A modeling method for discrete dynamic collectors based on Modelica language

Abstract

The present invention discloses a modeling method of a discrete dynamic collector based on the Modelica language, which builds a molten salt medium model for dynamic simulation; adopts the finite element method to build a dynamic heat exchanger pipeline on the molten salt side; based on the dynamic characteristics of the Modelica grammar, a dynamic molten salt collector based on the finite element method is obtained. The present invention divides the heat exchanger into a series of non-repetitive discrete units based on the finite volume method, considers the radiation heat transfer, convection heat transfer of the heat collecting tube, the mutual influence between the tubes due to temperature, and the heat transfer mode of the molten salt in the tube in each discrete unit, and splits the collector into different components to create their own thermodynamic models. Not only does it realize the function of measuring the dynamic distribution of the temperature and radiation of each tube of the collector, but it can also observe the real-time changes in the thermal state of the medium in the collector, and the heat transfer characteristics in the reaction heat transfer process.

Description

Technical Field

[0001] The invention relates to the field of heat collectors, and in particular to a modeling method of a discrete dynamic heat collector based on Modelica language. Background Art

[0002] Solar thermal power generation technology uses renewable solar energy, reduces pollution, and has high economic efficiency. It is being vigorously promoted and developed. Molten salt is used in energy storage design because of its good heat transfer and heat storage performance. The collector is one of the important components in tower solar power generation. High-temperature and high-pressure molten salt flows in the collector. In order to study the dynamic distribution characteristics of the molten salt temperature in the heat exchanger and improve the solar energy resource conversion efficiency of the overall system, a discrete dynamic modeling method is used to build a heat exchanger, which enables a comprehensive simulation of the dynamic changes in the medium temperature and heat transfer in the heat exchanger.

[0003] Modelica is an object-oriented, open source, non-causal, multi-physics modeling language that uses non-causal mathematical descriptions, uses equations to represent system behavior, supports dynamic, discrete physical system modeling, and is widely used in modeling and simulation of complex physical systems in multiple fields. The connections between model elements satisfy the generalized Kirchhoff's law, which can realize coupled modeling and simulation of multiple fields and multiple systems, and serve the virtual design and heat collection optimization of molten salt tower power generation systems. Summary of the invention

[0004] Purpose of the invention: In view of the defects of the prior art, the present invention discloses a modeling method for a dynamic and discrete tower solar power generation system based on the Modelica language.

[0005] Technical solution: In order to achieve the above technical objectives, the present invention adopts the following technical solution.

[0006] A modeling method for a discrete dynamic collector based on Modelica language includes the following steps:

[0007] S1. Build a molten salt medium model for dynamic simulation and add the derivative function of the molten salt medium properties with respect to time;

[0008] S2. Build a collector pipeline model for fluid heat transfer based on the finite volume method; discretize the fluid pipeline into n control volumes along the length direction, define the boundary variables and source terms of the control volumes, and construct the mass, momentum and energy balance equations between the n control volumes;

[0009] S3. Build a collector outer surface model that absorbs solar radiation based on the finite volume method; discretize the collector into n control volumes along the pipeline flow direction, and define the number of collector pipelines as m, that is, discretize the collector outer tube screen into m×n control volumes, and construct the heat transfer equation of the control volume;

[0010] S4. Based on the syntax of Modelica language, connect each discrete unit, connect each component, construct connection equations, and obtain the collector pipeline model based on discrete units.

[0011] Beneficial effects:

[0012] 1. Modelica is a secondary development language for dynamic performance simulation models based on differential algebraic equations. It supports continuous and discrete system modeling and simulation calculations. It can cross different fields and easily realize the modeling of large, complex, and multi-disciplinary physical systems. The mathematical description of the Modelica model is differential, algebraic, and discrete equations (groups). The relevant Modelica tools can determine how to automatically solve the equation variables without manual processing. The Modelica language enables developers to focus on building mathematical models of objects without having to worry too much about the process of model solving and programming implementation. The Modelica language can improve the efficiency of modeling and the reusability of the model.

[0013] 2. The Modelica language organizes and encapsulates data with classes as the center. Connectors define flow variables and potential variables, ensuring the directionality of flow. It supports connecting components through connectors, thereby building the transfer of physical quantities between components.

[0014] 3. Modelica language adopts non-causal modeling. When declaring an equation, there is no limit on the solution direction of the equation. The solution direction of the equation is ultimately determined automatically by the simulation solver according to the data flow environment of the equation system, making it easier to build a dynamic collector pipeline model. The finite volume method can be used to more intuitively observe the temperature distribution of the collector. This solution speed is much faster than the computational fluid dynamics method, providing great convenience for engineering design and theoretical discussion. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flow chart of a collector pipe modeling method of the present invention;

[0016] Figure 2 It is a schematic diagram of the finite volume discreteness of the molten salt side pipeline of the present invention;

[0017] Figure 3 It is a schematic diagram of the molten salt side tube wall of the present invention;

[0018] Figure 4 It is a schematic diagram of the collector tube panel of the present invention;

[0019] Figure 5 It is an overall schematic diagram of the heat collector of the present invention. DETAILED DESCRIPTION

[0020] The present invention provides a modeling method for a dynamic collector based on the Modelica language, which can not only realize the function of measuring the dynamic distribution of the temperature and radiation of each tube of the collector, but also can observe the real-time change of the thermal state of the medium in the collector and the heat transfer characteristics in the reaction heat transfer process. The present invention will be described in detail below with reference to the accompanying drawings and in combination with examples.

[0021] The dynamic heat exchanger modeling method based on Modelica language of the present invention is mainly implemented by the following steps, as shown in the attached figure: Figure 1 A collector pipeline modeling method for a discrete dynamic collector based on Modelica language includes the following steps:

[0022] S1. Build a molten salt medium model for dynamic simulation and add the derivative function of the molten salt medium properties with respect to time;

[0023] S2. Build a collector pipeline model for fluid heat transfer based on the finite volume method; discretize the fluid pipeline into n control volumes along the length direction, define the boundary variables and source terms of the control volumes, and construct the mass, momentum and energy balance equations between the n control volumes;

[0024] S3. Build a collector outer surface model that absorbs solar radiation based on the finite volume method; discretize the collector into n control volumes along the pipeline flow direction, and define the number of collector pipelines as m, that is, discretize the collector outer tube screen into m×n control volumes, and construct the heat transfer equation of the control volume;

[0025] S4. Based on the syntax of Modelica language, connect each discrete unit, connect each component, construct connection equations, and obtain the collector pipeline model based on discrete units.

[0026] The Dymola software supports the general simulation language Modelica. In this embodiment, the process implemented in the Dymola software is given. It should be noted that the method described in the present invention can be implemented in other simulation software supporting the Modelica language. The following steps are implemented in the Dymola software:

[0027] Step 1: Add the derivative functions of the dynamic viscosity, density, specific enthalpy and other physical quantities of the molten salt to the time in the molten salt medium model, which are used for the dynamic heat transfer calculation of the heat exchange medium in the heat exchanger.

[0028] The derivative of dynamic viscosity with respect to time is:

[0029]

[0030] in is the dynamic viscosity, For time, is the temperature, is the exponent part, which represents the power of 10;

[0031] Derivative of density with respect to time:

[0032]

[0033] in is the density;

[0034] Derivative of specific enthalpy with respect to time:

[0035]

[0036] in is the specific enthalpy.

[0037] In the medium property function, use a statement to indicate the function package that points to the time derivative. For example, in the function package that calculates dynamic viscosity, add the following statement:

[0038]

[0039] In the dynamic heat transfer calculation of the heat exchange tube, Calculate the time derivative of the dynamic viscosity.

[0040] Step 2: If Figure 2 As shown, the finite volume method is used to discretize the pipeline into n parts along the length of the pipeline. The mass and energy dynamic balance model of each control volume is defined in the thermal unit of the heat exchange pipeline, and the momentum conservation equation of the control body is defined in the hydraulic unit.

[0041] (11) Dynamic mass conservation equation:

[0042]

[0043] In nodes 1 to n, there are

[0044]

[0045] in, is the mass flow rate of the ith control volume, is the discrete number of collector pipes, is the fluid volume of the ith control volume, is the medium density of the ith control volume, is the mass flow rate of the fluid across the segment boundary of the ith control volume, is the mass flow rate of the fluid across the segment boundary of the i+1th control volume, is the time derivative of the mass flow rate of the ith control volume, is the source term flow rate of the ith control volume; .

[0046] (12) Dynamic energy conservation equation:

[0047]

[0048] in, is the internal energy of the fluid in the ith control volume, is the fluid enthalpy of the ith control volume, is the mechanical work, is the heat flux of the ith control volume;

[0049]

[0050] Using the upwind discretization method, calculate :

[0051]

[0052] in is the enthalpy flow value of the first control volume where the fluid crosses the segment boundary, is the enthalpy flow value of the last control volume where the fluid crosses the segment boundary, is the enthalpy flow value of the ith control volume, where , semilinear is a function for solving differential equations; is the mass flow rate of the fluid across the segment boundary of the ith control volume, is the enthalpy of the i-1th control volume, is the enthalpy of the ith control volume, is the mass flow rate at port a, is the mass flow rate at port b, is the enthalpy at port a, is the enthalpy at port b;

[0053] (13) Dynamic momentum conservation equation:

[0054] Using a staggered grid, n-1 momentum balance equations are defined between n control volumes;

[0055]

[0056] in, is the momentum of the control volume, is the momentum of the fluid across the segment boundary, is the pressure of the control volume, It is friction and gravity;

[0057]

[0058] in, is the fluid density of the ith control volume, is the fluid density of the i+1th control volume, is the average flow rate in the ith control volume, is the average flow rate in the i+1th control volume, is the cross-sectional area of ​​the ith control volume, is the cross-sectional area of ​​the i+1th control volume;

[0059] The spatial discretization of the pipe wall corresponds to the discretization of the connected fluid model; the pipe wall is discretized into n segments along the length direction, and the first and last thermal interfaces are used , Represents a section of pipe wall, each section of which is perpendicular to the heat conduction;

[0060] like Figure 3 As shown in the figure, the wall interface represents the surface temperature of the wall, which is used to exchange heat work. The three variables of enthalpy, temperature and density need to be calculated in N equally spaced nodes of the control volume, including the fluid inlet node infl and the fluid outlet node outfl.

[0061] Dynamic mass conservation equation:

[0062]

[0063] in, is the time derivative of the mass flow rate in each control volume between two nodes, is the number of parallel pipelines, is the pipe inlet mass flow rate, is the pipe outlet mass flow rate, is the cross-sectional area of ​​the pipe, is the pipe length, is the derivative of the density of the ith control volume with respect to the enthalpy value, is the derivative of the average density of the ith control volume with respect to the enthalpy value, is the time derivative of the enthalpy of the ith control volume, is the derivative of the density of the ith control volume with respect to pressure, is the derivative of the density of the i+1th control volume with respect to the enthalpy value, is the derivative of the average pressure of the ith control volume with respect to the enthalpy, is the time derivative of the pressure of the ith control volume; is the time derivative of the mass flow rate of the ith control volume;

[0064] Dynamic energy conservation equation:

[0065]

[0066] in, is the medium density of the ith control volume, is the time derivative of the enthalpy of the ith control volume, is the mass flow rate through the ith control volume of a single pipe, , is the specific enthalpy of the fluid at the i-th and i+1-th control volume nodes, is the time derivative of pressure, is the heat flux from the boundary into the i-th control volume; is the density of the ith control volume, is the density of the i+1th control volume;

[0067]

[0068] in, is the specific heat capacity of the collector, is the mass of the jth collector tube wall, is the derivative function of the jth collector tube wall temperature with respect to time, is the heat flux into the thermal interface of the jth collector tube wall, is the heat flux outflowing from the thermal interface of the jth collector tube wall;

[0069]

[0070] in, is the thermal conductivity of the collector tube wall material, is the collector tube wall thickness, , is the interface node temperature, is the heat transfer area;

[0071] Momentum conservation equation:

[0072]

[0073] in, is the mass flow rate, is the pipeline fluid momentum, is the pipeline inlet pressure, is the pipe outlet pressure, is the water head pressure drop, is the friction loss.

[0074] Step 3: If Figure 4As shown in the figure, the direct radiation generated by the sun acts on the tube panel, generating radiation heat absorption. At the same time, the tube panel radiates heat to the sky, performs convective heat exchange with the surrounding air, and performs radiation heat dissipation between the tube panels. Finally, the total net heat flowing through the tube panel passes through the tube wall interface port_b, and is transferred to the tube wall interface port_a through wall heat conduction. Finally, the heat is transferred to the fluid in the pipe.

[0075] The collector is discretized into n control volumes along the pipeline flow direction, and the number of collector pipelines is defined as m, that is, the outer tube screen of the collector is discretized into m×n control volumes, and the heat transfer equation of the control volume is constructed;

[0076] Use heat transfer equations to describe the state of each control volume;

[0077] (1) Radiant heat absorption:

[0078]

[0079] Among them, Q abs is the radiation heat, DNI is the direct solar radiation, α rec is the absorption rate;

[0080] (2) Heat transfer to the sky:

[0081]

[0082] Among them, Q rad is the radiation heat transfer, σ is the Stefan-Boltzmann constant, T surf is the collector surface temperature, T sky is the sky temperature, A1 is the surface area, and ε is the reflectivity;

[0083] (3) Convective heat transfer:

[0084]

[0085] Among them, Q conv is the convective heat transfer, h c is the convective heat transfer coefficient, T surf is the collector surface temperature, T amb is the ambient temperature;

[0086] (4) Heat transfer loss from radiation between tubes:

[0087]

[0088] Among them, Q radloss is the radiation heat loss, is the surface temperature of the jth collector tube wall, is the surface temperature of the j+1th collector tube wall, VF is the angular coefficient, is the reflectivity of the jth collector tube wall; is the reflectivity of the j+1th collector tube wall;

[0089] (5) Net heat transfer

[0090]

[0091] in, is the net heat transfer, To absorb heat, To exchange heat for radiation to the sky, is the radiation loss heat between the tubes, Convection heat transfer.

[0092] Step 4, such as Figure 5 As shown, the discrete units are connected based on the connect statement of the Modelica language, and the connection equation is constructed to obtain the collector model based on the finite volume method.

[0093] The simulation modeling of the solar collector of the photothermal system of the present invention uses the finite volume method to discretize the collector space. Based on the finite volume method, the heat exchanger is divided into a series of non-repetitive discrete units, and each discrete unit is represented by a node. In each discrete unit, the radiation heat transfer, convection heat transfer, mutual influence between tubes due to temperature, and heat transfer mode of molten salt in the tube of the collector are considered, and the collector is split into different components to create their own thermodynamic models, which are then converted into the continuous control equations in the solution area. The discrete equations of the relationship between the function values ​​to be solved on the unit nodes facilitate researchers to conduct one-dimensional dynamic monitoring and alleviate the problem of slow iteration speed of three-dimensional simulation to a certain extent.

[0094] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A modeling method for discrete dynamic collectors based on Modelica language, characterized by: The following steps are involved: S1. Build a molten salt medium model for dynamic simulation and add the derivative function of the molten salt medium properties with respect to time; The process of building the molten salt medium model is to add the derivative of the physical quantity of the molten salt with respect to time in the molten salt medium package, wherein the physical quantity includes dynamic viscosity, density, and specific enthalpy; The derivative of dynamic viscosity with respect to time is: Where η is the dynamic viscosity, t is the time, T is the temperature, and e is the exponential part, which represents the power of 10; Derivative of density with respect to time: Where ρ is the density; Derivative of specific enthalpy with respect to time: Where h is the specific enthalpy; S2. Build a collector pipeline model for fluid heat transfer based on the finite volume method; discretize the fluid pipeline into n control volumes along the length direction, define the boundary variables and source terms of the control volumes, and construct the mass, momentum and energy balance equations between the n control volumes; S3. Build a collector outer surface model that absorbs solar radiation based on the finite volume method; discretize the collector into n control volumes along the pipeline flow direction, and define the number of collector pipelines as m, that is, discretize the collector outer tube screen into m×n control volumes, and construct the heat transfer equation of the control volume; The specific process is: use heat transfer formula to describe the state of each control volume; The outer wall of the collector absorbs the radiation generated by DNI, the tube wall loses radiation to the sky, generates convection heat transfer to the air, and there is radiation heat transfer between the tubes. Finally, the outer wall transfers the net heat to the wall behind it, and the wall transfers it to the fluid through heat conduction; (1) Radiant heat absorption: Q abs =DNI×α rec Among them, Q abs is the radiation heat, DNI is the direct solar radiation, α rec is the absorption rate; (2) Heat transfer to the sky: Among them, Q rad is the radiation heat transfer, σ is the Stefan-Boltzmann constant, T surf is the collector surface temperature, T sky is the sky temperature, A1 is the surface area, and ε is the reflectivity; (3) Convective heat transfer: Among them, Q conv is the convective heat transfer, h c is the convective heat transfer coefficient, T surf is the collector surface temperature, T amb is the ambient temperature; (4) Heat transfer loss from radiation between tubes: Among them, Q radloss is the radiation heat loss, T surf,j is the surface temperature of the jth collector tube, T surf,j+1 is the surface temperature of the j+1th collector tube, VF is the angular coefficient, ε j is the reflectivity of the jth collector; ε j+1 is the reflectivity of the j+1th collector tube; A is the cross-sectional area of ​​the tube; (5) Net heat transfer Q net =Q abs +Q rad -Q radloss -Q conv Among them, Q net is the net heat transfer, Q abs To absorb heat, Q rad is the radiation heat exchange to the sky, Q radloss is the radiation loss heat between the tubes, Q conv It is convection heat transfer; S4. Based on the syntax of Modelica language, connect each discrete unit, connect each component, construct connection equations, and obtain a collector model based on discrete units.

2. The modeling method of discrete dynamic collector based on Modelica language according to claim 1, characterized in that: Defining the boundary variables and source terms of the control volumes as described in step S2 above, and constructing the mass and energy balance equations of n control volumes; The specific process is: (11) Dynamic mass conservation equation: ms i =V i ×ρ i before i =mf i -mf i+1 In nodes 1 to n, there are Among them, ms i is the mass flow rate of the ith control volume, n is the discrete number of collector pipes, V i is the fluid volume of the ith control volume, ρ i is the medium density of the ith control volume, mf i is the mass flow rate of the fluid across the segment boundary of the ith control volume, mf i+1 is the mass flow rate of the fluid across the segment boundary of the i+1th control volume, is the time derivative of the mass flow rate of the ith control volume, mb i is the source term flow rate of the i-th control volume; 1<i<n+1; (12) Dynamic energy conservation equation: Among them, US i is the internal energy of the fluid in the ith control volume, Hb i is the fluid enthalpy of the ith control volume, Wb i is the mechanical work, Qb i is the heat flux of the ith control volume; Hb i =Hf i -Hf i+1 Using the upwind discretization method, calculate Hf i : Hf i =semilinear(mf i ,mediums i-1 .h,mediums i .h) Hf1=semilinear(port_a.m_flow,instream(port_a.h_outflow),mediums1.h) Hf n+1 =-semilinear(port_b.m_flow,instream(port_b.h_outflow),mediums n .h) Where Hf1 is the enthalpy flow value of the first control volume of the fluid across the segment boundary, Hf n+1 is the enthalpy flow value of the last control volume where the fluid crosses the segment boundary, Hf i is the enthalpy flow value of the i-th control volume, where 1<i<n+1, mf i is the mass flow rate of the fluid across the segment boundary of the ith control volume, semilinear is the function for solving the differential equation, mediums i-1 .h is the enthalpy of the i-1th control volume, mediums i .h is the enthalpy of the ith control volume, port_a.m_flow is the mass flow rate at port a, port_b.m_flow is the mass flow rate at port b, port_a.h_outflow is the enthalpy at port a, and port_b.h_outflow is the enthalpy at port b; (13) Dynamic momentum conservation equation: Using a staggered grid, n-1 momentum balance equations are defined between n control volumes; in, is the momentum of the control volume, Ib f is the momentum of the fluid across the segment boundary, Fs p is the pressure of the control volume, Fs fg It is friction and gravity; Ib f =ρ i ×vs i 2 ×A i -r i+1 ×vs i+1 2 ×A i+1 Among them, ρ i is the fluid density of the ith control volume, ρ i+1 is the fluid density of the i+1th control volume, vs i is the average flow rate in the ith control volume, vs i+1 is the average flow rate in the i+1th control volume, A i is the cross-sectional area of ​​the ith control volume, A i+1 is the cross-sectional area of ​​the i+1th control volume; The spatial discretization of the pipe wall corresponds to the discretization of the connected fluid model; the pipe wall is discretized into n segments along the length direction, and the first and last thermal interfaces heatPort_a and heatPort_b are used to represent a section of the pipe wall. Each section of the pipe wall is perpendicular to the heat conduction. The pipe wall interface represents the surface temperature of the pipe wall and is used to exchange heat work. The three variables of enthalpy, temperature, and density need to be calculated at N equally spaced nodes in the control volume, including the inlet node and the outlet node. (21) Dynamic mass conservation equation: where dMdt is the time derivative of the mass flow rate in each control volume between two nodes, Nt is the number of parallel pipes, and m in is the pipe inlet mass flow rate, m out is the mass flow rate at the pipe outlet, A is the cross-sectional area of ​​the pipe, l is the length of the pipe, is the derivative of the density of the ith control volume with respect to the enthalpy value, The derivative of the average density of the ith control volume with respect to the enthalpy, is the time derivative of the enthalpy of the ith control volume, is the derivative of the density of the ith control volume with respect to pressure, is the derivative of the density of the i+1th control volume with respect to the enthalpy value, is the derivative of the average pressure of the ith control volume with respect to the enthalpy, is the time derivative of the pressure of the ith control volume; dMdt i is the time derivative of the mass flow rate of the ith control volume; (22) Dynamic energy conservation equation: Among them, ρ bi is the medium density of the ith control volume, is the time derivative of the enthalpy of the ith control volume, is the mass flow rate through the ith control volume of a single pipeline, h i 、h i+1 is the specific enthalpy of the fluid at the i-th and i+1-th control volume nodes, is the time derivative of pressure, is the heat flux from the boundary into the i-th control volume; ρ i is the density of the ith control volume, ρ i+1 is the density of the i+1th control volume; Among them, c wall is the specific heat capacity of the collector tube, m j is the mass of the jth collector tube wall, is the derivative function of the wall temperature of the jth collector tube with respect to time, Q heatPort_a[j] is the heat flux into the thermal interface of the jth collector, Q heatPort_b[j] is the heat flux outflowing from the thermal interface of the jth collector; Q heatPort_a[j] 2×K wall / s×(Ta j -T j )×a h / n Q heatPort_b[j] =2×K wall / s×(Tb j -T j )×a h / n Among them, K wall is the thermal conductivity of the collector tube wall material, s is the collector tube wall thickness, Ta j , Tb j is the interface node temperature, a h is the heat transfer area; (23) Momentum conservation equation: L / A×dwdt+(p out -p in )+dp stat +dp fric =0 Where w is the mass flow rate, dwdt is the pipeline fluid momentum, and p in is the pipeline inlet pressure, p out is the pipe outlet pressure, dp stat is the head pressure drop, dp fric is the friction loss.

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