CN109237988A - The coolant water temperature of platform of internet of things technology is in real time from optimizing variable-flow method - Google Patents
The coolant water temperature of platform of internet of things technology is in real time from optimizing variable-flow method Download PDFInfo
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- CN109237988A CN109237988A CN201810984294.4A CN201810984294A CN109237988A CN 109237988 A CN109237988 A CN 109237988A CN 201810984294 A CN201810984294 A CN 201810984294A CN 109237988 A CN109237988 A CN 109237988A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F28—HEAT EXCHANGE IN GENERAL
- F28F—DETAILS OF HEAT-EXCHANGE AND HEAT-TRANSFER APPARATUS, OF GENERAL APPLICATION
- F28F27/00—Control arrangements or safety devices specially adapted for heat-exchange or heat-transfer apparatus
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Abstract
The invention proposes a kind of coolant water temperatures of platform of internet of things technology in real time from optimizing variable-flow method, comprising: acquires environmental data using sensory device, and is sent to platform of internet of things by things-internet gateway；The environmental data received is stored in different data by platform of internet of things, calculates refrigeration duty；Platform of internet of things calculates optimal cooling water temperature relationship corresponding with rate of load condensate according to history data and establishes prediction model, goes out optimal cooling water temperature using the refrigeration duty Auto-matching of actual measurement, and the setup parameter by the temperature as variable-flow carries out variable-flow；Platform of internet of things is monitored the parameter under variable-flow actual condition, calculates, and the data and measured result for obtaining prediction model are analyzed, and corrects prediction model in real time.The present invention is unable to the variable-flow strategy of real-time response on solving the prior art to actual load, incorporates big data, Internet of Things, cloud computing the relevant technologies, solves the problems, such as that data deficiencies or data analysis capabilities are not enough to support real-time optimizing.
Description
Technical field
The present invention relates to cooling water system technical field, in particular to a kind of coolant water temperature of platform of internet of things technology is real-time
From optimizing variable-flow method.
Background technique
Since the cooling capacity of cooling water system is related to the operation power of power-equipment, heat exchange equipment etc., cooling system
The energy consumption of system is also the technical essential that refrigeration industry is paid close attention to always.Existing technology generally by monitoring determine cooling water pressure,
Supply head, for poor, return water temperature etc. of rising again, and then by pump variable frequency, increase and decrease cooling device quantity come the stream to cooling water
Amount is adjusted, to reach energy-efficient purpose.Also there is the thermic load by acquiring heat-exchange network, it is negative to calculate practical heat indirectly
Lotus, then system-head curve is calculated by equipment technical parameters to reduce the resistance of ducting by transformation water pump vane to realize energy conservation.
Summary of the invention
The purpose of the present invention aims to solve at least one of described technological deficiency.
For this purpose, it is an object of the invention to propose a kind of coolant water temperature of platform of internet of things technology in real time from optimizing variable-flow
Method.
To achieve the goals above, the embodiment of the present invention provide a kind of platform of internet of things technology coolant water temperature in real time from
Optimizing variable-flow method, comprising:
Step S1 acquires environmental data using sensory device, and is sent to platform of internet of things by things-internet gateway；
The environmental data received is stored in different data by step S2, the platform of internet of things, calculates refrigeration duty；
Step S3, it is corresponding with rate of load condensate that the platform of internet of things according to history data calculates optimal cooling water temperature
Relationship establish prediction model, then according to the prediction model, gone out most using the refrigeration duty Auto-matching surveyed in step S2
Excellent cooling water temperature, the setup parameter by the temperature as variable-flow carry out variable-flow；
Step S4, the platform of internet of things are monitored the parameter under variable-flow actual condition, calculate, and obtain prediction mould
The data of type are analyzed with measured result, correct prediction model in real time.
Further, the disparate databases on the platform of internet of things include: real-time data base, warning data storehouse, history number
According to library.
Further, in the step S2, refrigeration duty=by building enclosure obtain heat formation refrigeration duty+Indoor Thermal
The refrigeration duty that source, wet source are formed.
Further, in the step S3, the measured data three-dimensional figure of similar projects is established, i.e. system overall refrigerating effect/be
System power COPsys-Tc- rate of load condensate carries out optimizing to cooling water temperature, and the TC under one group of COPsys of calculating is optimal is about load
The model of rate, and to the model ladder.
Further, described to model ladder, comprising: the cooling water temperature changed about rate of load condensate is subjected to ladder.
Further, described that optimizing is carried out to cooling water temperature, comprising: will to be born according to the measured data three-dimensional figure of similar projects
Lotus classification, the coolant water temperature when system COP maximum under rate of load condensate at the same level is found out using area of computer aided.
Further, in the step S4, the platform of internet of things is simultaneously by the measured data of acquisition and prediction model
Operation result compares, and deviation value is analyzed, thus correction model.
The coolant water temperature of platform of internet of things technology according to an embodiment of the present invention from optimizing variable-flow method, is based on object in real time
Networked platforms technology solves the variable-flow energy conservation that cooling system is realized across multidisciplinary, multi-specialized, multi-field technology.According to negative
Lotus rate look for best coolant water temperature in real time adjust the frequency conversion of water pump and heat exchange equipment, booting quantity reaches energy-efficient purpose.
Platform of internet of things technology includes perfect internet of things data acquisition, data access, data-pushing, data storage, data analysis etc.
Aspect is related to hardware: sensor, data collector, protocol analysis equipment, server etc., software: the data acquisition of high concurrent,
Access, storage, the analysis of big data level etc..
The present invention realizes the reality of coolant water temperature in combination with Internet of Things technology using novel big data technology, cloud computing technology
When optimizing, by heat exchange, power-equipment self character and coolant water temperature, rate of load condensate between relationship obtain optimum operation plan
Slightly, optimal operation plan with system stabilization, safety, energy conservation for principle, solution the prior art on cannot be real-time to actual load
The variable-flow strategy of response, and big data, Internet of Things, cloud computing the relevant technologies are incorporated, solve data deficiencies or data analysis
The problem of scarce capacity is to support real-time optimizing.
The present invention is similar with the method, and difference is that is acquired is the load of direct external environment, and in addition the present invention is not
Start in the case where pipeline and selected parameters of pump from pipeline, looks for best coolant water temperature in real time according to rate of load condensate to adjust
The frequency conversion of water-saving pump and heat exchange equipment, booting quantity reach energy-efficient purpose.The present invention solve variable volume control mode by
Originally the mode for not considering dynamic load or indirect load, is improved to the mode based on real-time dynamic load variable-flow, variable-flow
While closer to practical application request, comfort is also improved while energy saving；It is carried out in the present invention by system COP cold
But the optimizing of water temperature, not only considers power consumption, it is also contemplated that the on-road efficiency of whole system, so that system is always in or closest
In efficient operation, the utilization rate of system is improved.The present invention combine for the first time multidisciplinary field, especially big data analysis,
Application of the cloud computing technology in Variable Cooling Water Flow amount has widened research ideas and methods to the field.
The additional aspect of the present invention and advantage will be set forth in part in the description, and will partially become from the following description
Obviously, or practice through the invention is recognized.
Detailed description of the invention
Above-mentioned and/or additional aspect of the invention and advantage will become from the description of the embodiment in conjunction with the following figures
Obviously and it is readily appreciated that, in which:
Fig. 1 is the coolant water temperature according to the platform of internet of things technology of the embodiment of the present invention in real time from optimizing variable-flow method
Flow chart；
Fig. 2 is to have different degrees of shadow to host, pump power according to the variation of the cooling water temperature of the embodiment of the present invention
Loud schematic diagram；
Fig. 3 is the schematic diagram according to the access platform of internet of things of the indoor and outdoor sensing data of the embodiment of the present invention；
Fig. 4 is the schematic diagram that platform of internet of things is accessed according to the entry of the embodiment of the present invention；
Fig. 5 is according to the real-time load of the embodiment of the present invention, system COP, coolant water temperature three-dimensional statistical model schematic diagram；
Fig. 6 is model schematic of the TC about rate of load condensate according to the COPsys of the embodiment of the present invention under optimal.
Specific embodiment
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, it is intended to is used to explain the present invention, and is not considered as limiting the invention.
The present invention proposes that a kind of coolant water temperature of platform of internet of things technology in real time from optimizing variable-flow method, utilizes cooling water
The variable-flow power-saving technology of the cooling system of cooling, and be the power-saving technology of dynamic auto regulating flow variation strategy in real time.
Some terms of the present invention and background are illustrated below:
Cooling water side variable-flow product on the market is typically all to set fixed temperature or temperature difference as reference quantity now,
Variable-flow is carried out, and the setting of temperature or the temperature difference is in accordance with the existing subjective experience of people, and is fixed and invariable.
Actually the variation of cooling water temperature has different degrees of influence to host, pump power, as shown in Figure 2.Wherein,
N1 is water cooler power, and N3 is cooling water pump, power of fan, and N1+N3 is general power.Therefore cooling from the point of view of system energy efficiency
Coolant-temperature gage should set the value of optimum temperature point.
On this basis, it is considered herein that optimal cooling water temperature will not only consider system power, it is also contemplated that this power
Whether the income of the refrigerating capacity of lower acquisition is maximum, therefore in the above theoretical basis, and the present invention will (be based on system COP
System overall refrigerating effect/system power) calculate optimal coolant water temperature.
Optimal coolant water temperature is from optimizing is defined as: under different load, the temperature of the cooling water when system COP is maximum
Degree is optimal coolant water temperature, this expression obtains maximum refrigerating capacity benefit by the smallest power consumption at this time.Therefore, pass through adjusting
Pump variable frequency, refrigeration unit start and stop come so that system COP is in maximum always or is called coolant water temperature close to the case where maximum value
From optimizing.
The basic condition of actual load rate acquisition: need to dispose a whole set of biography of correlation of perfect outdoor, indoor load monitoring
Sensor, such as: outdoor temperature humidity, irradiance sensor, indoor thermal imaging system, indoor temperature and humidity sensor.And need multiple spot
Acquisition.
The basic condition of system COP acquisition: power-equipment, heat exchange equipment operation data, power consumption data, heat exchange data etc.
In real time acquisition, pipeline other such as flow, the real-time acquisition of water temperature, pressure.
As shown in figures 1 to 6, the coolant water temperature of the platform of internet of things technology of the embodiment of the present invention is in real time from optimizing variable-flow
Method, comprising:
Step S1 acquires environmental data using sensory device, and is sent to platform of internet of things by things-internet gateway.
Specifically, firstly the need of indoors, outer typical location arrangements sensory device.Wherein, sensory device includes: temperature and humidity
The sensory device of the calculated loads such as sensor, irradiation instrument, thermal imaging system, while needing all environmental control access systems.
If the complete arrangement for reducing sensor of the data of environmental control.Then the environmental data of acquisition is passed through object by sensory device
Networking gateway is passed to platform of internet of things, as shown in Figure 3.
The environmental data received is stored in different data by step S2, platform of internet of things, calculates refrigeration duty.In this step
In rapid, the disparate databases on platform of internet of things include: real-time data base, warning data storehouse, historical data base.
Wherein, refrigeration duty=cold negative by the way that building enclosure obtains refrigeration duty+indoor airflow of heat formation, wet source is formed
Lotus.
Step S3, platform of internet of things calculate optimal cooling water temperature pass corresponding with rate of load condensate according to history data
System establishes prediction model, then according to prediction model, goes out optimal cooling using the refrigeration duty Auto-matching surveyed in step S2
Coolant-temperature gage, the setup parameter by the temperature as variable-flow carry out variable-flow.
Specifically, platform of internet of things calculates optimal cooling water temperature pass corresponding with rate of load condensate according to history data
System establishes prediction model, includes the following steps:
As shown in figure 4, to establish the model of such a real-time on-line self-optimizing, the data of single project are to be not enough to prop up
Support, therefore we need the long term data of a large amount of disparity items (project A, project B, project C etc.), to can just set up reality
Measured data three-dimensional figure (COPsys-Tc- rate of load condensate).For example, being passed through respectively by the data of the acquisitions such as project A, project B, project C
Respective history data is uploaded on platform of internet of things by respective gateway.
In step s3, the present invention establishes data analysis center on the basis of existing project data, carries out to system
The refrigeration system of sort research, same form is one kind, establishes the measured data three-dimensional figure (as shown in Figure 5) of similar projects, i.e.,
System overall refrigerating effect/system power COPsys-Tc- rate of load condensate carries out optimizing to cooling water temperature, according to the actual measurement of similar projects
Load rating is found out the coolant water temperature when system COP maximum under rate of load condensate at the same level using area of computer aided by data three-dimensional figure.
Then calculate one group of COPsys it is optimal under model of the TC about rate of load condensate, and to the model ladder.
In one embodiment of the invention, to model ladder, comprising: the cooling water temperature that will change about rate of load condensate
Ladder is carried out, to avoid unit frequent start-stop.
Step S4, platform of internet of things are monitored the parameter under variable-flow actual condition, calculate, and obtain prediction model
Data are analyzed with measured result, correct prediction model in real time.
Specifically, platform of internet of things simultaneously compares the measured data of acquisition with the operation result of prediction model, analyze
Deviation value, thus correction model.
With reference to Fig. 6, using TC of the obtained COPsys under optimal about rate of load condensate model realization to the number of centralized control system
According to monitoring, using collected real time data as the history data in step S1.
The coolant water temperature of platform of internet of things technology according to an embodiment of the present invention from optimizing variable-flow method, is based on object in real time
Networked platforms technology solves the variable-flow energy conservation that cooling system is realized across multidisciplinary, multi-specialized, multi-field technology.According to negative
Lotus rate look for best coolant water temperature in real time adjust the frequency conversion of water pump and heat exchange equipment, booting quantity reaches energy-efficient purpose.
Platform of internet of things technology includes perfect internet of things data acquisition, data access, data-pushing, data storage, data analysis etc.
Aspect is related to hardware: sensor, data collector, protocol analysis equipment, server etc., software: the data acquisition of high concurrent,
Access, storage, the analysis of big data level etc..
The present invention realizes the reality of coolant water temperature in combination with Internet of Things technology using novel big data technology, cloud computing technology
When optimizing, by heat exchange, power-equipment self character and coolant water temperature, rate of load condensate between relationship obtain optimum operation plan
Slightly, optimal operation plan with system stabilization, safety, energy conservation for principle, solution the prior art on cannot be real-time to actual load
The variable-flow strategy of response, and big data, Internet of Things, cloud computing the relevant technologies are incorporated, solve data deficiencies or data analysis
The problem of scarce capacity is to support real-time optimizing.
The present invention is similar with the method, and difference is that is acquired is the load of direct external environment, and in addition the present invention is not
Start in the case where pipeline and selected parameters of pump from pipeline, looks for best coolant water temperature in real time according to rate of load condensate to adjust
The frequency conversion of water-saving pump and heat exchange equipment, booting quantity reach energy-efficient purpose.The present invention solve variable volume control mode by
Originally the mode for not considering dynamic load or indirect load, is improved to the mode based on real-time dynamic load variable-flow, variable-flow
While closer to practical application request, comfort is also improved while energy saving；It is carried out in the present invention by system COP cold
But the optimizing of water temperature, not only considers power consumption, it is also contemplated that the on-road efficiency of whole system, so that system is always in or closest
In efficient operation, the utilization rate of system is improved.The present invention combine for the first time multidisciplinary field, especially big data analysis,
Application of the cloud computing technology in Variable Cooling Water Flow amount has widened research ideas and methods to the field.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is included at least one embodiment or example of the invention.In the present specification, schematic expression of the above terms are not
Centainly refer to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be any
One or more embodiment or examples in can be combined in any suitable manner.
Although the embodiments of the present invention has been shown and described above, it is to be understood that above-described embodiment is example
Property, it is not considered as limiting the invention, those skilled in the art are not departing from the principle of the present invention and objective
In the case where can make changes, modifications, alterations, and variations to the above described embodiments within the scope of the invention.The scope of the present invention
By appended claims and its equivalent limit.
Claims (7)
1. a kind of coolant water temperature of platform of internet of things technology is in real time from optimizing variable-flow method, which is characterized in that including walking as follows
It is rapid:
Step S1 acquires environmental data using sensory device, and is sent to platform of internet of things by things-internet gateway；
The environmental data received is stored in different data by step S2, the platform of internet of things, calculates refrigeration duty；
Step S3, the platform of internet of things calculate optimal cooling water temperature pass corresponding with rate of load condensate according to history data
System establishes prediction model, then according to the prediction model, is gone out using the refrigeration duty Auto-matching surveyed in step S2 optimal
Cooling water temperature, the setup parameter by the temperature as variable-flow carry out variable-flow；
Step S4, the platform of internet of things are monitored the parameter under variable-flow actual condition, calculate, and obtain prediction model
Data are analyzed with measured result, correct prediction model in real time.
2. the coolant water temperature of platform of internet of things technology as described in claim 1 is in real time from optimizing variable-flow method, feature exists
In the disparate databases on the platform of internet of things include: real-time data base, warning data storehouse, historical data base.
3. the coolant water temperature of platform of internet of things technology as described in claim 1 is in real time from optimizing variable-flow method, feature exists
In, in the step S2, refrigeration duty=by building enclosure obtain heat formation refrigeration duty+indoor airflow, wet source formed
Refrigeration duty.
4. the coolant water temperature of platform of internet of things technology as described in claim 1 is in real time from optimizing variable-flow method, feature exists
In in the step S3, establishing the measured data three-dimensional figure of similar projects, i.e. system overall refrigerating effect/system power COPsys-
Tc- rate of load condensate, carries out optimizing to cooling water temperature, model of the TC about rate of load condensate under one group of COPsys of calculating is optimal, and right
The model ladder.
5. the coolant water temperature of platform of internet of things technology as claimed in claim 4 is in real time from optimizing variable-flow method, feature exists
In described to model ladder, comprising: the cooling water temperature changed about rate of load condensate is carried out ladder.
6. the coolant water temperature of platform of internet of things technology as claimed in claim 4 is in real time from optimizing variable-flow method, feature exists
In described to carry out optimizing to cooling water temperature, comprising: according to the measured data three-dimensional figure of similar projects by load rating, utilize
Area of computer aided finds out the coolant water temperature when system COP maximum under rate of load condensate at the same level.
7. the coolant water temperature of platform of internet of things technology as claimed in claim 4 is in real time from optimizing variable-flow method, feature exists
In in the step S4, the platform of internet of things is simultaneously by the measured data of acquisition compared with the operation result of prediction model
Compared with analysis deviation value, thus correction model.
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| JP2005233557A (en) * | 2004-02-20 | 2005-09-02 | Mitsubishi Heavy Ind Ltd | Refrigeration system and its operating method |
| CN101413709A (en) * | 2008-11-26 | 2009-04-22 | 湖南工程学院 | Cooling water flow control method for optimizing total energy consumption of refrigerating machine and cooling water pump |
| CN102022799A (en) * | 2009-09-19 | 2011-04-20 | 袁恒杰 | Energy-saving control method for central air conditioner system |
| CN201875843U (en) * | 2010-07-23 | 2011-06-22 | 荣飞 | Digital and intelligent power-saving device for central air-conditioner |
| CN106403207A (en) * | 2016-10-24 | 2017-02-15 | 珠海格力电器股份有限公司 | Load-prediction-based control system and method for heating ventilation air-conditioning system |
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2018
- 2018-08-28 CN CN201810984294.4A patent/CN109237988A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005233557A (en) * | 2004-02-20 | 2005-09-02 | Mitsubishi Heavy Ind Ltd | Refrigeration system and its operating method |
| CN101413709A (en) * | 2008-11-26 | 2009-04-22 | 湖南工程学院 | Cooling water flow control method for optimizing total energy consumption of refrigerating machine and cooling water pump |
| CN102022799A (en) * | 2009-09-19 | 2011-04-20 | 袁恒杰 | Energy-saving control method for central air conditioner system |
| CN201875843U (en) * | 2010-07-23 | 2011-06-22 | 荣飞 | Digital and intelligent power-saving device for central air-conditioner |
| CN106403207A (en) * | 2016-10-24 | 2017-02-15 | 珠海格力电器股份有限公司 | Load-prediction-based control system and method for heating ventilation air-conditioning system |
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