Light field distribution optimization method and device, electronic equipment and storage medium

Abstract

The invention discloses a light field distribution optimization method and device, electronic equipment and a storage medium. According to the application, incident angle related parameters can be determined based on optical characteristics of a photovoltaic module, and an installation inclination angle is dynamically adjusted in combination with environmental parameters, so that dynamic adaptation of a light spot diffusion coefficient and a sun trajectory parameter is realized; through linkage of a light field intensity distribution model and a photo-thermal power distribution strategy, the energy distribution proportion of a photovoltaic power generation unit and a photo-thermal conversion unit is optimized in real time, and the problem that the speed distribution of fluid in a heat collection pipe is not uniform is solved; meanwhile, when the system runs abnormally, a preset control strategy is started to adjust related parameters, it is guaranteed that the energy conversion process is stable and efficient, and the technical effects of improving the photoelectric conversion efficiency, optimizing the photo-thermal utilization effect, improving the comprehensive energy efficiency utilization rate of the system, guaranteeing stable running of the system and adapting to different environment working conditions are achieved.

Description

Technical Field

[0001] This disclosure relates to the field of data processing technology, and in particular to a method and apparatus for optimizing light field distribution, electronic equipment, and storage medium. Background Technology

[0002] Photovoltaic-thermal integrated systems, as an important technological path for the comprehensive utilization of new energy, are widely used in building energy supply, off-grid power plants, and other fields. With the improvement of photovoltaic module efficiency and the optimization of photothermal material performance, existing technologies have constructed a multi-energy coupled energy conversion system through the physical integration of photovoltaic-photothermal modules and the coordinated operation of energy storage systems. However, existing photovoltaic-thermal integrated systems employ a single-point tilt design and a straight-tube heat collection structure. These systems suffer from limitations such as a lack of dynamic matching between the light spot diffusion coefficient and solar trajectory parameters, as well as uneven fluid velocity distribution within the heat collection tubes. These limitations result in low photoelectric conversion efficiency and insufficient overall energy utilization. Summary of the Invention

[0003] This disclosure provides a method, apparatus, electronic device, and storage medium for optimizing light field distribution.

[0004] According to a first aspect of this disclosure, a method for optimizing light field distribution is provided, comprising: Determine the incident angle-related parameters based on the optical characteristics of photovoltaic modules; The installation tilt angle of the photovoltaic module array is dynamically adjusted by combining environmental parameters and the incident angle-related parameters. The energy distribution ratio between photovoltaic power generation units and photothermal conversion units is adjusted in real time by linking the light field intensity distribution model with the photothermal power allocation strategy. When a system malfunction is detected, a preset control strategy is activated to adjust the relevant operating parameters.

[0005] Optionally, determining the incident angle-related parameters based on the optical characteristics of the photovoltaic module includes: The incident angle-related parameters are calculated by collecting solar position information and local geographic information, combined with the structural characteristics of the photovoltaic module.

[0006] Optionally, dynamically adjusting the installation tilt angle of the photovoltaic module array by combining environmental parameters and incident angle-related parameters includes: A drive mechanism is used to rotate the photovoltaic module array, ensuring that the adjustment accuracy of the installation tilt angle is not lower than a preset threshold and the adjustment response time does not exceed a preset duration.

[0007] Optionally, the linked light field intensity distribution model and photothermal power allocation strategy, which adjusts the energy allocation ratio between the photovoltaic power generation unit and the photothermal conversion unit in real time, includes: A light field intensity distribution model is constructed based on the light field distribution data of the photovoltaic module surface; The power allocation coefficient is dynamically adjusted according to the light field intensity distribution model to maintain the ratio of photothermal conversion energy to photovoltaic power generation energy within a preset range.

[0008] Optionally, the system malfunction includes the temperature difference between the hot and cold ends of the thermoelectric conversion module exceeding a preset threshold or the power fluctuation exceeding a set range. The preset control strategy is an improved fuzzy PID control, which adjusts the power of the heat dissipation device and the output power of the photovoltaic module.

[0009] According to a second aspect of this disclosure, an optical field distribution optimization device is provided, comprising: The determination unit is used to determine the incident angle-related parameters based on the optical characteristics of the photovoltaic module; The adjustment unit is used to dynamically adjust the installation tilt angle of the photovoltaic module array by combining environmental parameters and the incident angle-related parameters; The adjustment unit is also used to link the light field intensity distribution model and the photothermal power allocation strategy to adjust the energy allocation ratio between the photovoltaic power generation unit and the photothermal conversion unit in real time. The adjustment unit is also used to adjust relevant operating parameters by activating a preset control strategy when an abnormal system operation is detected.

[0010] Optionally, the determining unit is further configured to: The incident angle-related parameters are calculated by collecting solar position information and local geographic information, combined with the structural characteristics of the photovoltaic module.

[0011] Optionally, the adjustment unit is further configured to: A drive mechanism is used to rotate the photovoltaic module array, ensuring that the adjustment accuracy of the installation tilt angle is not lower than a preset threshold and the adjustment response time does not exceed a preset duration.

[0012] Optionally, the adjustment unit is further configured to: A light field intensity distribution model is constructed based on the light field distribution data of the photovoltaic module surface; The power allocation coefficient is dynamically adjusted according to the light field intensity distribution model to maintain the ratio of photothermal conversion energy to photovoltaic power generation energy within a preset range.

[0013] Optionally, the system malfunction includes the temperature difference between the hot and cold ends of the thermoelectric conversion module exceeding a preset threshold or the power fluctuation exceeding a set range. The preset control strategy is an improved fuzzy PID control, which adjusts the power of the heat dissipation device and the output power of the photovoltaic module.

[0014] According to a third aspect of this disclosure, an electronic device is provided, comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method described in the first aspect above.

[0015] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method described in the first aspect above.

[0016] According to a fifth aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0017] The light field distribution optimization method, apparatus, electronic device, and storage medium disclosed herein, through this application, can determine the incident angle-related parameters based on the optical characteristics of photovoltaic modules, and dynamically adjust the installation tilt angle in combination with environmental parameters to achieve dynamic adaptation between the light spot diffusion coefficient and the solar trajectory parameters; by linking the light field intensity distribution model and the photothermal power allocation strategy, the energy allocation ratio between the photovoltaic power generation unit and the photothermal conversion unit is optimized in real time, improving the problem of uneven fluid velocity distribution in the heat collection tube; at the same time, when the system is in abnormal operation, a preset control strategy is activated to adjust the relevant parameters to ensure the stable and efficient energy conversion process. Therefore, it can solve the technical bottleneck of existing photovoltaic-photothermal integrated systems, which suffer from low photoelectric conversion efficiency and insufficient overall energy efficiency due to the lack of dynamic matching between the light spot diffusion coefficient and the solar trajectory parameters and uneven fluid velocity distribution in the heat collection tube caused by the use of single-point tilt design and straight tube heat collection structure. It achieves the technical effects of improving photoelectric conversion efficiency, optimizing photothermal utilization effect, improving the overall energy efficiency of the system, ensuring stable system operation, and adapting to different environmental conditions.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0019] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein: Figure 1 This is a flowchart illustrating a method for optimizing light field distribution provided in an embodiment of this disclosure. Figure 2 This is a schematic diagram of the structure of an optical field distribution optimization device provided in an embodiment of the present disclosure; Figure 3 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0020] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0021] The following description, with reference to the accompanying drawings, outlines a method, apparatus, electronic device, and storage medium for optimizing the light field distribution according to embodiments of the present disclosure.

[0022] Figure 1 This is a schematic flowchart of a light field distribution optimization method provided in an embodiment of the present disclosure.

[0023] like Figure 1 As shown, the method includes the following steps: Step 101: Determine the incident angle-related parameters based on the optical characteristics of the photovoltaic module; By scientifically determining the key parameters related to the incident angle based on the optical characteristics of photovoltaic modules, a fundamental basis is provided for the efficient reception of sunlight by photovoltaic modules. Among the parameters related to the incident angle, the optimal incident angle correction coefficient is the core, as it directly affects the adaptability of photovoltaic modules to incident light at different angles, and thus relates to the module's light reception efficiency and photoelectric conversion effect.

[0024] The optical characteristics of photovoltaic modules encompass many aspects, including the spectral response range of the front surface to sunlight, the optical performance of the surface anti-reflective coating, and the wavelength-selective reflection characteristics of the back reflective layer. These characteristics determine the absorption, reflection, and utilization of light by the module at different incident angles. For example, if the front surface of the module has a broad spectral response capability, its absorption efficiency of different wavelengths of sunlight will exhibit a specific pattern as the incident angle changes. This pattern needs to be used as an important reference for determining the relevant parameters of the incident angle. If the back reflective layer of the module can selectively reflect specific wavelengths of light, the angular distribution characteristics of the light during this reflection process will also affect the overall light reception effect of the module, and this also needs to be included in the scope of parameter determination.

[0025] In the actual determination process, it is necessary to combine the specific optical characteristics of the photovoltaic module and analyze the changing trend of the module's light utilization efficiency under different incident angles, and then adjust parameters such as the optimal incident angle correction coefficient. The incident angle-related parameters determined in this way enable the photovoltaic module to better adapt to the dynamic changes of the solar incident angle, ensuring that the module can receive sunlight at a better angle at different times and under different lighting conditions, laying the foundation for subsequent improvements in photoelectric conversion efficiency.

[0026] Step 102: Based on environmental parameters and the incident angle-related parameters, dynamically adjust the installation tilt angle of the photovoltaic module array; By combining environmental parameters with incident angle-related parameters, the installation tilt angle of the photovoltaic module array can be dynamically adjusted to ensure that the array always maintains a state of efficient sunlight reception. Environmental parameters encompass key factors such as solar altitude angle, solar azimuth angle, and local latitude. The solar altitude angle, which is the angle between the sun's rays and the horizontal plane, fluctuates regularly with day-night cycles and seasonal changes, directly affecting the verticality of sunlight incident on the photovoltaic module surface. The solar azimuth angle, the angle between the projection of sunlight onto the horizontal plane and the due south direction, reflects the sun's position in the horizontal direction and determines the horizontal angle of sunlight incidence. Local latitude, a fixed geographical parameter, determines the basic range of the sun's trajectory in the local sky and is the fundamental basis for calculating the solar altitude angle and azimuth angle.

[0027] The incident angle parameters were previously determined based on the optical characteristics of photovoltaic modules, with the core being the optimal incident angle correction coefficient. This coefficient reflects the module's optical characteristics' adaptability to light at different incident angles. During dynamic adjustment, it is necessary to collect real-time data on changes in environmental parameters and, combined with the optimal incident angle correction coefficient, continuously optimize the installation tilt angle of the photovoltaic module array through preset tilt angle adjustment logic. For example, when the solar altitude angle increases, adjusting the tilt angle reduces the angle between the light and the module surface, thus reducing light reflection loss; when the solar azimuth angle changes, the tilt angle is adjusted synchronously to better align the module array with the sun's azimuth, ensuring that more light can effectively incident on the module surface, thereby providing angle adaptation guarantees for improving the photovoltaic module's photoelectric conversion efficiency.

[0028] Step 103: Link the light field intensity distribution model and the photothermal power allocation strategy to adjust the energy allocation ratio between the photovoltaic power generation unit and the photothermal conversion unit in real time; By linking the light field intensity distribution model with the photothermal power allocation strategy, the energy allocation ratio between photovoltaic (PV) power generation units and photothermal conversion units can be adjusted in real time to ensure efficient utilization of solar energy resources in both energy conversion paths. The light field intensity distribution model accurately calculates the light field intensity at different coordinate locations. Its core is based on key parameters such as the maximum light field intensity at the concentrator center, the light spot diffusion coefficient, and the coordinates of the concentrator center, reflecting the current spatial distribution pattern of illumination and identifying areas with sufficient and relatively weak illumination. This provides data support for judging the energy conversion potential of PV power generation units and photothermal conversion units. The photothermal power allocation strategy revolves around the optimization coefficient and the output power of the PV power generation unit. This strategy determines a reasonable range of thermal power allocated to the photothermal conversion unit, ensuring that the energy allocation of the photothermal conversion process matches the photovoltaic conversion process and avoiding excessive consumption of solar energy resources by a single unit.

[0029] In actual operation, it is necessary to acquire real-time illumination distribution data from the light field intensity distribution model. If the light field intensity is high in a certain area, it indicates that the area is more conducive to efficient photovoltaic power generation unit conversion, and the energy allocation ratio of that unit can be appropriately increased. Simultaneously, combined with the solar thermal power allocation strategy, the thermal power allocation of the solar thermal conversion unit is adjusted according to the real-time output power of the photovoltaic power generation unit, preventing insufficient or excessive energy input from affecting the conversion efficiency. Through this dynamic linkage adjustment, the photovoltaic power generation unit and the solar thermal conversion unit can always adapt their energy allocation ratios according to the current illumination conditions and energy conversion needs, effectively reducing the waste of solar energy resources and improving the overall system's comprehensive solar energy utilization efficiency.

[0030] Step 104: When a system malfunction is detected, a preset control strategy is activated to adjust the relevant operating parameters.

[0031] By promptly detecting system malfunctions and activating preset control strategies, relevant operating parameters can be quickly adjusted to ensure stable system operation and prevent abnormal conditions from affecting system efficiency or component safety. System malfunctions typically manifest as key operating indicators deviating from normal ranges. For example, the temperature difference between the hot and cold ends of the thermoelectric conversion module may exceed a set threshold, system power may fluctuate beyond normal ranges, or bus voltage may deviate from the standard range. If these malfunctions are not addressed promptly, they may lead to decreased energy conversion efficiency or even component damage.

[0032] The preset control strategy is an adaptive control scheme pre-set based on the system's long-term operating characteristics and common abnormal scenarios. It can quickly match the corresponding control logic for different types of anomalies without the need to build a control model on the spot, ensuring timely and accurate response. After the preset control strategy is activated, relevant operating parameters will be precisely adjusted according to the detected anomaly type: if an abnormal temperature difference is detected, the operating power of the heat dissipation device will be adjusted to balance the hot and cold end temperatures of the thermoelectric conversion module by changing the heat dissipation efficiency; if an abnormal power fluctuation is detected, the energy output intensity of the photovoltaic power generation unit or the heat power distribution ratio of the photothermal conversion unit will be adjusted to stabilize the overall power output of the system; if an abnormal bus voltage occurs, the working status of the voltage regulation components can also be adjusted to bring the bus voltage back to the normal range. Through such targeted adjustments, abnormal operating conditions can be quickly alleviated, allowing the system to return to a stable and efficient operating state and reducing the impact of anomalies on the overall system performance.

[0033] In some embodiments, determining the incident angle-related parameters based on the optical characteristics of the photovoltaic module includes: The incident angle-related parameters are calculated by collecting solar position information and local geographic information, combined with the structural characteristics of the photovoltaic module.

[0034] When determining the parameters related to the incident angle based on the optical characteristics of photovoltaic (PV) modules, it is necessary to first collect solar position information and local geographic information, and then combine this with the structural characteristics of the PV modules to complete the calculations. This ensures that the obtained parameters accurately match the modules' requirements for receiving and utilizing light. Solar position information mainly includes the solar altitude angle and solar azimuth angle. The solar altitude angle refers to the angle between the sun's rays and the ground plane, and its value changes periodically with the alternation of day and night and the changing seasons, directly determining the verticality of the light rays incident on the surface of the PV modules. The solar azimuth angle refers to the angle between the projection of the sun's rays onto the ground plane and the due south direction, reflecting the sun's horizontal position movement and affecting the horizontal angle of light incidence. The core of the local geographic information is the local latitude, a fixed geographic parameter that determines the basic range of the sun's trajectory in the local sky and is the basis for subsequent calculations of the solar altitude angle, solar azimuth angle, and incident angle parameters.

[0035] The structural and optical characteristics of photovoltaic (PV) modules are closely related. For example, the perovskite-crystalline silicon stacked structure used on the front surface of the module affects the spectral response range of the module to different wavelengths of sunlight due to the thickness and bandgap characteristics of its different layers, thus determining the module's light absorption efficiency at different incident angles. Similarly, the wavelength-selective reflective layer integrated on the back of the module affects the reflection pattern of specific wavelengths of light due to its coating material, thickness, and other structural parameters. The angular distribution characteristics of these reflected rays also affect the overall light reception performance of the module. When calculating incident angle-related parameters, it is necessary to combine the collected solar position information, local geographical information, and the structural characteristics of the module to analyze the absorption and reflection patterns of light at different incident angles. This allows for the accurate calculation of incident angle correction coefficients and other incident angle-related parameters, providing a scientific basis for the subsequent dynamic adjustment of the PV module array installation tilt angle.

[0036] In some embodiments, dynamically adjusting the installation tilt angle of the photovoltaic module array by combining environmental parameters and incident angle-related parameters includes: A drive mechanism is used to rotate the photovoltaic module array, ensuring that the adjustment accuracy of the installation tilt angle is not lower than a preset threshold and the adjustment response time does not exceed a preset duration.

[0037] The drive mechanism typically uses a stepper motor drive system, which consists of a stepper motor, a transmission gear set, and a support frame. It can drive the photovoltaic module array to rotate smoothly around a preset rotation axis according to the control signal, avoiding shaking or displacement of the modules during the adjustment process and ensuring the stability and reliability of the adjustment action.

[0038] The adjustment accuracy must be no less than a preset threshold. This threshold is usually determined based on the optical characteristics of the photovoltaic module and actual operating requirements. For example, a common preset accuracy threshold is ±0.5°. If the adjustment accuracy is lower than this threshold, the photovoltaic module will not be able to accurately align with the angle of sunlight incidence, resulting in increased reflection loss when light is incident, which in turn reduces the light receiving efficiency of the module and affects the subsequent photoelectric conversion effect.

[0039] The response time adjustment must not exceed the preset duration, which is generally set in the second range, such as within 5 seconds. Because environmental parameters such as solar altitude angle and solar azimuth angle change dynamically over time, if the response time is too long, the installation tilt angle adjustment of the photovoltaic module array will lag behind the change in the sun's position, causing the modules to be at a suboptimal receiving angle for a period of time, thus missing the opportunity for efficient light reception.

[0040] During the actual adjustment process, the drive mechanism receives real-time signals of changes in environmental parameters (such as solar altitude angle and solar azimuth angle) and incident angle-related parameters (such as the optimal incident angle correction coefficient). Based on these signals, it quickly calculates the target tilt angle and immediately executes the rotation action. Under the premise of meeting the accuracy and response time requirements, it completes the dynamic optimization of the installation tilt angle, laying the foundation for photovoltaic modules to efficiently receive sunlight and improve photoelectric conversion efficiency.

[0041] In some embodiments, the linkage between the light field intensity distribution model and the photothermal power allocation strategy, which adjusts the energy allocation ratio between the photovoltaic power generation unit and the photothermal conversion unit in real time, includes: A light field intensity distribution model is constructed based on the light field distribution data of the photovoltaic module surface; The power allocation coefficient is dynamically adjusted according to the light field intensity distribution model to maintain the ratio of photothermal conversion energy to photovoltaic power generation energy within a preset range.

[0042] A light field intensity distribution model is constructed based on the light field distribution data of the photovoltaic module surface. Specifically, light intensity sensors are deployed at preset intervals on the photovoltaic module surface to collect light field intensity data at different coordinate points in real time. This data can intuitively reflect the spatial distribution differences of sunlight on the module surface, such as the changes in light intensity gradient between the central and edge regions of the module, and the concentration or dispersion of local light spots. Subsequently, the collected discrete light intensity data is fitted and calculated by combining key parameters such as the maximum light field intensity at the concentrator center, the light spot diffusion coefficient, and the coordinates of the concentrator center to form a light field intensity distribution model. This model can accurately present the current distribution pattern of sunlight on the module surface, clearly identify areas with sufficient sunlight and areas with relatively weak sunlight, and provide data support for subsequent determination of energy distribution direction.

[0043] Based on this, the power allocation coefficient is dynamically adjusted according to the light field intensity distribution model to maintain the ratio of photothermal conversion energy to photovoltaic power generation energy within a preset range. The power allocation coefficient is a core parameter directly related to the proportion of the two energy conversion paths. When the model shows that the overall light field intensity on the component surface is high and uniformly distributed, it indicates that the photovoltaic power generation unit has higher potential for photoelectric conversion efficiency. The power allocation coefficient can be appropriately lowered to reduce the proportion of energy allocated to the photothermal conversion unit, increase the energy input of the photovoltaic power generation unit, and make full use of strong light conditions to improve photoelectric output. When the model shows that the light field intensity is low or the light intensity in some areas is insufficient, the power allocation coefficient can be appropriately increased to increase the proportion of energy in the photothermal conversion unit and avoid energy waste caused by the decrease in photoelectric conversion efficiency under weak light conditions. The preset range is set based on the principle of optimal overall system energy efficiency. For example, a common preset range is 0.6-0.8. By dynamically adjusting the power allocation coefficient, it is ensured that the two energy conversion processes are always in a highly efficient and coordinated state, avoiding excessive use of solar energy resources by a single unit and maximizing the utilization of solar energy by the system.

[0044] In some embodiments, the system malfunction includes the temperature difference between the hot and cold ends of the thermoelectric conversion module exceeding a preset threshold or the power fluctuation exceeding a set range. The preset control strategy is an improved fuzzy PID control, which adjusts the power of the heat dissipation device and the output power of the photovoltaic module.

[0045] When the system malfunctions, the main symptoms are a temperature difference between the hot and cold ends of the thermoelectric conversion module exceeding a preset threshold or power fluctuations exceeding the set range. If the temperature difference exceeds the preset threshold, it disrupts the internal energy conversion balance of the module, leading to a significant decrease in thermoelectric conversion efficiency. Prolonged exposure to this state may also cause degradation of the module's internal materials, affecting its lifespan. Power fluctuations exceeding the set range disrupt the overall energy supply and demand stability of the system, potentially causing unstable charging of subsequent energy storage units or abnormal load power supply. To address these anomalies, an improved fuzzy PID control strategy is employed. This strategy combines the rapid response characteristics of fuzzy control with the precise adjustment capabilities of PID control, dynamically optimizing control parameters based on the type and severity of the anomaly, thus avoiding the lag issues of traditional control methods. When the temperature difference between the hot and cold ends of the thermoelectric conversion module exceeds a preset threshold, the improved fuzzy PID control calculates the temperature difference deviation in real time and adjusts the power of the heat dissipation device based on the deviation change rate. If the temperature difference is too large, the heat dissipation power of the heat dissipation device is increased to accelerate heat dissipation and reduce the temperature difference. If the temperature difference is close to the threshold, the heat dissipation power is gradually reduced to prevent excessive temperature fluctuations. When the power fluctuation exceeds the set range, the control strategy analyzes the magnitude and trend of the power deviation and stabilizes the system power by adjusting the output power of the photovoltaic module. For example, if the power is too high, the energy output intensity of the photovoltaic module is appropriately reduced. If the power is too low, the module's working state is optimized based on the previously determined incident angle parameters to increase energy output. Ultimately, targeted adjustments ensure that the system quickly recovers stable operation and guarantees the high efficiency of energy conversion and transmission.

[0046] Corresponding to the aforementioned light field distribution optimization method, this invention also proposes a light field distribution optimization device. Since the device embodiments of this invention correspond to the aforementioned method embodiments, details not disclosed in the device embodiments can be referred to the aforementioned method embodiments, and will not be repeated here.

[0047] Figure 2 This is a schematic diagram of the structure of a light field distribution optimization device provided in an embodiment of the present disclosure, as shown below. Figure 2 As shown, it includes: Furthermore, in one possible implementation of the embodiments of this disclosure, such as Figure 3 As shown, Determining unit 21 is used to determine incident angle related parameters based on the optical characteristics of photovoltaic modules; Adjustment unit 22 is used to dynamically adjust the installation tilt angle of the photovoltaic module array by combining environmental parameters and the incident angle-related parameters; The adjustment unit 22 is also used to link the light field intensity distribution model and the photothermal power allocation strategy to adjust the energy allocation ratio between the photovoltaic power generation unit and the photothermal conversion unit in real time. The adjustment unit 22 is also used to adjust relevant operating parameters by activating a preset control strategy when an abnormal system operation is detected.

[0048] Furthermore, in one possible implementation of this disclosure, the determining unit 21 is further configured to: The incident angle-related parameters are calculated by collecting solar position information and local geographic information, combined with the structural characteristics of the photovoltaic module.

[0049] Furthermore, in one possible implementation of this disclosure, the adjustment unit 22 is further configured to: A drive mechanism is used to rotate the photovoltaic module array, ensuring that the adjustment accuracy of the installation tilt angle is not lower than a preset threshold and the adjustment response time does not exceed a preset duration.

[0050] Furthermore, in one possible implementation of this disclosure, the adjustment unit 22 is further configured to: A light field intensity distribution model is constructed based on the light field distribution data of the photovoltaic module surface; The power allocation coefficient is dynamically adjusted according to the light field intensity distribution model to maintain the ratio of photothermal conversion energy to photovoltaic power generation energy within a preset range.

[0051] Furthermore, in one possible implementation of the present disclosure, the system malfunction includes the temperature difference between the hot and cold ends of the thermoelectric conversion module exceeding a preset threshold or the power fluctuation exceeding a set range. The preset control strategy is an improved fuzzy PID control, which adjusts the power of the heat dissipation device and the output power of the photovoltaic module.

[0052] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of the embodiments of this disclosure, and the principle is the same. Therefore, the embodiments of this disclosure are not limited thereto.

[0053] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0054] Figure 3 A schematic block diagram of an example electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0055] like Figure 3 As shown, device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 402 or a computer program loaded from storage unit 408 into RAM (Random Access Memory) 403. RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. I / O (Input / Output) interface 405 is also connected to bus 404.

[0056] Multiple components in device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of monitors, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0057] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as the light field distribution optimization method. For example, in some embodiments, the light field distribution optimization method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform the aforementioned light field distribution optimization method by any other suitable means (e.g., by means of firmware).

[0058] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0059] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0060] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0061] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0062] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0063] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0064] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0065] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0066] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for optimizing light field distribution, characterized in that, include: Determine the incident angle-related parameters based on the optical characteristics of photovoltaic modules; The installation tilt angle of the photovoltaic module array is dynamically adjusted by combining environmental parameters and the incident angle-related parameters. The energy distribution ratio between photovoltaic power generation units and photothermal conversion units is adjusted in real time by linking the light field intensity distribution model with the photothermal power allocation strategy. When a system malfunction is detected, a preset control strategy is activated to adjust the relevant operating parameters.

2. The method according to claim 1, characterized in that, The determination of incident angle-related parameters based on the optical characteristics of photovoltaic modules includes: The incident angle-related parameters are calculated by collecting solar position information and local geographic information, combined with the structural characteristics of the photovoltaic module.

3. The method according to claim 1, characterized in that, The dynamic adjustment of the installation tilt angle of the photovoltaic module array by combining environmental parameters and incident angle-related parameters includes: A drive mechanism is used to rotate the photovoltaic module array, ensuring that the adjustment accuracy of the installation tilt angle is not lower than a preset threshold and the adjustment response time does not exceed a preset duration.

4. The method according to claim 1, characterized in that, The linked light field intensity distribution model and photothermal power allocation strategy adjust the energy allocation ratio between the photovoltaic power generation unit and the photothermal conversion unit in real time, including: A light field intensity distribution model is constructed based on the light field distribution data of the photovoltaic module surface; The power allocation coefficient is dynamically adjusted according to the light field intensity distribution model to maintain the ratio of photothermal conversion energy to photovoltaic power generation energy within a preset range.

5. The method according to claim 1, characterized in that, The system malfunctions include temperature differences between the hot and cold ends of the thermoelectric conversion module exceeding a preset threshold or power fluctuations exceeding a set range. The preset control strategy is an improved fuzzy PID control, which adjusts the power of the heat dissipation device and the output power of the photovoltaic module.

6. A device for optimizing light field distribution, characterized in that, include: The determination unit is used to determine the incident angle-related parameters based on the optical characteristics of the photovoltaic module; The adjustment unit is used to dynamically adjust the installation tilt angle of the photovoltaic module array by combining environmental parameters and the incident angle-related parameters; The adjustment unit is also used to link the light field intensity distribution model and the photothermal power allocation strategy to adjust the energy allocation ratio between the photovoltaic power generation unit and the photothermal conversion unit in real time. The adjustment unit is also used to adjust relevant operating parameters by activating a preset control strategy when an abnormal system operation is detected.

7. The apparatus according to claim 6, characterized in that, The determining unit is further configured to: The incident angle-related parameters are calculated by collecting solar position information and local geographic information, combined with the structural characteristics of the photovoltaic module.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1-5.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method according to any one of claims 1-5.

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