Electromagnetic resource intelligent control method based on data acquisition and digital model driving
The intelligent control method for electromagnetic resources driven by data acquisition and digital models solves the problem that solar energy equipment cannot be adjusted in real time in outdoor environments, achieving efficient energy utilization and stable energy supply, and improving the flexibility and autonomy of outdoor activities.
Patent Information
- Application Number
- CN202511334856.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-18
- Publication Date
- 2025-12-12
AI Technical Summary
Existing technologies lack data analysis capabilities, making it impossible for solar energy equipment to be adjusted in real time in outdoor environments. This results in inflexible energy use, reduced efficiency, and reliance on traditional fossil fuels, increasing costs and causing frequent malfunctions. It also hinders the promotion of green transformation and affects the flexibility and efficiency of outdoor activities.
Through data acquisition and digital model-driven intelligent control methods for electromagnetic resources, the electromagnetic and solar data of solar energy equipment are monitored and analyzed in real time, the equipment mode is adjusted, and real-time adjustments are made according to environmental changes. Artificial intelligence is used for fault diagnosis and optimization.
It improves the energy conversion efficiency of solar energy equipment, reduces the failure rate, ensures system stability and reliability, optimizes energy use, reduces waste, enhances the autonomy and overall capability of outdoor activities, and provides a stable energy guarantee.
Smart Images
Figure CN121116005A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of electromagnetic resource technology, and specifically to an intelligent control method for electromagnetic resources based on data acquisition and digital model-driven approaches. Background Technology
[0002] With the continuous development of technology, portable equipment is increasingly reliant on energy, especially in outdoor equipment, where the use of renewable electromagnetic energy sources such as solar energy is becoming increasingly important. Solar energy, as a clean and sustainable energy source, has increasingly broad application prospects. Solar power generation utilizes electromagnetic radiation from nature to convert it into electrical energy, providing an important solution for mitigating climate change and reducing greenhouse gas emissions. Therefore, improving the operating efficiency of solar energy equipment and ensuring its stability and reliability in variable outdoor environments has become an urgent need for outdoor activities.
[0003] Existing technologies lack data analysis capabilities, and decisions are based on experience rather than data, which may lead to unreasonable resource allocation and inefficient energy use. When faced with rapidly changing outdoor environments, they cannot make quick adjustments, making energy use inflexible and affecting execution efficiency. Obviously, this control method has at least the following problems: 1. Existing technologies usually cannot assess environmental changes in real time, which means that solar energy equipment cannot adjust in time according to sunlight intensity and weather conditions, affecting the efficiency of energy collection and utilization. It is impossible to dynamically match energy output with specific needs, which may result in energy surplus or shortage.
[0004] 2. Due to the lack of effective solar energy management, existing technologies may still require reliance on traditional fossil fuels in some situations, increasing energy procurement costs and logistical pressures. Frequent malfunctions and unstable operation increase maintenance and replacement costs. Furthermore, the technology fails to effectively utilize clean energy and continues to rely on traditional energy sources that are highly polluting, thus burdening and impacting the environment.
[0005] 3. Existing technologies lack effective promotion of renewable energy, making it difficult to drive the green transformation of outdoor equipment. At critical moments, insufficient energy may affect the use of portable equipment, weakening overall activity capabilities. The outdoor environment changes rapidly, and existing systems may not be able to adapt quickly, affecting the flexibility and efficiency of outdoor activities. Summary of the Invention
[0006] To address the aforementioned technical shortcomings, the purpose of this invention is to provide an intelligent control method for electromagnetic resources based on data acquisition and digital model-driven approaches.
[0007] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The present invention provides an intelligent control method for electromagnetic resources based on data acquisition and digital model driving, comprising: Step 1: Data Acquisition: During the operation of each solar energy device in the target area, several data collection time points are set. Electromagnetic data and illumination data corresponding to each solar energy device are collected at each data collection time point. Then, the electromagnetic evaluation coefficient and illumination evaluation coefficient corresponding to each solar energy device at each data collection time point are analyzed. Step 2: Obtaining the solar radiation assessment coefficient: Based on the electromagnetic assessment coefficient and solar radiation assessment coefficient corresponding to each solar energy device at each collection time point, the solar radiation assessment coefficient corresponding to each solar energy device at each collection time point is obtained through analysis. Step 3: Obtaining Environmental Impact Factors: Collect environmental impact data for each solar energy device at each collection time point. The environmental impact data includes cloud cover, solar altitude angle, and atmospheric transmittance. Analyze the data to obtain the environmental impact factors for each solar energy device at each collection time point. Step 4: Obtaining the comprehensive electromagnetic resource assessment coefficient: Based on the solar radiation assessment coefficient and environmental impact factor corresponding to each solar energy device at each collection time point, the comprehensive electromagnetic resource assessment coefficient corresponding to each solar energy device at each collection time point is obtained through analysis. Step 5: Adjustment of Equipment Mode: Based on the comprehensive electromagnetic resource evaluation coefficient corresponding to each solar energy device at each data collection time point, analyze the equipment mode corresponding to each solar energy device at each data collection time point, and adjust each solar energy device at each data collection time point according to the corresponding equipment mode.
[0008] Preferably, the electromagnetic data includes radiant energy density, radiant power, and radiant flux, and the illumination data includes illumination intensity, radiant intensity, and illumination reflectivity.
[0009] Preferably, the analysis yields the electromagnetic evaluation coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: The radiant energy density, radiant power, and radiant flux corresponding to each solar energy device at each data collection time point are respectively denoted as follows: , and ,in, This indicates the number corresponding to each data collection time point. u is any integer greater than 2. This indicates the serial number corresponding to each solar energy device. Let n be any integer greater than 2, and substitute it into the calculation formula. In this process, the electromagnetic evaluation coefficients corresponding to each solar energy device at each data collection time point were obtained. ,in, , , These are the standard radiative energy density, standard radiative power, and standard radiative flux corresponding to the specified solar energy equipment. , , These are the weighting factors corresponding to the set solar energy density, radiation power, and radiation flux, respectively, where e represents the natural constant.
[0010] Preferably, the analysis yields the illumination evaluation coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: The light intensity, radiation intensity, and light reflectance corresponding to each solar energy device at each data collection time point are respectively denoted as follows: , and Substitute into the calculation formula In this process, the illumination evaluation coefficients corresponding to each solar energy device at each data collection time point are obtained. ,in, , , These are the standard light intensity, standard radiation intensity, and standard light reflectance corresponding to the set solar energy equipment. , , These are the weighting factors corresponding to the set solar energy equipment's light intensity, radiation intensity, and light reflectance, respectively, where e represents the natural constant.
[0011] Preferably, the analysis yields the solar radiation assessment coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: Substitute the electromagnetic evaluation coefficient and solar radiation evaluation coefficient corresponding to each solar energy device at each data collection time point into the calculation formula. In this process, the solar radiation assessment coefficients corresponding to each solar energy device at each data collection time point were obtained. ,in, , These are the weighting factors corresponding to the electromagnetic evaluation coefficient and the solar energy evaluation coefficient, respectively.
[0012] Preferably, the analysis yields the environmental impact factors corresponding to each solar energy device at each data collection time point. The specific analysis process is as follows: The cloud cover, solar altitude angle, and atmospheric transmittance corresponding to each solar energy device at each data collection time point are respectively denoted as follows: , and Substitute into the calculation formula In this process, the environmental impact factors corresponding to each solar energy device at each data collection time point were obtained. Where ΔA, ΔB, and ΔF represent the reference deviation ranges for cloud cover, solar altitude angle, and atmospheric transmittance, respectively, for the solar energy equipment. , , These are the standard cloud cover, standard solar altitude angle, and standard atmospheric transmittance corresponding to the set solar energy equipment. , , These are the weighting factors corresponding to the cloud cover, solar altitude angle, and atmospheric transmittance of the solar energy equipment, respectively.
[0013] Preferably, the analysis yields the comprehensive electromagnetic resource evaluation coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: Substitute the solar radiation assessment coefficient and environmental impact factor corresponding to each solar energy device at each data collection time point into the calculation formula. In this process, the comprehensive electromagnetic resource assessment coefficients corresponding to each solar energy device at each data collection time point were obtained. , where e represents the natural constant.
[0014] Preferably, the analysis of the device mode corresponding to each solar energy device at each data collection time point is carried out in the following specific analysis process: The comprehensive electromagnetic resource evaluation coefficients corresponding to each solar energy device at each collection time point are compared with the comprehensive electromagnetic resource evaluation coefficient ranges corresponding to each device mode in the database. If the comprehensive electromagnetic resource evaluation coefficient of a solar energy device at a certain collection time point is within the comprehensive electromagnetic resource evaluation coefficient range corresponding to a certain device mode in the database, then the device mode in the database is recorded as the device mode corresponding to the solar energy device at the current collection time point. In this way, the device modes corresponding to each solar energy device at each collection time point are analyzed.
[0015] Preferably, the database is used to store the comprehensive electromagnetic resource evaluation coefficient range corresponding to each device mode.
[0016] The beneficial effects of the present invention are as follows: 1. The present invention provides an intelligent control method for electromagnetic resources based on data acquisition and digital model driving. By monitoring and analyzing the electromagnetic data and light data of solar energy equipment in real time, the operating mode of the equipment can be adjusted in a timely manner, thereby improving energy conversion efficiency and maximizing power output. The equipment settings can be adjusted in real time according to changes in environmental influencing factors (such as cloud cover, solar altitude angle, etc.) to ensure optimal operating conditions in a variable outdoor environment.
[0017] In this embodiment of the invention, by continuously monitoring electromagnetic resources, potential problems can be detected in a timely manner and early warnings can be issued, thereby reducing equipment failure rates and ensuring the stability and reliability of the system. By utilizing artificial intelligence technology, equipment operating data can be quickly analyzed, fault modes can be identified, fault diagnosis and maintenance suggestions can be provided, power production and use can be optimized, energy waste can be reduced, resource utilization efficiency can be improved, and energy procurement costs can be reduced.
[0018] This invention provides a way to ensure energy supply for outdoor activities through efficient solar energy equipment, thereby improving the autonomy and flexibility of outdoor activities, enhancing overall activity capabilities, providing stable and reliable energy support for high-tech weapon systems, ensuring their normal operation in complex outdoor environments, enabling the system to respond quickly to changes in the outdoor environment, flexibly adjust equipment modes, ensure efficient energy utilization in different outdoor environments, and make personalized equipment adjustments according to different mission requirements and environmental conditions to meet specific activity needs. Attached Figure Description
[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0020] Figure 1 This is a flowchart illustrating the implementation steps of the method of the present invention. Detailed Implementation
[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0022] Examples of embodiments of the present invention Figure 1 As shown, an intelligent control method for electromagnetic resources based on data acquisition and digital model-driven approaches includes: Step 1: Data Acquisition: During the operation of each solar energy device in the target area, several data collection time points are set. Electromagnetic data and illumination data corresponding to each solar energy device are collected at each data collection time point. Then, the electromagnetic evaluation coefficient and illumination evaluation coefficient corresponding to each solar energy device at each data collection time point are analyzed.
[0023] In one specific embodiment, the electromagnetic data includes radiant energy density, radiant power, and radiant flux, and the illumination data includes illumination intensity, radiant intensity, and illumination reflectivity.
[0024] It should be noted that each solar energy device in the target area is equipped with a radiometer, a photovoltaic power monitor, and a photometer, which can measure the radiant energy per unit area, monitor the output power of the solar energy devices in real time, and measure the flow of radiant energy through a certain area.
[0025] It should also be noted that a light intensity meter is used to measure the light intensity per unit area, a radiometer is used to measure the radiation intensity per unit area, and a reflectance meter or spectroreflectometer is used to measure the ratio of the intensity of reflected light to the intensity of incident light.
[0026] In another specific embodiment, the analysis yields the electromagnetic evaluation coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: The radiant energy density, radiant power, and radiant flux corresponding to each solar energy device at each data collection time point are respectively denoted as follows: , and ,in, This indicates the number corresponding to each data collection time point. u is any integer greater than 2. This indicates the serial number corresponding to each solar energy device. Let n be any integer greater than 2, and substitute it into the calculation formula. In this process, the electromagnetic evaluation coefficients corresponding to each solar energy device at each data collection time point were obtained. ,in, , , These are the standard radiative energy density, standard radiative power, and standard radiative flux corresponding to the specified solar energy equipment. , , These are the weighting factors corresponding to the set solar energy density, radiation power, and radiation flux, respectively, where e represents the natural constant.
[0027] It should be noted that, , , All are greater than 0 and less than 1.
[0028] It should also be noted that this process involves summarizing a large amount of research and experimental data. Standard radiative energy density, standard radiative power, and standard radiative flux for solar energy equipment were set by professional and research institutions. Furthermore, the data was based on the expertise and research of field experts, and discussed and confirmed with industry organizations or professional institutions. Experts then set the weighting factors for the radiative energy density, radiative power, and radiative flux of the solar energy equipment based on their experience and knowledge.
[0029] In another specific embodiment, the analysis yields the illumination evaluation coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: The light intensity, radiation intensity, and light reflectance corresponding to each solar energy device at each data collection time point are respectively denoted as follows: , and Substitute into the calculation formula In this process, the illumination evaluation coefficients corresponding to each solar energy device at each data collection time point are obtained. ,in, , , These are the standard light intensity, standard radiation intensity, and standard light reflectance corresponding to the set solar energy equipment. , , These are the weighting factors corresponding to the set solar energy equipment's light intensity, radiation intensity, and light reflectance, respectively, where e represents the natural constant.
[0030] It should be noted that, , , All are greater than 0 and less than 1.
[0031] It should also be noted that this process involves summarizing a large amount of research and experimental data. Standard light intensity, standard radiation intensity, and standard reflectance for solar energy equipment were set by professional and research institutions. Furthermore, the process was based on the professional knowledge and research of experts in the field, and was discussed and confirmed with industry organizations or professional institutions. Experts then set the weighting factors for light intensity, radiation intensity, and reflectance for the solar energy equipment based on their experience and knowledge.
[0032] Step 2: Obtaining the solar radiation assessment coefficient: Based on the electromagnetic assessment coefficient and solar radiation assessment coefficient corresponding to each solar energy device at each collection time point, the solar radiation assessment coefficient corresponding to each solar energy device at each collection time point is obtained through analysis.
[0033] In a specific embodiment, the analysis yields the solar radiation assessment coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: Substitute the electromagnetic evaluation coefficient and solar radiation evaluation coefficient corresponding to each solar energy device at each data collection time point into the calculation formula. In this process, the solar radiation assessment coefficients corresponding to each solar energy device at each data collection time point were obtained. ,in, , These are the weighting factors corresponding to the electromagnetic evaluation coefficient and the solar energy evaluation coefficient, respectively.
[0034] It should be noted that, , All are greater than 0 and less than 1.
[0035] It should also be noted that the weighting factors for the electromagnetic evaluation coefficient and the solar radiation evaluation coefficient of solar equipment are determined by experts based on their professional knowledge and research, and after discussions and confirmation with industry organizations or professional institutions.
[0036] Step 3: Obtaining Environmental Impact Factors: Collect environmental impact data for each solar energy device at each collection time point. The environmental impact data includes cloud cover, solar altitude angle, and atmospheric transmittance. Analyze the data to obtain the environmental impact factors for each solar energy device at each collection time point.
[0037] It should be noted that meteorological instruments or cloud cover sensors can be used. These devices can automatically measure cloud height and cloud cover in the sky, providing real-time data. Cloud cover information for a specific region can be obtained using data from meteorological satellites. Publicly available meteorological data platforms, such as NOAA and NASA, can also be used.
[0038] In one specific embodiment, the analysis yields the environmental impact factors corresponding to each solar energy device at each data collection time point. The specific analysis process is as follows: The cloud cover, solar altitude angle, and atmospheric transmittance corresponding to each solar energy device at each data collection time point are respectively denoted as follows: , and Substitute into the calculation formula In this process, the environmental impact factors corresponding to each solar energy device at each data collection time point were obtained. Where ΔA, ΔB, and ΔF represent the reference deviation ranges for cloud cover, solar altitude angle, and atmospheric transmittance, respectively, for the solar energy equipment. , , These are the standard cloud cover, standard solar altitude angle, and standard atmospheric transmittance corresponding to the set solar energy equipment. , , These are the weighting factors corresponding to the cloud cover, solar altitude angle, and atmospheric transmittance of the solar energy equipment, respectively.
[0039] It should be noted that, , , All are greater than 0 and less than 1.
[0040] It should also be noted that this process involves summarizing a large amount of research and experimental data. Standard cloud cover, standard solar altitude angle, and standard atmospheric transmittance were set by professional and research institutions for solar energy equipment. Furthermore, the process was based on the professional knowledge and research of experts in the field, and was discussed and confirmed with industry organizations or professional institutions. Experts then set the weighting factors for cloud cover, solar altitude angle, and atmospheric transmittance for the solar energy equipment based on their experience and knowledge.
[0041] Step 4: Obtaining the comprehensive electromagnetic resource assessment coefficient: Based on the solar radiation assessment coefficient and environmental impact factor corresponding to each solar energy device at each collection time point, the comprehensive electromagnetic resource assessment coefficient corresponding to each solar energy device at each collection time point is obtained through analysis.
[0042] In a specific embodiment, the analysis yields the comprehensive electromagnetic resource evaluation coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: Substitute the solar radiation assessment coefficient and environmental impact factor corresponding to each solar energy device at each data collection time point into the calculation formula. In this process, the comprehensive electromagnetic resource assessment coefficients corresponding to each solar energy device at each data collection time point were obtained. , where e represents the natural constant.
[0043] Step 5: Adjustment of Equipment Mode: Based on the comprehensive electromagnetic resource evaluation coefficient corresponding to each solar energy device at each data collection time point, analyze the equipment mode corresponding to each solar energy device at each data collection time point, and adjust each solar energy device at each data collection time point according to the corresponding equipment mode.
[0044] In a specific embodiment, the analysis of the device mode corresponding to each solar energy device at each data collection time point is carried out as follows: The comprehensive electromagnetic resource evaluation coefficients corresponding to each solar energy device at each collection time point are compared with the comprehensive electromagnetic resource evaluation coefficient ranges corresponding to each device mode in the database. If the comprehensive electromagnetic resource evaluation coefficient of a solar energy device at a certain collection time point is within the comprehensive electromagnetic resource evaluation coefficient range corresponding to a certain device mode in the database, then the device mode in the database is recorded as the device mode corresponding to the solar energy device at the current collection time point. In this way, the device modes corresponding to each solar energy device at each collection time point are analyzed.
[0045] In one specific embodiment, the database is used to store the comprehensive electromagnetic resource evaluation coefficient range corresponding to each device mode.
[0046] This invention provides an intelligent control method for electromagnetic resources based on data acquisition and digital model driving. By monitoring and analyzing the electromagnetic and solar data of solar energy equipment in real time, the operating mode of the equipment can be adjusted in a timely manner, thereby improving energy conversion efficiency and maximizing power output. The method can also adjust the equipment settings in real time according to changes in environmental factors (such as cloud cover, solar altitude angle, etc.) to ensure optimal operation in variable outdoor environments.
[0047] In this embodiment of the invention, by continuously monitoring electromagnetic resources, potential problems can be detected in a timely manner and early warnings can be issued, thereby reducing equipment failure rates and ensuring the stability and reliability of the system. By utilizing artificial intelligence technology, equipment operating data can be quickly analyzed, fault modes can be identified, fault diagnosis and maintenance suggestions can be provided, power production and use can be optimized, energy waste can be reduced, resource utilization efficiency can be improved, and energy procurement costs can be reduced.
[0048] This invention provides a way to ensure energy supply for outdoor activities through efficient solar energy equipment, thereby improving the autonomy and flexibility of outdoor activities, enhancing overall activity capabilities, providing stable and reliable energy support for high-tech weapon systems, ensuring their normal operation in complex outdoor environments, enabling the system to respond quickly to changes in the outdoor environment, flexibly adjust equipment modes, ensure efficient energy utilization in different outdoor environments, and make personalized equipment adjustments according to different mission requirements and environmental conditions to meet specific activity needs.
[0049] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.
Claims
1. A method for intelligent control of electromagnetic resources based on data acquisition and digital model-driven approaches, characterized in that, include: Step 1: Data Acquisition: During the operation of each solar energy device in the target area, several data collection time points are set. Electromagnetic data and illumination data corresponding to each solar energy device are collected at each data collection time point. Then, the electromagnetic evaluation coefficient and illumination evaluation coefficient corresponding to each solar energy device at each data collection time point are analyzed. Step 2: Obtaining the solar radiation assessment coefficient: Based on the electromagnetic assessment coefficient and solar radiation assessment coefficient corresponding to each solar energy device at each collection time point, the solar radiation assessment coefficient corresponding to each solar energy device at each collection time point is obtained through analysis. Step 3: Obtaining Environmental Impact Factors: Collect environmental impact data for each solar energy device at each collection time point. The environmental impact data includes cloud cover, solar altitude angle, and atmospheric transmittance. Analyze the data to obtain the environmental impact factors for each solar energy device at each collection time point. Step 4: Obtaining the comprehensive electromagnetic resource assessment coefficient: Based on the solar radiation assessment coefficient and environmental impact factor corresponding to each solar energy device at each collection time point, the comprehensive electromagnetic resource assessment coefficient corresponding to each solar energy device at each collection time point is obtained through analysis. Step 5: Adjustment of Equipment Mode: Based on the comprehensive electromagnetic resource evaluation coefficient corresponding to each solar energy device at each data collection time point, analyze the equipment mode corresponding to each solar energy device at each data collection time point, and adjust each solar energy device at each data collection time point according to the corresponding equipment mode.
2. The intelligent control method for electromagnetic resources based on data acquisition and digital model-driven approach as described in claim 1, characterized in that, The electromagnetic data includes radiation energy density, radiation power, and radiation flux, while the illumination data includes illumination intensity, radiation intensity, and illumination reflectivity.
3. The intelligent control method for electromagnetic resources based on data acquisition and digital model-driven approach as described in claim 2, characterized in that, The analysis yielded electromagnetic evaluation coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: The radiant energy density, radiant power, and radiant flux corresponding to each solar energy device at each data collection time point are respectively denoted as follows: , and ,in, This indicates the number corresponding to each data collection time point. u is any integer greater than 2. This indicates the serial number corresponding to each solar energy device. Let n be any integer greater than 2, and substitute it into the calculation formula. In this process, the electromagnetic evaluation coefficients corresponding to each solar energy device at each data collection time point were obtained. ,in, , , These are the standard radiative energy density, standard radiative power, and standard radiative flux corresponding to the specified solar energy equipment. , , These are the weighting factors corresponding to the set solar energy density, radiation power, and radiation flux, respectively, where e represents the natural constant.
4. The intelligent control method for electromagnetic resources based on data acquisition and digital model-driven approach as described in claim 3, characterized in that, The analysis yielded the illumination evaluation coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: The light intensity, radiation intensity, and light reflectance corresponding to each solar energy device at each data collection time point are respectively denoted as follows: , and Substitute into the calculation formula In this process, the illumination evaluation coefficients corresponding to each solar energy device at each data collection time point are obtained. ,in, , , These are the standard light intensity, standard radiation intensity, and standard light reflectance corresponding to the set solar energy equipment. , , These are the weighting factors corresponding to the set solar energy equipment's light intensity, radiation intensity, and light reflectance, respectively, where e represents the natural constant.
5. The intelligent control method for electromagnetic resources based on data acquisition and digital model-driven approach as described in claim 4, characterized in that, The analysis yielded the solar radiation assessment coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: Substitute the electromagnetic evaluation coefficient and solar radiation evaluation coefficient corresponding to each solar energy device at each data collection time point into the calculation formula. In this process, the solar radiation assessment coefficients corresponding to each solar energy device at each data collection time point were obtained. ,in, , These are the weighting factors corresponding to the electromagnetic evaluation coefficient and the solar energy evaluation coefficient, respectively.
6. The intelligent control method for electromagnetic resources based on data acquisition and digital model-driven approach as described in claim 5, characterized in that, The analysis yielded environmental impact factors for each solar energy device at each data collection time point. The specific analysis process is as follows: The cloud cover, solar altitude angle, and atmospheric transmittance corresponding to each solar energy device at each data collection time point are respectively denoted as follows: , and Substitute into the calculation formula In this process, the environmental impact factors corresponding to each solar energy device at each data collection time point were obtained. Where ΔA, ΔB, and ΔF represent the reference deviation ranges for cloud cover, solar altitude angle, and atmospheric transmittance, respectively, for the solar energy equipment. , , These are the standard cloud cover, standard solar altitude angle, and standard atmospheric transmittance corresponding to the set solar energy equipment. , , These are the weighting factors corresponding to the cloud cover, solar altitude angle, and atmospheric transmittance of the solar energy equipment, respectively.
7. The intelligent control method for electromagnetic resources based on data acquisition and digital model-driven approach as described in claim 6, characterized in that, The analysis yielded the comprehensive electromagnetic resource evaluation coefficients for each solar energy device at each data collection time point. The specific analysis process is as follows: Substitute the solar radiation assessment coefficient and environmental impact factor corresponding to each solar energy device at each data collection time point into the calculation formula. In this process, the comprehensive electromagnetic resource assessment coefficients corresponding to each solar energy device at each data collection time point were obtained. , where e represents the natural constant.
8. The intelligent control method for electromagnetic resources based on data acquisition and digital model-driven approach as described in claim 7, characterized in that, The analysis of the device modes corresponding to each solar energy device at each data collection time point is as follows: The comprehensive electromagnetic resource evaluation coefficients corresponding to each solar energy device at each collection time point are compared with the comprehensive electromagnetic resource evaluation coefficient ranges corresponding to each device mode in the database. If the comprehensive electromagnetic resource evaluation coefficient of a solar energy device at a certain collection time point is within the comprehensive electromagnetic resource evaluation coefficient range corresponding to a certain device mode in the database, then the device mode in the database is recorded as the device mode corresponding to the solar energy device at the current collection time point. In this way, the device modes corresponding to each solar energy device at each collection time point are analyzed.
9. The intelligent control method for electromagnetic resources based on data acquisition and digital model-driven as described in claim 1, characterized in that, It also includes a database, which stores the comprehensive electromagnetic resource evaluation coefficient range corresponding to each device mode.