Control method of solar heat collection evaporator

Abstract

The invention relates to a control method for a solar heat collection evaporator, and the method comprises the steps: determining an overturning angle of a daylighting plane based on the optimal energy conversion efficiency, expected direction angle data and expected elevation angle data of the solar heat collection evaporator, and controlling the overturning of the daylighting plane according to the overturning angle. The difference value between the target energy conversion efficiency and the optimal energy conversion efficiency of the turned solar heat collection evaporator is within the preset efficiency difference value range; therefore, when the energy conversion efficiency is reduced, the lighting plane angle of the solar heat collection evaporator is adjusted to reach the maximum lighting efficiency, and the energy conversion efficiency of the solar heat collection evaporator is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of automatic control technology, and in particular to a control method for a solar thermal collector evaporator. Background Art

[0002] With the increasing scarcity of fossil fuels, the development of new renewable energy sources is an urgent task, especially the utilization of solar energy, a natural energy source, has begun to take shape. The solar thermal evaporator converts the liquid substance in the container into a gaseous substance by collecting solar energy. The gaseous substance condenses into liquid after encountering cold water and releases heat to the cold water, thereby achieving the effect of heating the cold water. During the use of the solar thermal evaporator, improving the tracking accuracy of sunlight can greatly improve the heat conversion efficiency. In the related technology, the tracking accuracy of sunlight is not very ideal, and the efficiency of utilizing sunlight cannot reach the maximum value. The full spectrum cascade utilization is an important scientific and technological problem that needs to be solved in the current solar energy utilization technology. Summary of the invention

[0003] In order to overcome the problems existing in the related art, the present disclosure provides a control method for a solar thermal collector evaporator, the method comprising: When it is determined that the current first energy conversion efficiency of the solar thermal evaporator is less than a set threshold, a photosensitive detection device is used to determine multiple direction angle data and multiple altitude angle data of sunlight on the lighting plane corresponding to the solar thermal evaporator at multiple preset historical time points before the current moment; Sorting the multiple azimuth angle data and the multiple altitude angle data according to the multiple preset historical time points to generate azimuth angle input vectors and altitude angle input vectors; performing feature extraction on the azimuth angle input vectors and the altitude angle input vectors in the time domain space to generate azimuth angle time series feature vectors and altitude angle time series feature vectors; According to the direction angle time series feature vector and the altitude angle time series feature vector, predicting the direction angle change trend and altitude angle change trend of the sunlight within an expected time range, and generating expected direction angle data and expected altitude angle data; Based on the optimal energy conversion efficiency of the solar thermal collector evaporator and the expected direction angle data and the expected altitude angle data, the flip angle of the lighting plane is determined, and according to the flip angle, the flipping of the lighting plane is controlled so that the difference between the target energy conversion efficiency of the solar thermal collector evaporator and the optimal energy conversion efficiency after flipping is within a preset efficiency difference range.

[0004] Optionally, the determining the flip angle of the lighting plane based on the optimal energy conversion efficiency of the solar thermal evaporator and the expected direction angle data and the expected altitude angle data includes: Randomly transform the expected direction angle data and the expected altitude angle data to generate multiple random particle parameters in the initial particle group, wherein the first particle parameter includes a first position and a first speed of the particle in the initial particle group, the first position and the first speed are used to indicate candidate solutions of the sunlight direction angle and the sunlight altitude, and the first particle parameter is any of the multiple random particle parameters; According to the optimal energy conversion efficiency, the position and speed of each random particle parameter in the multiple random particle parameters are updated to determine multiple energy conversion efficiencies corresponding to the updated random particle parameters; Determine a plurality of fitness parameters corresponding to the updated plurality of random particle parameters according to the plurality of energy conversion efficiencies; determine global direction angle data and global altitude angle data of the updated plurality of random particle parameters according to the plurality of fitness parameters; The flip angle of the lighting plane is determined according to the global direction angle data and the global altitude angle data.

[0005] Optionally, determining the flip angle of the lighting plane according to the global direction angle data and the global altitude angle data includes: In the case where it is determined that the set termination condition is not met, based on the updated multiple random particle parameters, repeating the step of determining the global direction angle data and the global altitude angle data of the updated multiple random particle parameters according to the optimal energy conversion efficiency to generate target global direction angle data and target global altitude angle data; When it is determined that the set termination condition is met based on the target global direction angle data and the target global altitude angle data, the flip angle of the lighting plane is determined according to the target global direction angle data and the target global altitude angle data.

[0006] Optionally, determining the flip angle of the lighting plane according to the target global direction angle data and the target global altitude angle data includes: Determine a first rotation angle of the lighting plane in a first set direction according to a difference between the target global direction angle data and the initial direction angle data detected by the current lighting plane, wherein the first set direction is parallel to the lighting plane; Determine a second rotation angle of the lighting plane in a second set direction according to a difference between the target global altitude angle data and the initial altitude angle data detected by the current lighting plane, wherein the second set direction is perpendicular to the lighting plane; The flip angle is determined according to the first rotation angle and the second rotation angle.

[0007] Optionally, the setting of the termination condition includes: The update times of the plurality of random particle parameters reaches the maximum number of iterations; or, The difference between the target energy conversion efficiency and the optimal energy conversion efficiency is less than a preset threshold, and the target energy conversion efficiency is the energy conversion efficiency corresponding to the updated multiple random particle parameters.

[0008] Optionally, the extracting features of the direction angle input vector and the altitude angle input vector in the time domain space to generate a direction angle time series feature vector and an altitude angle time series feature vector comprises: Inputting the direction angle input vector into a preset multi-scale domain extraction model to generate the direction angle time domain feature vector, wherein the multi-scale domain extraction model is used to extract the time domain features in the vector; The altitude angle input vector is input into the preset multi-scale domain extraction model to generate the altitude angle time domain feature vector.

[0009] Optionally, controlling the flipping of the lighting plane according to the flipping angle includes: According to the flipping angle, determining the flipping angle of the lighting plane in the first set direction and the lifting and lowering limit of the lighting plane in the vertical direction; The lighting plane is controlled to flip according to the flip angle and the lifting limit.

[0010] According to a second aspect of an embodiment of the present disclosure, a control device for a solar thermal evaporator is provided, comprising: A determination module, for determining, when determining that the current first energy conversion efficiency of the solar thermal collector evaporator is less than a set threshold, multiple directional angle data and multiple altitude angle data of sunlight on the lighting plane corresponding to the solar thermal collector evaporator at multiple preset historical time points before the current moment through a photosensitive detection device; A first generating module is used to sort the multiple azimuth angle data and the multiple altitude angle data according to the multiple preset historical time points to generate an azimuth angle input vector and an altitude angle input vector; perform feature extraction on the azimuth angle input vector and the altitude angle input vector in a time domain space to generate an azimuth angle time series feature vector and an altitude angle time series feature vector; A second generating module is used to predict the direction angle change trend and the altitude angle change trend of the sunlight within the expected time range according to the direction angle time series feature vector and the altitude angle time series feature vector, and generate expected direction angle data and expected altitude angle data; An execution module is used to determine the flipping angle of the lighting plane based on the optimal energy conversion efficiency of the solar thermal evaporator and the expected direction angle data and the expected altitude angle data, and control the flipping of the lighting plane according to the flipping angle so that the difference between the target energy conversion efficiency of the solar thermal evaporator and the optimal energy conversion efficiency after flipping is within a preset efficiency difference range.

[0011] According to a third aspect of an embodiment of the present disclosure, there is provided a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of any one of the methods described in the first aspect are implemented.

[0012] According to a fourth aspect of an embodiment of the present disclosure, there is provided an electronic device, including: processor; a memory for storing processor-executable instructions; The processor is configured to execute executable instructions in the memory to implement the method described in any one of the first aspects.

[0013] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects: Through the above method, when it is determined that the current first energy conversion efficiency of the solar thermal collector evaporator is less than the set threshold, the photosensitive detection device is used to determine multiple directional angle data and multiple altitude angle data of sunlight on the lighting plane corresponding to the solar thermal collector evaporator at multiple preset historical time points before the current moment, and the multiple directional angle data and the multiple altitude angle data are sorted according to multiple preset historical time points to generate directional angle input vectors and altitude angle input vectors; feature extraction is performed on the directional angle input vector and the altitude angle input vector in the time domain space to generate directional angle time series feature vectors and altitude angle time series feature vectors; according to the directional angle time series feature vectors and the altitude angle time series feature vectors, the directional angle change trend and the altitude angle change trend of sunlight within the expected time range are predicted to generate expected directional angle data and expected altitude angle data; based on the optimal energy conversion efficiency of the solar thermal collector evaporator and the expected directional angle data and the expected altitude angle data, the flip angle of the lighting plane is determined; and according to the flip angle, the flipping of the lighting plane is controlled so that the difference between the target energy conversion efficiency and the optimal energy conversion efficiency of the solar thermal collector evaporator after flipping is within the preset efficiency difference range. Therefore, when the energy conversion efficiency is reduced, the lighting plane angle of the solar thermal collector evaporator is adjusted to achieve the maximum lighting efficiency, thereby improving the energy conversion efficiency of the solar thermal collector evaporator.

[0014] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0016] Figure 1 The figure is a flow chart of a control method of a solar thermal evaporator according to an exemplary embodiment.

[0017] Figure 2 The figure is a block diagram of a control device for a solar thermal evaporator according to an exemplary embodiment. DETAILED DESCRIPTION

[0018] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0019] It should be noted that all actions of acquiring signals, information or data in this application are carried out in compliance with the relevant data protection laws and policies of the country where they are located, and with the authorization given by the owner of the corresponding device.

[0020] Figure 1 is a flow chart showing a control method of a solar thermal evaporator according to an exemplary embodiment. Figure 1 As shown, the method includes: In step S11, when it is determined that the current first energy conversion efficiency of the solar thermal evaporator is less than the set threshold, a photosensitive detection device is used to determine multiple directional angle data and multiple altitude angle data of sunlight on the lighting plane corresponding to the solar thermal evaporator at multiple preset historical time points before the current moment.

[0021] For example, the solar thermal decomposition evaporator absorbs solar energy to heat the liquid solution in the heat collecting tube, evaporates it into gas, and then continues to heat the gaseous material. When the temperature rises, it rises to the condenser tube, precools on the condenser tube to release heat and becomes liquid, and then flows back to the heat collecting tube. Repeatedly repeat the process of liquid absorbing heat to gaseous state, releasing heat to become liquid, and then heating from liquid. In the process of liquid in the heat collecting tube changing, the solar thermal evaporator first absorbs solar energy through the lighting plane, heats the liquid, and then changes from liquid to gas, releases heat on the outer surface of the condenser tube, and the released heat heats the cold water in the condenser tube. Thereby realizing the process of heat collection and evaporation. However, the solar thermal evaporator is affected by the intensity of sunlight and the incident angle of sunlight, which easily leads to low conversion efficiency of solar energy into thermal energy. Therefore, in this embodiment, the solar irradiation angle of the solar thermal evaporator is adjusted based on the energy conversion efficiency to improve the energy conversion efficiency of the solar thermal evaporator and avoid the problem of less converted hot water and affecting the user experience.

[0022] For example, in this embodiment, the energy conversion efficiency of the solar thermal evaporator is measured in real time by a related detection device. For example, the energy conversion efficiency of the solar thermal evaporator can be measured by a thermometer and a sunlight intensity detection device. The sunlight intensity detection device detects solar energy, and the thermometer detects heat. The current energy conversion efficiency of the solar thermal evaporator is obtained by dividing the heat energy with the solar energy. In this embodiment, in order to reduce the adjustment frequency of the solar thermal evaporator, when the current energy conversion efficiency is less than the set threshold and cannot support heat collection and evaporation, the lighting angle of the lighting plane of the current solar thermal evaporator is adjusted. The photosensitive detection device is used to determine multiple directional angle data and multiple altitude angle data of sunlight on the lighting plane corresponding to the solar thermal evaporator before the current moment and at multiple preset historical time points at the moment. It should be noted that the direction and intensity of sunlight are constantly changing with time. Therefore, in this embodiment, the solar direction angle and altitude angle at the historical time point are used to predict the direction angle and altitude angle of sunlight, thereby adjusting the solar thermal evaporator.

[0023] In step S12, multiple directional angle data and multiple altitude angle data are sorted according to multiple preset historical time points to generate directional angle input vectors and altitude angle input vectors; feature extraction is performed on the directional angle input vectors and altitude angle input vectors in the time domain space to generate directional angle time series feature vectors and altitude angle time series feature vectors.

[0024] For example, based on multiple directional angle data and multiple altitude angle data, the directional angle and altitude angle of sunlight in the future are predicted. In this embodiment, multiple directional angle data and multiple altitude angle data are sorted according to multiple expected historical time points, and the directional angle input vector and the altitude angle input vector are extracted according to the sorted data. The time domain characteristics of the input vector in the time domain space are extracted to generate the directional angle timing characteristics and the altitude angle timing characteristics. The directional angle timing characteristics and the altitude angle timing characteristics are used to indicate the time series change characteristics of the directional angle of sunlight in time, that is, the directional angle timing characteristics represent the current geographical location of the solar thermal evaporator as a fixed reference, the sun relative to the solar thermal evaporator, the horizontal plane where the solar thermal evaporator is located as the baseline, the angle between the direction of the sun's appearance and the baseline, and the change characteristic vector within multiple historical time ranges, and the length of the change characteristic vector is used to indicate the change characteristics of the directional angle. The solar altitude angle is the temporal variation characteristic of the solar altitude over time. For example, in this embodiment, a solar intensity detection device can be set on the solar thermal evaporator to determine the height variation characteristics of the solar altitude within a preset historical time range at multiple preset historical time points, with the current solar thermal evaporator as a reference.

[0025] It should be understood that in this embodiment, the input vector can also be subjected to time series feature extraction through a trained neural network. The neural network can extract azimuth angle data and altitude angle data based on multiple non-continuous preset historical time points, determine the azimuth angle change characteristics and altitude angle change characteristics of the sun relative to the solar thermal collector evaporator during the period from sunrise to sunset, and obtain the azimuth angle input vector and the altitude angle input vector.

[0026] In step S13, the direction angle change trend and altitude angle change trend of sunlight within the expected time range are predicted according to the direction angle time series feature vector and the altitude angle time series feature vector, and expected direction angle data and expected altitude angle data are generated.

[0027] For example, in this embodiment, the full-link neural network that has been trained can predict the change trend of the angular direction and the change trend of the altitude angle of sunlight within the expected time range based on the angular direction time series feature vector and the altitude angle time series feature vector, and generate expected angular direction data and expected altitude data. The expected angular direction data and expected altitude data are the change trend data of the angular direction and the altitude angle of sunlight within the future time range. That is, the change angle of the angular direction within the future time range, and the change angle of the altitude within the future time range. It should be noted that when the reference point is fixed, within the expected time range (for example, within three days to seven days), the degree of change of the angular direction and the altitude angle of the sun relative to the reference point is low, and for the solar energy collection evaporator to collect solar energy resources, this degree of change has a low degree of change in the amount of solar energy collected and can be ignored. Therefore, when analyzing the change trend of the angular direction and the altitude angle of the sun, the change trend of the altitude angle and the angular direction collected in multiple historical times before the current moment can be used as a reference to predict the change trend of the altitude angle and the angular direction of the sun at multiple future moments after the current moment. For example, the above multiple historical moments can be the sun altitude and sun angle collected by the solar thermal evaporator within the past 3 days to predict the trend of sun altitude and sun angle changes after the current moment. For example, the full-link neural network is used to identify the time series feature vector of the azimuth angle and the time series feature vector of the altitude angle, match the trend change characteristics of sunlight, and after finding the corresponding sunlight change characteristics, generate the expected azimuth angle data and expected altitude angle data from the current moment to the sunset moment.

[0028] In step S14, based on the optimal energy conversion efficiency and expected direction angle data and expected altitude angle data of the solar thermal evaporator, the flip angle of the lighting plane is determined, and according to the flip angle, the flipping of the lighting plane is controlled so that the difference between the target energy conversion efficiency and the optimal energy conversion efficiency of the solar thermal evaporator after flipping is within a preset efficiency difference range.

[0029] For example, in this embodiment, the flip angle of the lighting plane corresponding to the solar thermal evaporator is determined according to the expected altitude angle, the expected direction angle, and the optimal energy conversion efficiency of the solar thermal evaporator. According to the flip angle, the lighting plane of the solar thermal evaporator is controlled to flip, so that the difference between the target energy conversion efficiency and the optimal conversion efficiency of the solar thermal evaporator after flipping is within the preset efficiency difference range, that is, the lighting angle of the lighting plane is adjusted by predicting the direction angle and altitude angle of sunlight, so as to increase the lighting efficiency of the lighting plane, and then increase the energy conversion efficiency of the solar thermal evaporator, so that the energy conversion efficiency is close to the optimal energy conversion efficiency.

[0030] Optionally, in some embodiments, the above steps control the flipping of the lighting plane according to the flipping angle, including: According to the flipping angle, determining the flipping angle of the lighting plane in the first set direction and the lifting and lowering limit of the lighting plane in the vertical direction; According to the flipping angle and lifting limit, the flipping of the lighting plane is controlled.

[0031] For example, in this embodiment, the flip angle of the lighting plane in the first set direction and the lifting limit of the lighting plane in the vertical direction are determined according to the flip angle, and the flipping of the lighting plane is controlled according to the flip angle and the lifting limit.

[0032] Optionally, in some embodiments, the above step S14 includes: In step S141, the expected direction angle data and the expected altitude angle data are randomly transformed to generate multiple random particle parameters in the initial particle group, where the first particle parameter includes the first position and the first speed of the particle in the initial particle group, where the first position and the first speed are used to indicate candidate solutions of the sunlight direction angle and the sunlight altitude, and the first particle parameter is any one of the multiple random particle parameters.

[0033] It should be noted that a rotating motor is provided on the solar thermal evaporator for adjusting the lighting angle of the lighting plane on the solar thermal evaporator relative to the sun. In this embodiment, a particle swarm algorithm is used to determine how the solar thermal evaporator adjusts the flip angle of the lighting plane at different times and different solar direction angles and altitude angles, so that the solar thermal evaporator can achieve the maximum energy conversion efficiency under the current trend of the sun's altitude change and angle change.

[0034] For example, in this embodiment, the optimal direction angle and optimal altitude angle of the lighting plane within the future time range are determined according to the predicted direction angle data and the expected altitude angle data. The particle swarm algorithm is used to determine the optimal direction angle and optimal altitude angle of the lighting plane. The expected direction angle data and the expected altitude angle data are used as the initialization particles in the corresponding search space in the particle swarm algorithm, and the expected direction angle data and the expected altitude angle data are randomly transformed to generate multiple random particle parameters in the initial particle swarm, that is, after determining multiple expected direction angle data and multiple expected altitude angle data based on the above steps, because the solar thermal collector evaporator can randomly transform the direction angle of the lighting plane based on the lighting plane, therefore, there may be a variety of different direction angles and a variety of different altitude angles. Combinations, through random transformation, obtain multiple combinations of direction angles and altitude angles. Among them, any particle parameter includes the position and speed of the particle, which is used to indicate the candidate solution of the sunlight direction angle and sunlight altitude. Based on the optimal energy conversion efficiency, the optimal position is constructed in the search space, and the current speed of the particle parameter is obtained according to the degree of proximity of each particle to the optimal position during the random transformation process.

[0035] In step S142, the position and velocity of each random particle parameter among the multiple random particle parameters are updated according to the optimal energy conversion efficiency, and multiple energy conversion efficiencies corresponding to the updated random particle parameters are determined.

[0036] For example, the position and speed of each random particle parameter in the multiple random particle parameters are updated according to the optimal energy conversion efficiency, that is, the multiple random particle parameters generated in the above transformation process are iteratively transformed based on the optimal energy conversion efficiency. After obtaining the transformed multiple random particle parameters, the energy conversion efficiency currently corresponding to the updated random particle parameters is determined based on the calculation relationship between the solar altitude angle and the solar azimuth angle configured in the solar thermal collector evaporator and the energy conversion efficiency. It should be noted that in this embodiment, the conversion relationship between the energy conversion efficiency and the solar altitude and the solar incident angle can be determined through limited experiments when the relevant conversion parameters of the current solar thermal collector evaporator are certain. Based on the energy conversion relationship, the corresponding relationship between the lighting plane angle and the energy conversion efficiency at different incident angles and different incident solar altitudes can be determined. Based on the above random transformation method, the energy conversion efficiency corresponding to each random particle parameter after the random transformation is determined through the corresponding relationship.

[0037] In step S143, multiple fitness parameters corresponding to the updated multiple random particle parameters are determined according to the multiple energy conversion efficiencies; and global direction angle data and global altitude angle data of the updated multiple random particle parameters are determined according to the multiple fitness parameters.

[0038] For example, according to the energy conversion efficiency corresponding to each particle parameter, the fitness parameter corresponding to each random particle parameter after the update is determined. According to each fitness parameter, the global angular direction data and global elevation angle data of multiple random particle parameters after the update are determined. In this embodiment, the energy conversion efficiency is compared with the optimal energy conversion efficiency to determine the degree of adaptation between the energy conversion efficiency of the corresponding particle under the current random transformation and the optimal energy conversion efficiency. For example, if the current energy conversion efficiency obtained after the random transformation is large in difference from the optimal energy conversion efficiency, it is determined that the fitness parameter of the current particle is low. If the overall fitness parameter of each particle exceeds the global optimal fitness corresponding to the optimal energy conversion efficiency, the global optimal position corresponding to the optimal particle is updated, that is, the corresponding global angular direction data and global elevation angle data are updated. That is, in this application, after obtaining multiple random particle parameters based on the transformation of the above-mentioned particle group, the fitness of multiple random particle parameters is obtained. When the fitness does not exceed the global optimal fitness corresponding to the current optimal solution, the random transformation is continued until the fitness exceeds the optimal fitness. If it exceeds the global optimal fitness of the optimal solution, the global optimal solution is updated to obtain global angular direction data and global elevation angle data. Among them, the global direction angle data and the global altitude angle data are used to indicate the optimal direction angle change of the corresponding direction angle data at different altitude angles in order to obtain the optimal energy conversion efficiency. The optimal energy conversion efficiency is the total energy conversion efficiency of the solar thermal collector evaporator from sunrise to sunset.

[0039] In step S144, the flip angle of the lighting plane is determined according to the global direction angle data and the global altitude angle data.

[0040] For example, the flip angle corresponding to the lighting plane is determined according to the global direction angle data and the global altitude angle data, so that the direction angle and altitude angle of the sunlight match the global data, thereby making the energy conversion efficiency of the solar thermal evaporator greater than the set threshold.

[0041] Optionally, in some embodiments, the above step S144 includes: In the case where it is determined that the set termination condition is not met, based on the updated multiple random particle parameters, repeating the step of determining the global direction angle data and the global altitude angle data of the updated multiple random particle parameters according to the optimal energy conversion efficiency to generate target global direction angle data and target global altitude angle data; When it is determined that the set termination condition is met based on the target global direction angle data and the target global altitude angle data, the flip angle of the lighting plane is determined according to the target global direction angle data and the target global altitude angle data.

[0042] For example, the particle swarm algorithm is an optimal parameter solving algorithm that is continuously iterated and updated. In the process of updating the parameters of each particle in the particle swarm, it is continuously determined whether the termination condition of the iterative transformation is currently reached. If it is determined that the set termination condition is not met, the global direction angle data and global altitude angle data of the updated multiple random particle parameters are repeated according to the optimal energy conversion efficiency based on the updated multiple random particle parameters, and then the target global direction angle data and target global altitude angle data are generated. Repeat the above steps to continuously update the position and speed of each particle parameter in the particle swarm until the set termination condition is reached. Generate the global direction angle and the global altitude angle, and then obtain the flip angle of the lighting plane based on the global direction angle and the global direction angle.

[0043] Optionally, in some embodiments, the above step of “determining the flip angle of the lighting plane according to the target global direction angle data and the target global altitude angle data” includes: Determine a first rotation angle of the lighting plane in a first set direction according to a difference between the target global direction angle data and the initial direction angle data detected by the current lighting plane, wherein the first set direction is parallel to the lighting plane; Determine a second rotation angle of the lighting plane in a second set direction according to a difference between the target global altitude angle data and the initial altitude angle data detected by the current lighting plane, where the second set direction is perpendicular to the lighting plane; A flip angle is determined according to the first rotation angle and the second rotation angle.

[0044] For example, according to the target global direction angle data and the initial direction angle data detected by the current lighting plane, as well as the target global altitude angle data and the initial altitude angle data detected by the current lighting plane, the first rotation angle and the second rotation angle of the lighting plane are determined. The first rotation angle is the rotation angle of the lighting plane in the first set direction, through which the lighting plane is flipped with the central axis as the central axis. According to the second rotation angle, the lighting plane is controlled to flip in the second set direction.

[0045] Optionally, in some embodiments, setting the termination condition includes: The update times of the plurality of random particle parameters reaches the maximum number of iterations; or, The difference between the target energy conversion efficiency and the optimal energy conversion efficiency is less than a preset threshold, and the target energy conversion efficiency is the energy conversion efficiency corresponding to the updated multiple random particle parameters.

[0046] For example, in this embodiment, a particle swarm algorithm is used to determine the adjusted sunlight direction angle and altitude angle of the lighting plane within the expected time range. With energy conversion efficiency as the objective function of the particle swarm algorithm, the particle swarm is randomly updated to obtain the optimal direction angle and optimal altitude angle. The main steps of the particle swarm algorithm are: (1) Define the optimization problem: First, it is necessary to clearly define the optimization problem, that is, determine the objective function of the sunlight angle. In this case, the objective function can be the energy conversion efficiency of the solar system, or the output power of the solar system. This depends on the specific system design goals. (2) Initialize the particle swarm: Initialize a group of random particles, each particle represents a possible sunlight angle. The position and velocity of each particle are used to represent the candidate solution of the sunlight angle. (3) Update the particle position and velocity: According to the specific rules of PSO (Particle Swarm Optimization, particle swarm algorithm), the position and velocity of each particle are updated. This usually includes adjusting the movement direction of the particle according to the current position and velocity of each particle and the global optimal position and velocity. (4) Evaluate fitness: For each new position of each particle, calculate its corresponding objective function value, that is, the energy conversion efficiency or output power of the solar system. According to the value of the objective function, the fitness of the particles is evaluated. (5) Update the global optimal solution: According to the fitness values ​​of all particles, the global optimal solution is updated and the global optimal sunlight angle is recorded. (6) Termination condition: Set the termination condition, such as reaching the maximum number of iterations or reaching the required solution accuracy. If the termination condition is not met, return to step 3 and continue iterating. (7) Output result: The final global optimal solution is the optimal sunlight angle determined by the particle swarm algorithm, which is applied to the solar energy system to maximize the energy collection efficiency.

[0047] Through the above method, when it is determined that the current first energy conversion efficiency of the solar thermal collector evaporator is less than the set threshold, the photosensitive detection device is used to determine multiple directional angle data and multiple altitude angle data of sunlight on the lighting plane corresponding to the solar thermal collector evaporator at multiple preset historical time points before the current moment, and the multiple directional angle data and the multiple altitude angle data are sorted according to multiple preset historical time points to generate directional angle input vectors and altitude angle input vectors; feature extraction is performed on the directional angle input vector and the altitude angle input vector in the time domain space to generate directional angle time series feature vectors and altitude angle time series feature vectors; according to the directional angle time series feature vectors and the altitude angle time series feature vectors, the directional angle change trend and the altitude angle change trend of sunlight within the expected time range are predicted to generate expected directional angle data and expected altitude angle data; based on the optimal energy conversion efficiency of the solar thermal collector evaporator and the expected directional angle data and the expected altitude angle data, the flip angle of the lighting plane is determined; and according to the flip angle, the flipping of the lighting plane is controlled so that the difference between the target energy conversion efficiency and the optimal energy conversion efficiency of the solar thermal collector evaporator after flipping is within the preset efficiency difference range. Therefore, when the energy conversion efficiency is reduced, the lighting plane angle of the solar thermal collector evaporator is adjusted to achieve the maximum lighting efficiency, thereby improving the energy conversion efficiency of the solar thermal collector evaporator.

[0048] Figure 2 FIG. 1 is a block diagram of a control device for a solar thermal evaporator according to an exemplary embodiment. Figure 2 As shown, the device 100 includes: The determination module 110 is used to determine, when it is determined that the current first energy conversion efficiency of the solar thermal evaporator is less than a set threshold, multiple direction angle data and multiple altitude angle data of sunlight on the lighting plane corresponding to the solar thermal evaporator at multiple preset historical time points before the current moment through a photosensitive detection device; The first generating module 120 is used to sort the multiple azimuth angle data and the multiple altitude angle data according to the multiple preset historical time points to generate an azimuth angle input vector and an altitude angle input vector; perform feature extraction on the azimuth angle input vector and the altitude angle input vector in the time domain space to generate an azimuth angle time series feature vector and an altitude angle time series feature vector; A second generating module 130 is used to predict the direction angle change trend and the altitude angle change trend of the sunlight within the expected time range according to the direction angle time series feature vector and the altitude angle time series feature vector, and generate expected direction angle data and expected altitude angle data; The execution module 140 is used to determine the flipping angle of the lighting plane based on the optimal energy conversion efficiency of the solar thermal evaporator and the expected direction angle data and the expected altitude angle data, and control the flipping of the lighting plane according to the flipping angle so that the difference between the target energy conversion efficiency of the solar thermal evaporator and the optimal energy conversion efficiency after flipping is within a preset efficiency difference range.

[0049] Optionally, the execution module 140 includes: A first generation submodule is used to randomly transform the expected direction angle data and the expected altitude angle data to generate multiple random particle parameters in the initial particle group, wherein the first particle parameter includes a first position and a first speed of the particle in the initial particle group, the first position and the first speed are used to indicate candidate solutions of the sunlight direction angle and the sunlight altitude, and the first particle parameter is any of the multiple random particle parameters; A first determination submodule is used to update the position and speed of each random particle parameter among the multiple random particle parameters according to the optimal energy conversion efficiency, and determine multiple energy conversion efficiencies corresponding to the updated random particle parameters; The second determination submodule is used to determine a plurality of fitness parameters corresponding to the updated plurality of random particle parameters according to the plurality of energy conversion efficiencies; and to determine the global direction angle data and the global altitude angle data of the updated plurality of random particle parameters according to the plurality of fitness parameters; The third determination submodule is used to determine the flip angle of the lighting plane according to the global direction angle data and the global altitude angle data.

[0050] Optionally, the third determining submodule includes: A first determination unit is used for, when it is determined that the set termination condition is not met, repeating the step of determining the global direction angle data and the global altitude angle data of the updated multiple random particle parameters according to the optimal energy conversion efficiency based on the updated multiple random particle parameters, so as to generate target global direction angle data and target global altitude angle data; The second determination unit is used to determine the flip angle of the lighting plane according to the target global direction angle data and the target global altitude angle data when it is determined that the set termination condition is met based on the target global direction angle data and the target global altitude angle data.

[0051] Optionally, the second determination unit is configured to: Determine a first rotation angle of the lighting plane in a first set direction according to a difference between the target global direction angle data and the initial direction angle data detected by the current lighting plane, wherein the first set direction is parallel to the lighting plane; Determine a second rotation angle of the lighting plane in a second set direction according to a difference between the target global altitude angle data and the initial altitude angle data detected by the current lighting plane, where the second set direction is perpendicular to the lighting plane; A flip angle is determined according to the first rotation angle and the second rotation angle.

[0052] Optionally, setting the termination condition includes: The number of updates of multiple random particle parameters reaches the maximum number of iterations; or, The difference between the target energy conversion efficiency and the optimal energy conversion efficiency is less than a preset threshold, and the target energy conversion efficiency is the energy conversion efficiency corresponding to the updated multiple random particle parameters.

[0053] Optionally, the first generating module is used to: Inputting the directional angle input vector into a preset multi-scale domain extraction model to generate a directional angle time domain feature vector, wherein the multi-scale domain extraction model is used to extract the time domain features in the vector; The altitude angle input vector is input into the preset multi-scale domain extraction model to generate the altitude angle time domain feature vector.

[0054] Optionally, an execution module is used to: According to the flipping angle, determining the flipping angle of the lighting plane in the first set direction and the lifting and lowering limit of the lighting plane in the vertical direction; According to the flipping angle and lifting limit, the flipping of the lighting plane is controlled.

[0055] Through the above method, when it is determined that the current first energy conversion efficiency of the solar thermal collector evaporator is less than the set threshold, the photosensitive detection device is used to determine multiple directional angle data and multiple altitude angle data of sunlight on the lighting plane corresponding to the solar thermal collector evaporator at multiple preset historical time points before the current moment, and the multiple directional angle data and the multiple altitude angle data are sorted according to multiple preset historical time points to generate directional angle input vectors and altitude angle input vectors; feature extraction is performed on the directional angle input vector and the altitude angle input vector in the time domain space to generate directional angle time series feature vectors and altitude angle time series feature vectors; according to the directional angle time series feature vectors and the altitude angle time series feature vectors, the directional angle change trend and the altitude angle change trend of sunlight within the expected time range are predicted to generate expected directional angle data and expected altitude angle data; based on the optimal energy conversion efficiency of the solar thermal collector evaporator and the expected directional angle data and the expected altitude angle data, the flip angle of the lighting plane is determined; and according to the flip angle, the flipping of the lighting plane is controlled so that the difference between the target energy conversion efficiency and the optimal energy conversion efficiency of the solar thermal collector evaporator after flipping is within the preset efficiency difference range. Therefore, when the energy conversion efficiency is reduced, the lighting plane angle of the solar thermal collector evaporator is adjusted to achieve the maximum lighting efficiency, thereby improving the energy conversion efficiency of the solar thermal collector evaporator.

[0056] The present disclosure also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the method described in any one of the aforementioned embodiments are implemented.

[0057] The present disclosure also provides an electronic device, including: processor; a memory for storing processor-executable instructions; The processor is configured to execute executable instructions in the memory to implement the method described in any one of the aforementioned embodiments.

[0058] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the present disclosure. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary technical means in the art that are not disclosed in the present disclosure. The specification and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0059] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A control method for a solar thermal evaporator, characterized in that: The method comprises: When it is determined that the current first energy conversion efficiency of the solar thermal evaporator is less than a set threshold, a photosensitive detection device is used to determine multiple direction angle data and multiple altitude angle data of sunlight on the lighting plane corresponding to the solar thermal evaporator at multiple preset historical time points before the current moment; Sorting the multiple azimuth angle data and the multiple altitude angle data according to the multiple preset historical time points to generate azimuth angle input vectors and altitude angle input vectors; performing feature extraction on the azimuth angle input vectors and the altitude angle input vectors in the time domain space to generate azimuth angle time series feature vectors and altitude angle time series feature vectors; According to the direction angle time series feature vector and the altitude angle time series feature vector, predicting the direction angle change trend and altitude angle change trend of the sunlight within an expected time range, and generating expected direction angle data and expected altitude angle data; Based on the optimal energy conversion efficiency of the solar thermal collector evaporator and the expected direction angle data and the expected altitude angle data, the flip angle of the lighting plane is determined, and according to the flip angle, the flipping of the lighting plane is controlled so that the difference between the target energy conversion efficiency of the solar thermal collector evaporator and the optimal energy conversion efficiency after flipping is within a preset efficiency difference range.

2. The control method of the solar thermal evaporator according to claim 1, characterized in that: The method of determining the flip angle of the lighting plane based on the optimal energy conversion efficiency of the solar thermal evaporator and the expected direction angle data and the expected altitude angle data comprises: Randomly transform the expected direction angle data and the expected altitude angle data to generate multiple random particle parameters in the initial particle group, wherein the first particle parameter includes a first position and a first speed of the particle in the initial particle group, the first position and the first speed are used to indicate candidate solutions of the sunlight direction angle and the sunlight altitude, and the first particle parameter is any of the multiple random particle parameters; According to the optimal energy conversion efficiency, the position and speed of each random particle parameter in the multiple random particle parameters are updated to determine multiple energy conversion efficiencies corresponding to the updated random particle parameters; Determine a plurality of fitness parameters corresponding to the updated plurality of random particle parameters according to the plurality of energy conversion efficiencies; determine global direction angle data and global altitude angle data of the updated plurality of random particle parameters according to the plurality of fitness parameters; The flip angle of the lighting plane is determined according to the global direction angle data and the global altitude angle data.

3. The control method of the solar thermal evaporator according to claim 2, characterized in that: The step of determining the flip angle of the lighting plane according to the global direction angle data and the global altitude angle data comprises: In the case where it is determined that the set termination condition is not met, based on the updated multiple random particle parameters, repeating the step of determining the global direction angle data and the global altitude angle data of the updated multiple random particle parameters according to the optimal energy conversion efficiency to generate target global direction angle data and target global altitude angle data; When it is determined that the set termination condition is met based on the target global direction angle data and the target global altitude angle data, the flip angle of the lighting plane is determined according to the target global direction angle data and the target global altitude angle data.

4. The control method of the solar thermal evaporator according to claim 3, characterized in that: The step of determining the flip angle of the lighting plane according to the target global direction angle data and the target global altitude angle data comprises: Determine a first rotation angle of the lighting plane in a first set direction according to a difference between the target global direction angle data and the initial direction angle data detected by the current lighting plane, wherein the first set direction is parallel to the lighting plane; Determine a second rotation angle of the lighting plane in a second set direction according to a difference between the target global altitude angle data and the initial altitude angle data detected by the current lighting plane, wherein the second set direction is perpendicular to the lighting plane; The flip angle is determined according to the first rotation angle and the second rotation angle.

5. The control method of the solar thermal evaporator according to any one of claims 3-4, characterized in that: The setting of the termination conditions includes: The update times of the plurality of random particle parameters reaches the maximum number of iterations; or, The difference between the target energy conversion efficiency and the optimal energy conversion efficiency is less than a preset threshold, and the target energy conversion efficiency is the energy conversion efficiency corresponding to the updated multiple random particle parameters.

6. The control method of the solar thermal evaporator according to claim 1, characterized in that: The step of extracting features of the direction angle input vector and the altitude angle input vector in the time domain space to generate a direction angle time series feature vector and an altitude angle time series feature vector comprises: Inputting the direction angle input vector into a preset multi-scale domain extraction model to generate the direction angle time domain feature vector, wherein the multi-scale domain extraction model is used to extract the time domain features in the vector; The altitude angle input vector is input into the preset multi-scale domain extraction model to generate the altitude angle time domain feature vector.

7. The control method of the solar thermal evaporator according to claim 1, characterized in that: The controlling the flipping of the lighting plane according to the flipping angle includes: According to the flipping angle, determining the flipping angle of the lighting plane in the first set direction and the lifting and lowering limit of the lighting plane in the vertical direction; The lighting plane is controlled to flip according to the flip angle and the lifting limit.

8. A control device for a solar thermal evaporator, characterized in that: include: A determination module, for determining, when determining that the current first energy conversion efficiency of the solar thermal collector evaporator is less than a set threshold, multiple directional angle data and multiple altitude angle data of sunlight on the lighting plane corresponding to the solar thermal collector evaporator at multiple preset historical time points before the current moment through a photosensitive detection device; A first generating module is used to sort the multiple azimuth angle data and the multiple altitude angle data according to the multiple preset historical time points to generate an azimuth angle input vector and an altitude angle input vector; perform feature extraction on the azimuth angle input vector and the altitude angle input vector in a time domain space to generate an azimuth angle time series feature vector and an altitude angle time series feature vector; A second generating module is used to predict the direction angle change trend and the altitude angle change trend of the sunlight within the expected time range according to the direction angle time series feature vector and the altitude angle time series feature vector, and generate expected direction angle data and expected altitude angle data; An execution module is used to determine the flipping angle of the lighting plane based on the optimal energy conversion efficiency of the solar thermal evaporator and the expected direction angle data and the expected altitude angle data, and control the flipping of the lighting plane according to the flipping angle so that the difference between the target energy conversion efficiency of the solar thermal evaporator and the optimal energy conversion efficiency after flipping is within a preset efficiency difference range.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to execute executable instructions in the memory to implement the method described in any one of claims 1-7.

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