Control method for a solar thermochemical energy storage device

Abstract

This application provides a control method for a solar thermochemical energy storage device, belonging to the field of solar energy technology. This method determines the target residence time of particles and obtains multiple parameter sets including scraper angle, feed rate, scraper spacing, and turntable rotation speed. A target numerical model based on the parameters of the particles and the device is used to calculate the residence time of particles corresponding to each parameter set. Based on the residence times of multiple particles corresponding to each parameter set in the device, the average residence time and variance of the residence time of multiple particles corresponding to each parameter set are obtained. Multiple first target parameter sets are determined from the multiple parameter sets, and a second target parameter set is determined from the multiple first target parameter sets. The second target parameter set is the first target parameter set with the smallest variance of the corresponding residence time among the multiple first target parameter sets. Based on the second target parameter control device, the beneficial effect of accurately controlling the particle residence time is achieved.

Description

Technical Field

[0001] This application relates to the field of solar energy technology, and more specifically, to a control method for a solar thermochemical energy storage device. Background Technology

[0002] Thermochemical energy storage technology boasts advantages such as high energy density, long storage time, low material cost, and wide applicable temperature range, demonstrating broad application prospects in the field of solar thermal energy storage. Among these advantages, the residence time of particles within the reactor is closely related to the reaction conversion rate, energy storage efficiency, and system operational stability. Insufficient particle residence time leads to a decrease in reaction conversion rate and energy density; while excessive residence time reduces energy storage efficiency and may even cause particle sintering, thus affecting the system's cycle stability. Therefore, rationally controlling the particle residence time in the reactor is crucial.

[0003] In existing technologies, particles typically move within the reactor by gravity, and the residence time is controlled by adjusting the valve opening at the discharge port or the rotational speed of the screw conveyor to change the discharge rate.

[0004] However, due to the interaction between particles and the limitations of reactor structure design, channeling or dead zones are easily formed in the bed, resulting in unclear particle motion characteristics and local particle residence time deviating from the design value, making it difficult to achieve precise control.

[0005] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this application is to overcome the shortcomings of the prior art and provide a control method for a solar thermochemical energy storage device, the technical solution of which is as follows: According to one aspect of this application, a control method for a solar thermochemical energy storage device is provided. The device includes a housing, a turntable, a baffle assembly, a feed pipe, and a rotating assembly. The turntable and the baffle assembly are located within the housing. The rotating assembly is connected to the turntable and drives it to rotate. One end of the feed pipe is located above the center of the turntable, and the other end is located outside the housing, and it releases particles for storing solar energy onto the turntable. The baffle assembly is located above the turntable and includes a plurality of scrapers arranged along a first direction away from the center of the turntable. The scrapers form an acute angle with respect to the first direction, with the end of the angle facing the center of the turntable. The housing further includes a light-introducing assembly for providing light to the turntable. The method includes: Determine the target residence time of the particles in the device; Multiple parameter groups are obtained. Each parameter group includes four parameters: the angle between the scraper and the first direction, the feeding speed of the feed pipe to the turntable for providing the particles, the spacing of the scraper, and the rotation speed of the turntable. At least one parameter in any two parameter groups is different. A target numerical model of the particles and the device is established based on the parameters of the particles and the device. The target numerical model is used to determine the residence time of each of the multiple particles in the device based on the parameter set. By inputting the multiple parameter sets into the target numerical model, the residence time of the multiple particles corresponding to each parameter set in the device is obtained; Based on the residence time of multiple particles corresponding to each parameter group in the device, the average residence time and variance of the residence time of multiple particles corresponding to each parameter group in the device are obtained. Multiple first target parameter sets are determined from the multiple parameter sets, and the average value of the dwell time corresponding to each first target parameter set is equal to the target dwell time; A second target parameter set is determined from the plurality of first target parameter sets, wherein the second target parameter set is the first target parameter set with the smallest variance of the corresponding dwell time among the plurality of first target parameter sets; The device is controlled based on the second target parameter.

[0007] Optionally, determining the second target parameter set from the plurality of first target parameter sets includes: Obtain the variance of the dwell time corresponding to each of the plurality of first target parameter groups; Among the plurality of first target parameter sets, obtain the two first target parameter sets with the smallest variance of the corresponding dwell time; If the difference in the variance of the dwell time corresponding to the two first target parameter groups is less than 10% of the mean of the variance of the dwell time corresponding to the two first target parameter groups, then obtain the proportion of particles whose dwell time is equal to the target dwell time among the multiple particles corresponding to each of the two first target parameter groups. The first target parameter group with the largest proportion among the two first target parameter groups is determined as the second target parameter group; If the difference in variance of the dwell time corresponding to the two first target parameter groups is greater than or equal to 10% of the mean of the variance of the dwell time corresponding to the two first target parameter groups, then the first target parameter group with the smallest variance of the dwell time among the two first target parameter groups is determined as the second target parameter group.

[0008] Optionally, establishing a target numerical model of the particle and the device based on the parameters of the particle and the device includes: The parameters of the particles and the device are collected. The parameters of the particles include Poisson's ratio, density, shear modulus, collision recovery coefficient between particles, static friction coefficient between particles, dynamic friction coefficient between particles, particle size, collision recovery coefficient between particles and the rotating disk, static friction coefficient between particles and the rotating disk, and dynamic friction coefficient between particles and the rotating disk. The parameters of the device include Poisson's ratio, density, and shear modulus of the rotating disk. An initial numerical model of the particle and the device is established based on the parameters of the particle and the device; The device is configured based on one of the multiple parameters, and granular material is added to the device, the granular material comprising multiple tracer particles and multiple particles; Based on the tracer particles, a first test average value of the residence time of multiple particles in the granular material in the device and a first test variance of the residence time are determined. By inputting the test parameter set into the initial numerical model, the second test average value of the residence time of multiple particles corresponding to the test parameter set in the device and the second test variance of the residence time are obtained. When the difference between the first test average and the second test average is less than 10% of the first test average, and the difference between the first test variance and the second test variance is less than 10% of the first test variance, the initial numerical model is determined as the target numerical model. The step of collecting the parameters of the particle and the device is performed when the difference between the first test average and the second test average is less than 10% of the first test average, and / or the difference between the first test variance and the second test variance is less than 10% of the first test variance.

[0009] Optionally, the step of inputting the plurality of parameter sets into the target numerical model to obtain the residence time of the plurality of particles corresponding to each parameter set in the device includes: Input one of the parameter groups into the target numerical model and obtain the distribution parameters of the particles on the turntable. The distribution parameters include the stacking thickness of particles at multiple locations on the turntable at different distances from the center of the turntable. When the change in the distribution parameter is less than a preset threshold, the residence time of the multiple particles corresponding to the parameter group in the device is obtained.

[0010] Optionally, the angle between the scraper and the first direction ranges from 30 degrees to 70 degrees.

[0011] Optionally, the spacing between the scraper blades is 6 mm to 14 mm.

[0012] Optionally, the feed pipe provides the particles to the turntable at a feed rate of 0.8 g / s to 1.6 g / s.

[0013] Optionally, the rotational speed of the turntable is from 6 revolutions per minute to 14 revolutions per minute.

[0014] Optionally, the average dwell time ranges from 60 seconds to 120 seconds.

[0015] Optionally, controlling the device based on the second target parameter includes: During the operation of the device, the thickness of the particle bed on the turntable is monitored; When the absolute difference between the particle bed thickness and the target thickness is greater than 3 mm, adjust the feed rate and / or the turntable rotation speed, and re-execute the step of monitoring the particle bed thickness on the turntable.

[0016] The beneficial effects of the technical solutions provided in this application include at least the following: A control method for a solar thermochemical energy storage device is provided. By determining the target residence time of the particles, multiple parameter sets including scraper angle, feed rate, scraper spacing, and turntable speed are obtained. A target numerical model based on the particle and device parameters is used to calculate the residence time of the particles corresponding to each parameter set, obtaining the average and variance of the residence time for each parameter set. Multiple first target parameter sets with average values ​​equal to the target residence time are determined. Then, the second target parameter set with the smallest variance is selected from these first target parameter sets. This second target parameter set corresponds to the most concentrated distribution of particle residence times, minimizing the possibility of some particles having excessively short or long residence times. Controlling the device operation based on this second target parameter clarifies the particle motion characteristics and achieves the beneficial effect of precisely controlling the particle residence time.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0019] Figure 1 This is a flowchart illustrating a control method for a solar thermochemical energy storage device according to an embodiment of this application.

[0020] Figure 2 This is a cross-sectional view of a solar thermochemical energy storage device shown in an embodiment of this application.

[0021] Figure 3 yes Figure 2 A top view of a partial structure of the solar thermochemical energy storage device shown.

[0022] Figure 4 yes Figure 2 The diagram shows a partial structural schematic of a solar thermochemical energy storage device.

[0023] Figure 5 This is a flowchart illustrating another control method for a solar thermochemical energy storage device as shown in the embodiments of this application.

[0024] Figure 6 This is a comparison and verification diagram of the first test average value and the second test average value under different turntable speeds provided in the embodiments of this application.

[0025] Figure 7 This is a steady-state particle distribution morphology diagram provided in an embodiment of this application.

[0026] Figure 8 This is a particle bed distribution diagram for the start-up stage provided in an embodiment of this application.

[0027] Figure 9 This is a curve showing the average variation of particle residence time during the start-up phase, provided as an embodiment of this application.

[0028] Figure 10 This is a steady-state particle motion trajectory diagram provided in an embodiment of this application.

[0029] Figure 11 This is a distribution curve of particle residence time under different scraper angles provided in an embodiment of this application.

[0030] Figure 12 This is a graph showing the characteristic parameters of particle residence time under different scraper angles, provided in an embodiment of this application.

[0031] Figure 13 This is an RTD curve of particles with different blade spacing provided in an embodiment of this application.

[0032] Figure 14 This is a graph showing the characteristic parameters of particle residence time under different blade spacings, provided in an embodiment of this application.

[0033] Figure 15 This is an RTD curve of particles under different feed flow rates provided in an embodiment of this application.

[0034] Figure 16 This is a graph showing the characteristic parameters of particle residence time under different feed flow rates, provided in an embodiment of this application.

[0035] Figure 17 This application provides an embodiment of the RTD curves of particles at different turntable speeds.

[0036] Figure 18 This is a graph showing the characteristic parameters of particle residence time at different turntable speeds, provided for an embodiment of this application. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0038] Figure 1 This is a flowchart illustrating a control method for a solar thermochemical energy storage device according to an embodiment of this application. Figure 2 This is a cross-sectional view of a solar thermochemical energy storage device shown in an embodiment of this application. Figure 3 yes Figure 2 The diagram shows a partial top view of the solar thermochemical energy storage device. Figure 4 yes Figure 3 The diagram shows a partial structural schematic of a solar thermochemical energy storage device, in which... Figure 3 A top view of the turntable is shown. Figure 4 An enlarged schematic diagram of the structure of multiple scrapers is shown, combined with... Figure 1 , Figure 2 , Figure 3 and Figure 4 As shown, the device includes a housing 11, a turntable 12, a baffle assembly 13, a feed pipe 14, and a rotating assembly 15. The turntable 12 and the baffle assembly 13 are located inside the housing 11. The rotating assembly 15 is connected to the turntable 12 and is used to drive the turntable 12 to rotate. One end of the feed pipe 14 is located above the center of the turntable 12, and the other end is located outside the housing 11. It is used to release particles for storing solar energy onto the turntable 12. The baffle assembly 13 is located above the turntable 12 and includes a plurality of scrapers 131 arranged along a first direction away from the center of the turntable 12. The scrapers 131 have an acute angle with the first direction f. θ And the included angle θ The end of the particle faces the center of the turntable 12. The housing 11 also includes a light-inlet component 16 that provides light to the turntable and a discharge port located below the turntable 12. After absorbing and storing solar energy, the particles can leave the device from the discharge port. The specific steps of this method are as follows: Step 101: Determine the target residence time of the particles in the device.

[0039] Step 102: Obtain multiple parameter groups. Each parameter group includes four parameters: the angle between the scraper and the first direction, the feed rate of the feed pipe to the turntable for providing particles, the spacing between the scrapers, and the rotation speed of the turntable. At least one parameter in any two parameter groups is different.

[0040] Step 103: Establish a target numerical model of the particles and the device based on the parameters of the particles and the device. The target numerical model is used to determine the residence time of each particle in the device based on the parameter set.

[0041] Step 104: Input multiple parameter sets into the target numerical model to obtain the residence time of multiple particles in the device corresponding to each parameter set.

[0042] Step 105: Based on the residence time of multiple particles corresponding to each parameter group in the device, obtain the average residence time and variance of the residence time of multiple particles corresponding to each parameter group in the device.

[0043] Step 106: Determine multiple first target parameter sets from multiple parameter sets, where the average dwell time of each first target parameter set is equal to the target dwell time.

[0044] Step 107: Determine the second objective parameter set from multiple first objective parameter sets. The second objective parameter set is the first objective parameter set with the smallest variance of the corresponding dwell time among multiple first objective parameter sets.

[0045] Step 108: Control device based on second target parameters.

[0046] In summary, the embodiments of this application provide a control method for a solar thermochemical energy storage device. By determining the target residence time of the particles, multiple parameter sets including scraper angle, feed speed, scraper spacing, and turntable speed are obtained. The residence time of the particles corresponding to each parameter set is calculated by a target numerical model established based on the parameters of the particles and the device, and the average and variance of the residence time corresponding to each parameter set are obtained. Multiple first target parameter sets with average values ​​equal to the target residence time are determined. Then, the second target parameter set with the smallest variance is selected from the multiple first target parameter sets. The particle residence time distribution corresponding to this parameter set is the most concentrated, which can minimize the situation where some particles have too short or too long residence times. The device is controlled based on the second target parameter, which clarifies the particle motion characteristics and achieves the beneficial effect of accurately controlling the particle residence time.

[0047] Figure 5 This is a flowchart illustrating another control method for a solar thermochemical energy storage device as shown in the embodiments of this application, such as... Figure 5 As shown, the specific steps of the control method for this solar thermochemical energy storage device are as follows: Step 201: Determine the target residence time of the particles in the device.

[0048] The residence time of the target particle can be determined by factors such as the particle material and size. The particle can absorb and store solar energy under the influence of sunlight or other light. If the particle residence time in the device is too long, problems such as sintering may occur; if the residence time is too short, insufficient heat absorption will lead to reduced efficiency. The particle material can include calcium carbonate (CaCO3), and the chemical equation for the endothermic reaction is as follows: ; The target residence time of particles in the device can be determined through prior calculations and experiments. The device involved in the embodiments of this application can be the above-mentioned solar thermochemical energy storage device.

[0049] Step 202: Obtain multiple parameter groups. Each parameter group includes four parameters: the angle between the scraper and the first direction, the feed rate of the feed pipe to the turntable for providing particles, the spacing between the scrapers, and the rotation speed of the turntable. At least one parameter in any two parameter groups is different.

[0050] To ensure that particles leave the reactor via the edge of the turntable, in this embodiment, the angle between the scraper and the first direction ranges from 30 degrees to 70 degrees, where the angle value can be any value among 30 degrees, 40 degrees, 50 degrees, 60 degrees, and 70 degrees. The angle between the scraper and the first direction can also be other values, which are not limited in this embodiment.

[0051] During device operation, the particle accumulation thickness should be less than the scraper height. Therefore, in this embodiment, the feed rate of particles supplied to the turntable by the feed pipe is 0.8 g / s to 1.6 g / s. For example, the feed rate can be any value among 0.8 g / s, 1.0 g / s, 1.2 g / s, 1.4 g / s, and g / s, or other values, which are not limited in this embodiment.

[0052] Since the blade spacing must be larger than the particle size to ensure smooth particle passage, in this embodiment, the spacing between two adjacent blades is 6 mm to 14 mm. For example, the blade spacing can be any value among 6 mm, 8 mm, 10 mm, and 12 mm, or other values; this embodiment does not limit the specific values.

[0053] During device operation, excessively high turntable speed increases the centrifugal force on the particles, causing them to be easily thrown off the turntable surface. Therefore, in this embodiment, the turntable speed is between 6 and 14 revolutions per minute. For example, the turntable speed can be any value among 6, 8, 10, 12, and 14 revolutions per minute, or other values; this embodiment does not limit the specific values.

[0054] Step 203: Establish a target numerical model of the particles and the device based on the parameters of the particles and the device. This target numerical model is used to determine the residence time of each particle in the device based on the parameter set.

[0055] The establishment of target numerical models for particles and devices based on their parameters can be accomplished through the following sub-steps: 1) Collect parameters of the particles and the device. The parameters of the particles include Poisson's ratio, density, shear modulus, collision recovery coefficient between particles, static friction coefficient between particles, dynamic friction coefficient between particles, particle size, collision recovery coefficient between particles and the rotating disk, static friction coefficient between particles and the rotating disk, and dynamic friction coefficient between particles and the rotating disk. The parameters of the device include Poisson's ratio, density, and shear modulus of the rotating disk.

[0056] In this embodiment, the specific parameters of the particles are as follows: the Poisson's ratio of the particles is 0.3, the density of the particles is 2700 kg / m³, and the shear modulus of the particles is 5 × 10⁻⁶. 6 The parameters of the device include: the collision restitution coefficient between particles is 0.411, the static friction coefficient between particles is 0.75, the dynamic friction coefficient between particles is 0.07, the particle size is 1 mm, the collision restitution coefficient between particles and the rotating disk is 0.378, the static friction coefficient between particles and the rotating disk is 0.5, and the dynamic friction coefficient between particles and the rotating disk is 0.05. The parameters of the device also include: the Poisson's ratio of the rotating disk is 0.35, the density of the rotating disk is 7.98 kg / m³, and the shear modulus of the rotating disk is 7.27 × 10¹. 0 Pa.

[0057] 2) Establish an initial numerical model of the particles and the device based on the parameters of the particles and the device; In this embodiment, the Discrete Element Method (EDEM) software is used for numerical simulation. The Hertz-Mindlin (No Slip) model and the Standard Rolling Friction model are used to simulate the elastic collision and friction behavior between particles and between particles and the rotating disk. According to this contact model, the contact forces between particles and between particles and the rotating disk include normal and tangential components. The normal force component... F nDue to elastic contact force F n e and damping force F n d Composition, the normal force component F n and elastic contact force F n e The formula is as follows: (Formula 1); (Formula 2); in, It is the equivalent Young's modulus. The equivalent radius, δ n The formulas for the equivalent Young's modulus and equivalent radius, which represent the normal overlap, are as follows: (Formula 3); (Formula 4); In the formula: E i , v i , R i and E j , v j , R j These are Young's modulus, Poisson's ratio, and the radius of the contacting sphere, respectively. i and j represent two objects in contact; i and j can be two different particles, or a particle and a rotating disk.

[0058] Damping force F n d The calculation formula is as follows: (Formula 5); (Formula 6); In the formula: For equivalent mass, m i and m j Let be the masses of the two objects in contact. v n The normal component of the relative velocity. S n For normal stiffness, β is the damping coefficient.

[0059] βand normal stiffness S n The calculation formula is as follows: (Formula 7); (Formula 8); In the formula: e It is the collision recovery coefficient.

[0060] Tangential force F t Based on Mindlin's contact theory and Coulomb's law of friction, and based on elastic contact force F t e and damping force F t d The composition, and its calculation formula are as follows: (Formula Nine); (Formula 10); (Formula Eleven); (Formula 12); In the formula: S t It is the normal stiffness. δ t It is the tangential overlap. It is the equivalent shear modulus. v t It is the tangential component of the relative velocity.

[0061] According to Coulomb's law of friction, the tangential force is limited by friction, that is: (Formula Thirteen); Rolling friction torque M i The formula for calculating the resistance to the rotational motion of particles is as follows: (Formula Fourteen); In the formula: μ r It is the rolling friction coefficient. ω i It is the angular velocity vector of the object at the point of contact.

[0062] Formulas one through fourteen above form the basis of the initial numerical model.

[0063] 3) Set up the device based on one of the test parameter groups of multiple parameters, and add granular material to the device. The granular material includes multiple tracer particles and multiple particles. Select a set of test parameters, for example, the angle between the scraper and the first direction is 30°, the spacing between the scrapers is 10 mm, the feeding speed is 1.0 g / s, and the turntable speed is 10 rpm.

[0064] The experiment employed a visual rotating moving bed apparatus, using 1 mm spherical calcium carbonate (CaCO3) particles. Before the experiment, the particles were screened using a 30-mesh (1 mm) 304 stainless steel sieve to ensure their diameter was as close to 1 mm as possible. The tracer particles were colored glass microspheres with similar physical properties (mainly composed of silicon dioxide (SiO2), 1 mm in diameter, and a density of 2500 kg / m³), and their concentration was controlled to be below 5% of the total particle concentration.

[0065] 4) Determine the first test average value and the first test variance of the residence time of multiple particles in the granular material in the device based on the tracer particles; To ensure the accuracy of data processing and the statistical reliability of results, each experiment was repeated three times; residence time data of 200 tracer particles were collected in each experiment.

[0066] 5) Input the test parameter set into the initial numerical model to obtain the second test average value of the residence time of multiple particles in the device and the second test variance of the residence time corresponding to the test parameter set.

[0067] The same set of test parameters is input into the initial numerical model established in step 2032 to run the simulation, and the second test mean and the second test variance obtained from the simulation are calculated.

[0068] 6) When the difference between the first test mean and the second test mean is less than 10% of the first test mean, and the difference between the first test variance and the second test variance is less than 10% of the first test variance, the initial numerical model is determined as the target numerical model. Figure 6 This is a comparison and verification chart showing the first test average value and the second test average value under different turntable speeds provided in the embodiments of this application. Figure 6 The horizontal axis represents the rotary table speed (in revolutions per minute, rpm), and the vertical axis represents the average particle residence time (in seconds). Figure 6 It can be seen that the relative error range between the average value of the first test and the average value of the second test is 2.59% to 8.71%, both below 10%, indicating that the model is reliable. Therefore, the initial numerical model is determined as the target numerical model.

[0069] 7) If the difference between the first test average and the second test average is greater than or equal to 10% of the first test average, and / or the difference between the first test variance and the second test variance is greater than or equal to 10% of the first test variance, it indicates that the parameter acquisition may be inaccurate. In this case, the process can be returned to step 1) of acquiring the parameters of the particles and the device. That is, if either the first test average or the first test variance is less than 10%, the parameters should be reacquired or the model adjusted until the verification conditions are met.

[0070] Step 204: Input one of the parameter groups into the target numerical model and obtain the distribution parameters of the particles on the turntable. The distribution parameters include the stacking thickness of particles at multiple locations on the turntable at different distances from the center of the turntable.

[0071] In this embodiment, the steady-state stage refers to the stage after the device has reached dynamic equilibrium. Figure 7 A steady-state particle distribution morphology diagram is provided for an embodiment of this application, wherein... Figure 7 Figure (a) is a front view of the particle distribution morphology during the steady-state stage. Figure 7 Figure (b) is a left view of the particle distribution morphology during the steady-state stage. Figure 7 Figure (c) is a top view of the particle distribution morphology during the steady-state stage, as shown in Figure (c). Figure 7 As shown, under the influence of the scraper's disturbance, particles gradually diffuse towards the edge of the rotating disk along the scraper, eventually forming a regular concentric ring-shaped distribution of peaks and troughs. The particle distribution is denser and the accumulation thickness is greater in the inner ring region, while the particle distribution is looser in the outer ring region. The thickness of the bed and scraper regions tends to be relatively stable. The thickness of the bed region is between 2 and 3 mm, while the thickness of the scraper region gradually decreases radially, ranging from 2 to 10 mm, with the scraper region being significantly thicker than the bed region. Although the scraper provides a clearer movement path for the particles, local particle accumulation also exists in the scraper region, which further exacerbates the non-uniformity of particle movement within the reactor.

[0072] Step 205: When the change in the distribution parameter is less than the preset threshold, obtain the residence time of multiple particles corresponding to a parameter group in the device.

[0073] The preset thresholds include thresholds for changes in the stacking thickness at multiple locations.

[0074] Figure 8 This application provides a particle bed distribution diagram for the start-up phase. Figure 9 This application provides an embodiment of a curve showing the average variation of particle residence time during the start-up phase, wherein... Figure 8 In this context, 't' represents time, and the unit is seconds. Figure 9The horizontal axis represents the device's operating time, the left side of the vertical axis represents the average residence time of the particles (i.e., the average residence time of the particles), and the right side of the vertical axis represents the rate of change of the average residence time of the particles (i.e., the rate of change of the average residence time of the particles). For example... Figure 8 and Figure 9 As shown, in the initial stage (0-52.3 s), the particles gradually fill the reactor, mainly concentrated on the surface of the rotating disk. A small number of particles bounce to a farther area of ​​the rotating disk or even fall off due to interaction forces and gravity. As the running time increases, the average residence time of the particles rises rapidly, and the particles gradually form a relatively uniform accumulation layer inside the reactor, covering the surface of the rotating disk, forming the initial stage particle accumulation layer.

[0075] During the transition phase (52.3–190.14 s), the rate of increase in average residence time slowed rapidly with increasing running time. At 190.14 s, the average residence time curve tended to plateau and stabilized at around 37.75 s, and the particle distribution morphology and geometric characteristics of the accumulation region remained stable, indicating that the particle movement inside the reactor had reached dynamic equilibrium.

[0076] After approximately 190 seconds of operation, the device enters a steady-state phase, at which point the change in the distributed parameters is less than a preset threshold. When the change in the distributed parameters is less than the preset threshold (i.e., the device is in a steady-state phase), the time from entering the device to leaving the device for each particle under that parameter set is recorded as the residence time of each particle. Figure 10 A steady-state particle motion trajectory diagram is provided for embodiments of this application, wherein... Figure 10 Figure (a) in the diagram is a three-dimensional trajectory diagram of the particle during the steady-state stage. Figure 10 Figure (b) shows the two-dimensional motion trajectory of the particles during the steady-state stage. After entering the reactor, the particles exhibit a spiral motion trajectory with slight axial fluctuations. Each time a particle passes the scraper, it will undergo a short radial displacement under the action of the scraper, eventually falling off the edge of the turntable, entering the discharge port, and finally leaving the reactor.

[0077] Step 206: Based on the residence time of multiple particles corresponding to each parameter group in the device, obtain the average residence time and variance of the residence time of multiple particles corresponding to each parameter group in the device.

[0078] The residence time of particles is a key parameter for evaluating their movement behavior and reaction processes within a reactor. The average residence time... t m and the variance of the length of stay σ t 2 The following formula can be used for calculation: (Formula 15); (Formula Sixteen); (Formula 17); Where t represents the residence time of the particle, t i The actual residence time (in seconds) of the i-th tracer particle. R （t） Let be the residence time distribution (RTD) density function of the particles. The formula for calculating the particle RTD density function is as follows: (Formula 18); (Formula 19); in, N ( t (The duration of stay is...) t The number of particles per second.

[0079] Step 207: Determine multiple first target parameter groups from multiple parameter groups, where the average dwell time of each first target parameter group is equal to the target dwell time.

[0080] The average dwell time for each first target parameter group is within the target dwell time range, which can be between 60 seconds and 120 seconds.

[0081] Step 208: Determine the second target parameter group from multiple first target parameter groups. The second target parameter group is the first target parameter group with the smallest variance of the corresponding dwell time among multiple first target parameter groups.

[0082] The process of determining the second set of objective parameters from multiple first sets of objective parameters includes the following sub-steps: 2.1) Obtain the variance of the dwell time corresponding to each of the multiple first target parameter groups.

[0083] Figure 11 This application provides a particle residence time distribution curve for different scraper angles, as shown in the embodiments of this application. Figure 12 This application provides a characteristic parameter diagram of particle residence time under different scraper angles, in which... Figure 12 The horizontal axis represents the angle (in degrees) between the scraper and the first direction, and the left side of the vertical axis represents the average dwell time (in seconds). t m Right side: Variance of dwell time σ t 2 .like Figure 11 and 12As shown, the residence time distribution curves of particles exhibit a distinct bimodal distribution under different angles between the scraper and the first direction. With increasing angle, the RTD curve range widens, and the tailing phenomenon intensifies. The main peak of the RTD curve gradually shifts to the right, with the peak height first increasing and then decreasing, reaching a maximum of 33.4% at 50 degrees. For smaller angles (30 degrees and 40 degrees), the RTD peaks are biased to the left, appearing at 41.5 s and 52.5 s respectively, indicating that smaller angles cause particles to move rapidly from the center to the edge. Conversely, for larger angles, the main peak shifts significantly to the right, appearing at 77.4 s at 60 degrees and at 95.1 s at 70 degrees.

[0084] As the angle increases, the average residence time of particles gradually increases, from 60.31 s at 30 degrees to 116.73 s at 70 degrees. The residence time of particles in the reactor is significantly prolonged. Furthermore, the variance of the residence time first decreases and then increases with increasing angle. When the angle is 50 degrees, the average residence time is 87.94 s, and the variance reaches its minimum of 0.077, indicating that under this condition the particle motion is closest to plug flow.

[0085] Figure 13 This application provides an embodiment of the RTD curves of particles with different blade spacing. Figure 14 This application provides a characteristic parameter diagram of particle residence time under different blade spacings, in which... Figure 14 The horizontal axis represents the spacing between the scraper blades (mm), and the left side of the vertical axis represents the average dwell time (seconds). t m Right side: Variance of dwell time σ t 2 .like Figure 13 and 14 As shown, with increasing spacing (D), the RTD curve range widens and the tailing phenomenon intensifies. The height of the main peak of the RTD curve does not change significantly, but gradually shifts to the right. When D = 6 mm, the proportion of particles within the main peak is 69.3%, with a distribution range of approximately 35–85 s. When D = 14 mm, this proportion rises to 82.4%, and the distribution range expands to 65–145 s. Simultaneously, with increasing D, the height of the secondary peaks gradually decreases.

[0086] Among the characteristic parameters of particle residence time under different scraper spacings, the average residence time gradually increases with the increase of D, while the variance of residence time gradually decreases. Specifically, when D = 6 mm, the average residence time is 77.06 s, and the variance of residence time is 0.20; when D = 14 mm, the average residence time increases to 117.80 s, and the variance of residence time decreases to 0.159. This phenomenon is mainly attributed to the fact that a larger D reduces the number of radial offsets caused by the scraper and weakens the particle accumulation thickness in the scraper area.

[0087] Figure 15 This application provides an embodiment of the RTD curves of particles under different feed flow rates. Figure 16 This application provides a characteristic parameter diagram of particle residence time under different feed flow rates, wherein... Figure 16 The horizontal axis represents the feed rate (g / s), and the left side of the vertical axis represents the average residence time (seconds). t m Right side: Variance of dwell time σ t 2 .like Figure 15 and 16 As shown, with increasing feed rate, the RTD curve range narrows and the tailing phenomenon weakens. Furthermore, with increasing feed rate, the main peak of the RTD curve gradually shifts to the left. At a feed rate of 0.8 g / s, the main peak distribution range is approximately 35–96 s, with a particle percentage of 61.3%. At a feed rate of 1.6 g / s, the main peak distribution range shortens to approximately 20–75 s, and the particle percentage increases to 75.6%.

[0088] Among the characteristic parameters of particle residence time under different particle feed flow rates, the average residence time gradually decreases with increasing feed rate. This is because a higher feed flow rate accelerates particle movement within the reactor. The variance of residence time first decreases and then increases. When the feed rate is 1.0 g / s, the average residence time is 78.68 s, and the variance reaches its minimum value of 0.225. Both excessively low and excessively high feed flow rates can lead to uneven particle movement.

[0089] Figure 17 This application provides an embodiment of the RTD curves of particles at different rotary disk rotation speeds. Figure 18 This application provides a characteristic parameter diagram of particle residence time under different turntable rotation speeds, in which... Figure 18 The horizontal axis represents the turntable speed (revolutions per minute), and the left side of the vertical axis represents the average dwell time (seconds). t m Right side: Variance of dwell time σt 2 .like Figure 17 and 18 As shown, with the increase of the rotary table speed, the range of the particle RTD curve narrows, and the tailing phenomenon weakens. The main peak of the RTD curve gradually shifts to the left, and the peak height first increases and then decreases. When the rotary table speed is 10 rpm, the main peak of the RTD curve reaches its maximum value of 31.2%, and 73.1% of the particle residence time falls within this range. At the same time, the RTD curve changes from a single-peak distribution to a double-peak distribution, and the secondary peak gradually appears and becomes more significant.

[0090] The residence time characteristics of particles at different turntable speeds are as follows: Figure 18 As shown, tm gradually decreases with increasing disc rotation speed. This trend can be attributed to the enhanced interparticle interaction and increased particle velocity at higher rotation speeds. These factors lead to an increase in the radial deflection frequency caused by the scraper, thus allowing the motion to reach dynamic equilibrium more quickly. However, when the rotation speed is further increased to disc rotation speeds of 12 rpm and 14 rpm, the average residence times are 76.35 s and 73.69 s, respectively, comparable to the values ​​at disc rotation speed of 10 rpm. The variance of residence time first increases and then decreases, reaching a maximum of 0.225 at disc rotation speed of 10 rpm.

[0091] 2.2) Obtain the two first target parameter groups with the smallest variance in the corresponding dwell time among multiple first target parameter groups.

[0092] 2.3) If the difference in variance of the dwell time corresponding to the two first target parameter groups is less than 10% of the mean of the variance of the dwell time corresponding to the two first target parameter groups, then obtain the proportion of particles whose dwell time is equal to the target dwell time among the multiple particles corresponding to each first target parameter group in the two first target parameter groups.

[0093] like Figure 11 , Figure 13 , Figure 15 , Figure 17 As shown, the residence time distribution curves corresponding to different parameter groups have different peak heights. When the target residence time matches the residence time corresponding to the peak, the function value is the peak height. For example, when the angle between the scraper and the first direction is 50°, the peak height is 33.4%; when the turntable speed is 10 revolutions per minute, the peak height is 31.2%. 2.4) The first target parameter group with the largest proportion among the two first target parameter groups is determined as the second target parameter group.

[0094] 2.5) If the difference in variance of the dwell time corresponding to the two first objective parameter groups is greater than or equal to 10% of the mean of the variance of the dwell time corresponding to the two first objective parameter groups, then the first objective parameter group with the smallest variance of the dwell time among the two first objective parameter groups is determined as the second objective parameter group.

[0095] The average residence time of particles increases with the increase of the scraper installation angle and spacing, and decreases with the increase of particle flow rate and turntable speed. By adjusting and coordinating these parameters, the particle residence time can be flexibly controlled, with a residence time range of 60-120 s. However, when the angle between the scraper and the first direction is 50° and the feed rate is 1.0 g / s, the residence time variance is the smallest, at 0.077, and the motion is closest to plug flow.

[0096] Step 209: Control device based on second target parameters.

[0097] After determining the second target parameter, the device can be controlled based on the second target parameter so that the residence time of multiple particles in the device can approach the target residence time.

[0098] During the operation of the device, the thickness of the particle bed on the turntable is monitored.

[0099] When the absolute difference between the particle bed thickness and the target thickness is greater than 3 mm, adjust the feed rate and / or the rotation speed of the turntable, and repeat the step of monitoring the particle bed thickness on the turntable.

[0100] In subsequent use, since the device may undergo some changes during operation, the second target parameter set can be re-determined based on steps 202 to 208 at predetermined intervals to improve the stability and reliability of the method.

[0101] Alternatively, after step 209, it can be detected whether a preset condition has been met. If the preset condition is met, the second target parameter set can be re-determined based on steps 202 to 208. The preset condition can include various conditions, such as the device running time reaching 100 hours. Alternatively, after the device running time reaches 100 hours, the reaction conversion rate of the particles exiting the outlet of the device can be detected. If the reaction conversion rate is less than or equal to 80%, the second target parameter set can be re-determined based on steps 202 to 208. Here, the reaction conversion rate is equal to the ratio of the actual weight loss of the particles to the theoretical maximum weight loss of the particles. The actual weight loss of the particles is the actual difference between the weight of the particles exiting the outlet and the weight of the particles entering the inlet. The theoretical maximum weight loss of the particles is the theoretical maximum weight loss of the particles after the above-mentioned endothermic reaction.

[0102] In summary, the embodiments of this application provide a control method for a solar thermochemical energy storage device. By determining the target residence time of the particles, multiple parameter sets including scraper angle, feed speed, scraper spacing, and turntable speed are obtained. The residence time of the particles corresponding to each parameter set is calculated by a target numerical model established based on the parameters of the particles and the device, and the average and variance of the residence time corresponding to each parameter set are obtained. Multiple first target parameter sets with average values ​​equal to the target residence time are determined. Then, the second target parameter set with the smallest variance is selected from the multiple first target parameter sets. The particle residence time distribution corresponding to this parameter set is the most concentrated, which can minimize the situation where some particles have too short or too long residence times. The device is controlled based on the second target parameter, which clarifies the particle motion characteristics and achieves the beneficial effect of accurately controlling the particle residence time.

[0103] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0104] The above description is merely an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A control method for a solar thermochemical energy storage device, characterized in that, The device includes a housing, a turntable, a baffle assembly, a feed pipe, and a rotating assembly. The turntable and the baffle assembly are located inside the housing. The rotating assembly is connected to the turntable and drives the turntable to rotate. One end of the feed pipe is located above the center of the turntable, and the other end is located outside the housing. The feed pipe is used to release particles for storing solar energy onto the turntable. The baffle assembly is located above the turntable and includes a plurality of scrapers arranged along a first direction away from the center of the turntable. The scrapers have an acute angle with the first direction, and the end of the angle faces the center of the turntable. The housing also includes a light-injecting assembly for providing light to the turntable. The method includes: Determine the target residence time of the particles in the device; Multiple parameter groups are obtained. Each parameter group includes four parameters: the angle between the scraper and the first direction, the feeding speed of the feed pipe to the turntable for providing the particles, the spacing of the scraper, and the rotation speed of the turntable. At least one parameter in any two parameter groups is different. A target numerical model of the particles and the device is established based on the parameters of the particles and the device. The target numerical model is used to determine the residence time of each of the multiple particles in the device based on the parameter set. By inputting the multiple parameter sets into the target numerical model, the residence time of the multiple particles corresponding to each parameter set in the device is obtained; Based on the residence time of multiple particles corresponding to each parameter group in the device, the average residence time and variance of the residence time of multiple particles corresponding to each parameter group in the device are obtained. Multiple first target parameter sets are determined from the multiple parameter sets, and the average value of the dwell time corresponding to each first target parameter set is equal to the target dwell time; Obtain the variance of the dwell time corresponding to each of the plurality of first target parameter groups; Among the plurality of first target parameter sets, obtain the two first target parameter sets with the smallest variance of the corresponding dwell time; If the difference in the variance of the dwell time corresponding to the two first target parameter groups is less than 10% of the mean of the variance of the dwell time corresponding to the two first target parameter groups, then obtain the proportion of particles whose dwell time is equal to the target dwell time among the multiple particles corresponding to each of the two first target parameter groups. The first target parameter group with the largest proportion among the two first target parameter groups is determined as the second target parameter group; If the difference in variance of the dwell time corresponding to the two first target parameter groups is greater than or equal to 10% of the mean of the variance of the dwell time corresponding to the two first target parameter groups, then the first target parameter group with the smallest variance of the dwell time among the two first target parameter groups is determined as the second target parameter group. The device is controlled based on the second target parameter, and the thickness of the particle bed on the turntable is monitored during the operation of the device. When the absolute difference between the particle bed thickness and the target thickness is greater than 3 mm, adjust the feed rate and / or the rotation speed of the turntable, and repeat the step of monitoring the particle bed thickness on the turntable. Every predetermined time interval, and / or when the device reaches a preset condition, the steps of obtaining multiple parameter sets to determining the second target parameter set from the multiple first target parameter sets are re-executed to determine the second target parameter set; The preset conditions include a reaction conversion rate of less than or equal to 80% for the particles in the device, or a device operating time of 100 hours.

2. The method according to claim 1, characterized in that, The step of establishing a target numerical model of the particles and the device based on the parameters of the particles and the device includes: The parameters of the particles and the device are collected. The parameters of the particles include Poisson's ratio, density, shear modulus, collision recovery coefficient between particles, static friction coefficient between particles, dynamic friction coefficient between particles, particle size, collision recovery coefficient between particles and the rotating disk, static friction coefficient between particles and the rotating disk, and dynamic friction coefficient between particles and the rotating disk. The parameters of the device include Poisson's ratio, density, and shear modulus of the rotating disk. An initial numerical model of the particle and the device is established based on the parameters of the particle and the device; The device is configured based on one of the multiple parameters, and granular material is added to the device, the granular material comprising multiple tracer particles and multiple particles; Based on the tracer particles, a first test average value of the residence time of multiple particles in the granular material in the device and a first test variance of the residence time are determined. By inputting the test parameter set into the initial numerical model, the second test average value of the residence time of multiple particles corresponding to the test parameter set in the device and the second test variance of the residence time are obtained. When the difference between the first test average and the second test average is less than 10% of the first test average, and the difference between the first test variance and the second test variance is less than 10% of the first test variance, the initial numerical model is determined as the target numerical model. The step of collecting the parameters of the particle and the device is performed when the difference between the first test average and the second test average is greater than or equal to 10% of the first test average, and / or the difference between the first test variance and the second test variance is greater than or equal to 10% of the first test variance.

3. The method according to claim 1, characterized in that, The step of inputting the multiple parameter sets into the target numerical model to obtain the residence time of the multiple particles corresponding to each parameter set in the device includes: Input one of the parameter groups into the target numerical model and obtain the distribution parameters of the particles on the turntable. The distribution parameters include the stacking thickness of particles at multiple locations on the turntable at different distances from the center of the turntable. When the change in the distribution parameter is less than a preset threshold, the residence time of the multiple particles corresponding to the parameter group in the device is obtained.

4. The method according to claim 1, characterized in that, The angle between the scraper and the first direction is in the range of 30 degrees to 70 degrees.

5. The method according to claim 1, characterized in that, The spacing between the scraper blades is 6 mm to 14 mm.

6. The method according to claim 1, characterized in that, The feed pipe supplies the particles to the turntable at a feed rate of 0.8 g / s to 1.6 g / s.

7. The method according to claim 1, characterized in that, The turntable rotates at a speed of 6 to 14 revolutions per minute.

8. The method according to claim 1, characterized in that, The average dwell time ranges from 60 seconds to 120 seconds.

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