CN103162346B - Based on central heating supervisory control system and the central heating system control method of cloud service - Google Patents
Based on central heating supervisory control system and the central heating system control method of cloud service Download PDFInfo
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Abstract
The invention discloses a kind of based on the central heating supervisory control system of cloud service and the method for adjustment of central heating system, the heating terminal monitoring equipment that described central heating supervisory control system comprises cloud server and communicates to connect with cloud server; Cloud server obtains user behavior function corresponding to each user according to historical data, user behavior function reaction house heating equipment parameter and the heat load of each user, supply water temperature and the relation of time, cloud server is predicted each user's heat load and is obtained the current supply water temperature of each user, and is issued to each heating terminal monitoring equipment according to above-mentioned parameter calculated room heating equipment parameter; Heating terminal monitoring equipment regulates according to described rooms device parameter.The present invention can optimize the heating system of each user on the whole, thus reduces the load of whole heating system, and degree of intelligence is high, and precision is good, and degree of power conservation is also increased.
Description
Technical field
The present invention relates to intelligent heating technology, be specifically related to the central heating supervisory control system based on cloud service and central heating system control method.
Background technology
China's concentrated supply of heating in the city area at least 30 hundred million square metres, the user in these area of heat-supply services scarcely possesses the energy conserving system automatically regulating heating temperature, both wastes energy like this, uncomfortable again.
A kind of user's of being manual adjustment of existing indoor heating terminal monitoring equipment control method user operation panel completes the adjustment to the flow for water return pipeline.This mode needs user's manual adjustment, and automaticity is low, and energy consumption is high.
Another kind of indoor heating terminal monitoring equipment is automatically adjusted by indoor temperature transmitter.After user sets indoor temperature, the Indoor Temperature angle value that the detected value of indoor temperature transmitter and user set is compared, comparative result sends to control section, by controlling the electric control valve be arranged on heat supply water pipe, indoor temperature can be made to reach the desired value of setting.Although this technical scheme can reach the effect of energy-saving and emission-reduction to a certain extent, the probe value according to temperature sensor carries out passive adjustment, and indoor actual temperature is difficult to remain in the setting value of user.And due to the conductibility of heat energy, the confession thermal losses of every unit has substantial connection with the pad structure of the position of this unit in building, neighbours' situation and building itself except the autophage of this unit, therefore, the adjustment accuracy of this indoor heating terminal monitoring equipment and degree of power conservation still need to improve.
Summary of the invention
The object of the invention is to propose a kind of central heating supervisory control system based on cloud service and control method thereof, based on the large-scale calculations ability in high in the clouds, plan as a whole the load of each user and the behavior pattern of individual subscriber in whole central heating system, improve adjustment accuracy and the degree of power conservation of indoor heating terminal monitoring equipment.
The invention discloses a kind of central heating supervisory control system based on cloud service, the heating terminal monitoring equipment comprising cloud server and communicate to connect with cloud server:
Described cloud server comprises user behavior function acquisition module, load and water temperature acquisition module and parameter calculating module;
Described user behavior function acquisition module is used for obtaining user behavior function corresponding to each user according to historical data, and described user behavior function is rooms device parameter and the function of relation between time, corresponding user's heat load, supply water temperature;
Described load and water temperature acquisition module are for predicting each user's heat load and obtaining the current supply water temperature of each user;
Described parameter calculating module is used for each user's heat load according to prediction, current supply water temperature and temporal information calculated room heating equipment parameter and is issued to each heating terminal monitoring equipment;
Described heating terminal monitoring equipment is for obtaining the current supply water temperature of user residing for monitored rooms equipment and regulating rooms equipment according to described rooms device parameter.
Preferably, described load and water temperature acquisition module are according to meteorological data and each user's heat load of energy consumption function prediction of obtaining in advance;
Described energy consumption function is the function embodying relation between described meteorological data and each user's heat load, and it is by obtaining the historical data matching of history meteorological data and each user's heat load.
Preferably, described meteorological data comprises temperature, humidity and illumination.
Preferably, described rooms device parameter is motorized adjustment valve opening.
Preferably, described cloud server also comprises feedback adjustment module:
Described feedback adjustment module is used for user behavior function according to the manual adjustments parameters revision of user.
Preferably, described cloud server also comprises optimal correction module;
Described optimal correction module is used for the user behavior function of other user of user behavior function correction according to the most energy-conservation user.
The invention also discloses a kind of central heating system control method based on cloud service, comprising:
Cloud server obtains user behavior function according to historical data, and described user behavior function is the function embodying rooms device parameter and relation between time, corresponding user's heat load, supply water temperature;
Cloud server is predicted each user's heat load and is obtained the current supply water temperature of each user by heating terminal monitoring equipment;
Cloud server is according to each user's heat load of prediction, current supply water temperature and temporal information calculated room heating equipment parameter be issued to each heating terminal monitoring equipment;
According to described rooms device parameter, rooms equipment is regulated.
Preferably, described cloud server is according to meteorological data and each user's heat load of energy consumption function prediction of obtaining in advance;
Described energy consumption function is the function of relation between described meteorological data and each user's heat load described, and it is by obtaining the historical data matching of history meteorological data and each user's heat load.
Preferably, described meteorological data comprises temperature, humidity and illumination.
Preferably, described rooms device parameter is motorized adjustment valve opening.
Preferably, described method also comprises:
User behavior function according to the manual adjustments parameters revision of user.
Preferably, described method also comprises:
According to the user behavior function of other user of user behavior function correction of the most energy-conservation user.
The present invention obtains user behavior function by historical data, server periodically calculates current rooms device parameter based on user behavior function according to each user's heat load of prediction and supply water temperature beyond the clouds, and regulates according to the rooms parameter calculated.Thus, the adjustment of rooms equipment can either meet the behavior pattern of user, and can optimize again the load of whole heating system on the whole, degree of intelligence is high, and precision is good, and degree of power conservation is also increased.
Accompanying drawing explanation
Fig. 1 is the schematic diagram of the central heating supervisory control system based on cloud service of first embodiment of the invention.
Fig. 2 is the schematic diagram of the heating terminal monitoring equipment of the central heating supervisory control system based on cloud service of first embodiment of the invention.
Fig. 3 is the flow chart of the control method of the central heating system based on cloud service of second embodiment of the invention.
Main Reference Numerals illustrates:
Cloud Server 11, heating terminal monitoring equipment 12, hot duct 13, RSMC 14, user behavior function acquisition module 111, load and water temperature acquisition module 112, parameter calculating module 113, optimal correction module 114, feedback regulation module 115, communication module 121, control circuit board 122, electric control valve 123, cooling-water temperature sensor 124, user operation setting knob 125
Detailed description of the invention
Technical scheme of the present invention is further illustrated by detailed description of the invention below in conjunction with accompanying drawing.
Fig. 1 is the schematic diagram of the central heating supervisory control system based on cloud service of first embodiment of the invention.As shown in Figure 1, central heating supervisory control system based on cloud service comprises Cloud Server 11 and local heating equipment, local heating equipment comprises the heating terminal monitoring equipment 12 and hot duct 13 of being located at user indoor, and heating terminal monitoring equipment 12 can control hot duct 13 and flow into the discharge of indoor room heating equipment thus control temperature.
Particularly, cloud server 11 comprises user behavior function acquisition module 111, load and water temperature acquisition module 112, parameter calculating module 113.
User behavior function acquisition module 111 is for obtaining user behavior function according to historical data, and user behavior function is the function embodying relation between rooms device parameter and time, each user's heat load, supply water temperature.
Load and water temperature acquisition module 112 are for predicting each user's heat load and obtaining current supply water temperature.
Parameter calculating module 113 is for each user's heat load according to prediction, current supply water temperature, temporal information calculated room heating equipment parameter be issued to heating terminal monitoring equipment.
Fig. 2 is the schematic diagram of the heating terminal monitoring equipment of the central heating system based on cloud service of first embodiment of the invention.As shown in Figure 2, the terminal monitoring equipment 12 that heats comprise communication module 121, control circuit board 122, be arranged on hot duct for regulating the electric control valve 123 entering indoor hot water flow and the cooling-water temperature sensor 124 be arranged on hot duct.Preferably, user operation setting knob 125 can also be comprised.
The hot duct supply water temperature of the current time that communication module 121 reports cooling-water temperature sensor 124 to measure for communicating with cloud server, and receive the rooms device parameter calculating acquisition from cloud server 11.
Control circuit board 122 is connected with communication module 121, and the rooms device parameter for transmitting according to communication module 121 controls electric control valve 123 and regulates.
Electric control valve 123 is for controlling to regulate inflow according to control circuit board 122.
Preferably, user operation setting knob 125 is connected with control circuit board 122, for transmitting the operational order of user to control circuit board 122.
In a preferred embodiment of the present embodiment, rooms device parameter is the aperture of heating terminal monitoring equipment electric control valve 123.The user behavior function acquisition module 111 of described cloud server sets up supply water temperature, functional relation between each user's heat load and rooms device parameter according to the historical data of supply water temperature of preserving, the historical data of each user's heat load and user's manual operation historical information, also namely, user behavior function.The acquisition of described historical data with two to three weeks for the cycle carries out, also, in cycle time, can not adjust automatically, but allows user operation adjust indoor heating terminal monitoring equipment, gathers the historical data of reflection user behavior pattern thus.
Preferably, experience curve matching can be carried out by the historical data of the user behavior function acquisition module 111 pairs of time, load, supply water temperature, motorized adjustment valve opening in this stage, calculate under different time, each user's heat load concentrated and supply water temperature, user regulates the rule of motorized adjustment valve opening, obtains described user behavior function as follows:
Phi=f(t)*(a1+a2*L+a3*L
2+b1*T+b2*T
2+c*L*T)
Wherein, Phi is electric control valve 123 aperture; F (t) is for representing the function of heating terminal monitoring equipment regulating time, and L is for concentrating each user's heat load, and it can be calculated by cloud server each user's heat load parameter within the function acquisition cycle and obtain; T is supply water temperature, and it is gathered by the cooling-water temperature sensor 124 be arranged on hot duct; A1, a2, a3, b1, b2, c are fitting coefficient.
Thus, cloud server can calculate according to time, each user's heat load and supply water temperature the rooms device parameter obtaining and meet user behavior pattern.
In a preferred embodiment of the present embodiment, the load of cloud server 11 and water temperature acquisition module 112 according to meteorological data and each user's heat load of energy consumption function prediction of obtaining in advance, and obtain the supply water temperature of the hot duct 13 of this heating terminal monitoring equipment by the communication module 121 of heating terminal monitoring equipment 12.
Described energy consumption function is the function embodying relation between described meteorological data and each user's heat load described, also be, each user heating meets the rule changed with the change of meteorological data, and it is by obtaining according to prediction algorithm training or matching historical data.Can by special module be set on Cloud Server 11 utilize the data coming from RSMC 14 and the historical data accumulated for obtaining user behavior function to train or matching obtain described in energy consumption function, also can train separately energy consumption function described in acquisition or matching acquisition to above-mentioned data.
Preferably, can beyond the clouds in server 11 based on weather prognosis algorithm according to the whole day weather information of the weather information of user region and weather forecast prediction by time the weather information such as accounting temperature, humidity, illumination.Utilize weather prognosis algorithm to carry out meteorologic parameter by time calculate can to a certain degree improve the acquisition efficiency of weather information.
The highest outdoor temperature T that instant time temperature T obtains according to weather forecast
hwith minimum outdoor temperature T
linformation adopts following formula to calculate:
T＝T
h-α
t×(T
h-T
l)，
In formula, α
tfor the t temperature prediction coefficient preset, this coefficient can obtain according to this area's historical temperature information matching.
By time humidity
historical data according to some day gathers humidity variation tendency, and the whole day average relative humidity information utilizing weather forecast to obtain is revised historical variations trend:
In formula,
for certain day τ moment typical meteorological year history humidity;
for the whole day of certain day adds up relative humidity; RH is the whole day average relative humidity that weather forecast obtains.
By time illumination calculated by formula below:
In formula, Q
τt () is t hourly total solar irradiance amount; Q is daily global radiation amount; t
r, t
dbe respectively the sun set/raise time that weather forecast obtains.
Certainly it will be understood by those skilled in the art that also can by provide by time weather forecast RSMC 14 directly obtain above-mentioned meteorological data from outside.
According to the history meteorological data of acquisition and the historical data of each user's heat load, namely set up energy consumption function by matching or alternate manner.
Preferably, can history is meteorological, load data as the training data of load prediction neural network algorithm, the corresponding relation of cold (heat) load and moment, outdoor temperature, relative humidity and irradiation level can be drawn through existing Algorithm for Training, also namely obtain energy consumption function, and energy consumption function is kept at cloud server 11.
Thus, the load of cloud server 11 and water temperature acquisition module 112 when rooms parameter will be carried out to be regulated (in a preferred mode, can be periodic or triggered by event regulate) can according to meteorological data and each user's heat load of the energy consumption obtained in advance function prediction.Thus subsequent parameter computing module 113 can according to each user's heat load of prediction, current supply water temperature and temporal information calculated room heating equipment parameter be issued to heating terminal monitoring equipment 12, and and then perform corresponding parameter by heating terminal monitoring equipment 12 and regulate, such as, the adjustment of motorized adjustment valve opening.
The present embodiment obtains user behavior function by historical data, server 11 periodically carrys out calculated room heating equipment parameter based on user behavior function according to each user's heat load of prediction and supply water temperature beyond the clouds, regulates according to rooms device parameter.Thus, the adjustment of rooms equipment can either meet the behavior pattern of user, and can optimize again the load of whole heating system on the whole, degree of intelligence is high, and precision is good, and degree of power conservation is also increased.
In a preferred embodiment of the present embodiment, cloud server 11 can also comprise optimal correction module 114, and it is according to the user behavior function of other user of user behavior function correction of the most energy-conservation user.
Particularly, optimal correction module 114 is according to the user behavior record of cloud server with zone user, select the personal behavior model record with this user place same building or the identical house type of similar building, analyze under various heating system integral load, supply water temperature condition user to the control information of rooms device parameter, and the most energy-conservation rooms device parameter control mode is found from record, set up optimum user behavior function.Then adjust according to the user behavior function of user behavior function to each user of optimum, and use the rooms device parameter of this corrected user behavior function to user to regulate.In this manner, user still manually can regulate rooms device parameter according to the comfort level demand of oneself, regulates record to be kept on the Cloud Server 11 of cloud service center.
In a preferred embodiment of the present embodiment, cloud server 11 can also comprise the module of user behavior function being carried out to dynamic conditioning, this module can be such as feedback adjustment module 115, and it is for user behavior function according to the manual adjustments parameters revision of user.
Particularly, feedback adjustment module 115 regulates the user of rooms device parameter record for having in the automatic control stage, according to user, the operation note of rooms equipment and corresponding time, load, supply water temperature information are carried out to experience curve matching according to the method in Model Identification stage to personal behavior model and obtained new user behavior function, and substitutes original user behavior function with this user behavior function.
This preferred embodiment can by the manual feedback continuous dynamic conditioning user behavior function of user, and the Intelligent Dynamic realized for rooms equipment regulates.
The adjusting module related in above-mentioned two kinds of embodiments can and deposit and also can independently exist, continuous dynamic conditioning user behavior function.
Fig. 3 is the flow chart of the control method of the central heating system based on cloud service of second embodiment of the invention.As shown in Figure 3, described method comprises:
Step 310, cloud server obtain user behavior function according to historical data, and described user behavior function is the function embodying relation between rooms device parameter and time, each user's heat load, supply water temperature.
In a preferred embodiment of the present embodiment, rooms device parameter is the aperture of heating terminal monitoring equipment electric control valve.Described cloud server sets up supply water temperature, functional relation between each user's heat load and rooms device parameter according to the historical data of supply water temperature of preserving, the historical data of each user's heat load and user's manual operation historical information, also namely, user behavior function.The acquisition of described historical data with two to three weeks for the cycle carries out, also, in cycle time, can not adjust automatically, but allows user operation adjust indoor heating terminal monitoring equipment, gathers the historical data of reflection user behavior pattern thus.
Preferably, can in this stage by carrying out experience curve matching to the historical data of time, load, supply water temperature, motorized adjustment valve opening, calculate under different time, each user's heat load and supply water temperature, user regulates the rule of motorized adjustment valve opening, obtains described user behavior function as follows:
Phi=f(t)*(a1+a2*L+a3*L
2+b1*T+b2*T
2+c*L*T)
Wherein, Phi is motorized adjustment valve opening; F (t) is the function of expression heating terminal monitoring equipment regulating time, and L is for concentrating each user's heat load, and it can gather the load parameter calculating acquisition of heating system within the function acquisition cycle by cloud server; T is supply water temperature, and it is by being arranged at the cooling-water temperature sensor collection on hot duct; A1, a2, a3, b1, b2, c are fitting coefficient.
Thus, cloud server can calculate according to time, each user's heat load of central heating system and supply water temperature the rooms device parameter obtaining and meet user behavior pattern.
Step 320, cloud server are predicted each user's heat load and are obtained the current supply water temperature of each user by heating terminal monitoring equipment.
In a preferred embodiment of the present embodiment, cloud server according to meteorological data and each user's heat load of energy consumption function prediction of obtaining in advance, and obtains the supply water temperature of the hot duct of this heating terminal monitoring equipment by the communication module of heating terminal monitoring equipment.
Described energy consumption function is the function embodying relation between described meteorological data and each user's heat load described, also be, each user heating meets the rule changed with the change of meteorological data, and it is by obtaining according to prediction algorithm training or matching historical data.Can by special module be set on Cloud Server utilize the data coming from RSMC and the historical data accumulated for obtaining user behavior function to train or matching obtain described in energy consumption function, also can train separately above-mentioned data or energy consumption function described in matching acquisition.
Preferably, can beyond the clouds in server based on weather prognosis algorithm according to the whole day weather information of the weather information of user region and weather forecast prediction by time the weather information such as accounting temperature, humidity, illumination.Utilize weather prognosis algorithm to carry out meteorologic parameter by time calculate can to a certain degree improve the acquisition efficiency of weather information.
The highest outdoor temperature T that instant time temperature T obtains according to weather forecast
hwith minimum outdoor temperature T
linformation adopts following formula to calculate:
T＝T
h-α
t×(T
h-T
l)，
In formula, α
tfor the t temperature prediction coefficient preset, this coefficient can obtain according to this area's historical temperature information matching.
By time humidity
historical data according to some day gathers humidity variation tendency, and the whole day average relative humidity information utilizing weather forecast to obtain is revised historical variations trend:
In formula,
for certain day τ moment typical meteorological year history humidity;
for the whole day of certain day adds up relative humidity; RH is the whole day average relative humidity that weather forecast obtains.
By time illumination calculated by formula below:
In formula, Q
τt () is t hourly total solar irradiance amount; Q is daily global radiation amount; t
r, t
dbe respectively the sun set/raise time that weather forecast obtains.
Certainly it will be understood by those skilled in the art that also can by provide by time weather forecast RSMC directly obtain above-mentioned meteorological data from outside.
According to the history meteorological data of acquisition and the historical data of each user's heat load, namely set up energy consumption function by matching or alternate manner.
Preferably, can history is meteorological, load data as the training data of load prediction neural network algorithm, the corresponding relation of cold (heat) load and moment, outdoor temperature, relative humidity and irradiation level can be drawn through existing Algorithm for Training, also namely obtain energy consumption function, and energy consumption function is kept at cloud server.
Thus, cloud server to carry out rooms parameter regulate time (in a preferred mode, can be periodic or triggered by event regulate), can according to meteorological data and each user's heat load of the energy consumption obtained in advance function prediction.
Step 330, cloud server are according to each user's heat load of prediction, current supply water temperature and temporal information calculated room heating equipment parameter be issued to heating terminal monitoring equipment.
Step 340, heating terminal monitoring equipment regulate rooms equipment according to described rooms device parameter.
In a preferred embodiment of the present embodiment, described method also comprises in step 350(figure represented by dashed line), according to the user behavior function of the user behavior function correction active user of the most energy-conservation user.
Particularly, according to the user behavior record of cloud server with zone user, select the personal behavior model record with this user place same building or the identical house type of similar building, analyze under various user's heat load, supply water temperature condition user to the control information of rooms device parameter, and the most energy-conservation rooms device parameter control mode is found from record, set up optimum user behavior function.Then adjust according to the user behavior function of user behavior function to each user of optimum, and use the rooms device parameter of this corrected user behavior function to user to regulate.In this manner, user still can according to manual the regulating rooms device parameter of the comfort level demand of oneself, regulate record to be kept on the Cloud Server of cloud service center, and according to the first correcting mode of this stage, personal behavior model is revised.
In a preferred embodiment of the present embodiment, described method also comprises in step 360(figure represented by dashed line), user behavior function according to the manual adjustments parameters revision of user.
Particularly, for the user having manual adjustment rooms device parameter in the automatic control stage, according to user, the operation note of rooms device parameter and corresponding time, load, supply water temperature information are carried out to experience curve matching according to the method in Model Identification stage to personal behavior model and obtained new user behavior function, and substitute original user behavior function with this user behavior function, then return step 320.
The adjustment mode related in above-mentioned two kinds of embodiments can and deposit and also can independently exist, continuous dynamic conditioning user behavior function, the Intelligent Dynamic realized for heating terminal monitoring equipment regulates.
The present embodiment obtains user behavior function by historical data, server 11 periodically carrys out calculated room heating equipment parameter based on user behavior function according to each user's heat load of prediction and supply water temperature beyond the clouds, regulates according to rooms device parameter.Thus, the adjustment of rooms equipment can either meet the behavior pattern of user, and can optimize again the load of whole heating system on the whole, degree of intelligence is high, and precision is good, and degree of power conservation is also increased.
Obviously, those skilled in the art should be understood that, above-mentioned of the present invention each module or each step can realize with general calculation element, they can concentrate on single calculation element, or be distributed on network that multiple calculation element forms, alternatively, they can realize with the executable program code of computer installation, thus they storages can be performed by calculation element in the storage device, or they are made into each integrated circuit modules respectively, or the multiple module in them or step are made into single integrated circuit module to realize.Like this, the present invention is not restricted to the combination of any specific hardware and software.
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, to those skilled in the art, the present invention can have various change and change.All do within spirit of the present invention and principle any amendment, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (12)
1. based on a central heating supervisory control system for cloud service, the heating terminal monitoring equipment comprising cloud server and communicate to connect with cloud server:
Described cloud server comprises user behavior function acquisition module, load and water temperature acquisition module and parameter calculating module;
Described user behavior function acquisition module is used for obtaining user behavior function corresponding to each user according to historical data, and described user behavior function is rooms device parameter and the function of relation between time, corresponding user's heat load, supply water temperature;
Described load and water temperature acquisition module are for predicting each user's heat load and obtaining the current supply water temperature of each user;
Described parameter calculating module is used for each user's heat load according to prediction, current supply water temperature and temporal information calculated room heating equipment parameter and is issued to each heating terminal monitoring equipment;
Described heating terminal monitoring equipment is for obtaining the current supply water temperature of user residing for monitored rooms equipment and regulating rooms equipment according to described rooms device parameter.
2. the central heating supervisory control system based on cloud service according to claim 1, is characterized in that, described load and water temperature acquisition module are according to meteorological data and each user's heat load of energy consumption function prediction of obtaining in advance;
Described energy consumption function is the function embodying relation between described meteorological data and each user's heat load, and described energy consumption function is by obtaining the historical data matching of history meteorological data and each user's heat load.
3. the central heating supervisory control system based on cloud service according to claim 2, is characterized in that, described meteorological data comprises temperature, humidity and illumination.
4. the central heating supervisory control system based on cloud service according to claim 1, is characterized in that, described rooms device parameter is motorized adjustment valve opening.
5. the central heating supervisory control system based on cloud service according to claim 1, is characterized in that, described cloud server also comprises feedback adjustment module:
Described feedback adjustment module is used for user behavior function according to the manual adjustments parameters revision of user.
6. the central heating supervisory control system based on cloud service according to claim 1, is characterized in that, described cloud server also comprises optimal correction module;
Described optimal correction module is used for the user behavior function of other user of user behavior function correction according to the most energy-conservation user.
7., based on a central heating system control method for cloud service, comprising:
Cloud server obtains user behavior function according to historical data, and described user behavior function is the function embodying rooms device parameter and relation between time, corresponding user's heat load, supply water temperature;
Cloud server is predicted each user's heat load and is obtained the current supply water temperature of each user by heating terminal monitoring equipment;
Cloud server is according to each user's heat load of prediction, current supply water temperature and temporal information calculated room heating equipment parameter be issued to each heating terminal monitoring equipment;
Heating terminal monitoring equipment regulates rooms equipment according to described rooms device parameter.
8. the central heating system control method based on cloud service according to claim 7, is characterized in that, described cloud server is according to meteorological data and each user's heat load of energy consumption function prediction of obtaining in advance;
Described energy consumption function is the function of relation between described meteorological data and each user's heat load described, and it is by obtaining the historical data matching of history meteorological data and each user's heat load.
9. the central heating system control method based on cloud service according to claim 8, it is characterized in that, described meteorological data comprises temperature, humidity and illumination.
10. the central heating system control method based on cloud service according to claim 7, is characterized in that, described rooms device parameter is motorized adjustment valve opening.
The 11. central heating system control methods based on cloud service according to claim 7, it is characterized in that, described method also comprises:
User behavior function according to the manual adjustments parameters revision of user.
The 12. central heating system control methods based on cloud service according to claim 7, it is characterized in that, described method also comprises:
According to the user behavior function of other user of user behavior function correction of the most energy-conservation user.
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