CN106123360A - Heat pump obtains heat forecast Control Algorithm with solar energy in solar water heater combined system - Google Patents
Heat pump obtains heat forecast Control Algorithm with solar energy in solar water heater combined system Download PDFInfo
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- CN106123360A CN106123360A CN201610506226.8A CN201610506226A CN106123360A CN 106123360 A CN106123360 A CN 106123360A CN 201610506226 A CN201610506226 A CN 201610506226A CN 106123360 A CN106123360 A CN 106123360A
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- temperature
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
- F24S50/00—Arrangements for controlling solar heat collectors
- F24S50/40—Arrangements for controlling solar heat collectors responsive to temperature
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24H—FLUID HEATERS, e.g. WATER OR AIR HEATERS, HAVING HEAT-GENERATING MEANS, e.g. HEAT PUMPS, IN GENERAL
- F24H4/00—Fluid heaters characterised by the use of heat pumps
- F24H4/02—Water heaters
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24S—SOLAR HEAT COLLECTORS; SOLAR HEAT SYSTEMS
- F24S20/00—Solar heat collectors specially adapted for particular uses or environments
- F24S20/40—Solar heat collectors combined with other heat sources, e.g. using electrical heating or heat from ambient air
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/40—Solar thermal energy, e.g. solar towers
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- Engineering & Computer Science (AREA)
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- Thermal Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Heat-Pump Type And Storage Water Heaters (AREA)
- Life Sciences & Earth Sciences (AREA)
- Sustainable Development (AREA)
- Sustainable Energy (AREA)
Abstract
The present invention relates to a kind of heat pump and obtain heat forecast Control Algorithm with solar energy in solar water heater combined system, feature is to set up the temperature rise Δ T t in time of storage tank, solar radiation meansigma methods I in the unit intervala, average ambient temperature ThPAnd storage tank initial temperature TCThe functional expression of change；According to history by time solar radiation sequence and average ambient temperature parameter set up neural network model, gather storage tank temperature rise real-time condition and average ambient temperature when using front 2～the hot-water heating system operation in 6 hours that started prediction the same day to input as network, the storage tank temperature prediction value that network model exports is placed to controller, obtains total temperature rise value Δ T ' of storage tank；Predict total temperature rise value Δ T ' and initial water temperature TCSum i.e. final temperature TZ, user set water temperature TSWith final temperature TZDifference △ T " for need Teat pump boiler auxiliary heating heat, when Teat pump boiler complete auxiliary heating this partial heat after out of service.Its advantage is: effective that heat prediction is more accurate to solar energy, Energy Efficiency Ratio is higher, and energy saving of system effect is obvious.
Description
Technical field
The present invention relates to a kind of heat pump and obtain heat forecast Control Algorithm with solar energy in solar water heater combined system.
Background technology
Air source hot pump water heater assisted solar hot water utensil has energy-conservation and that environmental suitability is strong advantage, in life heat
Water supply obtains increasingly be widely applied.The control that air source hot pump water heater is traditional in combining with solar water heater
Method is preferentially to use solar energy heating, does not reaches requirement when user uses hot water such as water temperature, then open Teat pump boiler and enter
Row heating, or open the most in advance or open in advance in a certain set time.Use the subject matter of above-mentioned control method
It is to raise owing to the Energy Efficiency Ratio of air source hot pump water heater raises with outdoor environment temperature, but drops with Water in Water Tank temperature rise
Low, as a example by after daily water consumption peak is when 18, its outdoor environment temperature is typically low than maximum temperature at noon 5～8 DEG C, and
The water tank water temperature also ratio at noon is relatively low.To this end, the patent of invention " energy-saving control method that heat pump combines with solar water heater
(ZL201210485068.4) propose in " and be predicted by solar water heater whole day is obtained heat, noon temperature relatively
The high period opens the technical scheme of Teat pump boiler supplementary heating in advance.But owing to meteorological condition every day is different from, how
The heat that Accurate Prediction solar water heater whole day can be provided by is the key implemented.
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art to provide a kind of heat pump and solar water heater combined system
Middle solar energy obtains heat forecast Control Algorithm, and it is based on neural network algorithm, can be according to history solar radiation data and use
The water tank on former hours of the same day is actual obtains heat, it was predicted that the effective of following certain section of time water tank obtains heat, so that it is determined that required heat
Pump water heater auxiliary adds heat and Teat pump boiler optimal available machine time and total operation time, it is achieved system energy saving in running
Purpose.
In order to achieve the above object, the present invention is achieved in that it is that a kind of heat pump is with solar water heater combination
In system, solar energy obtains heat forecast Control Algorithm, it is characterised in that heat pump and solar water heater include Teat pump boiler, heat pump
Water circulating pump, storage tank, solar energy water circulating pump, solar water heater, storage tank cooling-water temperature sensor, environment temperature sensor and
Controller；The water temperature that temperature is storage tank of described storage tank cooling-water temperature sensor sensing, the sensing of described environment temperature sensor
Temperature is ambient temperature, and the method step that described controller prediction solar water heater obtains heat is as follows:
(1) the effective factor obtaining heat affected in combined system mainly has solar energy irradiation and ambient temperature, by solar energy
The impact that irradiation, ambient temperature factor obtain heat to heat pump and solar water heater combined system is comprehensively expressed as storage tank
Effective heat, in the case of given storage tank volume, the temperature rise measured by storage tank cooling-water temperature sensor i.e. can be obtained
The effective of combined system obtains heat；
(2) the temperature rise Δ T t in time of storage tank, solar radiation meansigma methods I in the unit interval are set upa, average ambient temperature ThP
And storage tank initial temperature TCFunctional expression Δ T=(t, the I of changea, TC, ThP)；
(3) according to history by time solar radiation sequence and average ambient temperature parameter set up neural network model, gather to use and work as
Start when front 2～6 hours hot-water heating systems of prediction are run storage tank temperature rise real-time condition and average ambient temperature day as net
Network inputs, and the storage tank temperature prediction value that network model exports is placed to controller, obtains storage tank through mathematical calculation
Total temperature rise value Δ T '.
(4) total temperature rise value Δ T ' of the storage tank predicted and initial water temperature TCSum is the storage tank that prediction obtains
Final temperature TZ, user set water temperature TSWith final temperature TZDifference △ T ", i.e. △ T "=TS -TZFor needs Teat pump boiler
The heat of auxiliary heating, Teat pump boiler pre-cooling when whole day ambient temperature is higher runs generally 12:00 at noon, when
Teat pump boiler complete auxiliary heating this partial heat i.e. by Teat pump boiler run temperature rise reach △ T " after stop transport
OK.
Present invention advantage compared with prior art is: solar energy when changing greatly meteorological condition is effective that heat is pre-
It is more accurate to survey, and the Energy Efficiency Ratio that Teat pump boiler runs the time period is higher, and energy saving of system effect is obvious.
Accompanying drawing explanation
Fig. 1 is the systematic schematic diagram of the present invention.
Detailed description of the invention
Embodiments of the invention are described below in detail, and the example of described embodiment is shown in the drawings.Below with reference to
The embodiment that accompanying drawing describes is exemplary, is only used for explaining the present invention, and is not considered as limiting the invention.
As it is shown in figure 1, it is a kind of heat pump and solar water heater combined system forecast Control Algorithm, it is characterised in that heat
Pump and solar water heater combined system include Teat pump boiler 1, heat pump cycle water pump 2, storage tank 3, solar energy water circulating pump
4, solar water heater 5, storage tank cooling-water temperature sensor 6, environment temperature sensor 7 and controller 8；Wherein said Teat pump boiler
The outlet of 1 connects with a water inlet of storage tank cooling-water temperature sensor 6, and an outlet of described storage tank cooling-water temperature sensor 6 leads to
Crossing heat pump water circulating pump 2 to connect with the water inlet of Teat pump boiler 1, another outlet of storage tank cooling-water temperature sensor 6 is by too
Sun can connect with the water inlet of solar water heater 5 by water circulating pump 4, another water inlet of storage tank cooling-water temperature sensor 6 and the sun
The outlet connection of energy water heater 5；Heat pump cycle water pump 2 and the control of the controlled device of solar energy water circulating pump 48；Described water storage
The water temperature that temperature is storage tank 3 of case cooling-water temperature sensor 6 sensing, the temperature of described environment temperature sensor 7 sensing is environment temperature
Degree；Described controller 8 predict solar water heater 5 the method step of heat is as follows:
(1) the temperature rise Δ T t in time of storage tank 3, solar radiation meansigma methods I in the unit interval are set upa, average ambient temperature ThP
And water tank initial temperature TCFunctional expression Δ T=(t, the I of changea, TC, ThP), according to law of conservation of energy, Q=C × M ×
Δ T, C are that specific heat of water holds, and M is the quality of water in storage tank 3, C and M is definite value, i.e. Δ T=Q/ (C × M)=(QS-QC)/
(C × M), QSThe heating capacity of solar water heater 5, Q in express time tCRepresent the heat of storage tank 3 radiation loss；
(2) according to GBT50364-2005 " civil buildings solar water heating system application technology specification ", solar water heater 5
The heat collecting module heat-collecting capacity computing formula of a day is QS=R × I, R are constant, R and the gross area of heat collecting module, solar energy heating
The annual collecting efficiency of device, storage tank, pipeline heat loss rate and solar energy conversion ratio are relevant, and the value of R can be by same
The historical data reorganization in area draws, I is per day solar radiation quantity, for accuracy of judgement, by per day solar radiation quantitative change
Turn to by time average solar radiation quantity sum, i.e., IaAverage for solar radiation in the unit time
Value, QCFor storage tank 3 heat dissipation capacity, storage tank 3 temperature is the biggest with the ambient temperature temperature difference, dispels the heat the fastest, i.e. QCWith water tank temperature rise Δ T,
Initial water temperature TCAnd average ambient temperature ThPDirectly related, QC =ƒ (t, TC, ThP), concrete functional expression can be according to storage tank 3
Concrete structure, thermal conduction study correlation theory obtain；
(3) according to history by time solar radiation sequence and average ambient temperature parameter set up neural network model, gather to use and work as
Start storage tank 3 temperature rise real-time condition when front 2～6 hours hot-water heating systems of prediction are run and average ambient temperature conduct day
Neutral net inputs, and the storage tank 3 temperature prediction value that network model exports is placed to control system, obtains through mathematical calculation
Storage tank 3 temperature rise value Δ T ', specifically comprises the following steps that
(1) input this area sun by time radiation history sequence and average ambient temperature historical series, to most area, time
Section can be set to 7:00-18:00, within every 30 minutes, take 1 solar energy by time radiation value and average ambient temperature value；
(2) input uses the date on the same day and starts prediction and terminate the time of prediction, typically pre-using 12:00 at noon as starting
The time surveyed, using 18:00 in afternoon as the time terminating prediction；
(3) input uses average ambient temperature T measured the same day by environment temperature sensor 7hP, the general measure time is from upper
Noon 7:00 to 12:00 at noon, takes 1 secondary environment temperature T in every 30 minutesh, and as average ambient temperature T in these 30 minuteshP；
(4) input uses and proceeded by the temperature rise Δ T delta data of water in the storage tank 3 before prediction time t the same day, by storage
Water in Water Tank temperature sensor 6 is measured and is obtained, and the general measure time, from 7:00 to 12:00 at noon in the morning, takes 1 temperature number in every 30 minutes
According to；
(5) inputting the constant R of solar energy, the situation that meteorological condition is stable is predicted the outcome preferably by network neural algorithm, but to sky
Gas catastrophe prediction effect is not ideal enough, it is contemplated that Changes in weather pairImpact, at different gas
Under the conditions of as, the numerical value difference such as the solar insuring rate that R is reflected is relatively big, can be by DIFFERENT METEOROLOGICAL CONDITIONS according to historical data
Draw approximation；In neutral net input item, add R, data accuracy can be increased with effecting reaction meteorological factor, more have
The reply change in weather situation of effect；
(6) using neural networks with single hidden layer, the network sequence building nonlinear continuous convergence approaches storage tank (3) temperature rise value Δ
T, temperature rise value Δ T ' predicted by the storage tank 3 being met backtracking error requirements；
(4) total temperature rise value Δ T ' of the storage tank 3 predicted and initial water temperature TCSum is storage tank 3 that prediction obtains
Finishing temperature TZ, user set water temperature TSWith TZDifference △ T ", i.e. △ T "=TS -TZFor needing the heat of Teat pump boiler 1 auxiliary heating
Amount, Teat pump boiler 1 generally 12:00 pre-cooling at noon when whole day ambient temperature is higher runs, when Teat pump boiler 1
This partial heat completing auxiliary heating is i.e. run temperature rise reached △ T by Teat pump boiler 1 " after the most out of service.
Although an embodiment of the present invention has been shown and described, it will be understood by those skilled in the art that: not
These embodiments can be carried out multiple change in the case of the principle of the disengaging present invention and objective, revise, replace and deform, this
The scope of invention is limited by claim and equivalent thereof.
Claims (1)
1. a heat pump obtains heat forecast Control Algorithm with solar energy in solar water heater combined system, it is characterised in that heat pump
With solar water heater include Teat pump boiler (1), heat pump cycle water pump (2), storage tank (3), solar energy water circulating pump (4),
Solar water heater (5), storage tank cooling-water temperature sensor (6), environment temperature sensor (7) and controller (8)；Described storage tank water
The water temperature that temperature is storage tank (3) that temperature sensor (6) senses, the temperature that described environment temperature sensor (7) senses is environment
Temperature, the method step that described controller (8) prediction solar water heater (5) obtains heat is as follows:
(1) the effective factor obtaining heat affected in combined system mainly has solar energy irradiation and ambient temperature, by solar energy
The impact that irradiation, ambient temperature factor obtain heat to heat pump and solar water heater combined system is comprehensively expressed as storage tank
(3) effective heat, in the case of given storage tank (3) volume, the temperature rise measured by storage tank cooling-water temperature sensor (6)
I.e. can obtain the effective of combined system and obtain heat；
(2) the temperature rise Δ T t in time of storage tank (3), solar radiation meansigma methods I in the unit interval are set upa, average ambient temperature
ThPAnd storage tank (3) initial temperature TCFunctional expression Δ T=(t, the I of changea, TC, ThP)；
(3) according to history by time solar radiation sequence and average ambient temperature parameter set up neural network model, gather to use and work as
Start storage tank (3) temperature rise real-time condition and average ambient temperature conduct during front 2～hot-water heating system operation in 6 hours of prediction day
Network inputs, and storage tank (3) the temperature prediction value that network model exports is placed to controller (8), obtains through mathematical calculation
Total temperature rise value Δ T ' of storage tank (3)；
(4) total temperature rise value Δ T ' of the storage tank (3) predicted and initial water temperature TCSum is the storage tank (3) that prediction obtains
Final temperature TZ, user set water temperature TSWith final temperature TZDifference △ T ", i.e. △ T "=TS-TZFor needs Teat pump boiler (1)
The heat of auxiliary heating, Teat pump boiler (1) pre-cooling when whole day ambient temperature is higher runs and is generally noon 12:
00, reach △ when Teat pump boiler (1) completes to assist this partial heat of heating i.e. to run temperature rise by Teat pump boiler (1)
T is " rear out of service.
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107120833A (en) * | 2017-04-27 | 2017-09-01 | 东南大学 | A kind of heat pump heat pipe combined control system of solar energy water heater and operation method |
| CN108224816A (en) * | 2018-02-12 | 2018-06-29 | 武汉东湖学院 | A kind of solar water heater central heating information collection and display system and its control method |
| CN108362019A (en) * | 2018-04-02 | 2018-08-03 | 广州西奥多科技有限公司 | A kind of space energy water heater control system and control method |
| CN108413628A (en) * | 2018-02-06 | 2018-08-17 | 杭州龙华环境集成系统有限公司 | A kind of solar energy couples hot-water heating system and its control method with air source heat pump |
| CN108426354A (en) * | 2018-04-19 | 2018-08-21 | 天津大学 | Air-conditioning Load Prediction system based on radiated time sequence method |
| CN108444110A (en) * | 2018-04-11 | 2018-08-24 | 南通大学 | Air source heat pump hot water system design method based on BP neural network forecasts |
| CN110285567A (en) * | 2019-06-24 | 2019-09-27 | 青岛海尔科技有限公司 | For predicting method and device, the water body heating device of leaving water temperature |
| CN110779239A (en) * | 2019-11-06 | 2020-02-11 | 杭州电子科技大学 | Solar energy-air source heat pump control system based on prediction model and energy-saving control method |
| CN112781235A (en) * | 2020-07-29 | 2021-05-11 | 青岛海尔新能源电器有限公司 | Heat pump water heater control method and device, heat pump water heater and storage medium |
| CN113654242A (en) * | 2021-08-12 | 2021-11-16 | 湖南精朗能源科技有限公司 | Air can hot water unit control system based on outdoor ambient temperature |
| CN116182428A (en) * | 2023-04-25 | 2023-05-30 | 广东力王科技股份有限公司 | Optimal control method and system for solar heat pump |
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Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107120833A (en) * | 2017-04-27 | 2017-09-01 | 东南大学 | A kind of heat pump heat pipe combined control system of solar energy water heater and operation method |
| CN107120833B (en) * | 2017-04-27 | 2020-06-09 | 东南大学 | Heat pump and heat pipe combined solar water heater control system and operation method |
| CN108413628A (en) * | 2018-02-06 | 2018-08-17 | 杭州龙华环境集成系统有限公司 | A kind of solar energy couples hot-water heating system and its control method with air source heat pump |
| CN108224816A (en) * | 2018-02-12 | 2018-06-29 | 武汉东湖学院 | A kind of solar water heater central heating information collection and display system and its control method |
| CN108362019B (en) * | 2018-04-02 | 2020-02-18 | 广州西奥多科技有限公司 | Control method of space energy water heater |
| CN108362019A (en) * | 2018-04-02 | 2018-08-03 | 广州西奥多科技有限公司 | A kind of space energy water heater control system and control method |
| CN108444110A (en) * | 2018-04-11 | 2018-08-24 | 南通大学 | Air source heat pump hot water system design method based on BP neural network forecasts |
| CN108444110B (en) * | 2018-04-11 | 2019-06-25 | 南通大学 | Air source heat pump hot water system design method based on BP neural network forecast |
| CN108426354A (en) * | 2018-04-19 | 2018-08-21 | 天津大学 | Air-conditioning Load Prediction system based on radiated time sequence method |
| CN110285567B (en) * | 2019-06-24 | 2021-06-11 | 青岛海尔科技有限公司 | Method and device for predicting outlet water temperature and water body heating device |
| CN110285567A (en) * | 2019-06-24 | 2019-09-27 | 青岛海尔科技有限公司 | For predicting method and device, the water body heating device of leaving water temperature |
| CN110779239A (en) * | 2019-11-06 | 2020-02-11 | 杭州电子科技大学 | Solar energy-air source heat pump control system based on prediction model and energy-saving control method |
| CN110779239B (en) * | 2019-11-06 | 2022-01-04 | 杭州电子科技大学 | Solar energy-air source heat pump control system based on prediction model and energy-saving control method |
| CN112781235A (en) * | 2020-07-29 | 2021-05-11 | 青岛海尔新能源电器有限公司 | Heat pump water heater control method and device, heat pump water heater and storage medium |
| CN113654242A (en) * | 2021-08-12 | 2021-11-16 | 湖南精朗能源科技有限公司 | Air can hot water unit control system based on outdoor ambient temperature |
| CN116182428A (en) * | 2023-04-25 | 2023-05-30 | 广东力王科技股份有限公司 | Optimal control method and system for solar heat pump |
| CN116182428B (en) * | 2023-04-25 | 2023-08-08 | 广东力王科技股份有限公司 | Optimal control method and system for solar heat pump |
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