2004-09-09 | 2004-09-09 | Method for fuzzy expected controlling cold water system of central air conditioner |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN1598427A CN1598427A (en) | 2005-03-23 |
| CN1255653C true CN1255653C (en) | 2006-05-10 |
Family
ID=34664743
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN 200410040667 Expired - Fee Related CN1255653C (en) | 2004-09-09 | 2004-09-09 | Method for fuzzy expected controlling cold water system of central air conditioner |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN1255653C (en) |
Families Citing this family (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7925385B2 (en) * | 2006-03-08 | 2011-04-12 | Itt Manufacturing Enterprises, Inc | Method for optimizing valve position and pump speed in a PID control valve system without the use of external signals |
| CN100585303C (en) * | 2007-11-15 | 2010-01-27 | 南京五洲制冷集团有限公司 | Energy control method of cyclone compressor modularizing wind cold-hot pump unit |
| CN100578398C (en) * | 2008-10-09 | 2010-01-06 | 南京五洲制冷集团有限公司 | Energy control method for modularization helical lobe compressor unit |
| CN101881498B (en) * | 2009-05-06 | 2012-11-14 | 欧威尔空调科技(中国)有限公司 | Multiple connected air conditioning system and control method thereof |
| CN101737899B (en) * | 2009-12-14 | 2012-05-02 | 浙江大学 | Central air-conditioning control system and method based on wireless sensor network |
| CN102062459A (en) * | 2010-12-24 | 2011-05-18 | 东莞市虹德电子有限公司 | Energy-saving control system of central air conditioner |
| CN104089328B (en) | 2013-04-01 | 2018-10-12 | 开利公司 | Air-conditioning system and the method that air-conditioning system is controlled |
| CN104101055B (en) * | 2014-07-22 | 2016-11-16 | 浪潮电子信息产业股份有限公司 | A kind of control method of Water cooled air conditioners |
| CN104315673B (en) * | 2014-09-16 | 2017-07-11 | 珠海格力电器股份有限公司 | Fuzzy control system and method for central air conditioner |
| CN104633863B (en) * | 2015-02-04 | 2017-06-09 | 无锡市同舟电子实业有限公司 | A kind of central air-conditioner control method based on the discrete pid algorithm of Self-tuning System |
| CN104879898B (en) * | 2015-06-04 | 2017-11-17 | 北京百度网讯科技有限公司 | The control method and device of data center's chilled water system |
| CN105135616A (en) * | 2015-09-01 | 2015-12-09 | 大连葆光节能空调设备厂 | Winter tail end energy optimal distribution system for commercial central air conditioner |
| CN105160980A (en) * | 2015-09-24 | 2015-12-16 | 苏州科技学院 | Method, device and system for simulating air-conditioning cold source system based on simulation platform |
| CN106016623B (en) * | 2016-06-18 | 2022-04-22 | 杭州滨创能源科技有限公司 | Building air conditioner water wireless network distribution self-discipline intelligent power-saving controller and control method |
| CN106766271B (en) * | 2016-12-15 | 2019-05-24 | 常州龙腾光热科技股份有限公司 | A kind of thermal-arrest field lens field outlet temperature control method for solar energy heating power generation |
| CN107120799B (en) * | 2017-05-23 | 2020-07-07 | 青岛海尔空调电子有限公司 | A multi-line control method and system for a water system |
| CN108332346A (en) * | 2017-08-23 | 2018-07-27 | 南京南瑞继保电气有限公司 | A kind of central air-conditioning optimal control method based on load prediction and fuzzy control |
| CN109708258B (en) * | 2018-12-20 | 2021-01-12 | 南京达实能源技术有限公司 | Refrigeration house temperature feedforward-fuzzy control system and control method based on load dynamic change |
| CN112433547B (en) * | 2019-05-22 | 2022-02-15 | 石家庄华泰电力工具有限公司 | Heat dissipation temperature control system for control cabinet |
| CN110160230B (en) * | 2019-05-27 | 2021-12-28 | 上海美控智慧建筑有限公司 | Central air conditioner, air conditioner water system and control method and control device thereof |
| CN110186156A (en) * | 2019-06-03 | 2019-08-30 | 西安锦威电子科技有限公司 | Refrigeration plant Fuzzy control system |
| CN110375425B (en) * | 2019-07-22 | 2021-04-27 | 上海美控智慧建筑有限公司 | Air conditioning system, control method thereof, control device, and computer-readable storage medium |
| CN114517963B (en) * | 2020-11-20 | 2023-06-02 | 丁伟 | Air conditioner control method and system for intelligent resource allocation |
| CN112665233A (en) * | 2020-12-10 | 2021-04-16 | 珠海格力电器股份有限公司 | Control method and device for chilled water secondary pump, controller and water pump system |
| CN113983675B (en) * | 2021-11-10 | 2023-10-10 | 上海观燃智能科技有限公司 | Bypass differential pressure variable frequency air conditioner chilled water adjusting system and hydraulic balance method thereof |
| CN117366800B (en) * | 2023-10-16 | 2024-03-19 | 北京绿卡科技有限公司 | Transcritical carbon dioxide refrigerating system based on fuzzy PID control |
-
2004
- 2004-09-09 CN CN 200410040667 patent/CN1255653C/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN1598427A (en) | 2005-03-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN1255653C (en) | Method for fuzzy expected controlling cold water system of central air conditioner | |
| CN1255654C (en) | Method for self-adaptive optimizing controlling cold water system of central air conditioner and its apparatus | |
| CN100523635C (en) | Intelligent cluster control system of central air-conditioning | |
| CN1186572C (en) | Variable pressure difference and variable flow rate control method and system for air conditioning water system | |
| CN1206485C (en) | Central air-conditioning energy conserving fuzzy controlling method and fuzzy controller thereof | |
| CN1916519A (en) | System of adjusting quantity of cold, and adjustment method for central cooling in region | |
| CN201255459Y (en) | Weather compensator | |
| CN1869533A (en) | Energy-saving device of network type digital multivariable central air conditioning system | |
| CN109917646B (en) | System and method for optimizing operation of regional cooling and heating equipment | |
| CN102052739A (en) | Central air conditioner intelligent control system based on wireless sensor network and method | |
| CN102162443A (en) | Speed regulating and energy saving control method for multi-pump station municipal drainage pipe network system | |
| CN1811306A (en) | Automatic volume regulating and controlling method for gas-burning machine heat pump | |
| CN200943930Y (en) | Chill regulation system of centralized chill-supply two-stage chill exchange station | |
| CN102305451A (en) | Mixed ground source heat pump monitoring system and method based on health assessment technology | |
| CN201014677Y (en) | Central air-conditioning intelligent group control device | |
| CN110793173A (en) | Water pump frequency conversion control method based on dynamic change of worst air conditioner tail end | |
| Ahonen et al. | Energy efficiency optimizing speed control method for reservoir pumping applications | |
| CN101922773A (en) | Changeable flow ground source heat pump unit system, controller and control method | |
| CN105605748B (en) | Air-water joint adjustment control method and system for air conditioning system | |
| CN201476187U (en) | Dynamic energy saving system of central air-conditioning | |
| CN207365324U (en) | A kind of big data intelligent air condition equipment with household metering | |
| CN1189709C (en) | Controller of gas heat pump hot and cold water supply system | |
| CN114413458A (en) | Water pump parallel operation control method, device, equipment and medium for air-conditioning water system | |
| CN113757856A (en) | Control method and device for air conditioner cooling water system | |
| CN105571089A (en) | Energy-saving intelligent ecological central air conditioning device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| ASS | Succession or assignment of patent right |
Owner name: GUIZHOU HUITONGHUACHENG ENERGY-SAVING INVESTMENT M Free format text: FORMER OWNER: GUIZHOU HUICHENG TECHNOLOGY CO., LTD. Effective date: 20090515 |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20090515 Address after: Guizhou province Guiyang city Wudang District High Road No. 126 Patentee after: Guizhou Huitong Hua Cheng energy saving Cci Capital Ltd. Address before: Torch software garden, Xintian Road, Guiyang, Guizhou Patentee before: Huicheng Science & Technology Co.,Ltd. Guizhou |
|
| ASS | Succession or assignment of patent right |
Owner name: HUITONG HUACHENG BUILDING SCI. + TECH. CO., LTD., Free format text: FORMER OWNER: GUIZHOU HUITONG HUACHENG ENERGY SAVING INVESTMENT MANAGEMENT CO., LTD. Effective date: 20110812 |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20110812 Address after: 550018 Guizhou Province, Guiyang city Wudang District torch Avenue Magicstor Technology Industrial Park Patentee after: Guizhou Huitong Huacheng Building Technology Co.,Ltd. Address before: 550018 Guizhou Province, Guiyang city Wudang District High Road No. 126 Patentee before: Guizhou Huitong Hua Cheng energy saving Cci Capital Ltd. |
|
| ASS | Succession or assignment of patent right |
Owner name: GUIZHOU HUITONG HUACHENG CO., LTD. Free format text: FORMER OWNER: HUITONG HUACHENG BUILDING SCI. + TECH. CO., LTD., GUIZHOU Effective date: 20120709 |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20120709 Address after: 550018 Guizhou Province, Guiyang city Wudang District torch Avenue Magicstor Technology Industrial Park Patentee after: GUIZHOU HUITONG HUACHENG Co.,Ltd. Address before: 550018 Guizhou Province, Guiyang city Wudang District torch Avenue Magicstor Technology Industrial Park Patentee before: Guizhou Huitong Huacheng Building Technology Co.,Ltd. |
|
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20060510 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |