CN105910169B - District heating system regulating of heating net method and system based on mechanism model PREDICTIVE CONTROL - Google Patents
District heating system regulating of heating net method and system based on mechanism model PREDICTIVE CONTROL Download PDFInfo
- Publication number
- CN105910169B CN105910169B CN201610270475.1A CN201610270475A CN105910169B CN 105910169 B CN105910169 B CN 105910169B CN 201610270475 A CN201610270475 A CN 201610270475A CN 105910169 B CN105910169 B CN 105910169B
- Authority
- CN
- China
- Prior art keywords
- network
- prediction model
- heating
- flow
- formula
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D19/00—Details
- F24D19/10—Arrangement or mounting of control or safety devices
- F24D19/1006—Arrangement or mounting of control or safety devices for water heating systems
- F24D19/1009—Arrangement or mounting of control or safety devices for water heating systems for central heating
Abstract
The present invention relates to a kind of district heating system regulating of heating net method and system based on mechanism model PREDICTIVE CONTROL, this regulating of heating net method includes the following steps：Step S1, establishes prediction model；Step S2, using balanced heating as target, by prediction model predict obtain first-degree heating network in respectively pump, each valve regulation scheme；The present invention is using the prediction model of heat supply first-degree heating network as core, using sum in PREDICTIVE CONTROL acquisition first-degree heating network system in tens of accurate regulation schemes to hundreds of water pump and solenoid valve, heat supply network is adjusted in real time, solves the problems, such as that heating network control lag and heat user are uneven in temperature.
Description
Technical field
The present invention relates to the wisdom control techniques of district heating system, are supplied particular for the concentration based on Model Predictive Control
Hot systems first-degree heating network regulation technology.
Background technology
Under the background of China's energy production and consumption transition, the heat source condition of district heating system becomes more and more multiple
It is miscellaneous, there is the combination of the different forms such as cogeneration of heat and power factory, hot-water boiler, industrial exhaust heat, wind energy, underground heat.To support multi-source complementary operation,
The first-degree heating network of district heating system further to interconnection, the structural development of cyclization, meanwhile, be to reduce for valve between return pipe net
The restriction loss of door, and increase flexible adjustment, more use distributed variable frequency pump transmission ＆ distribution technology.Networking operation, reliability carry
But the difficulty of management and running is increased while high.China's heating system automation at present, intelligent level are also universal relatively low, pass
Hydraulic misadjustment problem is still serious under system regulative mode, and Load Distribution is unbalanced, and heat user satisfaction is low, and control is imitated with economical
The contradiction of benefit is becoming increasingly acute.
Since the heating network of large- and-medium size cities is a large-scale complicated thermal-hydraulic system, have non-linear, more
The characteristics of variable, strong coupling, high latency, the controlled plant during first-degree heating network traffic control include large number of frequency conversion
Pump, solenoid valve, traditional PID control method be easy to cause concussion for the system that coupling is strong, inertia is big, and then causes city
The hydraulic misadjustment of heating system.In recent years, model predictive control method due to can by design by the following rail of control variable
Mark carrys out the various situations of process control in simulation real world to greatest extent, and with preferable robustness and dynamic control
Effect has been widely used in fields such as oil refining, chemical industry, food processing, aviations, and this method is applied to domestic heating system
The control and regulation of system first-degree heating network have potential huge advantage.
Invention content
The object of the present invention is to provide a kind of regulating of heating net method and system, to solve regulating of heating net lag and pipe network water
The problem of power is lacked of proper care, heat user is uneven in temperature.
In order to solve the above technical problem, the present invention provides a kind of regulating of heating net methods, include the following steps：
Step S1, establishes prediction model；
Step S2 using balanced heating as target, is predicted by prediction model and is obtained the respectively adjusting of pump, each valve in first-degree heating network
Scheme.
Further, the step of establishing prediction model in the step S1 includes：Step S11, thermal hydraulic analysis solve；With
And step S12, prediction model correction.
Further, the method that thermal hydraulic analysis solves in the step S11 includes：
Pipe network is converted to the Directed Graph Model being made of node and section, i.e. pipe network figure by step S111；Wherein node table
Show there are the point that flow passes in and out, represented with set V, V=[V1,V2,…,Vn], in formula, n is the node number in pipe network；Section
It is the connection pipeline section between node, is represented with set E, E=[E1,E2,…,Em], m is sector number in formula, and digraph is expressed as G=<
V,E>；
The incidence matrix A of pipe network and fundamental circuit matrix B are obtained according to network graph theory, wherein A is n × m rank matrixes, B s
× m rank matrixes, s are fundamental circuit number s=m-n+1；
Step S112 calculates the characteristics resistance coefficient of pipe network；
Step S113 builds prediction model, i.e. hydraulic pipeline calculates mathematical model：
AGT=0；
BΔHT=0；
In formula, G is the row vector G=[G for recording each pipeline section inner volume flow in pipe network figure1,G2,…,Gm]；Δ H is record
The column vector of each pipeline section drag overall loss in pipe network figure, i.e. Δ H=S* | G | * G+Z-Hb；
In formula, S is the characteristics resistance coefficient matrix S=diag { S of each pipeline section in first-degree heating network1,S2,…,Sm}；
Equivalent absolute roughnesses of the K for tube wall, general K=0.0005m；D is internal diameter of the pipeline；l、ldRespectively pipe network calculates
The length of pipeline section and local resistance equivalent length；ρ is the averag density of hot water in pipe；
Z is the column vector Z=[Z of two node potential energy difference of pipeline section1,Z2,…,Zm]T；
HbFor the pump head column vector H in heat supply networkb=[Hb1,Hb2,…,Hbm]T；
Step S114, heat supply network thermal-hydraulic calculate, i.e.,
Hydraulic pipeline calculating mathematical model combination loop adjustment flow-rate adjustment algorithm through successive ignition is calculated, is obtained
The volume flow of hot water in each pipeline section.
Prediction model correction includes in the step S12：Prediction model is modified using heat supply network actual measurement operation data.
Further, it using balanced heating as target in the step S2, is predicted and is obtained in first-degree heating network respectively by prediction model
It pumps, the method for the regulation scheme of each valve includes the following steps：
Step S21 predicts the thermic load needed for each thermal substation using balanced heating as target obtaining should reach respectively
The primary side flow target value of thermal substation；
Step S22, using method of operation progress optimizing of the prediction model to pump, valve in first-degree heating network.
Further, the thermic load needed for each thermal substation is predicted using balanced heating as target in the step S21, obtained
Go out to reach the primary side flow target value of each thermal substation；I.e.
The target equation of primary side flow is：
(G in formula1r)iRepresent the primary side flow target value of i-th of thermal substation, s is the sum of thermal substation, and C is the ratio of water
Thermal capacitance, density of the ρ for hot water, ζiFor from radiator hot water to outdoor equivalent heat transfer factor, (K1F1)iRepresent i-th of thermal substation
The exchange capability of heat of middle heat exchanger, KconstRepresent quantitative；And
And
In ζi(K1F1)iFormula in, (G2)iRepresent thermal substation i secondary heat networks recirculated water volume flows, t2gRepresent two level heat
Net supply water temperature, t2hRepresent secondary heat networks return water temperature, t1gRepresent thermal substation first-degree heating network supply water temperature, t1hRepresent thermal substation
First-degree heating network return water temperature, twFor outdoor temperature, τ1-τ0≈ 3~5 days；
There is the total water supply flow G of first-degree heating network again1tEqual to the sum of each thermal substation primary side flow, i.e.,
G1tIt is known quantity for the total water supply flow of first-degree heating network.
By ζi、(K1F1)iSubstitute into (G1r)iCalculation formula (1), simultaneous formula (1), formula (2) solve KconstValue, Jin Ertong
It crosses formula (1) and obtains each thermal substation primary side flow target value.
Further, method of operation progress optimizing of the prediction model to pump, valve in first-degree heating network is used in the step S22,
Wherein the optimization aim of optimizing includes heat supply harmony target, and the first-degree heating network flow of each thermal substation heat exchanger is reached by distributing
(G1)iTo realize；
The object function of optimizing is
Wherein, Δ (G1)iDeviation for first-degree heating network flow and setting flow：
(G1)iFor the first-degree heating network flow rate calculation value of i-th of thermal substation of arrival simulated by prediction model；And
(Eb)jElectrical power for water pump consumption：
G is acceleration of gravity, (Gb)jTo pump the volume flow of hot water, (Hb)jFor pump head；(ηb)jEffect for water pump
Rate, subscript j represent water pump number；
In the calculation formula of respective objects function, Z be optimization overall target, NsFor thermal substation number, NbFor level-one heat
The number of net freq uency conversion supercharging pump, NvFor the number of first-degree heating network regulating valve, lkFor control valve opening, subscript k represents that regulating valve is compiled
Number, lminFor the minimum aperture that regulating valve allows, λG、λE、λlRespectively reach the first-degree heating network flow of each thermal substation, the electricity of water pump
The importance weight of consumption and valve opening.
Another aspect, the present invention also provides a kind of regulating of heating net system, including：
Prediction model establishes unit, and the regulating of heating net unit that unit is connected is established with the prediction model.
Further, the prediction model establishes unit and is adapted to set up prediction model, that is, includes：Thermal hydraulic analysis solves mould
Block and prediction model correction module.
Further, the thermal hydraulic analysis solves module, i.e.,
Pipe network is converted to the Directed Graph Model being made of node and section, i.e. pipe network figure；Wherein node represents there is stream
The point of disengaging is measured, is represented with set V, V=[V1,V2,…,Vn], in formula, n is the node number in pipe network；Section is between node
Connection pipeline section, represented with set E, E=[E1,E2,…,Em], m is sector number in formula, and digraph is expressed as G=<V,E>；
The incidence matrix A of pipe network and fundamental circuit matrix B are obtained according to network graph theory, wherein A is n × m rank matrixes, B s
× m rank matrixes, s are fundamental circuit number s=m-n+1；
Calculate the characteristics resistance coefficient of pipe network；
Prediction model is built, i.e. hydraulic pipeline calculates mathematical model：I.e.
AGT=0；
BΔHT=0；
In formula, G is the row vector G=[G for recording hot water volume flow in each pipeline section in pipe network figure1,G2,…,Gm]；Δ H is
The column vector of each pipeline section drag overall loss in pipe network figure is recorded, i.e. Δ H=S* | G | * G+Z-Hb；
In formula, S is the characteristics resistance coefficient matrix S=diag { S of each pipeline section in first-degree heating network1,S2,…,Sm}；
Equivalent absolute roughnesses of the K for tube wall, general K=0.0005m；D is internal diameter of the pipeline；l、ldRespectively pipe network calculates
The length of pipeline section and local resistance equivalent length；ρ is the averag density of hot water in pipe；
Z is the column vector Z=[Z of two node potential energy difference of pipeline section1,Z2,…,Zm]T；
HbFor the pump head column vector H in heat supply networkb=[Hb1,Hb2,…,Hbm]T；And
Heat supply network thermal-hydraulic calculates, i.e.,
Hydraulic pipeline calculating mathematical model combination loop adjustment flow-rate adjustment algorithm through successive ignition is calculated, is obtained
The volume flow of hot water in each pipeline section；And
The prediction model correction module is modified prediction model using heat supply network actual measurement operation data.
Further, the regulating of heating net unit is suitable for carrying out the thermic load needed for each thermal substation using balanced heating as target
Prediction obtains the primary side flow target value that should reach each thermal substation and uses prediction model to pump, valve in first-degree heating network
The method of operation carry out optimizing.
The invention has the advantages that the prediction model using first-degree heating network of the present invention is obtained as core using PREDICTIVE CONTROL
In heat supply first-degree heating network system sum in tens of accurate regulation schemes to hundreds of water pump and solenoid valve, in real time to heat supply network into
Row is adjusted, and solves the problems, such as that heating network control lag and heat user are uneven in temperature.
Description of the drawings
The present invention is further described with reference to the accompanying drawings and examples.
Fig. 1 is the flow chart of heating network adjusting method of the present invention；
Fig. 2 is the flow chart of step S2 in heating network adjusting method of the present invention.
Fig. 3 is the functional block diagram of the regulating of heating net system of the present invention.
Specific embodiment
In conjunction with the accompanying drawings, the present invention is further explained in detail.These attached drawings are simplified schematic diagram, only with
Illustration illustrates the basic structure of the present invention, therefore it only shows composition related to the present invention.
Embodiment 1
As shown in Figure 1, a kind of regulating of heating net method of the present invention, includes the following steps：
Step S1, establishes prediction model；
Step S2 using balanced heating as target, is predicted by prediction model and is obtained the respectively adjusting of pump, each valve in first-degree heating network
Scheme.
Specifically, the first-degree heating network that this regulating of heating net system can be used in district heating system is adjusted.
The step of establishing prediction model in the step S1 includes：
Step S11, thermal hydraulic analysis solve；And
Step S12, prediction model correction.
The method that thermal hydraulic analysis solves in the step S11 includes：
Pipe network is converted to the Directed Graph Model being made of node and section, i.e. pipe network figure by step S111；Wherein node table
Show there are the point that flow passes in and out, represented with set V, V=[V1,V2,…,Vn], in formula, n is the node number in pipe network；Section
It is the connection pipeline section between node, is represented with set E, E=[E1,E2,…,Em], m is sector number in formula, and digraph is expressed as G=<
V,E>；The incidence matrix A of pipe network and fundamental circuit matrix B are obtained according to network graph theory, wherein A is n × m rank matrixes, and B is s × m
Rank matrix, s are fundamental circuit number s=m-n+1；
Step S112 calculates the characteristics resistance coefficient of pipe network；
Step S113 builds prediction model, i.e. hydraulic pipeline calculates mathematical model：
AGT=0；
BΔHT=0；
In formula, G is the row vector G=[G for recording hot water volume flow in each pipeline section in pipe network figure1,G2,…,Gm]；Δ H is
The column vector of each pipeline section drag overall loss in pipe network figure is recorded, i.e., by Bernoulli equation and pepeline characteristic equation and considers that water pump is raised
Journey provides：Δ H=S* | G | * G+Z-Hb；
In formula, S is the characteristics resistance coefficient matrix S=diag { S of each pipeline section in first-degree heating network1,S2,…,Sm}；
Equivalent absolute roughnesses of the K for tube wall, general K=0.0005m；D is internal diameter of the pipeline；l、ldRespectively pipe network calculates
The length of pipeline section and local resistance equivalent length；ρ is the averag density of hot water in pipe；
Z is the column vector Z=[Z of two node potential energy difference of pipeline section1,Z2,…,Zm]T；
HbFor the pump head column vector H in heat supply networkb=[Hb1,Hb2,…,Hbm]T；When containing water pump in pipeline section, water pump
Lift is the H of the pipeline sectionb, when there is no water pump in pipeline section, the H of the pipeline sectionbIt is 0.
Step S114, heat supply network thermal-hydraulic calculate, i.e.,
Hydraulic pipeline calculating mathematical model combination loop adjustment flow-rate adjustment algorithm through successive ignition is calculated, is obtained
The volume flow of hot water in each pipeline section.
When optimizing calculating using prediction model control, first-degree heating network pipeline, heat source, thermal substation and weather correlation ginseng
Number is fixed value, and using valve opening adjustable in pipe network, pump rotary speed as the input parameter of prediction model, model, which exports, is
Reach the primary side flow value vector of each thermal substation.The loop adjustment flow-rate adjustment algorithm is known.
Prediction model correction includes in the step S12：Prediction model is modified using heat supply network actual measurement operation data.
The prediction model that the present invention is established includes online correction course, so that model can preferably describe the practical fortune of heat supply network
Row state is modified prediction model using heat supply network actual measurement operation data.In each sampling instant, transported by being surveyed to heat supply network
The comparison of theory state parameter that row state parameter is calculated with heat supply network state analysis system according to primary Calculation model, adjustment
Heat supply network state analysis computation model, and the important experiences such as pipe resistance coefficient, heat transfer coefficient parameter is corrected with service condition parameter
The value rule of variation establishes the dedicated computing model that can more preferably simulate heating network operation performance.
Using balanced heating as target in the step S2, by prediction model predict obtain first-degree heating network in respectively pump, each valve
The method of regulation scheme include the following steps：
Step S21 predicts the thermic load needed for each thermal substation using balanced heating as target obtaining should reach respectively
The primary side flow target value of thermal substation；
Step S22, using method of operation progress optimizing of the prediction model to pump, valve in first-degree heating network.
Specifically, obtaining a variety of different first-degree heating network pumps, valve regulation scheme first, and pass through prediction model and simulate not
With the primary side flow theory value of thermal substation each under scheme；Then according to optimization aim, by flow theory value and flow target value
It is compared, prioritization scheme is evaluated and (is calculated using iteration) by object function；The step is repeated, until obtaining
Meet the optimal solution of the object function of optimizing.
The thermic load needed for each thermal substation is predicted using balanced heating as target in the step S21, obtaining should
Reach the primary side flow target value of each thermal substation；I.e.
The target equation of primary side flow is：
(G in formula1r)iRepresent the primary side flow target value of i-th of thermal substation, s is the sum of thermal substation, and C is the ratio of water
Thermal capacitance, density of the ρ for hot water, ζiFor from radiator hot water to outdoor equivalent heat transfer factor, (K1F1)iRepresent i-th of thermal substation
The exchange capability of heat of middle heat exchanger, KconstRepresent quantitative；And
And
In ζi(K1F1)iFormula in, (G2)iRepresent thermal substation i secondary heat networks recirculated water volume flows, t2gRepresent two level heat
Net supply water temperature, t2hRepresent secondary heat networks return water temperature, t1gRepresent thermal substation first-degree heating network supply water temperature, t1hRepresent thermal substation
First-degree heating network return water temperature, twFor outdoor temperature, τ1-τ0≈ 3~5 days；
There is the total water supply flow G of first-degree heating network again1tEqual to the sum of each thermal substation primary side flow, i.e.,
G1tIt is known quantity for the total water supply flow of first-degree heating network.
By ζi、(K1F1)iSubstitute into (G1r)iCalculation formula (1), simultaneous formula (1), formula (2) solve KconstValue, Jin Ertong
It crosses formula (1) and obtains each thermal substation primary side flow target value；
Using method of operation progress optimizing of the prediction model to pump, valve in first-degree heating network, wherein optimizing in the step S22
Optimization aim include heat supply harmony target, pass through the first-degree heating network flow (G for distributing and reaching each thermal substation heat exchanger1)iWith reality
It is existing；
The object function of optimizing is
Wherein, Δ (G1)iDeviation for first-degree heating network flow and setting flow：
(G1)iFor the first-degree heating network flow rate calculation value of i-th of thermal substation of arrival simulated by prediction model；And
(Eb)jElectrical power for water pump consumption：
G is acceleration of gravity, (Gb)jTo pump the volume flow of hot water, (Hb)jFor pump head；(ηb)jEffect for water pump
Rate, subscript j represent water pump number；
In the calculation formula of respective objects function, Z be optimization overall target, NsFor thermal substation number, NbFor level-one heat
The number of net freq uency conversion supercharging pump, NvFor the number of first-degree heating network regulating valve, lkFor control valve opening, subscript k represents that regulating valve is compiled
Number, lminFor the minimum aperture that regulating valve allows, λG、λE、λlRespectively reach the first-degree heating network flow of each thermal substation, the electricity of water pump
The importance weight of consumption and valve opening.
Embodiment 2
On the basis of embodiment 1, the present invention also provides a kind of regulating of heating net system, including：Prediction model establishes unit,
The regulating of heating net unit that unit is connected is established with the prediction model.
The prediction model establishes unit and is adapted to set up prediction model, i.e. thermal hydraulic analysis solves module and prediction
Model correction module.
The thermal hydraulic analysis solves module, i.e.,
Pipe network is converted to the Directed Graph Model being made of node and section, i.e. pipe network figure；Wherein node represents there is stream
The point of disengaging is measured, is represented with set V, V=[V1,V2,…,Vn], in formula, n is the node number in pipe network；Section is between node
Connection pipeline section, represented with set E, E=[E1,E2,…,Em], m is sector number in formula, and digraph is expressed as G=<V,E>；
The incidence matrix A of pipe network and fundamental circuit matrix B are obtained according to network graph theory, wherein A is n × m rank matrixes, B s
× m rank matrixes, s are fundamental circuit number s=m-n+1；
Calculate the characteristics resistance coefficient of pipe network；
Prediction model is built, i.e. hydraulic pipeline calculates mathematical model：I.e.
AGT=0；
BΔHT=0；
In formula, G is the row vector G=[G for recording hot water volume flow in each pipeline section in pipe network figure1,G2,…,Gm]；Δ H is
The column vector of each pipeline section drag overall loss in pipe network figure is recorded, i.e. Δ H=S* | G | * G+Z-Hb；
In formula, S is the characteristics resistance coefficient matrix S=diag { S of each pipeline section in first-degree heating network1,S2,…,Sm}；
Equivalent absolute roughnesses of the K for tube wall, general K=0.0005m；D is internal diameter of the pipeline；l、ldRespectively pipe network calculates
The length of pipeline section and local resistance equivalent length；ρ is the averag density of hot water in pipe；
Z is the column vector Z=[Z of two node potential energy difference of pipeline section1,Z2,…,Zm]T；
HbFor the pump head column vector H in heat supply networkb=[Hb1,Hb2,…,Hbm]T；And
Heat supply network thermal-hydraulic calculates, i.e.,
Hydraulic pipeline calculating mathematical model combination loop adjustment flow-rate adjustment algorithm through successive ignition is calculated, is obtained
The volume flow of hot water in each pipeline section；And
The prediction model correction module is modified prediction model using heat supply network actual measurement operation data.
The regulating of heating net unit is suitable for predicting the thermic load needed for each thermal substation using balanced heating as target, be obtained
Go out to reach the primary side flow target value of each thermal substation and using operation of the prediction model to pump, valve in first-degree heating network
Mode carries out optimizing.
Specifically, the working method of regulating of heating net unit may refer to the corresponding discussion of embodiment 1.
Using above-mentioned desirable embodiment according to the present invention as enlightenment, by above-mentioned description, relevant staff is complete
Various changes and amendments can be carried out without departing from the scope of the technological thought of the present invention' entirely.The technology of this invention
Property range is not limited to the content on specification, it is necessary to determine its technical scope according to right.
Claims (6)
- A kind of 1. regulating of heating net method, which is characterized in that include the following steps：Step S1, establishes prediction model；Step S2, using balanced heating as target, by prediction model predict obtain first-degree heating network in respectively pump, each valve adjusting side Case；The step of establishing prediction model in the step S1 includes：Step S11, thermal hydraulic analysis solve；AndStep S12, prediction model correction；The method that thermal hydraulic analysis solves in the step S11 includes：Pipe network is converted to the Directed Graph Model being made of node and section, i.e. pipe network figure by step S111；Wherein node expression is deposited In the point of flow disengaging, represented with set V, V=[V1,V2,…,Vn], in formula, n is the node number in pipe network；Section is section Connection pipeline section between point, is represented with set E, E=[E1,E2,…,Em], m is sector number in formula, and digraph is expressed as G=<V,E >；The incidence matrix A of pipe network and fundamental circuit matrix B are obtained according to network graph theory, wherein A is n × m rank matrixes, and B is s × m Rank matrix, s are fundamental circuit number s=m-n+1；Step S112 calculates the characteristics resistance coefficient of pipe network；Step S113 builds prediction model, i.e. hydraulic pipeline calculates mathematical model：AGT=0；BΔHT=0；In formula, G is the row vector G=[G for recording the volume flow of hot water in each pipeline section in pipe network figure1,G2,…,Gm]；Δ H is note The column vector of each pipeline section drag overall loss in pipe network figure is recorded, i.e. Δ H=S* | G | * G+Z-Hb；In formula, S is the characteristics resistance coefficient matrix of each pipeline section in first-degree heating networkS=diag { S1,S2,…,Sm}；K is the equivalent absolute roughness of tube wall, and d is internal diameter of the pipeline；l、ldThe respectively length of pipe network run of designing and local resistance Equivalent length；ρ is the averag density of hot water in pipe；Z is the column vector Z=[Z of two node potential energy difference of pipeline section1,Z2,…,Zm]T；HbFor the pump head column vector H in heat supply networkb=[Hb1,Hb2,…,Hbm]T；Step S114, heat supply network thermal-hydraulic calculate, i.e.,Hydraulic pipeline calculating mathematical model combination loop adjustment flow-rate adjustment algorithm through successive ignition is calculated, obtains each pipe The volume flow of hot water in section；Prediction model correction includes in the step S12：Prediction model is modified using heat supply network actual measurement operation data.
- 2. regulating of heating net method according to claim 1, which is characterized in that using balanced heating as mesh in the step S2 Mark, by respectively being pumped in prediction model prediction acquisition first-degree heating network, the method for the regulation scheme of each valve includes the following steps：Step S21 predicts the thermic load needed for each thermal substation using balanced heating as target each heating power should be reached by obtaining The primary side flow target value stood；Step S22, using method of operation progress optimizing of the prediction model to pump, valve in first-degree heating network.
- 3. regulating of heating net method according to claim 2, which is characterized in thatThe thermic load needed for each thermal substation is predicted using balanced heating as target in the step S21, obtaining should reach The primary side flow target value of each thermal substation；I.e.The target equation of primary side flow is：(G in formula1r)iRepresenting the primary side flow target value of i-th of thermal substation, s is the sum of thermal substation, and C is the specific heat capacity of water, ζiFor from radiator hot water to outdoor equivalent heat transfer factor, (K1F1)iRepresent the exchange capability of heat of heat exchanger in i-th of thermal substation, KconstRepresent quantitative；AndAndIn ζi(K1F1)iFormula in, (G2)iRepresent thermal substation i secondary heat networks recirculated water volume flows, t2gRepresent that secondary heat networks supply Coolant-temperature gage, t2hRepresent secondary heat networks return water temperature, t1gRepresent thermal substation first-degree heating network supply water temperature, t1hRepresent thermal substation level-one Heat supply network return water temperature, twFor outdoor temperature, τ1-τ0≈ 3~5 days；There is the total water supply flow G of first-degree heating network again1tEqual to the sum of each thermal substation primary side flow, i.e.,G1tIt is known quantity for the total water supply flow of first-degree heating network；By ζi、(K1F1)iSubstitute into (G1r)iCalculation formula (1), simultaneous formula (1), formula (2) solve KconstValue, and then pass through formula (1) each thermal substation primary side flow target value is obtained.
- 4. regulating of heating net method according to claim 3, which is characterized in thatUsing method of operation progress optimizing of the prediction model to pump, valve in first-degree heating network in the step S22, wherein optimizing is excellent Change target and include heat supply harmony target, the first-degree heating network flow (G of each thermal substation heat exchanger is reached by distributing1)iTo realize；The object function of optimizing isWherein, Δ (G1)iDeviation for first-degree heating network flow and setting flow：(G1)iFor the first-degree heating network flow rate calculation value of i-th of thermal substation of arrival simulated by prediction model；And(Eb)jElectrical power for water pump consumption：G is acceleration of gravity, (Gb)jTo pump the volume flow of hot water, (Hb)jFor pump head；(ηb)jFor the efficiency of water pump, Subscript j represents water pump number；In the calculation formula of respective objects function, Z be optimization overall target, NsFor thermal substation number, NbBecome for first-degree heating network The number of frequency booster pump, NvFor the number of first-degree heating network regulating valve, lkFor control valve opening, subscript k represents regulating valve number, lmin For the minimum aperture that regulating valve allows, λG、λE、λlRespectively reach the first-degree heating network flow of each thermal substation, the electrisity consumption of water pump with And the importance weight of valve opening.
- 5. a kind of regulating of heating net system, which is characterized in that including：Prediction model establishes unit, and the regulating of heating net unit that unit is connected is established with the prediction model；The prediction model establishes unit and is adapted to set up prediction model, i.e.,Thermal hydraulic analysis solves module and prediction model correction module；The thermal hydraulic analysis solves, i.e.,Pipe network is converted to the Directed Graph Model being made of node and section, i.e. pipe network figure；Wherein node represent there are flow into The point gone out, is represented with set V, V=[V1,V2,…,Vn], in formula, n is the node number in pipe network；Section is the company between node Nozzle belt represents with set E, E=[E1,E2,…,Em], m is sector number in formula, and digraph is expressed as G=<V,E>；The incidence matrix A of pipe network and fundamental circuit matrix B are obtained according to network graph theory, wherein A is n × m rank matrixes, and B is s × m Rank matrix, s are fundamental circuit number s=m-n+1；Calculate the characteristics resistance coefficient of pipe network；Prediction model is built, i.e. hydraulic pipeline calculates mathematical model：I.e.AGT=0；BΔHT=0；In formula, G is the row vector G=[G for recording each pipeline section inner volume flow in pipe network figure1,G2,…,Gm]；Δ H is the column vector for recording each pipeline section drag overall loss in pipe network figure, i.e.,Δ H=S* | G | * G+Z-Hb；In formula, S is the characteristics resistance coefficient matrix of each pipeline section in first-degree heating networkS=diag { S1,S2,…,Sm}；K is the equivalent absolute roughness of tube wall；D is internal diameter of the pipeline；l、ldThe respectively length of pipe network run of designing and local resistance Equivalent length；ρ is the averag density of hot water in pipe；Z is the column vector Z=[Z of two node potential energy difference of pipeline section1,Z2,…,Zm]T；HbFor the pump head column vector H in heat supply networkb=[Hb1,Hb2,…,Hbm]T；AndHeat supply network thermal-hydraulic calculates, i.e.,Hydraulic pipeline calculating mathematical model combination loop adjustment flow-rate adjustment algorithm through successive ignition is calculated, obtains each pipe Volume flow in section；AndThe prediction model correction module is modified prediction model using heat supply network actual measurement operation data.
- 6. regulating of heating net system according to claim 5, which is characterized in thatThe regulating of heating net unit is suitable for predicting the thermic load needed for each thermal substation using balanced heating as target, obtains and answer It is pumped when the primary side flow target value for reaching each thermal substation and in using prediction model to first-degree heating network, the method for operation of valve Carry out optimizing.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610270475.1A CN105910169B (en) | 2016-04-27 | 2016-04-27 | District heating system regulating of heating net method and system based on mechanism model PREDICTIVE CONTROL |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610270475.1A CN105910169B (en) | 2016-04-27 | 2016-04-27 | District heating system regulating of heating net method and system based on mechanism model PREDICTIVE CONTROL |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105910169A CN105910169A (en) | 2016-08-31 |
| CN105910169B true CN105910169B (en) | 2018-06-22 |
Family
ID=56751925
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610270475.1A Active CN105910169B (en) | 2016-04-27 | 2016-04-27 | District heating system regulating of heating net method and system based on mechanism model PREDICTIVE CONTROL |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105910169B (en) |
Families Citing this family (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106647329B (en) * | 2016-12-16 | 2023-04-07 | 中国电力科学研究院 | Equivalent modeling method for heat supply pipe network |
| CN106849188B (en) * | 2017-01-23 | 2020-03-06 | 中国电力科学研究院 | Combined heat and power optimization method and system for promoting wind power consumption |
| CN106895478B (en) * | 2017-02-10 | 2019-10-29 | 青岛高校信息产业股份有限公司 | A kind of heating network adjusting method and system |
| CN106682369A (en) * | 2017-02-27 | 2017-05-17 | 常州英集动力科技有限公司 | Heating pipe network hydraulic simulation model identification correction method and system, method of operation |
| CN106958855B (en) * | 2017-03-31 | 2019-06-11 | 常州英集动力科技有限公司 | The hydraulically balanced model predictive control method of heating system and system |
| CN107543243B (en) * | 2017-08-26 | 2018-05-15 | 新疆恒蓝节能科技有限公司 | A kind of method and system of public building heating energy |
| CN107730036B (en) * | 2017-09-30 | 2021-09-28 | 新智能源系统控制有限责任公司 | Method and device for acquiring flow delay time in energy supply |
| CN107766972B (en) * | 2017-09-30 | 2021-04-27 | 新智能源系统控制有限责任公司 | Method and device for acquiring energy flow delay time |
| CN108876066A (en) * | 2018-09-04 | 2018-11-23 | 常州英集动力科技有限公司 | Heat supply network off-the-line operating scheme real-time optimization method and its system |
| CN110007595B (en) * | 2019-03-29 | 2022-04-22 | 常州英集动力科技有限公司 | Real-time load optimization scheduling method, unit model, unit and system for heat supply system |
| CN109945269A (en) * | 2019-04-04 | 2019-06-28 | 尚东奎 | A kind of heat exchange station energy-saving operating method |
| CN110287509B (en) * | 2019-04-25 | 2021-05-04 | 浙江大学 | Flexible analysis and structural defect diagnosis and positioning method and system for urban heat supply network |
| CN110160127A (en) * | 2019-05-17 | 2019-08-23 | 烟台锐控自动化控制工程有限公司 | Mist based on fluid heat transferring modeling calculates three-level net for thermal control system |
| CN110543108B (en) * | 2019-09-20 | 2022-09-30 | 常州英集动力科技有限公司 | Heating system measurement data correction method and system based on mechanism model prediction |
| CN111222213B (en) * | 2020-01-15 | 2021-08-03 | 许继集团有限公司 | Dynamic simulation method and device for thermodynamic network |
| CN111523210B (en) * | 2020-04-10 | 2023-05-16 | 浙江英集动力科技有限公司 | Predictive analysis method and predictive analysis system for temperature rising and reducing process of urban central heating system |
| CN111561734B (en) * | 2020-05-18 | 2020-12-22 | 瑞纳智能设备股份有限公司 | Heating household valve adjusting method, system and equipment based on artificial intelligence |
| CN113175700B (en) * | 2021-05-28 | 2022-05-10 | 呼伦贝尔安泰热电有限责任公司满洲里热电厂 | Intelligent equipment management and big data early warning analysis system and method for heat supply network |
| CN113503581A (en) * | 2021-06-01 | 2021-10-15 | 吕雪光 | Intelligent control method for heating system |
| CN113776122B (en) * | 2021-09-29 | 2022-08-12 | 北京百度网讯科技有限公司 | Heat supply control method, device, equipment, medium and product |
| CN115183318B (en) * | 2022-08-24 | 2023-04-07 | 北京硕人时代科技股份有限公司 | Heat supply adjusting method based on load prediction and heat progress consistency and related equipment |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007028938A1 (en) * | 2005-09-07 | 2007-03-15 | Endoenergy Systems Ltd | Thermal energy system and apparatus |
| CN103412526A (en) * | 2013-07-12 | 2013-11-27 | 国家电网公司 | Scheduling method of heat supply unit online load and system |
| CN104048347A (en) * | 2014-07-01 | 2014-09-17 | 威海国能自控科技有限公司 | Intelligent heat supply network integrated system and control method thereof |
| CN104534556A (en) * | 2014-12-08 | 2015-04-22 | 北京华电方胜技术发展有限公司 | Heat supply control method based on energy consumption monitoring |
| CN104791903A (en) * | 2015-04-30 | 2015-07-22 | 北京上庄燃气热电有限公司 | Intelligent heating network dispatching system |
-
2016
- 2016-04-27 CN CN201610270475.1A patent/CN105910169B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007028938A1 (en) * | 2005-09-07 | 2007-03-15 | Endoenergy Systems Ltd | Thermal energy system and apparatus |
| CN103412526A (en) * | 2013-07-12 | 2013-11-27 | 国家电网公司 | Scheduling method of heat supply unit online load and system |
| CN104048347A (en) * | 2014-07-01 | 2014-09-17 | 威海国能自控科技有限公司 | Intelligent heat supply network integrated system and control method thereof |
| CN104534556A (en) * | 2014-12-08 | 2015-04-22 | 北京华电方胜技术发展有限公司 | Heat supply control method based on energy consumption monitoring |
| CN104791903A (en) * | 2015-04-30 | 2015-07-22 | 北京上庄燃气热电有限公司 | Intelligent heating network dispatching system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105910169A (en) | 2016-08-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105910169B (en) | District heating system regulating of heating net method and system based on mechanism model PREDICTIVE CONTROL | |
| CN109270842B (en) | Bayesian network-based regional heat supply model prediction control system and method | |
| CN108916986B (en) | Information physical fusion secondary pipe network variable flow hydraulic balance regulation and control method and system | |
| CN112128841B (en) | Whole-network balance adjusting method based on load prediction and room temperature feedback correction | |
| CN110906571B (en) | Solar heat pump hot water system control strategy optimization method based on machine learning | |
| CN106958855B (en) | The hydraulically balanced model predictive control method of heating system and system | |
| CN108197768B (en) | Energy system and pipe network layout joint optimization method | |
| CN111222213B (en) | Dynamic simulation method and device for thermodynamic network | |
| CN112417662B (en) | Method for realizing dynamic hydraulic optimization of centralized heat supply pipe network system | |
| CN113266869B (en) | Real-time optimization regulation and control method of thermoelectric combined heating system based on digital twinning technology | |
| CN102063566A (en) | Multi-gas-source steam pipe network computing system of hydraulic thermal-coupling simulation model | |
| CN111046594B (en) | Hot water heating network dynamic simulation method based on cross iteration principle | |
| Gao et al. | Numerical and experimental investigation on thermal stratification characteristics affected by the baffle plate in thermal storage tank | |
| CN108229721A (en) | The Forecasting Methodology of pyrolysis of coal product based on Speed Controlling Based on Improving BP Neural Network | |
| CN109636037A (en) | A kind of multi-heat source ring-shaped heat-supply network hydraulic optimization dispatching method based on PSO algorithm | |
| CN108800303B (en) | Refined energy-saving heat supply method based on pattern recognition | |
| CN112016754A (en) | Power station boiler exhaust gas temperature advanced prediction system and method based on neural network | |
| CN111125938A (en) | Suboptimal algorithm-based optimization design method for large central air-conditioning chilled water pipe network | |
| CN113190999A (en) | Electric heating coordination method and device for regulating flow of heat supply pipe network to improve wind power consumption | |
| CN113361214A (en) | Open channel control model parameter identification method based on water level flow data | |
| CN108954491A (en) | A kind of control method of photo-thermal medium temperature offset-type electric boiler heating system | |
| CN105447256B (en) | A kind of enhancing excitation emulation genetic optimization method | |
| CN114781102A (en) | Energy flow modeling method and application of urban comprehensive energy system | |
| Wang et al. | A zoned group control of indoor temperature based on MPC for a space heating building | |
| CN110795845A (en) | Heat supply system margin quantitative calculation method and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |