CN117195778A - Parameter identification correction method for hydraulic simulation model of heating pipe network - Google Patents
Parameter identification correction method for hydraulic simulation model of heating pipe network Download PDFInfo
- Publication number
- CN117195778A CN117195778A CN202311475368.9A CN202311475368A CN117195778A CN 117195778 A CN117195778 A CN 117195778A CN 202311475368 A CN202311475368 A CN 202311475368A CN 117195778 A CN117195778 A CN 117195778A
- Authority
- CN
- China
- Prior art keywords
- matrix
- state estimation
- pipe section
- flow
- value
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 54
- 238000010438 heat treatment Methods 0.000 title claims abstract description 48
- 238000004088 simulation Methods 0.000 title claims abstract description 19
- 238000012937 correction Methods 0.000 title claims description 7
- 239000011159 matrix material Substances 0.000 claims abstract description 114
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 27
- 230000001105 regulatory effect Effects 0.000 claims description 14
- 238000010276 construction Methods 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 238000012795 verification Methods 0.000 claims description 3
- 230000036962 time dependent Effects 0.000 claims 1
- 238000012544 monitoring process Methods 0.000 description 6
- 238000001514 detection method Methods 0.000 description 5
- 238000011160 research Methods 0.000 description 3
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method for identifying and correcting parameters of a hydraulic simulation model of a heating pipe network, which comprises the following steps: constructing a linearization model based on a centralized heating unsteady hydraulic model of lumped parameter hypothesis; based on the linearization model, establishing a linearization model of a central heating network dynamic system; when the linear model meets observability, constructing a state estimation gain matrix; carrying out state estimation on the central heating network based on real-time sensor data by using a state estimation gain matrix to obtain a state estimation value of the flow of the residual branch pipe section; the invention relates to a state estimation method based on a linear model, which reduces the arrangement requirement on site sensors, and only needs the flow values of a heat source, a heating power station and a part of relay pump stations for a large-scale annular pipe network, so that the sensors are not required to be arranged in a water supply network or a water return network plane topological structure in each ring.
Description
Technical Field
The invention relates to the technical field of heat supply pipe network design, in particular to a heat supply pipe network hydraulic simulation model parameter identification correction method.
Background
As the scale of heat supply is increasingly enlarged and the structure of the annular network is increasingly complex, it becomes increasingly difficult to build a strictly accurate hydraulic simulation model of the heat supply network. The impedance of the heat supply pipe network is taken as an important pipe network operation parameter, and plays a vital role in adjusting the pipe network operation. If the impedance of the pipe network is not identified in the actual engineering, the pipe network impedance value calculated based on theory is mostly inconsistent with the actual value, the roughness of the pipe section with the on-way resistance coefficient is changed continuously along with the operation of the pipe network, and the estimated value of the local resistance coefficient is very inaccurate, so that the hydraulic analysis of the pipe network is greatly influenced.
At present, the research on the network impedance identification at home and abroad is mostly biased to a dendritic network, the research on the network impedance identification of the annular pipe is mainly realized by utilizing a steady-state hydraulic equation and applying a method based on a least square method or gradient descent, and the method needs a large number of steady-state working condition flow and pressure detection values and has extremely high requirements on intelligent monitoring, reconstruction and later data processing of the network; and the great fluctuation and error of the pressure value in the pipeline also lead to the difficulty of engineering application of the method.
In the current research of the hydraulic characteristics of the annular pipe network, the problem of the impedance identification of the annular pipe network is that the flow and the flow direction of the pipe sections of the annular pipe network are difficult to monitor, and the pressure difference and the flow of each pipe section cannot be identified. The pipe network becomes ring mainly because the planar ring structure appears in the water supply (return) network, and the heating power station is connected with the water supply and return pipe network to form the ring structure in the topological sense of heat source-water supply network-heating power station-water return network-heat source.
For the flow of each pipe section of the annular pipe network, the flow values which are only the same as the topological ring number of the pipe network are linearly independent, namely the flow of the rest pipe section. In the residual branch pipe section, only part of flow of the planar annular structure is undetectable, monitoring equipment in the heat source and the heating power station is comprehensive, real-time parameters of valve opening and water pump frequency can be obtained, and the conditions form a basis for state observation based on a dynamic model. However, how to dynamically monitor the conditions to meet the engineering needs is a problem to be solved.
Disclosure of Invention
The invention aims at solving the technical defects existing in the prior art and provides a method for identifying and correcting parameters of a hydraulic simulation model of a heating pipe network.
The technical scheme adopted for realizing the purpose of the invention is as follows:
a heat supply pipe network hydraulic simulation model parameter identification correction method comprises the following steps:
s1, constructing a centralized heating unsteady hydraulic model based on lumped parameter assumption, and constructing a linearization model;
s2, establishing a linear model of the central heating network dynamic system based on the linear model;
s3, judging whether the linear model meets observability, if so, entering a step S4, and if not, entering a step S8;
s4, constructing a state estimation gain matrix;
s5, performing state estimation of the central heating network based on real-time sensor data by using a state estimation gain matrix to obtain a state estimation value of the flow of the residual branch pipe section;
s6, judging whether the state estimation error and the speed meet the preset requirements or not based on the state estimation value of the flow of the residual branch pipe section, and if so, entering a step S7; if not, entering step S9;
s7, calculating an estimated value of the impedance of each pipe section of the pipe network based on the state estimated value of the flow of the residual branch pipe section;
s8, adjusting the observed residual branch pipe sections, correcting a basic loop matrix of the heating pipe network obtained based on the pipe network topology information, and returning to the step S2;
s9, adjusting the characteristic value and the state estimation gain coefficient of the state estimation gain matrix, and returning to the step S4.
In step S1, the linearization model expression is as follows:
，
wherein the coefficients areCalculated from the following formula:
，
wherein,represents a basic loop matrix of the heating network obtained based on the network topology information,representing a transpose of the basic loop matrix,for the flow value of each residual branch pipe section,representation ofThe derivative with respect to time is given by,is the flow value of the spare branch pipe section under the preset steady-state working condition,is a pipe section impedance matrix;is a water pumpA lift;the resistance of the regulating valve is represented,is the water flow density in the pipe;is the length of the pipe section;characterizing the inner diameter of the pipe section,representing a diagonal matrix.
In step S2, the expression of the linear model of the central heating network dynamic system is as follows:
，
the linear model of the central heating network dynamic system is abbreviated as follows:
，
，
in the method, in the process of the invention,for a monitorable flow value of the excess branch pipe section,representation ofThe matrix is formed by a matrix of,matrix for monitoring the number of spare branch pipe sectionsCorresponding to the remaining branch pipe sections of each column,each row element value indicates whether the corresponding spare branch pipe segment is monitorable,is thatControl vector, matrix of (a)Is thatMatrix, matrixIs thatThe matrix is formed by a matrix of,is the number of the rings, the number of the rings is the same,the number of pipe sections.
In step S3, judging whether the linear model meets the observability or not, and judging through constructing an observability matrix; wherein, the observability matrix is constructed based on the following formula, if the observability matrix array rank isThe linear model is considered to satisfy the observability:
， 。
in step S4, the construction process of the state estimation gain matrix includes:
for eigenvalue sets with negative real partConstruct oneMatrix arraySatisfies the following conditionsAnd is also provided withMatrix, i.e. matrixSum matrixNo identical characteristic value;representing dimensions asIs a matrix of units of (a);
structure of the deviceMatrix arraySatisfies the following conditionsIs controllable such that the rank of the constructed controllability matrix isThe controllability matrix is constructed by the following formula;
，
solving Lyapunov equationUnique solution，Is thatMatrix, verification matrixIs non-singular;
calculating a state estimation gain matrix as follows；
。
In step S5, a state estimation value of the flow rate of the residual branch pipe section is obtained by the following formula:
，
，
wherein,represent the firstThe time derivative of the state estimate of each excess branch pipe segment flow,a state estimate representing the flow of each excess branch pipe segment,is shaped likeThe state estimation error is used to estimate the state,represent the firstThe derivative of the state estimation error with respect to time of day,representation ofThe state estimation error of the moment in time,the initial value of (1) isThe method comprises the steps of carrying out a first treatment on the surface of the Along withTime-of-day monitorable flow value of the excess branch pipe sectionContinuously obtaining new state estimation value of the flow of the residual branch pipe section。
In step S6, it is determined whether the state estimation error and the speed meet the preset requirement, by determining the two norms of the error between the monitorable residual branch pipe segment flow value and the state estimation valueWhether to reduce to a preset value;the expression is as follows:
；
in the method, in the process of the invention,representation ofA time-of-day monitorable flow value of the excess branch pipe section,representation ofState estimation value of flow of each spare branch pipe section at moment.
Step S7, calculating the estimated value of the impedance of each pipe section of the pipe network by adopting the following formula:
，
，
in the method, in the process of the invention,represents the estimated value of the impedance of each pipe section of the pipe network,is the flow characteristic curve coefficient of the water pump,is the frequency conversion ratio of the water pump,the valve opening of the regulating valve;in order to adjust the valve-adjusting ratio of the valve,in order to adjust the valve flow capacity of the valve,a diagonal array is represented and is shown,represents an estimated value of the resistance of the regulator valve,representing the transpose of matrix C.
In step S9, the adjusting the eigenvalues and the state estimation gain coefficients of the state estimation gain matrix includes:
adjusting matrixIs corrected by the correction matrix>Adjusting the state estimation gain matrix +.>Is provided.
The invention regards the central heating pipe network as a dynamic system, constructs a linear model which takes the pump lift and the resistance of the regulating valve as input and takes the flow value of the detectable residual branch pipe section as output, carries out state estimation based on the linear model, estimates the unmonitored flow of the pipe section without monitoring equipment in the central heating pipe network and the pipe network resistance value, realizes the identification of the impedance of the central heating pipe network by using continuous flow monitoring data only, and thus completes the correction and identification of the hydraulic model of the central heating pipe network.
The method only needs to use the flow detection value, the water pump frequency, the valve opening of the regulating valve and other detectable amounts, does not depend on the pressure detection value any more, greatly simplifies the application requirement of the hydraulic simulation model, and avoids the problems of larger error and fluctuation of the pressure detection value.
The method utilizes the dynamic linear model, so that only one continuous dynamic flow detection value near the steady-state working condition is adopted, and the statistical requirement on a large amount of steady-state working condition data is avoided.
The method of the invention is based on the state estimation method of the linear model, reduces the arrangement requirement on the field sensor, only needs the flow values of the heat source, the heating power station and part of the relay pump stations for the large-scale annular pipe network, and does not need to arrange the sensor in the planar topological structure of the water supply network or the backwater network, thereby saving the hardware cost and being convenient for arrangement.
Drawings
FIG. 1 is a flow chart of a method for identifying and correcting parameters of a hydraulic simulation model of a heating network.
Detailed Description
The invention is described in further detail below with reference to the drawings and the specific examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, the method for identifying and correcting parameters of a hydraulic simulation model of a heating network according to the embodiment of the invention comprises the following steps:
s1, constructing a centralized heating unsteady hydraulic model based on lumped parameter assumption, and constructing a linearization model;
s2, establishing a linear model of the central heating network dynamic system based on the linear model;
s3, judging whether the linear model meets the observability requirement, if so, entering a step S4, and if not, entering a step S8;
s4, constructing a state estimation gain matrix;
s5, performing state estimation of the central heating network based on real-time sensor data by using a state estimation gain matrix to obtain a state estimation value of the flow of the residual branch pipe section;
s6, judging whether the state estimation error and the speed meet the preset requirements or not based on the state estimation value of the flow of the residual branch pipe section, and if so, entering a step S7; if not, entering step S9;
s7, calculating an estimated value of the impedance of each pipe section of the pipe network based on the state estimated value of the flow of the residual branch pipe section;
s8, adjusting the observed residual branch pipe sections, correcting a basic loop matrix of the heating pipe network obtained based on the pipe network topology information, and returning to the step S2;
s9, adjusting the characteristic value and the state estimation gain coefficient of the state estimation gain matrix, and returning to the step S4.
In the embodiment of the invention, when a linear model of a central heating network dynamic system is constructed, the following process is adopted:
defining the node number of a pipe network asThe number of pipe sections isThe number of rings (number of residual branch pipe sections) isThe number of branches isThe following relation is satisfied between them, and the following relation is shown in the formula (1):
；
firstly, constructing a basic association matrix for a complete heat supply network composed of a heat source, a water supply network, a heating power station and a water return networkBasic association matrixIs a method for describing the topological relation between pipe sections and nodes at two ends of the pipe sections in a pipe networkThe matrix is analyzed by using a Kruskal algorithm to obtain a spanning tree of the heating pipe network, wherein pipe sections in the spanning tree are called branches, and pipe sections which are not in the spanning tree are called residual branches. Constructing basic association matrix according to branch-residual branch sequenceWhereinOnly the branch pipe sections are covered,comprises only the rest branch pipe sections. The matrix elements and the manner of construction thereof are described by formula (2).
；
In step S1, a centralized heating unsteady hydraulic model based on lumped parameter assumption is constructed as shown in the following (3), the linearization model is linearized based on a certain steady-state working condition, the approximation degree of the working condition near the steady-state working condition is good, and the model calculates the flow value of each residual branch pipe sectionPipe section impedance matrix as state valuePump liftResistance of regulating valveIs the main pipe network parameter.
（3）；
Wherein,represents a basic loop matrix of the heating network obtained based on the network topology information,is the flow value of each branch pipe section,，representation ofThe derivative with respect to time is given by,for the flow value of the spare branch pipe section under a certain preset steady-state working condition,is a tube section impedance matrix,；is the lift of the water pump,；the resistance of the regulating valve is represented,；for the density of the water flow in the pipe,；for the length of the pipe section,；characterizing the inner diameter of the pipe section,，
wherein the coefficients areCalculated from formula (4):
（4）；
the basic loop matrixDescribing the relationship between individual annular circuits and pipe segments in a pipe networkAnd the matrix, wherein each row represents a circular loop, each column corresponds to a pipe section, the value is 1 or-1 if the pipe section exists in the circular loop, the value corresponds to the direction of the pipe section, and the value is 0 if the pipe section does not exist in the circular loop. Similar to the construction of matrix A, the basic Loop matrixThere is also a branch-to-branch sequence, i.e，、Can be calculated from formula (5), respectively; wherein the method comprises the steps ofThe number of the orders is the same as the number of the rest branches;
(5)；
the pump liftCalculated from formula (6), whereinIs the flow characteristic curve coefficient of the water pump,is the variable frequency ratio of the water pump, namely the ratio of the running frequency of the water pump to 50Hz,the value of the pipe section containing only the water pump is not 0. SuperscriptRepresenting a diagonal matrix.
(6)；
The resistance of the regulating valveCalculated from formula (7), whereinIn order to adjust the valve flow capacity of the valve,；in order to be a valve flow characteristic curve,the valve opening of the regulating valve;in order to adjust the valve-adjusting ratio of the valve,the value of the pipe section containing only the regulating valve is not 0.
(7)；
The combined type (3), (6) and (7) can obtain a linear model of the central heating network dynamic system, so in the step S2, the expression of the linear model of the central heating network dynamic system is shown as the following formula (8):
（8）；
the linear model of the central heating pipe network dynamic system is abbreviated as the following formula (9), and the input value of the linear model is a control vectorThe state value is the flow value of each residual branch pipe sectionThe output value is the flow value of the residual branch pipe section which can be monitored. The linear model output value can be detected. Equation (10) describes a matrix based on equation (8)、And、is a matrix described by the formula (11)、Meaning and method of construction of (a). Matrix arrayIs thatMatrix arrayMatrixIs thatMatrix, control vectorIs thatIs a vector of (a).
（9）；
（10），
In addition, the flow rate of the residual branch pipe section which can be monitored can be constructed according to the formula (11)Matrix array，Matrix for monitoring the number of spare branch pipe sectionsCorresponding to the remaining branch pipe sections of each column,the element values of each row represent whether the corresponding residual branch pipe section can be monitored, if 1 represents that the residual branch pipe section flow can be monitored, and 0 represents that the residual branch pipe section flow is not monitored, so that a foundation is laid for judging whether the linear model meets the observability requirement.
(11)，
Therefore, in step S3, when judging whether the linear model satisfies the observability, it is realized by constructing an observability matrix judgment; wherein, the observability matrix is constructed based on the following formula, if the column rank of the observability matrix isThe linear model is considered to satisfy the observability, so that the state estimation process is executed on the premise of ensuring the observability of the linear model:
。
in step S4, the construction process of the state estimation gain matrix includes:
for eigenvalue sets with negative real partConstruct oneMatrix arraySatisfies the following conditionsAnd is also provided with，
I.e. matrixSum matrixThere is no value of the same characteristic which,representing dimensions asIs a matrix of units of (a);
structure of the deviceMatrix arraySatisfies the following conditionsIs controllable such that the rank of the constructed controllability matrix isThe controllability matrix is constructed by the following formula;
；
solving Lyapunov equationUnique solution，Is thatMatrix, verification matrixIs non-singular;
calculating a state estimation gain matrix as follows；
。
In step S5, a state estimation gain matrix is utilized to perform state estimation of the central heating network based on real-time sensor data (the flow value of the residual branch pipe section detected by the sensor), so as to obtain a state estimation value of the flow of the residual branch pipe section; by the following formula:
；
；
wherein,represent the firstTime derivative of flow state estimated value of each residual branch pipe section, namely subscript、Respectively representing an old value and a new value,a state estimate representing the flow of each excess branch pipe segment,represent the firstThe derivative of the state estimation error with respect to time of day,is the state estimation error of the flow of each residual branch pipe section,representation ofState estimation error of each residual branch pipe section flow at moment, state estimation value of each residual branch pipe section flowThe initial value of (1) isThe method comprises the steps of carrying out a first treatment on the surface of the With detectable flow value of the residual branch pipe sectionAnd continuously inputting to continuously obtain a new state estimation value of the flow of the residual branch pipe section.
In step S6, based on the state estimation value of the flow of the residual branch pipe section, it is determined whether the state estimation error and the speed meet the engineering requirement, which is a two-norm of the error between the detectable flow value of the residual branch pipe section and the state estimation value of the flow of the residual branch pipe sectionWhether to reduce to a preset value; i.e. byJudging whether the state estimation error is continuously reduced and whether the descending speed meets the project requirement, wherein the method comprises the following stepsThe expression is as follows:
；
in the method, in the process of the invention,representation ofA time-of-day detectable flow value of the excess branch pipe segment.
Step S7, calculating an estimated value of the impedance of each pipe section of the pipe network based on the estimated value of the flow state of the residual branch pipe section, and estimating the estimated value by adopting the following formula:
；
in the method, in the process of the invention,represents an estimated value of the impedance of each pipe segment of the pipe network,is the flow characteristic curve coefficient of the water pump,is the frequency conversion ratio of the water pump,the valve opening of the regulating valve;in order to adjust the valve-adjusting ratio of the valve,to adjust the valve flow capacity of the valve, superscripts are givenA diagonal array is represented and is shown,represents the estimated value of the pump lift,represents an estimated value of the resistance of the regulator valve,representing the transpose of the matrix C,is the coefficient of the formula (3),the black dots marked on the upper scale refer to the derivative with respect to time; when (when)Falling gradually to a steady state or below a certain set value. At this time consider the state estimation valueIs accurate at this timeAnd calculating the estimated value of the impedance of each pipe section of the pipe network based on the state estimated value of the flow of the residual branch pipe section.
In step S8, the observed branch pipe sections are adjusted, and the basic loop matrix of the heating network obtained based on the topology information of the network is corrected by increasing or decreasing the number of branch pipe sections capable of observing the flow.
In step S9, the adjusting the eigenvalue and the state estimation gain coefficient of the state estimation gain matrix includes:
adjusting matrixIs used for correcting matrixAdjusting a state estimation gain matrixState estimation gain coefficient of (a) the matrixIs manually selected, refers to the characteristic value setIs a characteristic value of (a). State estimation gain matrixState estimation gain coefficient of (2), i.e. the state estimation gain matrixIs described.
While the fundamental and principal features of the invention and advantages of the invention have been shown and described, it will be apparent to those skilled in the art that the invention is not limited to the details of the foregoing exemplary embodiments, but may be embodied in other specific forms without departing from the spirit or essential characteristics thereof;
the present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Furthermore, it should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is provided for clarity only, and that the disclosure is not limited to the embodiments described in detail below, and that the embodiments described in the examples may be combined as appropriate to form other embodiments that will be apparent to those skilled in the art.
Claims (9)
1. The method for identifying and correcting the parameters of the hydraulic simulation model of the heating network is characterized by comprising the following steps:
s1, constructing a centralized heating unsteady hydraulic model based on lumped parameter assumption, and constructing a linearization model;
s2, establishing a linear model of the central heating network dynamic system based on the linear model;
s3, judging whether the linear model meets observability, if so, entering a step S4, and if not, entering a step S8;
s4, constructing a state estimation gain matrix;
s5, performing state estimation of the central heating network based on real-time sensor data by using a state estimation gain matrix to obtain a state estimation value of the flow of the residual branch pipe section;
s6, judging whether the state estimation error and the speed meet the preset requirements or not based on the state estimation value of the flow of the residual branch pipe section, and if so, entering a step S7; if not, entering step S9;
s7, calculating an estimated value of the impedance of each pipe section of the pipe network based on the state estimated value of the flow of the residual branch pipe section;
s8, adjusting the observed residual branch pipe sections, correcting a basic loop matrix of the heating pipe network obtained based on the pipe network topology information, and returning to the step S2;
s9, adjusting the characteristic value and the state estimation gain coefficient of the state estimation gain matrix, and returning to the step S4.
2. The method for identifying and correcting parameters of hydraulic simulation model of heat supply network according to claim 1, wherein in step S1, the expression of the linearization model is as follows:
，
wherein the coefficients areCalculated from the following formula:
，
wherein,basic loop matrix representing heat supply network obtained based on network topology information>Representing the transpose of the basic loop matrix,/->For the flow value of each spare branch pipe section, +.>Representation->Derivative with respect to time, < >>For the flow value of the spare branch pipe section under the preset steady-state working condition, < ->Is a pipe section impedance matrix; />Is the lift of the water pump; />Characterizing the resistance of the regulating valve>Is the water flow density in the pipe; />Is the length of the pipe section; />Characterizing the inner diameter of a pipe section>Representing a diagonal matrix.
3. The method for identifying and correcting parameters of hydraulic simulation model of heating network according to claim 2, wherein in step S2, the expression of the linear model of the central heating network dynamic system is as follows:
，
the linear model of the central heating network dynamic system is abbreviated as follows:
，
，
in the method, in the process of the invention,for the flow value of the residual branch pipe section which can be monitored, < ->Representation->Matrix (S)>Matrix for the number of monitorable branch segments>Corresponding to the remaining branch sections>The element values of each row indicate whether the corresponding spare branch pipe section can be monitored or not>Is->Control vector, matrix->Is->Matrix, matrix->Is->Matrix (S)>For the number of rings>The number of pipe sections.
4. The method for identifying and correcting parameters of a hydraulic simulation model of a heating network according to claim 3, wherein in step S3, whether the linear model meets the observability is judged and realized by constructing an observability matrix; wherein, the observability matrix is constructed based on the following formula, if the observability matrix array rank isThe linear model is considered to satisfy the observability:
， />。
5. the method for identifying and correcting parameters of hydraulic simulation model of heat supply network according to claim 4, wherein in step S4, the construction process of the state estimation gain matrix comprises:
for eigenvalue sets with negative real partConstruct a +.>Matrix->Satisfy->And is also provided withI.e. matrix->Sum matrix/>No identical characteristic value; />The representation dimension is +.>Is of the identity matrix of (a)
Structure of the deviceMatrix->Satisfy->Is controllable such that the rank of the constructed controllable matrix is +.>The controllability matrix is constructed by the following formula;
，
solving Lyapunov equationUnique solution->，/>Is->Matrix, verification matrix->Is non-singular;
calculating a state estimation gain matrix as follows；
。
6. The method for identifying and correcting parameters of hydraulic simulation model of heat supply network according to claim 5, wherein in step S5, the state estimation value of the flow of the residual branch pipe section is obtained by the following formula:
，
，
wherein,indicate->Time-dependent derivative of the state estimate of the flow of the branch pipe segments at the moment in time,/>Status estimate representing flow of each excess branch pipe segment,/->Is state estimation error, +.>Indicate->Time derivative of the time of day state estimation error, +.>Representation->Time of day state estimation error,/->The initial value of (2) is +.>The method comprises the steps of carrying out a first treatment on the surface of the Along with->Time-of-day monitorable flow value of the spare branch pipe section +.>Continuously obtaining new state estimation value +.>。
7. The method for identifying and correcting parameters of hydraulic simulation model of heat supply network according to claim 6, wherein in step S6, judging whether the state estimation error and speed meet the preset requirements is by judging two norms of the error of the monitorable residual branch pipe section flow value and the state estimation valueWhether to reduce to a preset value; />The expression is as follows:
；
in the method, in the process of the invention,representation->Time-of-day monitorable flow value of the spare branch pipe section,/->Representation->State estimation value of flow of each spare branch pipe section at moment.
8. The method for identifying and correcting parameters of hydraulic simulation model of heat supply network according to claim 7, wherein in step S7, the following is adopted to calculate the estimated value of the impedance of each pipe section of the network:
，
，
in the method, in the process of the invention,estimated value representing impedance of each pipe section of pipe network, +.>Is the flow characteristic curve coefficient of the water pump, < >>Is the frequency conversion ratio of the water pump>The valve opening of the regulating valve; />For adjusting the valve-adjusting ratio of the valve +.>For regulating the valve flow capacity of the valve, +.>Representing a diagonal matrix +_>Estimated value representing resistance of regulating valve, +.>Representing the transpose of matrix C.
9. The method for identifying and correcting parameters of hydraulic simulation model of heat supply network according to claim 8, wherein in step S9, the adjusting and constructing eigenvalues and state estimation gain coefficients of the state estimation gain matrix includes:
adjusting matrixIs corrected by the correction matrix>Adjusting the state estimation gain matrix +.>Is provided.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311475368.9A CN117195778B (en) | 2023-11-08 | 2023-11-08 | Parameter identification correction method for hydraulic simulation model of heating pipe network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311475368.9A CN117195778B (en) | 2023-11-08 | 2023-11-08 | Parameter identification correction method for hydraulic simulation model of heating pipe network |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117195778A true CN117195778A (en) | 2023-12-08 |
| CN117195778B CN117195778B (en) | 2024-02-20 |
Family
ID=88994697
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311475368.9A Active CN117195778B (en) | 2023-11-08 | 2023-11-08 | Parameter identification correction method for hydraulic simulation model of heating pipe network |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117195778B (en) |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105550405A (en) * | 2015-12-07 | 2016-05-04 | 哈尔滨工业大学 | Method for building municipal pipeline hydraulic model |
| 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 |
| CN108629112A (en) * | 2018-05-02 | 2018-10-09 | 苏州爱博斯蒂低碳能源技术有限公司 | A method of pump head is obtained by valve state |
| CN111062139A (en) * | 2019-12-24 | 2020-04-24 | 杭州电子科技大学 | Method for estimating water flow situation of urban underground drainage pipe network |
| CN111274668A (en) * | 2019-12-13 | 2020-06-12 | 天津大学 | Method for improving quality of time sequence data of centralized heat supply pipe network |
| CN111898816A (en) * | 2020-07-21 | 2020-11-06 | 南京信息工程大学 | Dynamic state estimation method for comprehensive energy system |
| CN112818589A (en) * | 2021-01-12 | 2021-05-18 | 大连理工大学 | Heat supply system optimization method based on Bayesian optimization algorithm |
| CN114893822A (en) * | 2022-03-30 | 2022-08-12 | 天津大学 | Hydraulic optimization scheduling method for multi-heat-source annular distributed variable-frequency pump heat supply system |
| CN116362720A (en) * | 2023-03-31 | 2023-06-30 | 杭州莱宸科技有限公司 | Leakage detection method, device and system for coping with operation change situation of water supply network |
-
2023
- 2023-11-08 CN CN202311475368.9A patent/CN117195778B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105550405A (en) * | 2015-12-07 | 2016-05-04 | 哈尔滨工业大学 | Method for building municipal pipeline hydraulic model |
| 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 |
| CN108629112A (en) * | 2018-05-02 | 2018-10-09 | 苏州爱博斯蒂低碳能源技术有限公司 | A method of pump head is obtained by valve state |
| CN111274668A (en) * | 2019-12-13 | 2020-06-12 | 天津大学 | Method for improving quality of time sequence data of centralized heat supply pipe network |
| CN111062139A (en) * | 2019-12-24 | 2020-04-24 | 杭州电子科技大学 | Method for estimating water flow situation of urban underground drainage pipe network |
| CN111898816A (en) * | 2020-07-21 | 2020-11-06 | 南京信息工程大学 | Dynamic state estimation method for comprehensive energy system |
| CN112818589A (en) * | 2021-01-12 | 2021-05-18 | 大连理工大学 | Heat supply system optimization method based on Bayesian optimization algorithm |
| CN114893822A (en) * | 2022-03-30 | 2022-08-12 | 天津大学 | Hydraulic optimization scheduling method for multi-heat-source annular distributed variable-frequency pump heat supply system |
| CN116362720A (en) * | 2023-03-31 | 2023-06-30 | 杭州莱宸科技有限公司 | Leakage detection method, device and system for coping with operation change situation of water supply network |
Non-Patent Citations (3)
| Title |
|---|
| FELIX AGNER ET AL.: "Hydraulic Parameter Estimation in District Heating Networks", 《ARXIV:2211.10395V2 [EESS.SY] 》, pages 1 - 14 * |
| XUEJING ZHENG ET AL.: "Hydraulic transient modeling and analysis of the district heating network", 《SUSTAINABLE ENERGY, GRIDS AND NETWORKS》, pages 1 - 20 * |
| 张军 等: "环状供热管网水力计算方法及应用", 《区域供热》, no. 1, pages 140 - 145 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117195778B (en) | 2024-02-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11204590B2 (en) | State estimation method for heating network in steady state based on bilateral equivalent model | |
| CN108105844B (en) | Intelligent heat exchange station control method based on indoor and outdoor temperature combined compensation | |
| CN107563674A (en) | A kind of electro thermal coupling system state estimation method for considering Dynamic Characteristic of Pipes | |
| Hu et al. | Small leak location for intelligent pipeline system via action-dependent heuristic dynamic programming | |
| CN112113146B (en) | Synchronous self-adaptive check method for roughness coefficient and node water demand of water supply pipe network pipeline | |
| CN107257130B (en) | Low-voltage distribution network loss calculation method based on regional measurement decoupling | |
| CN104500979A (en) | Online diagnosis and elimination system for steam flowing retention section in heating pipe network and working method | |
| CN111898816A (en) | Dynamic state estimation method for comprehensive energy system | |
| CN105740989B (en) | A kind of water supply network anomalous event method for detecting based on VARX model | |
| CN111414721A (en) | Heat supply network waterway modeling method for comprehensive energy system scheduling | |
| CN117195778B (en) | Parameter identification correction method for hydraulic simulation model of heating pipe network | |
| CN109494726A (en) | Stability of power system online evaluation method based on DLRNN neural network | |
| CN108021742A (en) | A kind of steam heating pipeline steady-state operating condition method of estimation for considering hydrophobic model | |
| CN114169239A (en) | Steam pipe network resistance coefficient and heat exchange coefficient identification method based on genetic algorithm | |
| CN112818589B (en) | Heating system optimization method based on Bayesian optimization algorithm | |
| CN111665882A (en) | Temperature control method and system | |
| CN116050037B (en) | Urban drainage system liquid level indirect monitoring and analyzing method based on directed topology network | |
| CN111412391B (en) | Pipe network leakage detection method and system | |
| KR101089170B1 (en) | Advanced process control method for district heat network | |
| CN110847112A (en) | River flood discharge early warning method based on hydraulics simulation | |
| WO2022160681A1 (en) | Method and system for estimating dynamic operation hydraulic state of steam heat supply network | |
| CN108629112B (en) | Method for acquiring water pump lift through valve state | |
| Jensen et al. | Iterative learning pressure control in water distribution networks | |
| CN110795810A (en) | Online hydraulic model generation method | |
| CN112818495A (en) | Novel dynamic correction method for pipeline pressure drop measurement and calculation algorithm parameters |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |