CN106123360B - 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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Abstract
The present invention relates to solar energy in a kind of heat pump and solar water heater combined system to obtain heat forecast Control Algorithm, and feature is the temperature rise Δ T for establishing storage tank with time t, solar radiation average value I in the unit intervala, average ambient temperature ThPAnd storage tank initial temperature TCThe functional expression of change；According to history by when solar radiation sequence and average ambient temperature parameter establish neural network model, storage tank temperature rise real-time condition and average ambient temperature are used as network inputs when 2~6 hour hot-water heating systems are run before collection started prediction using the same day, 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 is final temperature TZ, user's set water temperature TSWith final temperature TZDifference △ T " be need Teat pump boiler auxiliary heating heat, when Teat pump boiler complete auxiliary heating this partial heat after it is out of service.Its advantage is：Effective to solar energy that heat prediction is more accurate, Energy Efficiency Ratio is higher, energy saving of system positive effect.
Description
Technical field
The present invention relates to solar energy in a kind of heat pump and solar water heater combined system to obtain heat forecast Control Algorithm.
Background technology
Air source hot pump water heater assisted solar hot water utensil has the advantages of energy-conservation and environmental suitability are strong, in life heat
More and more extensive application has been obtained in water supply.Air source hot pump water heater control traditional in being combined with solar water heater
Method is preferentially to use solar energy heating, and when user is using hot water such as water temperature does not reach requirement, then opens Teat pump boiler and enter
Row heating, or manually open or opened in advance in a certain set time in advance.Using the subject matter of above-mentioned control method
It is due to Energy Efficiency Ratio rise with outdoor environment temperature rise of air source hot pump water heater, but is dropped with Water in Water Tank temperature rise
It is low, such as when daily water consumption peak is 18 after exemplified by, its outdoor environment temperature is typically lower than noon maximum temperature 5~8 DEG C, and
The water tank water temperature at noon is also than relatively low.Therefore, patent of invention " the energy-saving control method that heat pump combines with solar water heater
（ZL201210485068.4）" in propose and be predicted by obtaining heat to solar water heater whole day, noon temperature compared with
The high period opens the technical scheme of Teat pump boiler supplementary heating in advance.But because daily meteorological condition is different from, how
The heat that Accurate Prediction solar water heater whole day can be provided is the key implemented.
The content of the invention
The purpose of the present invention is overcome the deficiencies in the prior art and provides 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 of a few houres is actual before the same day obtains heat, and the effective of following certain section of time water tank of prediction obtains heat, so that it is determined that required heat
Pump water heater aids in heating amount and Teat pump boiler optimal available machine time and total run time, realizes that system operation saves
Purpose.
In order to achieve the above object, the present invention is achieved in that it is a kind of heat pump and solar water heater combination system
Solar energy obtains heat forecast Control Algorithm in system, it is characterised in that heat pump includes Teat pump boiler, heat pump with solar water heater
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 temperature of the storage tank cooling-water temperature sensor sensing is the water temperature of storage tank, the environment temperature sensor sensing
Temperature is environment temperature, and the method and step that the controller prediction solar water heater obtains heat is as follows：
（One）The effective factor for obtaining heat influenceed in combined system mainly has solar energy irradiation and environment temperature, will too
The influence synthesis that positive energy irradiation, environment temperature factor obtain heat to heat pump and solar water heater combined system is expressed as water storage
The effective of case obtains heat, and in the case of given storage tank volume, the temperature rise measured by storage tank cooling-water temperature sensor can
Obtain the effective of combined system and obtain heat；
（Two）The temperature rise Δ T of storage tank is established with time t, solar radiation average value I in the unit intervala, average environment temperature
Spend ThPAnd storage tank initial temperature TCFunctional expression Δ T=(t, I of changea, TC, ThP)；
（Three）According to history by when solar radiation sequence and average ambient temperature parameter establish neural network model, collection makes
Storage tank temperature rise real-time condition and average ambient temperature are made when starting 2~6 hour hot-water heating systems operations before predicting with the same day
For network inputs, the storage tank temperature prediction value that network model exports is placed to controller, water storage is obtained by mathematical computations
Total temperature rise value Δ T ' of case.
（Four）Total temperature rise value Δ T ' of the storage tank of prediction and initial water temperature TCSum as predicts obtained storage tank
Final temperature TZ, user's set water temperature TSWith final temperature TZDifference △ T ", i.e. △ T "=TS -TZTo need Teat pump boiler
The heat of heating is aided in, Teat pump boiler pre-cooling operation when whole day environment temperature is higher is generally noon 12:00, when
This partial heat that Teat pump boiler completes auxiliary heating is to run after temperature rise reaches △ T " to stop fortune by Teat pump boiler
OK.
The present invention compared with prior art the advantages of be：Solar energy when being changed greatly to meteorological condition is effective that heat is pre-
It is more accurate to survey, and the Energy Efficiency Ratio of Teat pump boiler run time section is higher, energy saving of system positive effect.
Brief description of the drawings
Fig. 1 is the systematic schematic diagram of the present invention.
Embodiment
Embodiments of the invention are described below in detail, the example of the embodiment is shown in the drawings.Below with reference to
The embodiment of accompanying drawing description is exemplary, is only used for explaining the present invention, and is not considered as limiting the invention.
As 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 includes Teat pump boiler 1, heat pump cycle water pump 2, storage tank 3, solar energy water circulating pump with solar water heater combined system
4th, solar water heater 5, storage tank cooling-water temperature sensor 6, environment temperature sensor 7 and controller 8；Wherein described Teat pump boiler
1 delivery port connects with a water inlet of storage tank cooling-water temperature sensor 6, and a delivery port of the storage tank cooling-water temperature sensor 6 leads to
The water inlet that heat pump cycle water pump 2 is crossed with Teat pump boiler 1 connects, and another delivery port of storage tank cooling-water temperature sensor 6 passes through too
Positive energy water circulating pump 4 connects with the water inlet of solar water heater 5, another water inlet and the sun of storage tank cooling-water temperature sensor 6
The delivery port connection of energy water heater 5；The control of heat pump cycle water pump 2 and the controlled device 8 of solar energy water circulating pump 4；The water storage
The temperature that case cooling-water temperature sensor 6 senses is the water temperature of storage tank 3, and the temperature that the environment temperature sensor 7 senses is environment temperature
Degree；The method and step that the prediction of controller 8 solar water heater 5 obtains heat is as follows：
（One）The temperature rise Δ T of storage tank 3 is established with time t, solar radiation average value I in the unit intervala, average environment temperature
Spend ThPAnd water tank initial temperature TCFunctional expression Δ T=(t, I of changea, TC, ThP), according to law of conservation of energy, Q=C
× M × Δ T, C is the specific heat capacity of water, and M is the quality of water in storage tank 3, and C and M are definite value, i.e. Δ T=Q/ (C × M)=(QS-
QC)/(C × M), QSRepresent the heating capacity of solar water heater 5 in time t, QCRepresent the heat of the radiation loss of storage tank 3；
（Two）According to GBT50364-2005《Civil buildings solar water heating system application technology specification》, solar water
The heat collecting module heat-collecting capacity calculation formula of one day of device 5 is QS=R × I, R are the gross area, the sun of constant, R and heat collecting module
Can the annual collecting efficiency of heat collector, storage tank, pipeline heat loss rate and solar energy conversion ratio it is related, R value can be with
Drawn by the historical data reorganization of areal, I is per day solar radiation quantity, for accuracy of judgement, by per day sun spoke
Penetrate quantitative change turn to by when average solar radiation quantity sum, i.e.,, IaFor sun spoke in the unit time
Penetrate average value, QCFor the heat dissipation capacity of storage tank 3, the temperature of storage tank 3 and the environment temperature temperature difference are bigger, and radiate faster, i.e. QCWith water tank temperature
Rise Δ T, initial water temperature TCAnd average ambient temperature ThPIt is directly related, QC =ƒ (t, TC, ThP), specific functional expression can basis
The concrete structure of storage tank 3, obtained by thermal conduction study correlation theory；
（Three）According to history by when solar radiation sequence and average ambient temperature parameter establish neural network model, collection makes
Started the temperature rise real-time condition of storage tank 3 and average ambient temperature during 2~6 hour hot-water heating systems operations before predicting with the same day
Inputted as neutral net, the temperature prediction value of storage tank 3 that network model exports is placed to control system, by mathematical computations
The temperature rise value Δ T ' of storage tank 3 is obtained, is comprised the following steps that：
（1）Input this area sun by when radiation history sequence and average ambient temperature historical series, to most area,
Period can be set to 7:00-18:00, take within every 30 minutes 1 solar energy by when radiation value and average ambient temperature value；
（2）Input use on the day of date and start to predict and terminates predict time, typically with noon 12:00 conduct is opened
Begin the time predicted, with afternoon 18:00 as the time for terminating prediction；
（3）The average ambient temperature T that input was measured using the same day by environment temperature sensor 7hP, the general measure time from
The morning 7:00 to noon 12:00, take within every 30 minutes 1 secondary environment temperature Th, and as average ambient temperature T in this 30 minuteshP；
（4）The temperature rise Δ T delta datas of water in the storage tank 3 before prediction time t was proceeded by using the same day are inputted, are led to
Cross the measurement of storage tank cooling-water temperature sensor 6 to obtain, general measure time from the morning 7:00 to noon 12:00, take 1 temperature within every 30 minutes
Degrees of data；
（5）The constant R of solar energy is inputted, network neural algorithm is preferable to the stable situation prediction result of meteorological condition, but
It is not ideal enough to change in weather situation prediction effect, it is contemplated that Changes in weather pairInfluence, not
With under meteorological condition, the numerical value difference such as solar insuring rate that R is reflected is larger, can be by DIFFERENT METEOROLOGICAL CONDITIONS according to history
Data draw approximation；R is added in neutral net input item, data accuracy can be increased with effecting reaction meteorologic factor, compared with
For effective reply change in weather situation；
（6）Using neural networks with single hidden layer, build nonlinear continuous convergent network sequence and approach storage tank（3）Temperature rise
It is worth Δ T, the storage tank 3 for being met backtracking error requirements predicts temperature rise value Δ T '；
（Four）Total temperature rise value Δ T ' of the storage tank 3 of prediction and initial water temperature TCSum as predicts obtained storage tank
3 final temperature TZ, user's set water temperature TSWith TZDifference △ T ", i.e. △ T "=TS -TZTo need the auxiliary heating of Teat pump boiler 1
Heat, Teat pump boiler 1 when whole day environment temperature is higher be generally noon 12:00 pre-cooling is run, and works as Heat Pump
It is out of service afterwards that this partial heat that auxiliary of hydrophone 1 completing heats reaches △ T " by the operation temperature rise of Teat pump boiler 1.
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 with a variety of changes, modification in the case of departing from principle and objective of the invention, replace and deform, this
The scope of invention is limited by claim and its equivalent.
Claims (1)
1. a kind of heat pump obtains heat forecast Control Algorithm with solar energy in solar water heater combined system, it is characterised in that heat pump
Include Teat pump boiler with solar water heater（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）；The storage tank water
Temperature sensor（6）The temperature of sensing is storage tank（3）Water temperature, the environment temperature sensor（7）The temperature of sensing is environment
Temperature, the controller（8）Predict solar water heater（5）The method and step for obtaining heat is as follows：
（One）The effective factor for obtaining heat for influenceing combined system mainly has solar energy irradiation and environment temperature, by solar energy spoke
The influence synthesis for obtaining heat to heat pump and solar water heater combined system according to amount, environment temperature factor is expressed as storage tank（3）
Effective heat, in given storage tank（3）In the case of volume, pass through storage tank cooling-water temperature sensor（6）The temperature rise of measurement is
The effective of combined system can be obtained and obtain heat；
（Two）Establish storage tank（3）Temperature rise Δ T with time t, solar radiation average value I in the unit intervala, average ambient temperature
ThPAnd storage tank（3）Initial temperature TCFunctional expression Δ T=(t, I of changea, TC, ThP)；
（Three）According to history by when solar radiation sequence and average ambient temperature parameter establish neural network model, collection is using working as
Start storage tank during preceding 2~6 hour hot-water heating systems operation of prediction day（3）Temperature rise real-time condition and average ambient temperature conduct
Network inputs, the storage tank that network model is exported（3）Temperature prediction value is placed to controller（8）, obtained by mathematical computations
Storage tank（3）Total temperature rise value Δ T '；
（Four）The storage tank of prediction（3）Total temperature rise value Δ T ' and initial water temperature TCSum as predicts obtained storage tank（3）
Final temperature TZ, user's set water temperature TSWith final temperature TZDifference △ T ", i.e. △ T "=TS-TZTo need Teat pump boiler（1）
Aid in the heat of heating, Teat pump boiler（1）When whole day environment temperature is higher, pre-cooling operation is generally noon 12:
00, work as Teat pump boiler（1）This partial heat of auxiliary heating is completed, that is, passes through Teat pump boiler（1）Operation temperature rise reaches
△ T " are out of service afterwards.
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Families Citing this family (11)
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| 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 |
| CN108413628B (en) * | 2018-02-06 | 2019-11-19 | 杭州龙华环境集成***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 |
| 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 |
| 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 |
| CN113654242B (en) * | 2021-08-12 | 2022-10-21 | 湖南精朗能源科技有限公司 | Air can hot water unit control system based on outdoor ambient temperature |
| 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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| US5206819A (en) * | 1990-09-06 | 1993-04-27 | Illing Wesley R | Control system for solar heater |
| US5347985A (en) * | 1993-03-03 | 1994-09-20 | Bucciarelli Douglas A | Constant temperature solar water heater switch |
| CN201083433Y (en) * | 2007-06-07 | 2008-07-09 | 昆明金利马热力设备有限公司 | Solar energy combined heat pump hot water supplying energy-saving apparatus |
| JP5025834B2 (en) * | 2010-11-10 | 2012-09-12 | パナソニック株式会社 | Operation planning method, operation planning device, operation method of heat pump hot water supply system, and operation method of heat pump hot water supply heating system |
| CN104121703B (en) * | 2014-08-01 | 2017-01-18 | 江苏天舒电器股份有限公司 | Method and device for controlling direct heat type double-source heat pump water heater |
| CN104101106B (en) * | 2014-08-01 | 2017-02-15 | 江苏天舒电器股份有限公司 | Directly-heated type double-source heat pump water heater and control method thereof |
| CN104482679B (en) * | 2014-11-13 | 2016-10-05 | 广东万家乐燃气具有限公司 | Multiple-energy-source composite hot-water system control method with anticipation computing function |
| CN105352190B (en) * | 2015-10-16 | 2017-12-01 | 顺德职业技术学院 | The energy-saving control method of solar energy, heat pump and the compound hot-water heating system of three kinds of energy of combustion gas |
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