CN108240679A

CN108240679A - A kind of heat supply method based on building heating load prediction, device and system

Info

Publication number: CN108240679A
Application number: CN201810153898.4A
Authority: CN
Inventors: 丁爱军; 王福林
Original assignee: Yantai Kechuang Jieneng Electromechanical Engineering Co Ltd
Current assignee: Yantai Kechuang Jieneng Electromechanical Engineering Co Ltd
Priority date: 2018-02-22
Filing date: 2018-02-22
Publication date: 2018-07-03
Anticipated expiration: 2038-02-22
Also published as: CN108240679B

Abstract

The present invention provides a kind of heat supply method based on building heating load prediction, device and system, this method includes：Based on get target heating user's architectural exterior-protecting construction situation, it is adjacent between the indoor temperature that needs of heat transfer conditions, instant out door climatic parameter and user predict dynamic space heating load；The control signal controlled based on the practical heating load data generation that dynamic space heating load and heat meter detect target valve, it is the valve controlled the heating water flow of target heating user to control and opening information and/or make-and-break time information, target valve are carried in signal；Control signal is sent to target valve, so that target valve performs corresponding action according to control signal.The present invention solves the problems, such as the technical issues of existing room temperature thermometric erection of equipment position difference causes thermometric offset issue and user that can realize heating according to need to different user difference room temperature demand to temperature measuring equipment interference and heat supply company.

Description

A kind of heat supply method based on building heating load prediction, device and system

Technical field

The present invention relates to building heating and control technology fields, pre- based on building heating dynamic load more particularly, to one kind The heat supply method of survey, device and system.

Background technology

The heating system in China causes cold and hot distribution not substantially without automaton at the heat user of end at present , phenomena such as some users wear cotta, open a window indoors, and some users wear cotton dress indoors.Such case not only user Comfort level, satisfaction it is poor, and be unfavorable for the health of user, also result in the waste of the heating energy.External heating System on the heating water pipe of every group of radiator is mounted on that the autocontrol valve outside regulation room can be carried out with control valve aperture, But since cost is higher, high to heating water quality requirement, user with can be due to behavior etc., can not temporarily be popularized in China should With.Many researchers attempt to solve the problems, such as this, for example, patent《Public building energy heating control device》Disclose one kind The heating control system being made of control valve, detector and controller, and based on the switch of ambient parameter information control control valve State, the heating-amount of control targe heat exchange station, by foregoing description it is found that existing power supply technique have with heat supply user it is non- Often close contact.Patent《Heating control system》Disclose a kind of heating control being made of water storage unit and rooms unit System processed only provides bath hot water for water heater and is designed without having heating function, in the water storage box of original water heater Install a series of devices additional, you can realize that shower can realize the functions such as heating again.Patent《A kind of collection monitors in real time and facilitates repair Heating control system》A kind of heating control system for collecting and monitoring and facilitate in real time repair is developed, passes through the automatic heat pump of controller Power supply and power-off control indoor temperature, and can prevent that heat pump crosses heat-induced damage or indoor temperature is excessively high.Patent《One Kind central heating control system and method》A kind of heating control system is disclosed, can realize that user is adjustable, heat supply is controllable, neck Lead can pipe central heating control system, while realize regulation and control to heat supply end and user terminal, realize to the greatest extent energy saving With improve heat supply efficiency, but the patent controls to adjust valve, the different installation positions of temperature measuring point using the method by indoor thermometric Putting causes detection temperature and normal room temperature to have relatively large deviation, in addition if caused at room temperature to control to adjust valve by indoor thermometric Drop, many users understand human interference temperature measuring equipment so as to make thrashing.It is by a kind of mode of charging per heat《Temperature area Method》, in the case where user area is certain, the subscriber payment amount of money is related to desired indoor temperature, and room temperature is higher, and payment is higher, Unrelated with user position direction etc., this method is seemingly reasonable, but just because of many user's human interference temperature measuring equipments And the program is caused to be difficult to promote.In addition, in order to save for thermal energy consumption, avoid heat supply energy waste, many cities have carried out pressing Area charging and double portion's caloric value systems by heat charging.Purpose by heat charging caloric value system is by " with how many heat flowers How much " charging means encourage the heat user correctly with can, avoid wasting, realize heating according to need, behavior energy saving, and force new It builds heating system and is respectively mounted household-based heat metering table, to realize that every household can charge by heat.However, for various reasons, Although being mounted with a large amount of heat meters, charge to be implemented by heat, the project exposure that pilot has been implemented Many problems, it is difficult to balance the interests between heat supply company and heat user, therefore most of heat supply expenses are received still according to area It takes, not only energy-efficient purpose is promoted not have by " how much is spent with how many heat " accomplished, but also cause a large amount of calorimeter Idle and investment the waste of resource.

Invention content

In view of this, the purpose of the present invention is to provide it is a kind of based on dynamic building heat load prediction heat supply method, Device and system cause thermometric offset issue and user to fill thermometric to solve existing room temperature thermometric erection of equipment position difference The technical issues of realizing heating according to need to different user difference room temperature demand can be met by putting interference problem and heat supply company.

In a first aspect, an embodiment of the present invention provides a kind of heat supply method based on the prediction of dynamic building heat load, packet It includes：Based on the outdoor weather data prediction dynamic space heating load of the target heating user's local environment got, wherein, it is described Dynamic space heating load is the heat demand of the target heating user predicted；Based on the dynamic space heating load and heat The control signal that the actually detected heating load data generation of gauge table controls target valve, wherein, the control signal Middle carrying opening information and/or make-and-break time information, the target valve are the heating water flow to the target heating user The valve controlled；The control signal is sent to the target valve, so that the target valve is believed according to the control Number perform corresponding action.

Further, the method further includes：Obtain the heating target of the target heating user；Based on the mesh got The outdoor weather data prediction dynamic space heating load of mark heating user's local environment includes：It is used based on the target heating got The outdoor weather data of family local environment and the heating target prediction dynamic space heating load of the target heating user.

Further, outdoor weather data and the target heating based on the target heating user's local environment got The heating target prediction dynamic space heating load of user includes：Target nerve network is transferred, the target nerve network is advance The neural network that training is completed；Using the outdoor weather data and the heating target as the defeated of the target nerve network Enter, so that the target nerve network handles the outdoor weather data and the heating target, and export described dynamic State space heating load.

Further, the target nerve network is expressed as the following formula：

Wherein, i=1,2 ..., n, n are the input number of nodes of the target nerve network；J=1,2 ..., m, m are described The node in hidden layer of target nerve network；x_iNeuron node value for i-th of input layer in the target nerve network； y_j,inFor the input value of j-th of hidden layer neuron node in the target nerve network, y_j,outFor the target nerve network In j-th of hidden layer neuron node output valve；w_i,jFor i-th of input layer section in the target nerve network O'clock to j-th of hidden layer neuron node calculating weight；u_jFor j-th of hidden layer neuron section in the target nerve network Point arrives the calculating weight of output layer neuron node；Q_inAnd Q_outIt is the input value and output valve of output layer neuron node respectively, Wherein, the output valve is the dynamic space heating load of prediction.

Further, the control controlled based on the dynamic space heating load and the generation of heating load data target valve Signal processed includes：The dynamic space heating load and the heating load data are compared, to determine that the dynamic supplies warm heat Deviation between load and the heating load data；The deviation is carried out by pid algorithm or FUZZY ALGORITHMS FOR CONTROL Processing, to obtain the opening information and the make-and-break time information；Based on the opening information and the make-and-break time information Generate the control signal controlled target valve.

Further, the deviation is handled by pid algorithm, to obtain the opening information and the break-make Temporal information includes：The deviation is handled by the calculation formula of pid algorithm, to obtain the opening information and institute State make-and-break time information：

Wherein, V is the opening information of the target valve；K is rate mu-factor；Q_pThe dynamic to predict supplies Warm heat load；Q_mThe heating load data measured for calorimeter；T_IFor the time of integration；T_DFor derivative time；τ is the time.

Further, the deviation is handled by FUZZY ALGORITHMS FOR CONTROL, to obtain the opening information and institute Make-and-break time information is stated to include：The deviation is handled by the calculation formula of FUZZY ALGORITHMS FOR CONTROL, it is described to obtain Opening information and the make-and-break time information：

Wherein, V is the make-and-break time information；K is rate mu-factor；Q_pThe dynamic to predict is born for warm heat Lotus；Q_mThe heating load data measured for calorimeter；τ is the time, and fuzzy is ambiguity function.

Further, before target nerve network is transferred, the method further includes：The target nerve network is carried out Training to determine the weight coefficient in the target nerve network between each neuron node, specifically includes：Pass through iteration public affairs Target nerve network is iterated training described in formula, and to determine the weight coefficient, the iterative formula isWherein, i=1,2 ..., n, n are the input number of nodes of the target nerve network；J=1,2 ..., M, m are the node in hidden layer of the target nerve network；x_iFor i-th of input layer section in the target nerve network Point value；y_j,outDefeated output valve for j-th of hidden layer neuron node in the target nerve network；WithRespectively institute J-th of hidden layer neuron node is stated to the calculating weight of output layer neuron node in n-th and the N+1 times repetitive exercise Value；WithIt is calculating power of i-th of input layer node to j-th of hidden layer neuron node respectively Focus on n-th and the value of the N+1 times repetitive exercise；η is iteration efficiency factor；δ is the output of the output layer neuron node The departure function of value and desired value is to the partial derivative of output layer node weights.

Further, the outdoor weather data include at least one of：Outdoor temperature change information, outdoor wind speed become Change information, outdoor intensity of solar radiation change information；The heating target is the target heating user purpose to be achieved Temperature.

Further, the method further includes：Heat Transfer Data between acquisition is adjacent, wherein, Heat Transfer Data is described between the neighbour Heat Transfer Data between target heating user heating user adjacent thereto；Based on the target heating user's local environment got Outdoor weather data and the heating target prediction dynamic space heating load of the target heating user further include：Based on the neighbour Between Heat Transfer Data, dynamically born for warm heat described in the heating target prediction of the outdoor weather data and the target heating user Lotus.

Second aspect, an embodiment of the present invention provides a kind of heating system based on building heating load prediction, including：The One controller, sensor, calorimeter and target valve, the target valve are the heating water flow to the target heating user The valve controlled；The sensor is used to acquire the outdoor weather data of target heating user's local environment；The heat Table is used to acquire the heating load data of target heating user；First controller is used for based on the outdoor weather data prediction Dynamic space heating load, and the control controlled based on the dynamic space heating load and the generation of heating load data target valve Signal processed, wherein, the dynamic space heating load is the heat demand of the target heating user predicted；The control letter Opening information and/or make-and-break time information are carried in number；The target valve is used to perform according to the control signal corresponding Action, to adjust the heating water flow of the target heating user.

Further, first controller is additionally operable to obtain the heating target of the target heating user, and based on institute State outdoor weather data and the heating target prediction dynamic space heating load.

Further, the target nerve network that training is completed in advance is embedded in the control chip of first controller； Wherein, the target nerve network is used for based on the outdoor weather data and the heating target prediction dynamic space heating load Predict dynamic space heating load.

Further, the heating system further includes：Second controller, wherein, the second controller is mounted on and institute The controller in target heating user's neighboring user is stated, the second controller is communicated to connect with first controller；It is described Second controller is used to transmit adjacent heating user heating load to first controller, based on adjacent heating user heat supply gauge Calculate it is adjacent between Heat Transfer Data so that first controller be based on it is described it is adjacent between Heat Transfer Data, outdoor weather data and described Dynamic space heating load described in the heating target prediction of target heating user, wherein, Heat Transfer Data is the target between the neighbour Heat Transfer Data between heating user heating user adjacent thereto.

Further, fuzzy controller or PID controller are embedded in the control chip of first controller；It is described Fuzzy controller or the PID controller are used for based on the dynamic space heating load and the generation of heating load data to target valve The control signal that door is controlled.

Further, the sensor includes：Temperature sensor, air velocity transducer, intensity of solar radiation sensor, In：The temperature sensor is used to acquire the outdoor temperature change information of target heating user's local environment；The wind speed Sensor is used to acquire the outdoor wind speed change information of target heating user's local environment；The intensity of solar radiation sensing Device is used to acquire the outdoor intensity of solar radiation change information of target heating user's local environment.

Further, first controller by wired or wireless connection mode respectively with the sensor, institute Calorimeter is stated with the target valve to be connected.

Further, when the connection mode be wired connection mode when, first controller by M-Bus buses with The calorimeter is connected；First controller is connected by 485 buses with the sensor, alternatively, passing through analog quantity Signal wire is connected with the sensor, and first controller is connected by 485 buses with the target valve, alternatively, It is connected by analog signals line with the target valve.

Further, when the connection mode is radio connection, first controller passes through following at least one Kind mode is connected respectively with the sensor, the calorimeter and the target valve：GPRS, 3G network, 4G networks, 5G nets Network, WIFI network are connected with internet.

Further, the calorimeter is respectively used to detect the temperature of return pipe and feed pipe in the heating system, water Flow obtains return water temperature, supply water temperature and water flow successively, wherein, the return water temperature, the supply water temperature and the water Flow is used to determine the heating load data.

Further, the target valve includes following any：The electrically operated valve that aperture can continuously adjust, Neng Goulian The continuous electromagnetic valve for carrying out break-make control can be carried out continuously the electric heating valve of break-make control, by mechanical device drive from Power formula control valve.

The third aspect, an embodiment of the present invention provides it is a kind of based on building load prediction heating plant, including：Prediction is single Member, for the outdoor weather data prediction dynamic space heating load based on the target heating user's local environment got, wherein, The dynamic space heating load is the heat demand of the target heating user predicted；Generation unit, it is described for being based on The control signal that dynamic space heating load and the generation of heating load data control target valve, wherein, the control signal Middle carrying opening information and/or make-and-break time information, the target valve are the heating water flow to the target heating user The valve controlled；Transmitting element, for sending the control signal to the target valve, so that the target valve is pressed Corresponding action is performed according to the control signal.

Further, described device further includes：Acquiring unit, for obtaining the heating target of the target heating user； Predicting unit is used for：Outdoor weather data and the target heating user based on the target heating user's local environment got Heating target prediction dynamic space heating load.

Further, the predicting unit is additionally operable to：Target nerve network is transferred, the target nerve network is instruction in advance Practice the neural network completed；Using the outdoor weather data and it is described heating target as the target nerve network input, So that the target nerve network handles the outdoor weather data and the heating target, and export the dynamic and supply Warm heat load.

Further, the network structure for the target nerve network being arranged in the heating plant is expressed as following public affairs Formula：Wherein, i=1,2 ..., n, n are the input number of nodes of the target nerve network；J=1,2 ..., M, m are the node in hidden layer of the target nerve network；x_iNeuron for i-th of input layer in the target nerve network Nodal value；y_j,inFor the input value of j-th of hidden layer neuron node in the target nerve network, y_j,outFor target god Output valve through j-th of hidden layer neuron node in network；w_i,jFor i-th of input layer god in the target nerve network Through first node to the calculating weight of j-th of hidden layer neuron node；u_jFor j-th of hidden layer god in the target nerve network Calculating weight through first node to output layer neuron node；Q_inAnd Q_outBe respectively output layer neuron node input value and Output valve, wherein, the output valve is the dynamic space heating load of prediction.

Further, generation unit is used for：The dynamic space heating load and the heating load data are compared, with Determine the deviation between the dynamic space heating load and the heating load data；It is calculated by pid algorithm or fuzzy control Method handles the deviation, to obtain the opening information and the make-and-break time information；Based on the opening information The control signal controlled with make-and-break time information generation target valve.

Further, generation unit is additionally operable to：The deviation is handled by the calculation formula of pid algorithm, with Obtain the opening information and the make-and-break time information：

Wherein, V is the target valve Opening information；K is rate mu-factor；Q_pFor the dynamic space heating load predicted；Q_mThe confession measured for calorimeter Thermal data；T_IFor the time of integration；T_DFor derivative time；τ is the time.

Further, generation unit is additionally operable to：By the calculation formula of FUZZY ALGORITHMS FOR CONTROL to the deviation at Reason, to obtain the opening information and the make-and-break time information：

Wherein, V is the make-and-break time information；Q_pFor the institute predicted State dynamic space heating load；Q_mThe heating load data measured for calorimeter；τ is the time, and fuzzy is ambiguity function.

Further, which is additionally operable to：Before target nerve network is transferred, the target nerve network is instructed Practice, to determine the weight coefficient in the target nerve network between each neuron node, specifically include：Pass through iterative formula The target nerve network is iterated training, and to determine the weight coefficient, the iterative formula isWherein, i=1,2 ..., n, n are the input number of nodes of the target nerve network；J=1,2 ..., M, m are the node in hidden layer of the target nerve network；x_iFor i-th of input layer section in the target nerve network Point value；y_j,outDefeated output valve for j-th of hidden layer neuron node in the target nerve network；WithRespectively institute J-th of hidden layer neuron node is stated to the calculating weight of output layer neuron node in n-th and the N+1 times repetitive exercise Value；WithIt is calculating power of i-th of input layer node to j-th of hidden layer neuron node respectively Focus on n-th and the value of the N+1 times repetitive exercise；η is iteration efficiency factor；δ is the output of the output layer neuron node The departure function of value and desired value is to the partial derivative of output layer node weights.

Fourth aspect, an embodiment of the present invention provides a kind of meters of non-volatile program code that can perform with processor Calculation machine readable medium, said program code make the processor perform method described above.

In embodiments of the present invention, first, based on the outdoor weather data of target heating user's local environment got Predict dynamic space heating load, wherein, the dynamic space heating load is that the heat supply of the target heating user predicted needs It asks；Then, the control signal controlled based on the dynamic space heating load and the generation of heating load data target valve, In, opening information and/or make-and-break time information are carried in the control signal, the target valve is that the target heating is used The valve that the heating water flow at family is controlled；Finally, the control signal is sent to the target valve, so that the target Valve performs corresponding action according to the control signal.In embodiments of the present invention, pass through load prediction and the survey of calorimeter Amount data can realize the accurate heat supply on demand of point family, meet the different room temperature demands of different heat supply users, can also avoid being subcooled The problem of overheat, so as to improve comfort level, to avoid heat supply energy waste, and then solves existing room temperature thermometric erection of equipment Position difference causes thermometric offset issue and user that can meet to different user temperature measuring equipment interference problem and heat supply company Different room temperature demands realize the technical issues of heating according to need.

Other features and advantages of the present invention will illustrate in the following description, also, partly become from specification It obtains it is clear that being understood by implementing the present invention.The purpose of the present invention and other advantages are in specification, claims And specifically noted structure is realized and is obtained in attached drawing.

For the above objects, features and advantages of the present invention is enable to be clearer and more comprehensible, preferred embodiment cited below particularly, and coordinate Appended attached drawing, is described in detail below.

Description of the drawings

It, below will be to specific in order to illustrate more clearly of the specific embodiment of the invention or technical solution of the prior art Embodiment or attached drawing needed to be used in the description of the prior art are briefly described, it should be apparent that, in being described below Attached drawing is some embodiments of the present invention, for those of ordinary skill in the art, before not making the creative labor It puts, can also be obtained according to these attached drawings other attached drawings.

Fig. 1 is a kind of schematic diagram of heating system based on building heating load prediction according to embodiments of the present invention；

Fig. 2 is the schematic diagram of another heating system based on building heating load prediction according to embodiments of the present invention；

Fig. 3 is a kind of flow chart of heat supply method based on building heating load prediction according to embodiments of the present invention；

A kind of structure diagram of neural network according to embodiments of the present invention Fig. 4；

Fig. 5 is a kind of schematic diagram of heating plant based on building heating load prediction according to embodiments of the present invention.

Specific embodiment

Purpose, technical scheme and advantage to make the embodiment of the present invention are clearer, below in conjunction with attached drawing to the present invention Technical solution be clearly and completely described, it is clear that described embodiment be part of the embodiment of the present invention rather than Whole embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not making creative work premise Lower all other embodiments obtained, shall fall within the protection scope of the present invention.

Embodiment one：

According to embodiments of the present invention, a kind of embodiment of the heating system based on building heating load prediction is provided.

Fig. 1 is a kind of schematic diagram of heating system predicted based on building load according to embodiments of the present invention, such as Fig. 1 institutes Show, which includes：First controller 100, sensor 200, calorimeter 300 and target valve 400, the target valve 400 The valve controlled for the heating water flow to the target heating user.

Specifically, the sensor is used to acquire the outdoor weather data of target heating user's local environment；

The calorimeter is used to acquire the heating load data of target heating user；

In the present embodiment, if being already installed with calorimeter in existing heating system, the heat can be established Communication connection between table and the first controller, so as to read the thermal data that the calorimeter detects.If in existing confession Calorimeter is fitted without in hot systems, then calorimeter can be separately provided in existing heating system, and establish the calorimeter With the communication connection between the first controller, so as to read the thermal data that the calorimeter detects.

First controller is used for based on the outdoor weather data prediction dynamic space heating load, and based on described dynamic The control signal that state space heating load and the generation of heating load data control target valve, wherein, the dynamic supplies warm heat Load is the heat demand of the target heating user predicted；Opening information and/or break-make are carried in the control signal Temporal information (for example, make-and-break time ratio)；

The target valve is used to perform corresponding action according to the control signal, to adjust the target heating user Heating water flow.

Specifically, in embodiments of the present invention, controller is properly termed as heating intelligent controller again, and target valve again can be with Referred to as heat water control valve, and sensor is properly termed as outdoor weather data pick-up again.Wherein, controller can be cloud service Center (alternatively, master system) replaces；Controller can also be and cloud service center (alternatively, master system) communication link The controller connect, at this point, controller can upload local data or be received to cloud service center (alternatively, master system) Data or instruction from cloud service center (alternatively, master system).

Brain of the controller 100 as heating system, for reading the room that sensor 200 (outdoor weather sensor) measures Outer meteorological data, and dynamic space heating load is predicted by intelligent algorithm；Controller 100 is additionally operable to read calorimeter 300 The heating load data measured, to be generated according to heating load data and dynamic space heating load for the opening information to target valve Or the signal that break-make is controlled.

The execution node that target valve 400 is adjusted as heating load heats water flow to adjust heating load by change.Tool Body, target valve 400 for example receives the control signal (for example, voltage control signal) exported from controller 100, by valve Adjust the corresponding aperture of the ratio between voltage value and full gate voltage value.

Sensor 200, as the sensing node of heating system, for measuring one or more outdoor weather data, including But it is not limited to：Gas epidemic disaster, intensity of solar radiation, wind speed, air pressure.Specifically, sensor 200 can be by wire communication side Outside air temperature measured value is sent to controller 100 by formula.

Heating field main target is to solve to balance heat supply at present, that is, solves the consistent of indoor temperature between each user Property, which can not meet individual demand of the user to indoor temperature.In embodiments of the present invention, which uses The concept of Dynamic Load Forecasting, can accurately predict indoor different demands according to different user workload demand, and by heat It is detected as sensor and compares thermic load, so as to fulfill accurate control.

It, can device for installing and adjusting, heating user can be in the interior of heating user in traditional temperature control mode Indoor temperature is manually adjusted by the regulating device.But in embodiments of the present invention, it is adjusted manually without user Temperature by the controller can be realized as that the indoor temperature of heating user is adjusted automatically.

In an optional embodiment, heating user can pre-set expectation heat supply temperature, that is, for thermal target.

At this point, above-mentioned first controller can just obtain the heating target of the target heating user, and based on the room Outer meteorological data and the heating target prediction dynamic space heating load.

Optionally, if first controller is cloud service center, then the heating target is advance for target heating user It sets, and is stored in cloud service center.If first controller is mounted on the controller of hotlist well, at this point, can With in the harvester of one heating target of indoor location of target heating user, which communicates to connect with controller. It should be noted that target heating user can adjust heating target according to different temperature requirements in the harvester.For example, In three nine-day periods after the winter solstice weather, after outdoor weather data and heating target prediction dynamic space heating load, warm heat is dynamically supplied by this The temperature that load carries out after heat supply target heating user is not ideal temperature.At this point, target heating user can be at this Interior adjusts heating target by the harvester, at this point, harvester is by the heating object transmission to controller, so that control Device predicts dynamic space heating load again according to the heating target newly got, and to realize, more accurately temperature controls, so as to The energy can more be saved.For example, when being heated by the dynamic space heating load predicted to target heating user, temperature is 20 degree, but in fact, the required temperature of target heating user is 18 degree, at this point, target heating user can be adopted by this Acquisition means reduce heating target, and are transmitted in controller, so that controller is based on the heating target and carries out prediction dynamic again Space heating load.By aforesaid operations, energy can be further saved during user individual heating demand is met Source.

It should be noted that in embodiments of the present invention, heating target is input to target nerve net as input data When being predicted in network, the personalized heating demands of different user can be realized.That is, the different user of heating target it Between dynamic space heating load be different.

In embodiments of the present invention, controller or cloud service center can be according to outdoor outdoor weather data and heating mesh Mark predicts dynamic space heating load, and the operation Jing Guo control algolithm, the aperture or break-make of output heating Water flow control valve Time than control signal.

Optionally, the target nerve network that training is completed in advance is embedded in the control chip of first controller；Its In, the target nerve network is used for pre- based on the outdoor weather data and the heating target prediction dynamic space heating load Survey dynamic space heating load.

As shown in Figure 1, in embodiments of the present invention, heating system further includes：Second controller 500, wherein, described second Controller 500 is mounted on and the controller in target heating user's neighboring user, the second controller and described first Controller communicates to connect.

In an optional embodiment, the second controller is used to transmit adjacent heating use to first controller The heating load at family, based on Heat Transfer Data between adjacent heating user heating load calculating neighbour, so that first controller is based on described It is dynamically born described in the heating target prediction of Heat Transfer Data between neighbour, the outdoor weather data and the target heating user for warm heat Lotus, wherein, the Heat Transfer Data between the neighbour between the Heat Transfer Data heating user adjacent thereto for the target heating user.

In an optional embodiment, be embedded in the control chip of first controller fuzzy controller or PID controller.

Wherein, the fuzzy controller or the PID controller are used for based on the dynamic space heating load and heat supply The control signal that amount data generation controls target valve.

It should be noted that controller uses the intelligent algorithms such as proportional integral differential (PID) controller, fuzzy controller, According to the heating load data that the dynamic space heating load and calorimeter of prediction measure, the opening information of required target valve is calculated Or make-and-break time information (for example, make-and-break time ratio).

In an optional embodiment, the sensor includes：Temperature sensor, air velocity transducer, solar radiation are strong Spend sensor.

The temperature sensor is used to acquire the outdoor temperature change information of target heating user's local environment；

The air velocity transducer is used to acquire the outdoor wind speed change information of target heating user's local environment；

The intensity of solar radiation sensor is used to acquire the outdoor solar radiation of target heating user's local environment Strength Changes information.

In embodiments of the present invention, temperature sensor, air velocity transducer and intensity of solar radiation sensor are to be mounted on Outdoor sensor, to detect the outdoor temperature change information of target heating user's local environment, ring residing for target heating user The environment weathers such as the outdoor wind speed change information in border, the outdoor intensity of solar radiation change information of target heating user's local environment Information.

It should be noted that in embodiments of the present invention, selected sensor is outdoor sensor, with sensing chamber outside Environment temperature rather than be that interior sensor measurement error, artificial damage etc. can be avoided to lead with the reason of indoor sensor The control deviation of cause, and the cost of investment and operation maintenance cost of sensor can be exempted.

In an optional embodiment, the sensor of outdoor weather data is non-required, and outdoor weather data may be used also To be obtained from cloud service center (master system).

In embodiments of the present invention, as shown in Fig. 2, intelligent heating controller (that is, first controller) can be arranged on heat In table well, which may be replaced by cloud service center (or host computer).In heat Calorimeter in table well is by the water temperature sensor and flowmeter that are set in return pipe, the water temperature sensor structure set in feed pipe Into.The calorimeter is connected respectively with the water temperature sensor and flowmeter set on return pipe, to acquire the temperature of return pipe, obtains To return water temperature and acquire the flow information of the flowmeter.The calorimeter is also connected with the water temperature sensor on feed pipe It connects, with the temperature of feed pipe, obtains supply water temperature.As shown in Fig. 2, target valve (that is, heating water control valve in Fig. 2) It is arranged on feed pipe.As shown in Fig. 2, sensor (that is, outdoor weather data pick-up) is arranged on target heating user institute In the outdoor environment at place, with meteorological data outside collection room.

First controller by wired or wireless connection mode respectively with the sensor, the calorimeter and described Target valve is connected.

Wherein, when the connection mode is wired connection mode, as shown in Fig. 2, first controller passes through M-Bus Bus is connected with the calorimeter；First controller is by 485 buses, alternatively, analog signals line and the sensing Device is connected, and first controller is by 485 buses, alternatively, analog signals line and the target valve are (that is, heating water Control valve) it is connected.

When the connection mode is radio connection, first controller is (that is, cloud service center or upper Machine) it is connected respectively with the sensor, the calorimeter and the target valve by way of following at least one：GPRS, 3G network, 4G networks, 5G networks, WIFI network are connected with internet.

In embodiments of the present invention, the target valve includes following any：The motor-driven valve that aperture can continuously adjust Door can be carried out continuously the electromagnetic valve of break-make control, can be carried out continuously the electric heating valve of break-make control, pass through mechanical device The self force type control valve door of driving.

By foregoing description it is found that in embodiments of the present invention, the heating system is by the first controller (that is, intelligent heating Controller), target valve (that is, heating water control valve), sensor form, pass through meteorological data prediction dynamic outside measuring chamber and supply Warm heat load has the heating load data that calorimeter measures by reading and compared with predicting thermic load, adjusts supply user's The size of heat reaches the target of prediction thermic load, realizes the utilization to calorimeter slack resources, meets different Indoor Temperatures The demand of degree avoids supercooling overheat, improves that thermal comfort is horizontal, avoids waste for heat energy.

Embodiment two：

According to embodiments of the present invention, a kind of embodiment for the heat supply method predicted based on building load is provided, is needed Bright, step shown in the flowchart of the accompanying drawings can be held in the computer system of such as a group of computer-executable instructions Row, although also, show logical order in flow charts, it in some cases, can be to be different from sequence herein Perform shown or described step.

Fig. 3 is a kind of flow chart of heat supply method based on building heating load prediction according to embodiments of the present invention, such as Shown in Fig. 3, this method comprises the following steps：

Step S302, the outdoor weather data prediction dynamic based on the target heating user's local environment got supply warm heat Load, wherein, the dynamic space heating load is the heat demand of the target heating user predicted；

The outdoor weather data include at least one of：Outdoor temperature change information, outdoor wind speed change information, room Outer intensity of solar radiation change information；The heating target is target heating user purpose temperature to be achieved.

Step S304 is generated based on the actually detected heating load data of the dynamic space heating load and heat meter to mesh The control signal that mark valve is controlled, wherein, carry opening information and/or make-and-break time information, institute in the control signal It is the valve controlled the heating water flow of the target heating user to state target valve；

Step S306 sends the control signal, so that the target valve is according to the control to the target valve Signal performs corresponding action.

In embodiments of the present invention, above-mentioned steps S302 to step S306 can pass through the controller in above-described embodiment (alternatively, cloud service center) performs.

In an optional embodiment, the method further includes：Obtain the heating target of the target heating user；

Outdoor weather data prediction dynamic space heating load based on the target heating user's local environment got includes： The heating target of outdoor weather data and the target heating user based on the target heating user's local environment got is pre- Survey dynamic space heating load.

In embodiments of the present invention, controller can also obtain the heating target of target heating user, that is, target heating The indoor temperature reached desired by user.Then, outdoor weather data of the controller based on target heating user's local environment With the heating target prediction dynamic space heating load of target heating user.

In embodiments of the present invention, controller is also based on the target heating user's architectural exterior-protecting construction shape got Heat transfer conditions, instant out door climatic parameter and heating target (that is, indoor temperature that user needs) prediction dynamic heating between condition, neighbour Thermic load.

By foregoing description it is found that in one embodiment, the cell building A for A areas and the cell for B areas Building B.Controller mounted on A areas can acquire the outdoor weather data of cell building A local environments, then, based on the outdoor The dynamic space heating load of meteorological data prediction cell building A；And the controller mounted on B areas can acquire cell building B institutes Locate the outdoor weather data of environment, then, the dynamic space heating load based on outdoor weather data prediction cell building B.Herein In the case of, the dynamic space heating load of each heating user may be identical (or being not much different) in cell building A, at this point, It can determine to be not much different for each heating user heating load.But the dynamic space heating load of cell building A and cell building B It is different, has different for the cell building A and cell building B heats supplied at this time.It by the above-mentioned means, can be real The personalized heating demands of existing different regions, while a large amount of energy can also be saved.

Further, for heating user each in cell building A, for example, heating user A1 and heating user A2, also has not Same heating demands.At this point, controller just can be according to the heating target and outdoor weather data of each heating user to each Heating user in predicting dynamic space heating load, to realize the personalized heating demands of different heating users.For example, heating user A1 Same cell building is in heating user A2, wherein, the heating target of heating user A1 is 22 degree, the heating of heating user A2 Target is 20 degree.At this point, the controller of heating user A1 can according to residing for the heating target of heating user A1 and cell building A ring The meteorologic parameter in border predicts dynamic space heating load for heating user A1；The controller of heating user A2 can be according to heating user The heating target of A2 and the meteorologic parameter of cell building A local environments predict dynamic space heating load for heating user A2.By upper Processing mode is stated, disclosure satisfy that in same cell building, the temperature between different user is different, so as to meet The heating demands of different user, additionally it is possible to further save the energy.

In an optional embodiment, outdoor weather data based on the target heating user's local environment got and The heating target prediction dynamic space heating load of the target heating user includes the following steps：

First, target nerve network is transferred, wherein, neural network of the target nerve network for training completion in advance；

Then, using the outdoor weather data and the input of the target as the target nerve network that heat, so that The target nerve network handles the outdoor weather data and the heating target, and exports the dynamic for warm heat Load.

In embodiments of the present invention, after outdoor weather data and heating target are got, controller can be transferred Target nerve network.Then using outdoor weather data and it is described heating target as target nerve network input so that the mesh Mark neural network handles, and export dynamic space heating load outdoor weather data and the heating target, to realize not With the personalized heat demand between user.

Optionally, the target nerve network is expressed as the following formula：

Wherein, i=1,2 ..., n, n are the input number of nodes of the target nerve network；J=1,2 ..., m, m are described The node in hidden layer of target nerve network；x_iNeuron node value for i-th of input layer in the target nerve network；y_j, Input values of the in for j-th of hidden layer neuron node in the target nerve network, y_j,outFor in the target nerve network The output valve of j-th of hidden layer neuron node；w_i,jFor i-th of input layer node in the target nerve network To the calculating weight of j-th of hidden layer neuron node；u_jFor j-th of hidden layer neuron node in the target nerve network To the calculating weight of output layer neuron node；Q_inAnd Q_outIt is the input value and output valve of output layer neuron node respectively, In, the output valve is the dynamic space heating load of prediction.

After dynamic space heating load is obtained, it is possible to based on dynamic space heating load and the generation of heating load data to mesh The control signal that mark valve is controlled.

Optionally, step S104 carries out target valve based on the dynamic space heating load and the generation of heating load data The control signal of control includes the following steps：

Step S1041 compares the dynamic space heating load and the heating load data, to determine the dynamic Deviation between space heating load and the heating load data；

Step S1042 is handled the deviation by pid algorithm or FUZZY ALGORITHMS FOR CONTROL, described to obtain Opening information and the make-and-break time information；

Step S1043 controls target valve based on the opening information and make-and-break time information generation Control signal.

In embodiments of the present invention, controller is after dynamic space heating load is got, and controller supplies dynamic first Warm heat load is compared with the heating load data got from confession hotlist, and then, determine dynamic for warm heat according to comparing result Deviation between load and the heating load data.Next, pid algorithm or FUZZY ALGORITHMS FOR CONTROL carry out the deviation Processing, processing obtain opening information and make-and-break time information (for example, make-and-break time ratio).Finally, based on the opening information and logical The control signal that disconnected temporal information generation controls target valve.

After generation controls signal, it is possible to target valve is sent control signals to, so that the target valve (that is, Water flow control valve) the control signal that provides of controller is obtained, valve opening is adjusted to required aperture or by valve break-make State is adjusted to required state.

Optionally, the deviation is handled by pid algorithm, during obtaining the opening information and the break-make Between information include：

The deviation is handled by the calculation formula of pid algorithm, to obtain the opening information and described logical Disconnected temporal information：

Optionally, the deviation is handled by FUZZY ALGORITHMS FOR CONTROL, to obtain the opening information and described Make-and-break time information includes：

The deviation is handled by the calculation formula of FUZZY ALGORITHMS FOR CONTROL, to obtain the opening information and institute State make-and-break time information：

In embodiments of the present invention, before target nerve network is transferred, the method further includes：To the target nerve Network is trained, and to determine the weight coefficient in the target nerve network between each neuron node, is specifically included：

Training is iterated by target nerve network described in iterative formula, to determine the weight coefficient, the iteration Formula is

Wherein, i=1,2 ..., n, n are the input number of nodes of the target nerve network；J=1,2 ..., m, m are described The node in hidden layer of target nerve network；x_iFor i-th of input layer nodal value in the target nerve network；y_j,out Defeated output valve for j-th of hidden layer neuron node in the target nerve network；WithRespectively described j-th hidden Neuron node containing layer to output layer neuron node calculating weight in n-th and the value of the N+1 times repetitive exercise；WithI-th of input layer node respectively to j-th of hidden layer neuron node calculating weight in N Secondary and the N+1 times repetitive exercise value；η is iteration efficiency factor；δ is output valve and the expectation of the output layer neuron node The departure function of value is to the partial derivative of output layer node weights.

It is the structure diagram of neural network as shown in Figure 4.In embodiments of the present invention, it is used in the controller Before, by pre-debug data, target nerve network is trained, is determined in target nerve network between each neuron node Weight coefficient.For example, target nerve network shown in Fig. 4 includes the hidden layer of 401, two nodes of input layer of six nodes 402 and the output layer 403 of a node.Six input layers can include outside air temperature, intensity of solar radiation, last moment Heating load, indoor target temperature, the heating load at adjacent family and wind pressure (or hot pressing etc.).Before target nerve network training, The random initial value for providing node weights, then using the neuroid with initial weight, using formula (1) heat load calculation Predicted value, and compared with heating load data, obtain deviation δ；Then, calculating, more new node are iterated using formula (4) The numerical value of weight until the prediction total deviation value of target nerve network meets preset required precision, then completes target nerve net The training of network.

In an optional embodiment, this method further includes：Heat Transfer Data between acquisition is adjacent, wherein, it conducts heat between the neighbour Heat Transfer Data between the data heating user adjacent thereto for the target heating user；It is used based on the target heating got The heating target prediction dynamic space heating load of the outdoor weather data of family local environment and the target heating user further include： Based on Heat Transfer Data between the neighbour, dynamic described in the heating target prediction of the outdoor weather data and the target heating user Space heating load.

In embodiments of the present invention, controller can also obtain the biography between the heating user adjacent with target heating user Dsc data；Then, based on Heat Transfer Data between neighbour, dynamic described in the heating target prediction of outdoor weather data and target heating user Space heating load.

Optionally, controller can also be by Heat Transfer Data between neighbour, the heating mesh of outdoor weather data and target heating user The input for above-mentioned target nerve network is denoted as, so that target nerve network Heat Transfer Data between neighbour, outdoor weather data and mesh The heating target of mark heating user is predicted, obtains dynamic space heating load.

In conclusion in embodiments of the present invention, it is pre- to target heating user that controller can be based on outdoor weather data Survey dynamic space heating load；The heating target prediction target heating for being also based on outdoor weather data and target heating user is used Predict dynamic space heating load in family；It is also based on Heat Transfer Data between neighbour, the heating of outdoor weather data and target heating user Target prediction target heating user in predicting dynamic space heating load.That is, Heat Transfer Data between neighbour, outdoor weather can be passed through At least one of data and the heating target of target heating user predict dynamic space heating load, to ensure different user Different demands meet plurality of application scenes.

To sum up, the embodiment of the present invention proposes a kind of heat supply method predicted based on building load, and this method is based on building Load prediction and calorimeter data carry out point family and precisely supply thermal control.This method is joined using neural network method by outdoor weather Number, indoor target temperature prediction dynamic space heating load；Have heating load data and the pre- calorimetric that calorimeter measures by reading Load compares, and the methods of by pid algorithm or fuzzy algorithmic approach, calculates the aperture or make-and-break time ratio of heating water regulating valve, Water is heated to adjust the thermic load that the size of the heat of supply user reaches prediction by change, realizes and leaves unused to calorimeter The utilization of resource, the demand for meeting different indoor temperatures avoid supercooling overheat, improve thermal comfort level, avoid confession The waste of heat energy.

The above method is introduced with a specific embodiment below.

Table 1

As shown in table 1 below is to be provided in the affordable housings of XXXXX armies (10X hospitals) using the embodiment of the present invention Method and system carry out heat supply when supply dsc data.In table 1, the heat supplies of 2013~2014 annual affordable housings be by Estate management, the heat supply in 2014~2015 years and 2015~2016 annual affordable housings is using institute of the embodiment of the present invention The method and system of offer is realized.That is, 2013~2014 years were not implemented using the present invention for dsc data For dsc data obtained by the method and system that example is provided；, supplied dsc data with 2015~2016 years in 2014~2015 years Dsc data is supplied for what is obtained using the method and system that the embodiment of the present invention is provided.As shown in table 1, heat supply data include heating Area, actual energy consumption, wherein, heating area includes mating construction area and heating building area；Actual energy consumption includes heating rate, Real heating duration, practical year heating load, entire warm season heating load and entire warm season power supply volume.By the table it is found that 2013 The heating area in~2014 years, 2014~2015 years and 2015~2016 years, heating rate and heating number of days are all year by year The trend of growth.But practical year heating load, entire warm season heating load and entire warm season power supply volume decline year by year. By being analyzed the data in table 1 it is found that adjusting point family flow using technology of the present invention, heat amount of energy saving is about 24%, power consumption about saves 60%.It, can be with by the measurement data of load prediction and calorimeter that is, in embodiments of the present invention Realization divides family accurate heat supply on demand, meets the different room temperature demands of different heat supply users, can also avoid the problem that supercooling overheat, So as to improve comfort level, to avoid heat supply energy waste, and then it can not be in the prior art dynamically heating user to alleviate The technical issues of carrying out indoor temperature adjusting.

Embodiment three：

The embodiment of the present invention additionally provides a kind of heating plant predicted based on building load, should be predicted based on building load Heating plant be mainly used for performing the heat supply method predicted based on building load that is provided of the above of the embodiment of the present invention, Specific introduction is done to the heating plant provided in an embodiment of the present invention based on building load prediction below.

Fig. 5 is a kind of schematic diagram of heating plant predicted based on building load according to embodiments of the present invention, such as Fig. 5 institutes Show, should predicting unit 10, generation unit 20 and transmitting element 30 mainly be included based on the heating plant that building load is predicted, In：

Predicting unit 10, for the outdoor weather data prediction dynamic based on the target heating user's local environment got Space heating load, wherein, the dynamic space heating load is the heat demand of the target heating user predicted；

Generation unit 20, for based on the actually detected heating load data life of the dynamic space heating load and heat meter The control signal that pairs of target valve is controlled, wherein, opening information and/or make-and-break time letter are carried in the control signal Breath, the target valve is the valve controlled the heating water flow of the target heating user；

Transmitting element 30, for sending the control signal to the target valve, so that the target valve is according to institute It states control signal and performs corresponding action.

In addition, in the description of the embodiment of the present invention unless specifically defined or limited otherwise, term " installation ", " phase Even ", " connection " should be interpreted broadly, for example, it may be being fixedly connected or being detachably connected or be integrally connected；It can To be mechanical connection or be electrically connected；It can be directly connected, can also be indirectly connected by intermediary, Ke Yishi Connection inside two elements.For the ordinary skill in the art, above-mentioned term can be understood at this with concrete condition Concrete meaning in invention.

In the description of the present invention, it should be noted that term " " center ", " on ", " under ", "left", "right", " vertical ", The orientation or position relationship of the instructions such as " level ", " interior ", " outer " be based on orientation shown in the drawings or position relationship, merely to Convenient for the description present invention and simplify description rather than instruction or imply signified device or element must have specific orientation, With specific azimuth configuration and operation, therefore it is not considered as limiting the invention.In addition, term " first ", " second ", " third " is only used for description purpose, and it is not intended that instruction or hint relative importance.

A kind of heat supply method predicted based on building load that the embodiment of the present invention is provided, the computer of device and system Program product, the computer readable storage medium of non-volatile program code that can perform including storing processor, the journey The instruction that sequence code includes can be used for performing the method described in previous methods embodiment, and specific implementation can be found in method and implement Example, details are not described herein.

It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description, The specific work process of device and unit can refer to the corresponding process in preceding method embodiment, and details are not described herein.

In several embodiments provided herein, it should be understood that disclosed systems, devices and methods, it can be with It realizes by another way.The apparatus embodiments described above are merely exemplary, for example, the division of the unit, Only a kind of division of logic function, can there is other dividing mode in actual implementation, in another example, multiple units or component can To combine or be desirably integrated into another system or some features can be ignored or does not perform.Another point, it is shown or beg for The mutual coupling, direct-coupling or communication connection of opinion can be by some communication interfaces, device or unit it is indirect Coupling or communication connection can be electrical, machinery or other forms.

The unit illustrated as separating component may or may not be physically separate, be shown as unit The component shown may or may not be physical unit, you can be located at a place or can also be distributed to multiple In network element.Some or all of unit therein can be selected according to the actual needs to realize the mesh of this embodiment scheme 's.

In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, it can also That each unit is individually physically present, can also two or more units integrate in a unit.

If the function is realized in the form of SFU software functional unit and is independent product sale or in use, can be with It is stored in the non-volatile computer read/write memory medium that a processor can perform.Based on such understanding, the present invention The part that substantially contributes in other words to the prior art of technical solution or the part of the technical solution can be with software The form of product embodies, which is stored in a storage medium, including some instructions use so that One computer equipment (can be personal computer, server or the network equipment etc.) performs each embodiment institute of the present invention State all or part of step of method.And aforementioned storage medium includes：USB flash disk, mobile hard disk, read-only memory (ROM, Read- Only Memory), random access memory (RAM, Random Access Memory), magnetic disc or CD etc. are various can be with Store the medium of program code.

Finally it should be noted that：Embodiment described above, only specific embodiment of the invention, to illustrate the present invention Technical solution, rather than its limitations, protection scope of the present invention is not limited thereto, although with reference to the foregoing embodiments to this hair It is bright to be described in detail, it will be understood by those of ordinary skill in the art that：Any one skilled in the art In the technical scope disclosed by the present invention, it can still modify to the technical solution recorded in previous embodiment or can be light It is readily conceivable that variation or equivalent replacement is carried out to which part technical characteristic；And these modifications, variation or replacement, do not make The essence of corresponding technical solution is detached from the spirit and scope of technical solution of the embodiment of the present invention, should all cover the protection in the present invention Within the scope of.Therefore, protection scope of the present invention described should be subject to the protection scope in claims.

Claims

1. a kind of heat supply method based on building heating load prediction, which is characterized in that including：

Based on the outdoor weather data prediction dynamic space heating load of the target heating user's local environment got, wherein, institute It is the heat demand of the target heating user predicted to state dynamic space heating load；

Target valve is controlled based on the actually detected heating load data generation of the dynamic space heating load and heat meter The control signal of system, wherein, it carries opening information in the control signal and/or make-and-break time information, the target valve is The valve controlled the heating water flow of the target heating user；

The control signal is sent to the target valve, so that the target valve performs accordingly according to the control signal Action.

2. heat supply method according to claim 1, which is characterized in that

The method further includes：Obtain the heating target of the target heating user；

Outdoor weather data prediction dynamic space heating load based on the target heating user's local environment got includes：It is based on The outdoor weather data of target heating user's local environment and the heating target prediction of the target heating user got are moved State space heating load.

3. heat supply method according to claim 2, which is characterized in that based on the target heating user's local environment got Outdoor weather data and the heating target prediction dynamic space heating load of the target heating user include：

Transfer target nerve network, neural network of the target nerve network for training completion in advance；

Using the outdoor weather data and it is described heating target as the target nerve network input so that the target is refreshing The outdoor weather data and the heating target are handled, and export the dynamic space heating load through network.

4. heat supply method according to claim 3, which is characterized in that the target nerve network is expressed as following public affairs Formula：

Wherein, i=1,2 ..., n, n are the input number of nodes of the target nerve network；J=1,2 ..., m, m are the target The node in hidden layer of neural network；x_iNeuron node value for i-th of input layer in the target nerve network；y_j,inFor The input value of j-th of hidden layer neuron node, y in the target nerve network_j,outIt is j-th in the target nerve network The output valve of hidden layer neuron node；w_i,jFor i-th of input layer node in the target nerve network to jth The calculating weight of a hidden layer neuron node；u_jIt is j-th of hidden layer neuron node in the target nerve network to defeated Go out the calculating weight of layer neuron node；Q_inAnd Q_outIt is the input value and output valve of output layer neuron node respectively, wherein, The output valve is the dynamic space heating load of prediction.

5. heat supply method according to claim 1, which is characterized in that based on the dynamic space heating load and heating load number The control signal controlled according to generation target valve includes：

The dynamic space heating load and the heating load data are compared, to determine the dynamic space heating load and institute State the deviation between heating load data；

The deviation is handled by pid algorithm or FUZZY ALGORITHMS FOR CONTROL, to obtain the opening information and described Make-and-break time information；

The control signal controlled based on the opening information and make-and-break time information generation the target valve.

6. heat supply method according to claim 5, which is characterized in that the deviation is handled by pid algorithm, Included with obtaining the opening information and the make-and-break time information：

The deviation is handled by the calculation formula of pid algorithm, during obtaining the opening information and the break-make Between information：

7. heat supply method according to claim 5, which is characterized in that carried out by FUZZY ALGORITHMS FOR CONTROL to the deviation Processing, is included with obtaining the opening information and the make-and-break time information：

The deviation is handled by the calculation formula of FUZZY ALGORITHMS FOR CONTROL, to obtain the opening information and described logical Disconnected temporal information：

Wherein, V is the make-and-break time information；K is rate mu-factor；Q_pFor the dynamic space heating load predicted；Q_m The heating load data measured for calorimeter；τ is the time, and fuzzy is ambiguity function.

8. heat supply method according to claim 3, which is characterized in that before target nerve network is transferred, the method It further includes：The target nerve network is trained, to determine in the target nerve network between each neuron node Weight coefficient, specifically include：

Training is iterated by target nerve network described in iterative formula, to determine the weight coefficient, the iterative formula For

Wherein, i=1,2 ..., n, n are the input number of nodes of the target nerve network；J=1,2 ..., m, m are the target The node in hidden layer of neural network；x_iFor i-th of input layer nodal value in the target nerve network；y_j,outFor institute State the defeated output valve of j-th of hidden layer neuron node in target nerve network；WithRespectively described j-th of hidden layer Neuron node to output layer neuron node calculating weight in n-th and the value of the N+1 times repetitive exercise；WithPoint Be not i-th of input layer node to j-th of hidden layer neuron node calculating weight in n-th and The value of N+1 repetitive exercise；η is iteration efficiency factor；δ be the output layer neuron node output valve and desired value it is inclined Difference function is to the partial derivative of output layer node weights.

9. heat supply method according to any one of claim 1 to 8, which is characterized in that the outdoor weather data include At least one of：Outdoor temperature change information, outdoor wind speed change information, outdoor intensity of solar radiation change information；It is described The target that heats is target heating user purpose temperature to be achieved.

10. a kind of heating system based on building heating load prediction, which is characterized in that including：First controller, sensor, Calorimeter and target valve, the target valve are the valve controlled the heating water flow of the target heating user；

The sensor is used to acquire the outdoor weather data of target heating user's local environment；

First controller is used for based on the outdoor weather data prediction dynamic space heating load, and is supplied based on the dynamic The control signal that warm heat load and the generation of heating load data control target valve, wherein, the dynamic space heating load For the heat demand of the target heating user predicted；Opening information and/or make-and-break time are carried in the control signal Information；

The target valve is used to perform corresponding action according to the control signal, to adjust the confession of the target heating user Warm water flow.