CN105135616A - Winter tail end energy optimal distribution system for commercial central air conditioner - Google Patents
Winter tail end energy optimal distribution system for commercial central air conditioner Download PDFInfo
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- CN105135616A CN105135616A CN201510556906.6A CN201510556906A CN105135616A CN 105135616 A CN105135616 A CN 105135616A CN 201510556906 A CN201510556906 A CN 201510556906A CN 105135616 A CN105135616 A CN 105135616A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D19/00—Details
- F24D19/10—Arrangement or mounting of control or safety devices
- F24D19/1006—Arrangement or mounting of control or safety devices for water heating systems
- F24D19/1051—Arrangement or mounting of control or safety devices for water heating systems for domestic hot water
- F24D19/1054—Arrangement or mounting of control or safety devices for water heating systems for domestic hot water the system uses a heat pump
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- Thermal Sciences (AREA)
- Chemical & Material Sciences (AREA)
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- General Engineering & Computer Science (AREA)
- Air Conditioning Control Device (AREA)
Abstract
The invention discloses a winter tail end energy optimal distribution system for a commercial central air conditioner. In order to solve the common problem that top floors are too hot and bottom floors are too cold for commercial public buildings on which central air conditioner heating is adopted, the average temperature error of the top floor of a building and the average temperature error changing trend of the top floor of the building are taken as the judgment criteria, a fuzzy expert algorithm established based on an improved T-S fuzzy rule is adopted, the opening degree of a water valve of the top floor is lowered properly in proper time, and implement is conducted on an air conditioner control system of a certain shopping mall. According to the technology, more hot water can flow through the bottom floor under the premise that the number of opening heat pump units and circulation pumps is not increased, the temperature of the bottom floor and the temperature of the top floor can be kept in a satisfying range, and the energy saving effect is obvious.
Description
Technical field
The invention belongs to and improve efficiency of energy utilization field, relate to a kind of commercial heat pump central air-conditioning heating system.
Background technology
General central air-conditioning is made up of machine set system and end-equipment.The main task of machine set system is the recirculated water producing proper temperature, then adopt circulating pump that these recirculated waters are delivered to end-equipment, carry out heat exchange by the parts such as fan coil and room air, the circulating water flow after heat exchange to reflux unit through return pipe, completes whole air conditioning process.
For effectively utilizing heat energy, the recirculated water that unit produces reasonably should distribute at each floor gap, and this target realizes by the valve be arranged on each corridor, and each layer of whole central air-conditioning is shown in Fig. 1 for water return loop schematic diagram.
As Fig. 1, be the cold and hot energy that reasonable distribution unit produces, the water inlet pipe of every floor space has all installed manually-operated gate and automatic valve, change the distribution of recirculated water at every floor space by the aperture of control valve.The aperture of valve is generally determined by PID (ratio, differential, integration) algorithm.Specifically, be arranged on the actual temperature of each layer of temperature sensor measurement of each layer, contrasted by the design temperature (expection control objectives temperature) with each layer, determine control deviation, calculate temporal changing tendencies (differential D) and the accumulative variation tendency (integration I) of control deviation simultaneously, decided the aperture of valve by the linear combination of three.
In general, above-mentioned pid control algorithm can meet control overflow substantially in summer.But above-mentioned control algolithm regulates for the aperture of central air-conditioning water valve under winter condition, then can produce obvious top layer problems of excessive heat.Its main cause is, hot-air proportion is less, the hot-air of bottom can float to top layer gradually, and a lot of commercial building is purchased for convenience of client at present, rotating ladder is provided with at floor gap, rotating ladder many employings open by design, open by design is convenient to the drift of hot-air, and thus this problem is fairly obvious in a lot of market.And traditional PID control algorithm lacks adaptive adjustment capability for this change, thus often cause the problem of market " top layer is overheated, and bottom is excessively cold ".
For solving the problem, this patent proposes a set of Centralized Air-conditioning in Public Buildings energy-saving control system of meter.
Summary of the invention
For market ubiquitous " top layer is overheated; bottom the is excessively cold " problem adopting central air-conditioning to carry out heat supply in winter, the invention provides a kind of Centralized Air-conditioning in Public Buildings end in winter energy source optimization distribution system that can be solved the problem by the optimization of Intelligent adjustment top layer water valve aperture.
The technical scheme that the present invention adopts for technical solution problem is:
A kind of Centralized Air-conditioning in Public Buildings end in winter energy source optimization distribution system, comprise the energy-conservation Preliminary design theory of central air-conditioning in winter, the workflow of Energy Saving Algorithm, the enforcement of algorithm, is characterized in that:
Winter, the energy-conservation Preliminary design theory of central air-conditioning was, when unit is opened and water pump unlatching number of units is certain, in the unit interval, the recirculated water total amount being supplied end by unit is certain, and the total amount of heat being supplied to end by recirculated water is also certain; If the valve now turning top layer down, by reducing the output of this layer, will cause the increase of other layer of output, and then heat will more be assigned to other layer.
The feature of Energy Saving Algorithm workflow is, the middle-temperature error E of top layer building and the middle-temperature error variation tendency EC of top layer building is adopted to input as system, adopting the fuzzy expert algorithm based on improving the formulation of T-S fuzzy rule, calculating the aperture of top layer water valve.
Further, the above-mentioned fuzzy expert algorithm based on improving the formulation of T-S fuzzy rule is divided into fuzzy variable to choose, and variable obfuscation, fuzzy rule is formulated, four parts such as fuzzy decision realization.
For the selected part of fuzzy variable, the middle-temperature error E of employing top layer building and the middle-temperature error variation tendency EC of top layer building is as fuzzy variable.
For variable obfuscation part, following fuzzy set is adopted to describe the middle-temperature error E of top layer building:
{NB,NM,NS,ZE,PS,PM,PB}(1)
Wherein NB represents that error is negative large, and NM represents that error is that in bearing, NS represents that error is negative little, and ZE represents that error is that zero, PS represents that error is just little, and PM represents that error is center, and PB represents that error is honest.Temperature departure E for the fuzzy variable in fuzzy set membership function curve as shown in Figure 2.
Following fuzzy set is adopted to describe the middle-temperature error variation tendency EC of top layer building:
{NB,NS,ZE,PS,PB}(2)
Wherein NB represents that error is negative large, and NS represents that error is negative little, and ZE represents that error is that zero, PS represents that error is just little, and PB represents that error is honest.Temperature departure variation tendency EC for the fuzzy variable in fuzzy set membership function curve as shown in Figure 3.
Formulate part for fuzzy rule, what be directed to different fuzzy set according to temperature departure E and temperature departure variation tendency EC respectively is subordinate to situation, by practical engineering experience, has formulated 35 fuzzy rules.
Realize part for fuzzy decision, adopt based on improvement T-S fuzzy model, adopt true value decision-making, weights decision-making, and information fusion three step, achieve the final decision for water valve aperture.
General T-S model can be summarized as follows:
If f is (x
1for A
1, x
2for A
2... x
kfor A
k)
(3)
Then have: y=g (x
1, x
2..., x
n)
In formula (3), function f represents certain logical operation relation, x
1, x
2... x
k(fuzzy) function argument, A
1, A
2for fuzzy set, function argument and fuzzy set (x
1and A
1, x
2and A
2...) between relation rely on membership function describe.And function g () represents independent variable x
1, x
2certain combination of function, generally in T-S model adopt linear sign, namely for T-S fuzzy model, have
y＝a
0+a
1x
1+a
2x
2+…a
nx
n(4)
Wherein a
1, a
2, a
nrepresent certain constant.
Adopt above-mentioned linear function to characterize fuzzy rule, have:
If x
1for A
1, and x
2for A
2, and x
3for A
3..., then y=a is had
1x
1+ a
2x
2+ ... a
nx
n(5)
Formula (5) characterizes the true value decision-making technique of T-S fuzzy model.
Weights decision-making is available following formulae discovery then:
In formula (6),
represent x
1corresponding to i-th fuzzy inference rule fuzzy set (i=1,2 ..., n, wherein n represents the quantity of whole fuzzy rules of formulation), symbol ∩ represents fuzzy intersection operation, namely gets
middle value reckling.
Information fusion adopts the true value y corresponding to n bar fuzzy rule
iand weights | y=y
i| calculate the output that whole fuzzy expert system is final:
Further, the feature of embodiment is, the relevant position of building top arranges six temperature sensors, measure the temperature conditions of this layer, by bus by signal transmission to main control computer, main control computer calculates temperature and the variations in temperature of this layer, calculates the opening value of this layer of valve in conjunction with above-mentioned Energy Saving Algorithm, by bus, control signal is fed back to fieldbus and realize the adjustment of water valve aperture, the workflow diagram of whole system is shown in Fig. 4.
In hardware implementation angle, the Energy Saving Control algorithm of whole central air-conditioning adopts DDC control structure, and its fundamental diagram is shown in Fig. 5.By Fig. 5, every floor space arranges a field control unit, is responsible for data acquisition and the preliminary treatment of carrying out the signals such as terminal temperature pressure flow.Whole control unit is connected to bus and operator station by communication interface.The signal through preliminary treatment that operator station passes back according to each field control unit, formation control instruction, and by bus and communications interface transmission to field control unit, then perform control instruction by amplification, executive component.
The invention has the beneficial effects as follows:
1, can under the prerequisite not increasing unit unlatching number of units, Appropriate application also distributes existing heat resource, realizes the reasonable distribution of heat energy in winter.
2, can according to the temperature of top layer building and variation tendency situation thereof, the water valve aperture of dynamic this layer of adjustment, under the prerequisite that other layer of water valve aperture keeps relative stability, indirect regulation flows into the discharge of other layer of feed pipe, and then under the prerequisite not increasing unit unlatching number of units, optimize the heat distributing each layer, all realize suitable temperature at every layer and regulate, part solves winter the problem of " top layer is overheated, and bottom is excessively cold ".
Accompanying drawing explanation
Fig. 1 is that the central air-conditioning in certain market is for water return loop schematic diagram.
In figure: 1. source pump, 2. machine group end circulating pump, 3. total feed pipe, 4. manually-operated gate 1,5. automatic valve 1,6. end water route 1,7. return pipe 1,8. manually-operated gate 2,9. automatic valve 2,10. end water route 2,11. return pipe 2,12. manually-operated gate N13. automatic valve N, 14. end water route N, 15. return pipe N, 16. total return pipes.
Fig. 2 is the membership function curve map of middle-temperature error E for seven fuzzy sets of its correspondence of top layer building, wherein Fig. 2-1 to Fig. 2-7 is respectively the membership function curve map that E corresponds to fuzzy set PB (honest), PM (center), PB (honest), PB (honest), PB (honest), PB (honest), PB (honest)
Fig. 3 is the membership function curve map of middle-temperature error variation tendency EC for five fuzzy sets of its correspondence of top layer building.Wherein Fig. 3-1 to Fig. 3-5 is respectively the membership function curve map that EC corresponds to fuzzy set PB (honest), PS (just little), ZE (zero), NS (negative little), NB (negative large).
Fig. 4 is the control system fundamental diagram of certain market central air-conditioning.
In figure: 1. operator station, 2. high-speed data highway, 3. communication interface Isosorbide-5-Nitrae. communication interface 2,5. communication interface 3, the 6. field control unit of end floor 1, the 7. field control unit of end floor 2,8. machine room field control unit, 9. switch 1,10. temperature sensor 1,11. water valve 1,12. switch 2,13. temperature sensors 2,14. water valve 2,15. water pumps, 16. pressure sensors, 17. flowmeters, 18. switches, 19. water valves.
Fig. 5 is the workflow diagram of market central air-conditioning winter energy Optimal Distributing System.
Detailed description of the invention
Six temperature sensors being installed on building top measured the corresponding temperature information t of acquisition every 10 seconds
1-t
6, calculate its mean value
namely can obtain every 10 seconds one new
in one minute, by obtained 6
add up, ask for the mean value of temperature in a minute
like this, can obtain every one minute one new
be expressed as
make t
0represent the control temperature of top layer setting, then
represent the mean error in a minute, namely
represent the mean error of first minute,
represent the mean error of second minute ...Error change EC is defined as the variation tendency of error E, EC
1=E
2-E
1represent the error change trend of first minute.EC
2=E
3-E
2represent the error change trend of second minute ...
The temperature error E of employing top layer building and temperature error variation tendency EC is as the distinguishing rule of water valve aperture, and the corresponding relation of the membership function of E and EC provided according to Fig. 2 and Fig. 3 and the fuzzy variable of its correspondence, constructs fuzzy inference rule.
Define function argument, Fuzzy Linguistic Variable, after fuzzy rule, just can carry out fuzzy decision.In this patent, function argument elects top layer building temperature error E and error change EC as, the Fuzzy Linguistic Variable set A of corresponding error E
1have seven PB (honest), PM (center), PS (just little), ZE (zero), NS (negative little), NM (in negative), PS (negative large) }, the Fuzzy Linguistic Variable A of corresponding error E C
2have five { PB (honest), PS (just little), ZE (zero), NS (negative little), PS (negative large) }.E corresponds to A
1the respectively corresponding membership function of each value (fuzzy set), therefore always have seven membership function curves, in like manner, EC corresponds to A
2have five membership function curves.
Whole decision making algorithm adopts the fuzzy expert algorithm based on improving the formulation of T-S fuzzy rule, algorithm is by true value decision-making, weights decision-making, form with information fusion three part, calculate according to formula (3)-(7), final decision provides the opening value of top layer water valve, and the DDC control system provided at Fig. 5 realizes.
The present invention is not limited to the present embodiment, any the present invention disclose technical scope in equivalent concepts or change, be all classified as protection scope of the present invention.
Claims (4)
1. Centralized Air-conditioning in Public Buildings end in a winter energy source optimization distribution system, comprise design concept, energy source optimization distribution control algolithm and the embodiment of algorithm on Centralized Air-conditioning in Public Buildings that Centralized Air-conditioning in Public Buildings end in winter energy source optimization distributes, it is characterized in that:
Under heat supply in winter pattern, after market central air-conditioning starts a period of time, the hot-air of bottom drifts about to top layer gradually, formation temperature gradient fields.Now temperature of top sensor records temperature of top, by control bus and communication interface, temperature is transferred to main control system, the mean temperature of main control system accounting temperature sensor and mean temperature variation tendency, the aperture of control algolithm decision top layer water valve is distributed by energy source optimization, to reduce the discharge in top layer oral siphon, and then indirectly increase the discharge flowing into bottom oral siphon place, solve top layer when not increasing extra energy resource consumption overheated, the problem that bottom is excessively cold.Then, main control system by top layer water valve aperture decision signal by control bus and communications interface transmission to top layer water valve place, thus realize water valve aperture and regulate.
2. energy source optimization according to claim 1 distributes control algolithm, it is characterized in that the fuzzy expert algorithm based on improving the formulation of T-S fuzzy rule, algorithm comprises process of choosing, the variable fuzzification process of fuzzy variable, fuzzy rule formulation process, and fuzzy decision forming process four step;
Fuzzy variable choose process, adopt the middle-temperature error variation tendency EC of the middle-temperature error E of top layer building and top layer building as fuzzy variable;
The middle-temperature error variation tendency EC of the middle-temperature error E of top layer building and top layer building adopts fuzzy variable to be described by variable fuzzification process, namely set up the corresponding relation between E (EC) and certain fuzzy variable (fuzzy set), adopt membership function curve to be described;
Fuzzy rule formulation process runs according to certain market central air-conditioning the engineering experience obtained for many years, based on the Fog property of the middle-temperature error E of top layer building and the middle-temperature error variation tendency EC of top layer building, utilize the T-S fuzzy model improved, give the judgement of the top layer water valve aperture under often kind of Fog property;
The Main Function of fuzzy decision forming process is information fusion, according to the fuzzy Judgment of the water valve aperture under often kind of Fog property, provides final water valve aperture decision-making and judges.
3. variable fuzzification process according to claim 2, is characterized in that:
According to the engineering experience that market central air-conditioning operation maintenance for many years obtains, the middle-temperature error E of top layer building is corresponded to 7 fuzzy sets { NB (negative large), NM (in negative), NS (negative little), ZE (zero), PS (just little), PM (center), PB (honest) }, and respectively define the membership function curve that E corresponds to above-mentioned seven fuzzy sets; The middle-temperature error variation tendency EC of top layer building is corresponded to 5 fuzzy sets { NB (negative large), NS (negative little), ZE (zero), PS (just little), PB (honest) }, and respectively define the membership function curve that EC corresponds to above-mentioned five fuzzy sets.
4. membership function curve according to claim 3, is characterized in that:
According to the engineering experience that market central air-conditioning operation maintenance for many years obtains, the middle-temperature error variation tendency EC of the middle-temperature error E and top layer building that have formulated top layer building respectively corresponds to the membership function curve of respective fuzzy set.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106642469A (en) * | 2016-12-29 | 2017-05-10 | 大连葆光节能空调设备厂 | Summer energy source optimal distribution system for cold water unit with courtyard public architecture |
| CN107702301A (en) * | 2017-10-09 | 2018-02-16 | 珠海格力电器股份有限公司 | Air conditioning system and air conditioning system control method |
| EP3816522A1 (en) * | 2019-10-31 | 2021-05-05 | Robert Bosch GmbH | Method for controlling a heating device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH03199846A (en) * | 1989-12-27 | 1991-08-30 | Asahi Kogyosha:Kk | Method of controlling fan in central air conditioning apparatus |
| US5718372A (en) * | 1997-03-17 | 1998-02-17 | Tishler; Carl | Temperature controller |
| CN1482409A (en) * | 2003-06-13 | 2004-03-17 | ���ݻ�ͨ����¥��Ƽ�����˾ | Central air-conditioning energy conserving fuzzy controlling method and fuzzy controller thereof |
| CN1598427A (en) * | 2004-09-09 | 2005-03-23 | 贵州汇诚科技有限公司 | Method for fuzzy expected controlling cold water system of central air conditioner |
| CN104315673A (en) * | 2014-09-16 | 2015-01-28 | 珠海格力电器股份有限公司 | Fuzzy control system and method for central air conditioner |
| CN104566785A (en) * | 2014-12-15 | 2015-04-29 | 郑州轻工业学院 | Intelligent distribution method and intelligent distribution system for refrigerating capacity of central air conditioner |
-
2015
- 2015-09-01 CN CN201510556906.6A patent/CN105135616A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH03199846A (en) * | 1989-12-27 | 1991-08-30 | Asahi Kogyosha:Kk | Method of controlling fan in central air conditioning apparatus |
| US5718372A (en) * | 1997-03-17 | 1998-02-17 | Tishler; Carl | Temperature controller |
| CN1482409A (en) * | 2003-06-13 | 2004-03-17 | ���ݻ�ͨ����¥��Ƽ�����˾ | Central air-conditioning energy conserving fuzzy controlling method and fuzzy controller thereof |
| CN1598427A (en) * | 2004-09-09 | 2005-03-23 | 贵州汇诚科技有限公司 | Method for fuzzy expected controlling cold water system of central air conditioner |
| CN104315673A (en) * | 2014-09-16 | 2015-01-28 | 珠海格力电器股份有限公司 | Fuzzy control system and method for central air conditioner |
| CN104566785A (en) * | 2014-12-15 | 2015-04-29 | 郑州轻工业学院 | Intelligent distribution method and intelligent distribution system for refrigerating capacity of central air conditioner |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106642469A (en) * | 2016-12-29 | 2017-05-10 | 大连葆光节能空调设备厂 | Summer energy source optimal distribution system for cold water unit with courtyard public architecture |
| CN107702301A (en) * | 2017-10-09 | 2018-02-16 | 珠海格力电器股份有限公司 | Air conditioning system and air conditioning system control method |
| CN107702301B (en) * | 2017-10-09 | 2019-08-23 | 珠海格力电器股份有限公司 | air conditioning system and air conditioning system control method |
| EP3816522A1 (en) * | 2019-10-31 | 2021-05-05 | Robert Bosch GmbH | Method for controlling a heating device |
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Application publication date: 20151209 |