CN107657095A - A method for optimizing the structure and operating parameters of a porous media solar heat absorber - Google Patents

Abstract

The invention discloses a kind of porous media solar heat absorber structure and optimization of operating parameters method applied to solar energy optical-thermal transformation technology field.The heat transfer characteristic of porous media solar heat absorber is calculated using Thermal Non-equilibrium Model, coupling genetic algorithm optimizes to the structural parameters and operational factor of heat dump, to obtain the parameter combination for causing heat dump best performance.The present invention has considered heat dump heat absorption, heat exchange links, and the automatic screening of parameter is realized using intelligent optimization algorithm, realizes multi-parameter while the function of optimization.The present invention has high efficiency, accuracy and versatility, can largely save the manpower and time cost of design, improve the precision of optimization, while can be used in design optimization parameter difference, optimization object function difference, the different porous media heat dump of geometry.

Description

A method for optimizing the structure and operating parameters of a porous media solar heat absorber

technical field

The invention belongs to the field of solar heat utilization, and in particular relates to a structure and an operation parameter optimization method of a porous medium solar heat absorber.

Background technique

Concentrating solar thermal power generation technology is a clean, safe, reliable and promising renewable energy utilization technology. As a key component in the conversion of light energy to heat energy, the solar thermal absorber is optimized for its heat transfer performance to provide an important guarantee for the efficient operation of the entire system. As a new type of volumetric heat absorber, porous media heat absorber has attracted great attention from scholars at home and abroad in recent years. Its high porosity allows solar radiation to be absorbed inside the heat absorber, forming a "bulk absorption" effect; and its complex and disordered three-dimensional structure increases the heat transfer surface, enhancing the heat exchange fluid and heat absorber. The previous convective heat transfer efficiency. However, the actual installation and commercial operation of porous media solar thermal absorbers still face a series of challenges. These include: (1) The research on porous media solar heat absorbers focuses on the influence of a single variable on the performance of the heat absorber, and there is a lack of multivariate analysis methods; (2) There is a lack of design methods for porous media heat absorbers. Under the specified conditions, there is no method to reasonably select the structural parameters and operating parameters of the heat sink to ensure the efficient operation of the heat sink.

At present, scholars at home and abroad have carried out a series of research on porous media solar heat absorbers. Wu et al. used the non-thermal equilibrium model (LTNE) coupled with the P1 model to solve the heat transfer characteristics of porous media solar heat absorbers. The effects of the porosity, pore size, thermal conductivity of the porous media and the flow velocity at the inlet of the absorber on the temperature distribution inside the absorber were studied respectively. Chen et al. used Monte Carlo ray tracing (MCRT) technology to obtain the distribution of solar radiation energy inside the porous media heat absorber, and coupled the non-heat balance model and P1 model to solve the flow heat transfer process inside the porous media solar heat absorber. . The influence of different solar radiation models on the calculation results is analyzed. S. Mey-Cloutier et al. experimentally studied the photothermal conversion efficiency of ceramic porous media of different materials as solar heat absorption. At the same time, the influence of geometric structure parameters (porosity, pore diameter, etc.) of porous media on the overall performance of the heat sink is analyzed. From the above analysis, it can be seen that the research on porous media solar heat absorbers mostly focuses on the analysis of the influence of a single parameter on the performance of the heat absorber. In order to screen heat absorbers with excellent performance, a lot of numerical simulation and experimental work are required. At the same time, in the case of multiple parameters changing at the same time, the existing research work fails to provide an optimal method for the parameters of the heat sink.

Contents of the invention

The purpose of the present invention is to address the deficiencies in the current research and design of porous media solar heat absorbers, and propose a high-efficiency optimization suitable for single-variable and multi-variable, which can realize the automatic optimization of heat absorber parameters, so as to meet the optimization requirements. A method for optimizing the structure and operating parameters of porous media solar heat absorbers for the required porous media structure parameters and heat absorber operating parameters.

In order to achieve the above object, the technical scheme adopted in the present invention is:

Step 1): Determine the non-optimized geometric parameters and operating parameters of the porous media solar heat absorber to be optimized;

Step 2): Initialize the geometric parameters and operating parameters of the porous media solar heat absorber to be optimized;

Step 3): According to the geometric parameters and operating parameters optimized by initialization or genetic algorithm, using Beer's law and the reflection characteristics of porous media, calculate the transmission loss and reflection loss of the porous media heat absorber, so as to determine the absorption rate; derive solar radiation according to Beer's law Distribution of energy flux density inside the absorber:

I(x)=I(0)Cβe ^-βx

I(x) is the radiation energy flux density at position x, C is the correction coefficient calculated according to the transmission and reflection losses, and β is the attenuation coefficient of porous media;

Step 4): Using the non-heat balance model to couple the Rosseland diffusion equation to solve the flow heat transfer inside the porous media solar heat absorber:

In the formula: ρ, u, μ, c _p , T _f , λ _fe are the density, velocity, dynamic viscosity coefficient, specific heat capacity at constant pressure, temperature and effective thermal conductivity of the heat exchange fluid respectively; ε, K, C _F , λ _se , T _s , n, k _r are the porosity, permeability, inertia coefficient, effective thermal conductivity, temperature, refractive index and equivalent radiation thermal conductivity of the porous medium skeleton. h _v volumetric convective heat transfer coefficient between the porous medium and the heat transfer fluid;

Step 5) Calculate the convergence, obtain the flow transfer characteristics of the porous media solar heat absorber, and calculate the thermal efficiency evaluation parameters of the heat absorber:

is the mass flow rate, q _in is the solar radiation intensity, and S _in is the front area of the heat sink. And pass the evaluation parameters to the genetic algorithm;

Step 6) The genetic algorithm performs crossover, mutation, and migration genetic calculations based on the evaluation parameters in step 5), updates the variables to be optimized, repeats steps 3), 4), and 5), and gradually obtains a porous medium structure with higher thermal efficiency parameters and the operating parameters of the heat sink, and finally the genetic algorithm reaches convergence and obtains the optimal parameter value.

The geometric parameters of the porous medium include the geometric dimensions of the porous medium, namely length, width, and height, the porosity of the porous medium, and the aperture of the porous medium; the operating parameters include inlet flow velocity, inlet temperature, and solar radiation energy flow density.

The characteristics of the heat absorber provided by the present invention are: a heat absorber with metal foam or porous ceramic material as the heat absorbing core, the metal foam or porous ceramic material has a three-dimensional through-hole structure connected in three dimensions, and has a relatively high through-hole ratio and Good thermal conductivity.

Since there are many factors affecting the porous medium solar heat absorber, and there are mutual constraints among the factors, the present invention makes full use of the efficient optimal solution search characteristic of the genetic algorithm. The non-heat balance model is used to calculate the heat transfer characteristics and thermal efficiency of the porous media solar heat absorber under specified conditions, and the genetic algorithm is used to automatically and efficiently search for the optimal solution that meets the optimization conditions. By coupling the thermal balance model and the genetic algorithm, the automatic evaluation and screening of porous media solar heat absorbers can be realized, and the efficiency of optimal design can be improved.

Description of drawings

Fig. 1 is a flowchart of the optimization method of the present invention;

Detailed ways

Below in conjunction with the accompanying drawings, the present invention will be described in detail by taking the simultaneous optimization of the porous medium porosity, aperture and heat absorber inlet flow velocity as an example:

As shown in Figure 1, the method for optimizing the structure and operating parameters of the porous medium solar heat absorber of the present invention is as follows:

First, the non-optimized geometric structure parameters and operating parameters of the porous media heat absorber are clarified. The two-dimensional calculation area is selected to represent the porous medium solar heat absorber, and its width and thickness are respectively set to 5cm and 4cm; the porous medium material is selected as silicon carbide, and the heat exchange fluid is selected as air; the temperature of the inlet air is set to 300K; The inlet solar radiation flux density is set to 600kW/m ² . At the same time, the value direction of the parameters to be optimized is limited. Here, the porosity of the porous medium is set at 0.65-0.95, the pore diameter is 0.5mm-2.0mm, and the inlet flow velocity is 0.5-2m/s.

Second, the reflection loss R and transmission loss T of the porous medium are calculated according to the specified heat absorber structural parameters (thickness, porosity, pore size). The reflection loss is calculated based on the numerical simulation results of Simon Guévelou et al.; the transmission loss is derived using Beer's law:

T=1-e- ^βx

In the formula, the attenuation coefficient is calculated using the assumption of geometric optics:

where d _p is the pore diameter of the porous medium. Correction coefficient C=1-RT. The distribution of solar radiation energy flux density inside the heat absorber is:

I(x)=I(0)Cβe ^-βx

Then, solve the flow heat transfer governing equation of the porous media solar heat absorber:

The empirical parameters in the formula are all calculated using the empirical correlation formulas related to the structural parameters of porous media. The empirical formula of Wu et al. is adopted here:

After solving the governing equation, the heat transfer characteristics of the porous media solar heat absorber are obtained, and the thermal efficiency is selected as the evaluation index of the heat absorber:

Next, the thermal efficiency value of the heat sink is fed back to the genetic algorithm, and the genetic algorithm performs genetic operations such as crossover, mutation, and migration to update the reserved parameter combinations to be optimized. Then, the calculation of the solar radiation absorption rate, the calculation of the solar radiation energy flow density distribution and the calculation of the thermal efficiency of the heat absorber are repeated until the genetic algorithm converges.

Finally, the porosity, pore size, and absorber inlet flow rate of the porous medium that optimize the thermal efficiency of the absorber are obtained. The optimization results show that under the experimental conditions, the optimum porosity of the heat absorber is 0.95, the optimum pore diameter is 1.78mm, and the optimum inlet velocity is 2.0m/s.

Table 1 shows the optimal combination of porosity, pore diameter and inlet velocity parameters under different thickness conditions of porous medium solar heat absorbers using the optimization method proposed by the present invention.

Table 1 Optimal combination of porosity, pore size and inlet velocity for solar heat absorbers with different thicknesses of porous media

It can be seen that the porous media solar heat absorber structure and operation parameter optimization method proposed by the present invention can optimize multiple variables at the same time, and can efficiently obtain the optimal parameter combination of the heat absorber. In the case of a thicker heat absorber, high porosity and high flow rate are beneficial to improve the efficiency of the heat absorber. This is because high porosity is conducive to increasing the penetration depth of solar radiation and reducing the energy flux density on the surface of the heat absorber, thereby reducing the surface temperature of the heat absorber and reducing radiation heat loss. The high flow rate is conducive to strengthening convective heat transfer, and is also conducive to reducing the surface temperature of the heat absorber. And the optimal pore size gradually increases with the increase of the thickness of the heat sink. In the case of smaller thickness, the optimal porosity and pore size are relatively reduced. Smaller porosity and pore size can reduce the transmission heat loss of the heat absorber and reduce the interval when the solid-liquid phase reaches thermal equilibrium. In this way, the fluid can reach a higher temperature in a shorter heat exchange interval.

The invention proposes a method for optimizing the structure and operating parameters of a porous medium solar heat absorber by coupling the non-heat balance model of the porous medium and the genetic algorithm. The invention can conveniently design the porous medium solar heat absorber, and provides a new idea for the screening of the structural parameters and operating parameters of the heat absorber.

Claims (2)

1. a kind of porous media solar heat absorber structure and optimization of operating parameters method, it is characterised in that comprise the following steps：

Step 1)：Determine the unoptimizable geometric parameter and operational factor of porous media solar heat absorber to be optimized；

Step 2)：Initialize the geometric parameter and operational factor of porous media solar heat absorber to be optimized；

Step 3)：According to initialization or the geometric parameter and operational factor of genetic algorithm optimization, using Beer laws and porous Jie Matter reflection characteristic, the transmission loss and reflection loss of porous media heat dump are calculated, so that it is determined that absorptivity；According to Beer laws Export distribution of the solar radiation energy-flux density inside absorber：

I (x)=I (0) C β e^-βx

I (x) is the radiant emittance at x position, and C is the correction factor being calculated according to transmission and reflection loss, and β is more The attenuation coefficient of hole medium；

Step 4)：Rosseland diffusion equations are coupled using Thermal Non-equilibrium Model, solved inside porous media solar heat absorber Fluid interchange：

<mrow> <mo>&amp;dtri;</mo> <mrow> <mo>(</mo> <mi>&amp;rho;</mi> <mover> <mi>u</mi> <mo>&amp;RightArrow;</mo> </mover> <mo>)</mo> </mrow> <mo>=</mo> <mn>0</mn> </mrow>

<mrow> <mo>&amp;dtri;</mo> <mrow> <mo>(</mo> <mfrac> <mrow> <mi>&amp;rho;</mi> <mover> <mi>u</mi> <mo>&amp;RightArrow;</mo> </mover> <mover> <mi>u</mi> <mo>&amp;RightArrow;</mo> </mover> </mrow> <mi>&amp;epsiv;</mi> </mfrac> <mo>)</mo> </mrow> <mo>=</mo> <mo>-</mo> <mi>&amp;epsiv;</mi> <mo>&amp;dtri;</mo> <mi>p</mi> <mo>+</mo> <mo>&amp;dtri;</mo> <mrow> <mo>(</mo> <mi>&amp;mu;</mi> <mo>&amp;dtri;</mo> <mover> <mi>u</mi> <mo>&amp;RightArrow;</mo> </mover> <mo>)</mo> </mrow> <mo>-</mo> <mfrac> <mrow> <mi>&amp;mu;</mi> <mi>&amp;epsiv;</mi> </mrow> <mi>K</mi> </mfrac> <mover> <mi>u</mi> <mo>&amp;RightArrow;</mo> </mover> <mo>-</mo> <mfrac> <mrow> <msub> <mi>&amp;rho;&amp;epsiv;C</mi> <mi>F</mi> </msub> <mrow> <mo>|</mo> <mover> <mi>u</mi> <mo>&amp;RightArrow;</mo> </mover> <mo>|</mo> </mrow> </mrow> <msqrt> <mi>K</mi> </msqrt> </mfrac> <mover> <mi>u</mi> <mo>&amp;RightArrow;</mo> </mover> </mrow>

<mrow> <mo>&amp;dtri;</mo> <mrow> <mo>(</mo> <msub> <mi>&amp;rho;c</mi> <mi>p</mi> </msub> <mover> <mi>u</mi> <mo>&amp;RightArrow;</mo> </mover> <msub> <mi>T</mi> <mi>f</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mo>&amp;dtri;</mo> <mrow> <mo>(</mo> <msub> <mi>&amp;lambda;</mi> <mrow> <mi>f</mi> <mi>e</mi> </mrow> </msub> <mo>&amp;dtri;</mo> <msub> <mi>T</mi> <mi>f</mi> </msub> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>h</mi> <mi>v</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>T</mi> <mi>s</mi> </msub> <mo>-</mo> <msub> <mi>T</mi> <mi>f</mi> </msub> <mo>)</mo> </mrow> </mrow>

<mrow> <mn>0</mn> <mo>=</mo> <mo>&amp;dtri;</mo> <mrow> <mo>(</mo> <msub> <mi>&amp;lambda;</mi> <mrow> <mi>s</mi> <mi>e</mi> </mrow> </msub> <mo>&amp;dtri;</mo> <msub> <mi>T</mi> <mi>s</mi> </msub> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>h</mi> <mi>v</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>T</mi> <mi>f</mi> </msub> <mo>-</mo> <msub> <mi>T</mi> <mi>s</mi> </msub> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mi>S</mi> <mi>r</mi> </msub> </mrow>

<mrow> <msub> <mi>q</mi> <mi>r</mi> </msub> <mo>=</mo> <mo>-</mo> <msub> <mi>k</mi> <mi>r</mi> </msub> <mfrac> <mrow> <mi>d</mi> <mi>T</mi> </mrow> <mrow> <mi>d</mi> <mi>x</mi> </mrow> </mfrac> <mo>=</mo> <mo>-</mo> <mfrac> <mrow> <mn>16</mn> <msup> <mi>n</mi> <mn>2</mn> </msup> <msup> <mi>&amp;sigma;T</mi> <mn>3</mn> </msup> </mrow> <mrow> <mn>3</mn> <mi>&amp;beta;</mi> </mrow> </mfrac> <mfrac> <mrow> <mi>d</mi> <mi>T</mi> </mrow> <mrow> <mi>d</mi> <mi>x</mi> </mrow> </mfrac> </mrow>

In formula：ρ、u、μ、c_p、T_f、λ_feIt is density, speed, dynamic viscosity coefficient, specific heat capacity at constant pressure, the temperature of heat exchanging fluid respectively And efficient thermal conductivity；ε、K、C_F、λ_se、T_s、n、k_rIt is porosity, permeability, inertia coeffeicent, the effective thermal conductivity of porous media skeleton Rate, temperature, refractive index and equivalent radiated power thermal conductivity.h_vBody convection transfer rate between porous media and heat exchanging fluid；

Step 5) calculates convergence, and characteristic is changed in the flowing for obtaining porous media solar heat absorber, calculates the evaluation of the heat dump thermal efficiency Parameter：

<mrow> <mi>&amp;eta;</mi> <mo>=</mo> <mfrac> <mrow> <mover> <mi>m</mi> <mo>&amp;CenterDot;</mo> </mover> <msubsup> <mo>&amp;Integral;</mo> <msub> <mi>T</mi> <mrow> <mi>f</mi> <mo>,</mo> <mi>i</mi> <mi>n</mi> </mrow> </msub> <msub> <mi>T</mi> <mrow> <mi>f</mi> <mo>,</mo> <mi>o</mi> <mi>u</mi> <mi>t</mi> </mrow> </msub> </msubsup> <msub> <mi>c</mi> <mi>p</mi> </msub> <msub> <mi>dT</mi> <mi>f</mi> </msub> </mrow> <mrow> <msub> <mi>q</mi> <mrow> <mi>i</mi> <mi>n</mi> </mrow> </msub> <msub> <mi>S</mi> <mrow> <mi>i</mi> <mi>n</mi> </mrow> </msub> </mrow> </mfrac> </mrow>

For mass flow, q_inFor intensity of solar radiation, S_inFor heat dump front end area.And evaluating is passed into hereditary calculation Method；

Step 6) genetic algorithm is intersected according to the evaluating in step 5), made a variation, migrating genetic operation, and renewal is to be optimized Variable, repeat step 3), step 4), step 5), progressively obtain and cause the higher porous media structure parameter of the thermal efficiency and heat absorption Device operational factor, final genetic algorithm reach convergence, obtain optimal value of the parameter.

2. porous media solar heat absorber structure according to claim 1 and optimization of operating parameters method, its feature exist In：The physical dimension of the geometric parameter of described porous media including porous media is length, the porosity of porous media, The aperture of porous media；Operational factor includes inlet flow rate, inlet temperature, solar radiation energy-flux density.