Communication method of photovoltaic interface adapter and related equipment

Abstract

The application provides a communication method of a photovoltaic interface adapter and related equipment, and the communication method comprises the following steps: acquiring a signal quality index of the photovoltaic interface adapter and analyzing the signal quality index to obtain an analysis result; generating a channel quality optimization instruction according to the analysis result; obtaining real-time communication correction parameters according to the channel quality optimization instruction; predicting the real-time communication correction parameters to obtain a prediction result and generate a real-time adjustment signal; monitoring the utilization rate of communication resources of the photovoltaic interface adapter according to the real-time adjustment signal and generating a load scheduling instruction; performing cross-layer optimization on the real-time communication correction parameters and the load scheduling instruction; and performing real-time updating on the communication protocol and network configuration of the photovoltaic interface adapter to obtain an optimal communication link. The communication work of the photovoltaic interface adapter is performed through the optimal communication link, the overall efficiency and reliability of the communication of the photovoltaic interface adapter are improved, and the problems of poor communication link stability and low resource utilization efficiency are solved.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic interface adapter technology, and more specifically to a communication method and related equipment for a photovoltaic interface adapter. Background Technology

[0002] With the increasing global demand for renewable energy, distributed photovoltaic (PV) power generation systems are being widely adopted due to their clean and efficient characteristics. In distributed PV systems, the communication interface adapter for the inverter plays a crucial role, connecting the inverter to the power grid, cloud platforms, or other monitoring systems to ensure real-time data acquisition and control command delivery. As the industry continuously evolves, the requirements for communication interface adapters are becoming increasingly stringent.

[0003] Among the relevant technical approaches, the use of microcontrollers and the ModBus protocol is employed. Typically, a microcontroller or other microcontroller serves as the processing core, and industrial communication protocols such as ModBus are used to complete data exchange between the inverter and the monitoring system. This approach simplifies the communication process between inverter manufacturers and third-party monitoring platforms, enabling real-time monitoring of the inverter's operating status and allowing for remote diagnostics and control.

[0004] While the above technical solutions can achieve fast and accurate data exchange and control command issuance through efficient microcontrollers and standardized communication protocols, problems such as signal quality fluctuations, uneven resource utilization, and poor communication stability exist when the number of inverters increases, the communication environment becomes more complex, or the signal changes frequently. Summary of the Invention

[0005] The purpose of this invention is to provide a communication method and related equipment for a photovoltaic interface adapter, so as to improve the problems of poor communication link stability and low resource utilization efficiency.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is: a communication method for a photovoltaic interface adapter, comprising: acquiring signal quality indicators of the photovoltaic interface adapter; performing statistical analysis on the signal quality indicators to obtain analysis results; inputting the analysis results into a preset dynamic signal conditioning algorithm to generate channel quality optimization instructions; inputting the channel quality optimization instructions into an adaptive communication strategy generator to obtain real-time communication correction parameters; performing feedback control prediction on the real-time communication correction parameters to obtain prediction results; generating a real-time conditioning signal based on the prediction results; monitoring the communication resource utilization rate of the photovoltaic interface adapter based on the real-time conditioning signal; inputting the communication resource utilization rate into a preset resource scheduling model to generate load scheduling instructions; performing cross-layer optimization on the real-time communication correction parameters and the load scheduling instructions based on a preset optimization algorithm to obtain cross-layer communication parameters and a data flow management strategy; updating the communication protocol and network configuration of the photovoltaic interface adapter in real time based on the cross-layer communication parameters and the data flow management strategy to obtain an optimal communication link; and performing communication operations of the photovoltaic interface adapter based on the optimal communication link.

[0007] Further, the acquisition of signal quality indicators of the photovoltaic interface adapter and the statistical analysis of these indicators to obtain analysis results include: real-time capture of signal strength, signal-to-noise ratio, and communication delay data of the photovoltaic interface adapter based on a preset signal detector; denoising and calibrating the signal strength, signal-to-noise ratio, and communication delay data using a data preprocessing algorithm to obtain preprocessed data; processing the preprocessed data using a signal feature extraction algorithm to identify and extract modulation errors and frequency offsets that reflect the communication quality of the photovoltaic interface adapter, and using the modulation errors and frequency offsets as key signal characteristics; standardizing the key signal characteristics to convert them into dimensionless signal quality indicators; and introducing preset statistical analysis tools to analyze and process the dimensionless signal quality indicators to obtain analysis results regarding the communication channel status and performance, wherein the analysis and processing include analysis of variance, regression analysis, and hypothesis testing.

[0008] Further, the step of inputting the analysis results into a preset dynamic signal conditioning algorithm to generate a channel quality optimization command includes: inputting the analysis results into the preset dynamic signal conditioning algorithm; performing an optimization algorithm on the analysis results based on transmission theory to obtain signal transmission parameters; using the transmission parameters to generate a channel selection scheme optimized for the current communication environment; wherein the channel selection scheme includes an optimal communication frequency band and an optimal power level; analyzing the optimal communication frequency band and the optimal power level in conjunction with channel usage records to determine a frequency hopping strategy; wherein the channel usage records are historical channel occupancy and communication performance data accumulated by the photovoltaic interface adapter in previous operations; allocating and adjusting power according to the quality of the communication channel and the current network load based on a power control algorithm to obtain a power control plan; and summarizing the channel selection scheme, the frequency hopping strategy, and the power control plan to generate a channel quality optimization command.

[0009] Further, the step of inputting the channel quality optimization command into an adaptive communication strategy generator to obtain real-time communication correction parameters, performing feedback control prediction on the real-time communication correction parameters to obtain prediction results, and generating a real-time adjustment signal based on the prediction results includes: using a preset adaptive algorithm generator to perform real-time conversion of the channel quality optimization command, outputting optimal coding selection, rate adjustment, and power adjustment; adaptively adjusting the coding selection and rate adjustment according to the current network load to obtain coding parameter settings and rate configuration schemes; performing error analysis on the coding parameter settings to obtain coding correction suggestions; performing delay prediction on the rate configuration scheme to obtain a delay optimization model, refining the rate configuration scheme using the delay optimization model to obtain a rate adjustment plan; inputting the coding correction suggestions, rate adjustment plan, and power adjustment to a preset feedback mechanism to obtain real-time communication correction parameters through real-time simulation; inputting the real-time communication correction parameters into a feedback control unit for future trend analysis and prediction to obtain prediction results, and generating a real-time adjustment signal based on the prediction results.

[0010] Furthermore, the step of monitoring the communication resource utilization rate of the photovoltaic interface adapter based on the real-time adjustment signal, and inputting the communication resource utilization rate into a preset resource scheduling model to generate a load scheduling command includes: inputting the real-time adjustment signal into the photovoltaic interface adapter to control the resource monitoring unit of the photovoltaic interface adapter to track and record the communication resource utilization rate in real time; inputting the communication resource utilization rate into a preset resource scheduling prediction model to predict the resource usage trend at future points in time based on historical data and current status analysis, and obtaining a prediction result; formulating a communication channel allocation scheme and a signal processing resource configuration scheme based on the prediction result; and inputting the communication channel allocation scheme and the signal processing resource configuration scheme into a preset decision engine to generate a load scheduling command.

[0011] Furthermore, the cross-layer optimization of the real-time communication correction parameters and the load scheduling instructions based on the preset optimization algorithm to obtain cross-layer communication parameters and data flow management strategies includes: normalizing the real-time communication correction parameters and the load scheduling instructions; inputting the normalized real-time communication correction parameters and load scheduling instructions into the preset optimization algorithm, wherein the optimization algorithm performs comprehensive cross-layer communication parameter and resource allocation strategy optimization calculations on the normalized real-time communication correction parameters and load scheduling instructions based on real-time response communication events and the current communication network status, and obtains calculation results; and generating cross-layer communication parameters and data flow management strategies based on the calculation results.

[0012] Further, the step of updating the communication protocol and network configuration of the photovoltaic interface adapter in real time according to the cross-layer communication parameters and the data flow management strategy to obtain the optimal communication link includes: updating the communication protocol and network configuration of the photovoltaic interface adapter in real time according to the cross-layer communication parameters and the data flow management strategy to obtain the optimal communication link; testing the optimal communication link using a network performance monitoring module to obtain test results and evaluate the communication quality of the test results; combining the test results and the communication quality evaluation to adjust and generate the optimal communication link configuration command; and inputting the optimal communication link configuration command to the photovoltaic interface adapter.

[0013] This invention also provides a communication device for a photovoltaic interface adapter, comprising: an acquisition module for acquiring signal quality indicators of the photovoltaic interface adapter, performing statistical analysis on the signal quality indicators, and obtaining analysis results; a generation module for inputting the analysis results into a preset dynamic signal conditioning algorithm to generate channel quality optimization instructions; a prediction module for inputting the channel quality optimization instructions into an adaptive communication strategy generator to obtain real-time communication correction parameters, performing feedback control prediction on the real-time communication correction parameters to obtain prediction results, and generating a real-time conditioning signal based on the prediction results; a monitoring module for monitoring the communication resource utilization rate of the photovoltaic interface adapter based on the real-time conditioning signal, inputting the communication resource utilization rate into a preset resource scheduling model, and generating load scheduling instructions; an optimization module for performing cross-layer optimization on the real-time communication correction parameters and the load scheduling instructions based on a preset optimization algorithm to obtain cross-layer communication parameters and a data flow management strategy; and a calibration module for updating the communication protocol and network configuration of the photovoltaic interface adapter in real time based on the cross-layer communication parameters and the data flow management strategy to obtain an optimal communication link, and performing communication operations of the photovoltaic interface adapter based on the optimal communication link.

[0014] The present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program that can run on the processor, characterized in that the processor executes the computer program to implement the above-described communication method of the photovoltaic interface adapter.

[0015] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when run by a processor, causes the processor to execute the above-described communication method of the photovoltaic interface adapter.

[0016] Compared with existing technologies, this invention has the following advantages: high stability and high resource utilization efficiency. By acquiring the signal quality indicators of the photovoltaic interface adapter and performing statistical analysis on these indicators to obtain detailed analysis results, the analysis results are input into a preset dynamic signal conditioning algorithm to generate optimization instructions for channel quality. These channel quality optimization instructions are then sent to an adaptive communication strategy generator, where real-time communication correction parameters are calculated and subjected to feedback control prediction to obtain prediction results. Based on the prediction results, corresponding real-time adjustment signals are generated. These real-time adjustment signals are used to monitor the communication resource utilization rate of the photovoltaic interface adapter, and this utilization information is also used in a preset resource scheduling model to generate corresponding load scheduling instructions. The obtained real-time communication correction parameters and load scheduling instructions are then optimized across layers using a preset optimization algorithm to generate suitable cross-layer communication parameters and data flow management strategies for real-time updating of the photovoltaic interface adapter. Communication protocols and network configurations are used to establish the optimal communication link, which is then used to complete the communication operations of the photovoltaic interface adapter. This effectively addresses various challenges faced by the photovoltaic interface adapter in actual operation, such as signal quality fluctuations and complex communication environments. The dynamic signal conditioning algorithm can adjust the communication strategy based on the analysis results of signal quality indicators to optimize channel quality. The adaptive communication strategy generator can adjust communication parameters in real time according to changes in the communication environment to ensure communication stability. Furthermore, feedback control prediction further enhances the system's foresight and adaptability. The resource scheduling model and cross-layer optimization can centrally allocate system resources, reduce resource waste, guide data flow management, and alleviate network congestion. This significantly improves the overall efficiency and reliability of the photovoltaic interface adapter's communication, ensuring stable system operation and optimized resource utilization, and improving the problems of poor communication link stability and low resource utilization efficiency. Attached Figure Description

[0017] 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.

[0018] The structures, proportions, sizes, etc., shown in the accompanying drawings of this specification are only for the purpose of assisting those skilled in the art in understanding and reading the content disclosed in the specification, and are not intended to limit the conditions under which the present invention can be implemented. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0019] Figure 1 This is a flowchart illustrating a communication method and related equipment for a photovoltaic interface adapter provided in an embodiment of the present invention;

[0020] Figure 2 This is a schematic block diagram of the communication device of the photovoltaic interface adapter provided in the embodiment of the present invention;

[0021] Figure 3 This is a schematic block diagram of the structure of the electronic device provided in the embodiment of the present invention.

[0022] Explanation of reference numerals in the attached figures:

[0023] 10. Communication device for photovoltaic interface adapter; 11. Acquisition module; 12. Generation module; 13. Prediction module; 14. Monitoring module; 15. Optimization module; 16. Calibration module; 20. Electronic device; 21. Memory; 22. Processor. Detailed Implementation

[0024] 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, not all, of the embodiments of the present invention. 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.

[0025] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0026] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0027] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0028] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0029] Example 1:

[0030] like Figure 1As shown in the embodiment of this application, a communication method for a photovoltaic interface adapter includes steps S100 to S600.

[0031] Example 1:

[0032] Step S100: Obtain the signal quality index of the photovoltaic interface adapter, perform statistical analysis on the signal quality index, and obtain the analysis results.

[0033] In this step, the monitoring system periodically or based on triggered events collects various signal quality index data from the photovoltaic interface adapter, such as received signal strength, error rate, and delay. Specifically, relevant data is collected through sensors and data acquisition modules, and then the collected signal quality indexes are processed using data analysis engines such as Fourier transform or time-domain analysis to determine signal stability, temporal distribution of strength, and possible periodic interference sources.

[0034] For example, the collected signal quality data may show an abnormal decrease in signal strength within a specific time period. After analysis, it can be identified that this is due to the signal being reflected by a large metal object near the equipment.

[0035] Step S200: Input the analysis results into the preset dynamic signal conditioning algorithm to generate channel quality optimization instructions.

[0036] In this step, the results of the previous statistical analysis are encoded as input parameters, and the dynamic signal conditioning algorithm module is run to respond to these changes. Specifically, the algorithm may include machine learning models, such as neural networks or decision trees, which predict possible trends based on the input signal quality indicators and output corresponding channel optimization instructions, such as frequency switching or power adjustment suggestions.

[0037] For example, if the signal strength remains below a set threshold for a certain period of time, the dynamic signal conditioning algorithm may recommend increasing the signal transmission power or switching to a communication frequency band with less interference.

[0038] Step S300: Input the channel quality optimization command into the adaptive communication strategy generator to obtain the real-time communication correction parameters, perform feedback control prediction on the real-time communication correction parameters to obtain the prediction results, and generate a real-time adjustment signal based on the prediction results.

[0039] In this step, the adaptive communication strategy generator, responsible for decision-making, formulates appropriate communication parameters based on channel quality optimization instructions; specifically, it adjusts transmission power levels, channel coding strategies, or packet transmission intervals, and uses feedback control loops to predict system performance, such as using a predictive controller to evaluate the effects of communication parameter changes over a future period.

[0040] For example, an adaptive communication strategy generator can predict, based on channel quality optimization instructions and historical data, that adjusting the antenna orientation under the current solar radiation intensity will minimize signal attenuation.

[0041] Step S400: Monitor the communication resource utilization rate of the photovoltaic interface adapter based on the real-time adjustment signal, input the communication resource utilization rate into the preset resource scheduling model, and generate load scheduling instructions.

[0042] In this step, the system monitors the utilization of communication resources in real time, such as communication bandwidth usage and power consumption, by adjusting signals in real time. Specifically, according to a preset resource scheduling model, such as a priority-based queuing model or a multi-objective optimization model, the system uses this real-time monitoring data to generate load scheduling instructions that guide the allocation of transmission tasks to the inverter.

[0043] For example, when the system detects that the usage rate of a certain communication frequency band is too high, the resource scheduling model will issue a load scheduling instruction to transfer some data transmission tasks to the frequency band with lower usage rate in order to balance the system load.

[0044] Step S500: Based on the preset optimization algorithm, perform cross-layer optimization on the real-time communication correction parameters and load scheduling instructions to obtain cross-layer communication parameters and data flow management strategies.

[0045] In this step, the optimization algorithm module analyzes the interaction between real-time communication correction parameters and load scheduling instructions; specifically, it uses methods such as genetic algorithms or simulated annealing algorithms to search for optimal solutions, and performs overall collaborative optimization by considering parameters and strategies at multiple levels such as the link layer, network layer, and transport layer.

[0046] For example, considering transmission latency and packet success rate, optimization algorithms may select data link layer parameters with low latency but higher error rate, combined with network layer flow control and error correction, to achieve the best overall communication performance.

[0047] Step S600: Update the communication protocol and network configuration of the photovoltaic interface adapter in real time according to the cross-layer communication parameters and data flow management strategy to obtain the optimal communication link, and perform the communication operation of the photovoltaic interface adapter based on the optimal communication link.

[0048] The communication protocol and network configuration management system makes adjustments based on recommendations from cross-layer communication parameters and data flow management strategies; specifically, such as adjusting the congestion window size of the transmission control protocol, changing the routing strategy, or reallocating IP addresses and port numbers.

[0049] For example, if a data flow management strategy recommends reducing the amount of data in transmission, the network management system may reduce the transmission control protocol's sending window, thereby alleviating network stress and improving data flow stability.

[0050] In this embodiment, signal quality indicators of the photovoltaic interface adapter are acquired and statistically analyzed to obtain detailed analysis results. These results are then input into a preset dynamic signal conditioning algorithm to generate optimization instructions for channel quality. Next, the channel quality optimization instructions are fed into an adaptive communication strategy generator, where real-time communication correction parameters are calculated and feedback control predictions are performed to obtain a series of prediction results. Based on these prediction results, corresponding real-time adjustment signals are generated. These signals are used to monitor the communication resource utilization of the photovoltaic interface adapter, and this utilization information is also used in a preset resource scheduling model to generate corresponding load scheduling instructions. Finally, the obtained real-time communication correction parameters and load scheduling instructions are optimized across layers using a preset optimization algorithm to generate suitable cross-layer communication parameters and data flow management strategies. These are used to update the communication protocol and network configuration of the photovoltaic interface adapter in real time, thereby establishing the optimal communication link and using this link to complete the communication operation of the photovoltaic interface adapter.

[0051] The above workflow effectively addresses various challenges faced by photovoltaic interface adapters in actual operation, such as signal quality fluctuations and complex communication environments. The dynamic signal conditioning algorithm adjusts communication strategies based on signal quality index analysis to optimize channel quality, while the adaptive communication strategy generator adjusts communication parameters in real time according to changes in the communication environment, ensuring communication stability. Furthermore, feedback control prediction further enhances the system's foresight and adaptability. The resource scheduling model and cross-layer optimization centrally allocate system resources, reduce resource waste, and guide data flow management, alleviating network congestion. This combination of optimization methods significantly improves the overall efficiency and reliability of photovoltaic interface adapter communication, ensuring stable system operation and optimized resource utilization, and addressing issues of poor communication link stability and low resource utilization efficiency.

[0052] Example 2:

[0053] In step S100, the signal strength, signal-to-noise ratio, and communication delay data of the photovoltaic interface adapter are captured in real time based on a preset signal detector. A data preprocessing algorithm is used to denoise and calibrate the signal strength, signal-to-noise ratio, and communication delay data to obtain preprocessed data. The preprocessed data is then processed using a signal feature extraction algorithm to identify and extract modulation errors and frequency offsets that reflect the communication quality of the photovoltaic interface adapter, using these as key signal characteristics. These key signal characteristics are then standardized and converted into dimensionless signal quality indicators. A preset statistical analysis tool is introduced to analyze and process the dimensionless signal quality indicators to obtain analysis results regarding the communication channel status and performance. The analysis includes variance analysis, regression analysis, and hypothesis testing.

[0054] By using real-time signal detection and preprocessing algorithms for noise reduction and calibration, the accuracy and stability of signal data are ensured. This allows subsequent signal feature extraction and signal quality index calculation to be based on reliable data, effectively improving the accuracy of communication quality assessment and optimization.

[0055] For example, by using data preprocessing algorithms, noise was successfully removed and communication delays were calibrated, ensuring the accuracy and reliability of signal quality data; by using signal feature extraction algorithms, key characteristics such as modulation errors and frequency offsets were accurately identified and extracted, providing an important basis for subsequent signal quality assessment; finally, by using statistical analysis tools, signal quality indicators were analyzed in depth, resulting in detailed analysis results on the state and performance of the communication channel, providing a scientific basis for optimizing the communication link.

[0056] In step S200, the analysis results are input into a preset dynamic signal conditioning algorithm. Based on transmission theory, the dynamic signal conditioning algorithm optimizes the analysis results to obtain signal transmission parameters. The transmission parameters are then used to generate a channel selection scheme optimized for the current communication environment. This channel selection scheme includes the optimal communication frequency band and the optimal power level. The optimal communication frequency band and optimal power level are analyzed in conjunction with channel usage records to determine a frequency hopping strategy. The channel usage records are historical channel occupancy and communication performance data accumulated by the photovoltaic interface adapter in previous operations. Power allocation and adjustment are performed based on the communication channel quality and current network load using a power control algorithm to obtain a power control plan. Finally, the channel selection scheme, frequency hopping strategy, and power control plan are summarized to generate a channel quality optimization instruction.

[0057] By optimizing the analysis results through dynamic signal conditioning algorithms, the photovoltaic interface adapter can be ensured to select the optimal communication frequency band and power level under different communication environments. Specifically, the dynamic signal conditioning algorithm may adjust the power level based on the received signal strength and signal-to-noise ratio to select the optimal communication frequency band to maximize communication efficiency.

[0058] For example, dynamic signal conditioning algorithms, based on transmission theory, precisely optimize signal transmission parameters according to analysis results, ensuring the optimal configuration of the channel selection scheme in the current communication environment; power control algorithms adjust communication power in real time according to network load, effectively reducing interference and bit error rate of communication channels, and improving communication stability and data transmission efficiency; the adoption of frequency hopping strategies can effectively avoid spectrum congestion and improve the reliability and continuity of communication channels.

[0059] In step S300, a preset adaptive algorithm generator is used to convert the channel quality optimization command in real time, outputting the optimal coding selection, rate adjustment, and power adjustment; the coding selection and rate adjustment are adaptively adjusted according to the current network load to obtain coding parameter settings and rate configuration schemes; error analysis is performed on the coding parameter settings to obtain coding correction suggestions; delay prediction is performed on the rate configuration scheme to obtain a delay optimization model, and the rate configuration scheme is refined using the delay optimization model to obtain a rate adjustment plan; the coding correction suggestions, rate adjustment plan, and power adjustment are input to a preset feedback mechanism to obtain real-time communication correction parameters through real-time simulation; the real-time communication correction parameters are input to the feedback control unit for future trend analysis and prediction to obtain prediction results, and real-time adjustment signals are generated based on the prediction results.

[0060] By using an adaptive algorithm to adjust the encoding selection, rate, and power in real time, the photovoltaic interface adapter can maintain optimal communication efficiency and stability under various communication loads. Specifically, the adaptive algorithm may dynamically adjust the encoding selection and rate based on real-time communication correction parameters to minimize communication latency and maximize data transmission rate.

[0061] For example, the adaptive algorithm generator dynamically adjusts the encoding, rate, and power based on real-time communication correction parameters, ensuring optimal configuration of communication parameters under different network environments and load conditions; the application of the delay optimization model effectively reduces latency during data transmission and improves the efficiency and stability of real-time communication; the application of the feedback mechanism enables the communication system to adjust its communication strategy in a timely manner based on real-time analysis results, achieving continuous optimization and improvement of communication quality.

[0062] In step S400, a real-time adjustment signal is input to the photovoltaic interface adapter to control the resource monitoring unit of the photovoltaic interface adapter to track and record the communication resource utilization rate in real time; the communication resource utilization rate is input to a preset resource scheduling prediction model, and the usage trend of resources at future points in time is predicted based on historical data and current status analysis to obtain the prediction result; based on the prediction result, a communication channel allocation scheme and a signal processing resource configuration scheme are formulated; the communication channel allocation scheme and the signal processing resource configuration scheme are input to a preset decision engine to generate a load scheduling instruction.

[0063] By tracking and recording communication resource utilization in real time, the photovoltaic interface adapter can effectively allocate resources under high load conditions. Specifically, the resource monitoring unit may record the usage and performance data of each communication channel so that the resource scheduling prediction model can analyze and predict future resource needs.

[0064] For example, the resource scheduling prediction model, based on historical data and current situation analysis, accurately predicts the future demand for communication resources, effectively avoiding over- or under-allocation of resources; the application of the decision engine enables flexible adjustment of communication channel allocation and signal processing resource configuration in different application scenarios, improving the adaptability and stability of the communication system.

[0065] In step S500, the real-time communication correction parameters and load scheduling instructions are normalized; the normalized real-time communication correction parameters and load scheduling instructions are input into a preset optimization algorithm; the optimization algorithm performs comprehensive cross-level communication parameter and resource allocation strategy optimization calculations on the normalized real-time communication correction parameters and load scheduling instructions based on real-time response communication events and the current communication network status, and obtains the calculation results; cross-level communication parameters and data flow management strategies are generated based on the calculation results.

[0066] Through normalization processing and comprehensive cross-level optimization calculations, the photovoltaic interface adapter can quickly respond to and adapt to changing communication needs in complex communication environments. Specifically, the optimization algorithm may combine real-time communication correction parameters and load scheduling instructions to dynamically adjust data flow management strategies and communication parameters in order to maximize the utilization of communication resources and the stability of data transmission.

[0067] For example, the optimization algorithm, based on real-time communication correction parameters and load scheduling instructions, ensures the rational utilization of communication resources and the optimization of communication performance through comprehensive cross-level optimization calculations. Normalization ensures that different types of communication parameters can be compared and processed within the same reference frame, enhancing the versatility and applicability of the optimization algorithm.

[0068] In step S600, the communication protocol and network configuration of the photovoltaic interface adapter are updated in real time according to the cross-layer communication parameters and data flow management strategy to obtain the optimal communication link; the optimal communication link is tested using the network performance monitoring module to obtain the test results and evaluate the communication quality of the test results; the optimal communication link configuration command is generated by combining the test results and the communication quality evaluation; and the optimal communication link configuration command is input to the photovoltaic interface adapter.

[0069] By updating communication protocols and network configurations in real time through cross-layer communication parameters and data flow management strategies, the optimal configuration and performance adjustment of communication links are ensured.

[0070] For example, by utilizing cross-layer communication parameters and data flow management strategies, the system can dynamically adjust communication protocols and network configurations to maximize the efficiency and reliability of communication links. The application of the network performance monitoring module ensures the real-time performance and stability of the optimal communication link, and through testing and evaluation results, it guarantees that the communication quality reaches the expected high level.

[0071] In this embodiment, by combining various technical means such as signal detectors, preprocessing algorithms, signal feature extraction, statistical analysis tools, dynamic signal conditioning algorithms, adaptive algorithm generators, resource scheduling prediction models, and optimization algorithms, comprehensive optimization and management of the photovoltaic interface adapter communication device are achieved, effectively improving the performance, stability, and resource utilization of the communication system.

[0072] Example 3:

[0073] like Figure 2 As shown, this application also provides a communication device 10 for a photovoltaic interface adapter, which includes an acquisition module 11, a generation module 12, a prediction module 13, an optimization module 15, and a calibration module 16.

[0074] The acquisition module 11 is mainly used to acquire the signal quality indicators of the photovoltaic interface adapter, perform statistical analysis on the signal quality indicators, and obtain the analysis results.

[0075] The generation module 12 is mainly used to input the analysis results into a preset dynamic signal conditioning algorithm to generate channel quality optimization instructions.

[0076] Prediction module 13 is mainly used to input channel quality optimization instructions into the adaptive communication strategy generator to obtain real-time communication correction parameters, perform feedback control prediction on the real-time communication correction parameters, obtain prediction results, and generate real-time adjustment signals based on the prediction results.

[0077] The monitoring module 14 is mainly used to monitor the communication resource utilization rate of the photovoltaic interface adapter based on the real-time adjustment signal, input the communication resource utilization rate into the preset resource scheduling model, and generate load scheduling instructions.

[0078] The optimization module 15 is mainly used to perform cross-layer optimization on real-time communication correction parameters and load scheduling instructions based on preset optimization algorithms, so as to obtain cross-layer communication parameters and data flow management strategies.

[0079] The calibration module 16 is mainly used to update the communication protocol and network configuration of the photovoltaic interface adapter in real time according to the cross-layer communication parameters and data flow management strategy to obtain the optimal communication link.

[0080] In this embodiment, through the synergistic effect of the above modules, comprehensive management and optimization of the photovoltaic interface adapter communication process are achieved, including signal quality assessment, dynamic signal adjustment, resource scheduling optimization, and real-time updates of the communication link, thereby effectively improving the performance and stability of the communication system.

[0081] It should be noted that, for the sake of convenience and brevity, the specific working processes of the device and each module described above can be referred to the corresponding processes in the aforementioned embodiment of the communication method for the photovoltaic interface adapter, and will not be repeated here.

[0082] Example 4:

[0083] like Figure 3 As shown, this application also provides an electronic device 20, including a memory 21 and a processor 22. The memory 21 stores a computer program that can run on the processor 22. When the processor 22 executes the computer program, it implements the communication method of the photovoltaic interface adapter of Embodiment 1.

[0084] In this embodiment, the computer program stored in the electronic device 20 and the processor 22 execute the automated management and control of the photovoltaic interface adapter communication method, which effectively improves the adaptive capability and response speed of the communication system and enhances the reliability and stability of the system.

[0085] Example 5:

[0086] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when run by a processor, causes the processor to execute a communication method for a photovoltaic interface adapter as described in Embodiment 1.

[0087] In this embodiment, a computer program stored on a computer-readable storage medium is used to standardize and automate the communication method of the photovoltaic interface adapter, thereby improving the operational efficiency and management convenience of the communication system and providing a flexible solution for communication needs in different application scenarios.

[0088] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A communication method for a photovoltaic interface adapter, characterized in that, include: Obtain the signal quality indicators of the photovoltaic interface adapter, perform statistical analysis on the signal quality indicators, and obtain the analysis results; The analysis results are input into a preset dynamic signal conditioning algorithm to generate channel quality optimization instructions; The channel quality optimization command is input into the adaptive communication strategy generator to obtain real-time communication correction parameters. Feedback control prediction is performed on the real-time communication correction parameters to obtain prediction results. Real-time adjustment signals are generated based on the prediction results. Based on the real-time adjustment signal monitoring of the photovoltaic interface adapter's communication resource utilization rate, the communication resource utilization rate is input into a preset resource scheduling model to generate a load scheduling instruction; Based on a preset optimization algorithm, the real-time communication correction parameters and the load scheduling instructions are optimized across layers to obtain cross-layer communication parameters and data flow management strategies. The communication protocol and network configuration of the photovoltaic interface adapter are updated in real time according to the cross-layer communication parameters and the data flow management strategy to obtain the optimal communication link, and the communication operation of the photovoltaic interface adapter is performed based on the optimal communication link.

2. The communication method of the photovoltaic interface adapter according to claim 1, characterized in that, The process involves acquiring the signal quality indicators of the photovoltaic interface adapter, performing statistical analysis on the signal quality indicators, and obtaining the analysis results, including: The signal strength, signal-to-noise ratio, and communication delay data of the photovoltaic interface adapter are captured in real time based on a preset signal detector. The signal strength, signal-to-noise ratio, and communication delay data are denoised and calibrated using a data preprocessing algorithm to obtain preprocessed data. The preprocessed data is processed by a signal feature extraction algorithm to identify and extract modulation errors and frequency offsets that reflect the communication quality of the photovoltaic interface adapter, and the modulation errors and frequency offsets are used as key signal characteristics. The key signal characteristics are standardized and converted into dimensionless signal quality indicators. A pre-defined statistical analysis tool is introduced to analyze and process the dimensionless signal quality index to obtain analysis results on the communication channel status and performance. The analysis and processing include analysis of variance, regression analysis, and hypothesis testing.

3. The communication method of the photovoltaic interface adapter according to claim 1, characterized in that, The step of inputting the analysis results into a preset dynamic signal conditioning algorithm to generate channel quality optimization instructions includes: The analysis results are input into a preset dynamic signal conditioning algorithm. Based on transmission theory, the dynamic signal conditioning algorithm performs an optimization algorithm on the analysis results to obtain signal transmission parameters. The transmission parameters are used to generate a channel selection scheme optimized for the current communication environment; wherein, the channel selection scheme includes an optimal communication frequency band and an optimal power level; The optimal communication frequency band and the optimal power level are analyzed in conjunction with channel usage records to determine the frequency hopping strategy; wherein, the channel usage records are historical channel occupancy and communication performance data accumulated by the photovoltaic interface adapter in previous operations; Based on the power control algorithm, power allocation and adjustment are performed on the quality of the communication channel and the current network load to obtain a power control plan; The channel selection scheme, frequency hopping strategy, and power control plan are summarized to generate a channel quality optimization instruction.

4. The communication method of the photovoltaic interface adapter according to claim 1, characterized in that, The process of inputting the channel quality optimization command into an adaptive communication strategy generator to obtain real-time communication correction parameters, performing feedback control prediction on the real-time communication correction parameters to obtain prediction results, and generating a real-time adjustment signal based on the prediction results includes: The channel quality optimization command is transformed in real time using a preset adaptive algorithm generator, and the optimal coding selection, rate adjustment and power regulation are output. The encoding selection and rate adjustment are adaptively adjusted according to the current network load to obtain the encoding parameter setting and rate configuration scheme. Error analysis is performed on the encoding parameter settings to obtain encoding correction suggestions; Delay prediction is performed on the rate configuration scheme to obtain a delay optimization model. The rate configuration scheme is then refined using the delay optimization model to obtain a rate adjustment plan. The encoding correction suggestion, rate adjustment plan, and power adjustment are input to a preset feedback mechanism, and real-time communication correction parameters are obtained through real-time simulation. The real-time communication correction parameters are input into the feedback control unit for future trend analysis and prediction to obtain prediction results, and a real-time adjustment signal is generated based on the prediction results.

5. The communication method of the photovoltaic interface adapter according to claim 1, characterized in that, The step of monitoring the communication resource utilization rate of the photovoltaic interface adapter based on the real-time adjustment signal, inputting the communication resource utilization rate into a preset resource scheduling model, and generating a load scheduling instruction includes: The real-time adjustment signal is input to the photovoltaic interface adapter to control the resource monitoring unit of the photovoltaic interface adapter to track and record the communication resource utilization rate in real time. The communication resource utilization rate is input into a preset resource scheduling prediction model. Based on historical data and current status analysis, the usage trend of resources at future points in time is predicted, and the prediction result is obtained. Based on the predicted results, a communication channel allocation scheme and a signal processing resource configuration scheme are formulated. The communication channel allocation scheme and the signal processing resource configuration scheme are input into a preset decision engine to generate load scheduling instructions.

6. The communication method of the photovoltaic interface adapter according to claim 1, characterized in that, The optimization algorithm based on a preset layer performs cross-layer optimization on the real-time communication correction parameters and the load scheduling instructions to obtain cross-layer communication parameters and data flow management strategies, including: The real-time communication correction parameters and the load scheduling instructions are normalized. The normalized real-time communication correction parameters and load scheduling instructions are input into a preset optimization algorithm. The optimization algorithm performs comprehensive cross-level communication parameter and resource allocation strategy optimization calculations on the normalized real-time communication correction parameters and load scheduling instructions based on real-time response communication events and the current communication network status, and obtains the calculation results. Based on the calculation results, cross-layer communication parameters and data flow management strategies are generated.

7. The communication method of the photovoltaic interface adapter according to claim 1, characterized in that, The step of updating the communication protocol and network configuration of the photovoltaic interface adapter in real time according to the cross-layer communication parameters and the data flow management strategy to obtain the optimal communication link includes: The communication protocol and network configuration of the photovoltaic interface adapter are updated in real time according to the cross-layer communication parameters and the data flow management strategy to obtain the optimal communication link. The optimal communication link is tested using a network performance monitoring module to obtain test results, and the communication quality of the test results is evaluated. Based on the test results and the communication quality assessment, the optimal communication link configuration command is adjusted and generated. Input the optimal communication link configuration command into the photovoltaic interface adapter.

8. A communication device for a photovoltaic interface adapter, characterized in that, include: The acquisition module is used to acquire the signal quality indicators of the photovoltaic interface adapter, perform statistical analysis on the signal quality indicators, and obtain the analysis results. The generation module is used to input the analysis results into a preset dynamic signal conditioning algorithm to generate channel quality optimization instructions; The prediction module is used to input the channel quality optimization command into the adaptive communication strategy generator to obtain real-time communication correction parameters, perform feedback control prediction on the real-time communication correction parameters to obtain prediction results, and generate real-time adjustment signals based on the prediction results. The monitoring module is used to monitor the communication resource utilization rate of the photovoltaic interface adapter according to the real-time adjustment signal, input the communication resource utilization rate into a preset resource scheduling model, and generate load scheduling instructions. The optimization module is used to perform cross-layer optimization on the real-time communication correction parameters and the load scheduling instructions based on a preset optimization algorithm, so as to obtain cross-layer communication parameters and data flow management strategies. The calibration module is used to update the communication protocol and network configuration of the photovoltaic interface adapter in real time according to the cross-layer communication parameters and the data flow management strategy, obtain the optimal communication link, and perform the communication operation of the photovoltaic interface adapter based on the optimal communication link.

9. An electronic device, characterized in that, The device includes a memory and a processor, the memory storing a computer program that can run on the processor, characterized in that the processor, when executing the computer program, implements the communication method of the photovoltaic interface adapter according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, causes the processor to perform the communication method of the photovoltaic interface adapter as described in any one of claims 1 to 7.

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