Sand wind monitoring and active defense system for photovoltaic inverter

Abstract

The invention relates to the technical field of photovoltaic inverter protection, in particular to a wind and sand monitoring and active defense system for a photovoltaic inverter, which comprises an environmental parameter sensing and analyzing module for acquiring wind and sand environmental parameters, performing characteristic analysis on the wind and sand environmental parameters and acquiring wind and sand types and particle kinetic energy values; the historical strategy matching module is used for mapping the sandstorm type and the particle kinetic energy value to a preset coping strategy database to obtain a historical optimal strategy; the real-time flow field calculation module is used for acquiring real-time wind speed data of an area where the photovoltaic inverter is located and terrain parameters around equipment, and performing flow field numerical simulation calculation on the real-time wind speed data and the terrain parameters around the equipment to obtain a real-time flow field deviation coefficient; the strategy dynamic correction module is used for dynamically correcting the historical optimal strategy based on the real-time flow field deviation coefficient to obtain a coping optimization strategy; and the intelligent decision-making module inputs the coping optimization strategy into an intelligent decision-making model to obtain a wind and sand prevention structure parameter instruction and a self-cleaning time sequence instruction.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of photovoltaic inverter protection, and particularly relates to a wind-sand monitoring and active defense system for a photovoltaic inverter. BACKGROUND

[0002] With the transformation of global energy structure to clean energy, photovoltaic power generation, as an important form of renewable energy utilization, has a continuously rapid growth in installed capacity. As the core equipment of a photovoltaic power generation system, a photovoltaic inverter is responsible for converting direct current generated by a photovoltaic module into alternating current that can be grid-connected or directly used, and the operation stability of the photovoltaic inverter directly affects the power generation efficiency and economic benefits of the entire photovoltaic power station.

[0003] In new energy-rich regions such as northwest China and north China, photovoltaic power stations often face severe challenges from wind-sand environments. Particulate matters in the wind-sand can invade the interior of the equipment through the ventilation openings of the inverter, cover the heat dissipation fins and circuit boards, cause the heat dissipation efficiency to decrease, the operating temperature of the inverter to rise, and then cause the power output to attenuate; the sand and dust particles accumulate between mechanical parts, cause poor contact, reduce the insulation performance, and even cause short-circuit faults, and shorten the service life of the equipment; long-term wind-sand erosion can aggravate the wear of the shell and the sealing element, and further reduce the protection level of the equipment. SUMMARY

[0004] The present application provides a wind-sand monitoring and active defense system for a photovoltaic inverter, which can effectively solve the problems in the background art.

[0005] To achieve the above-mentioned purpose, in a first aspect, the present application provides a wind-sand monitoring and active defense system for a photovoltaic inverter, comprising:

[0006] An environmental parameter sensing and analysis module acquires wind-sand environmental parameters, analyzes the characteristics of the wind-sand environmental parameters, and obtains a wind-sand type and a particle kinetic energy value;

[0007] A historical strategy matching module maps the wind-sand type and the particle kinetic energy value to a preset coping strategy database, and obtains a historical optimal strategy;

[0008] A real-time flow field calculation module acquires real-time wind speed data of an area where the photovoltaic inverter is located and terrain parameters around the equipment, performs flow field numerical simulation calculation on the real-time wind speed data and the terrain parameters around the equipment, and obtains a real-time flow field deviation coefficient;

[0009] A strategy dynamic correction module dynamically corrects the historical optimal strategy based on the real-time flow field deviation coefficient, and obtains a coping optimization strategy;

[0010] An intelligent decision-making module inputs the coping optimization strategy into an intelligent decision-making model, and obtains a wind-sand prevention structure parameter instruction and a self-cleaning timing instruction.

[0011] The execution and feedback module performs the wind and sand prevention operation according to the wind and sand prevention structure parameter instruction, feeds back a signal that the protection is in place after completion, and performs a self-cleaning timing instruction to perform a self-cleaning operation.

[0012] In combination with the first aspect, in a possible design, the environment parameter sensing and analyzing module further includes a data analysis processing unit configured to analyze the characteristics of the wind and sand environment parameters.

[0013] In combination with the first aspect, in a possible design, the wind and sand environment parameters include wind speed, wind direction, particulate matter concentration, and particulate matter particle size distribution.

[0014] In combination with the first aspect, in a possible design, the wind and sand types include blowing sand, floating dust, and sandstorm.

[0015] In combination with the first aspect, in a possible design, the coping strategy database content includes a correspondence between wind and sand types and strategies, a correspondence between particle kinetic energy values and strategies, and a comprehensive strategy library.

[0016] In combination with the first aspect, in a possible design, the wind and sand types and the particle kinetic energy values are mapped to a preset coping strategy database to obtain a historical optimal strategy.

[0017] The wind and sand types and the particle kinetic energy values are received as input parameters of the coping strategy database.

[0018] The wind and sand types are used as a first-level index to find corresponding sub-libraries in the database.

[0019] According to the particle kinetic energy values, a second-level search is performed in the sub-libraries to find the closest historical strategy as the historical optimal strategy.

[0020] In combination with the first aspect, in a possible design, the historical strategy matching module further includes a similarity evaluation unit configured to calculate the similarity between the wind and sand environment parameters and the corresponding parameters of each strategy in the database, and select the historical strategy with the highest similarity as the output result.

[0021] In combination with the first aspect, in a possible design, the historical optimal strategy includes initial parameters of the wind and sand prevention structure and initial parameters of the self-cleaning timing.

[0022] In combination with the first aspect, in a possible design, the initial parameters of the wind and sand prevention structure include the opening angle of the louver, the material and aperture of the louver, the louver adjustment response threshold, the sealing component protection start threshold, and the angle of the flow guide rib.

[0023] With reference to the first aspect, in a possible design, the self-cleaning timing initial parameter includes initial air pressure of pulse air flow, pulse air flow spraying time length and interval, pulse air hole distribution, vibration frequency, vibration time length, and interval from wind-sand prevention operation.

[0024] The technical scheme can realize the following technical effects:

[0025] The system obtains various parameters in the wind-sand environment in real time through the environmental parameter perception and analysis module, and analyzes the characteristics thereof; this helps to master the environmental changes in real time, ensures that the system can quickly make response strategies, and avoids the influence of the environment on the inverter; the system analyzes and decides in combination with historical data and real-time data through the historical strategy matching module and the real-time flow field calculation module; the historical strategy provides the system with the best response measures in the past, and the flow field calculation is corrected according to the real-time wind speed and the environment around the device, so that the response strategy is more personalized and dynamic; the strategy dynamic correction module dynamically adjusts the historical strategy on the basis of real-time data; the response strategy can be optimized in real time according to the environmental changes, and will not be restricted by outdated strategies; the system can always respond to changes in the wind-sand environment, thereby ensuring the stable operation of the inverter; through the intelligent decision module, the system can automatically generate wind-sand prevention structure parameter instructions and self-cleaning timing instructions, and accurately operate through the execution and feedback module; the system can efficiently perform wind-sand prevention operations and automatically perform self-cleaning, so as to ensure that the inverter device works in a clean state for a long time, reduces the need for manual intervention, and improves work efficiency; through monitoring, analysis, and response to wind-sand, the system can prevent the device from being damaged by wind-sand; through optimization of wind-sand prevention and regular self-cleaning, the system can effectively improve the heat dissipation efficiency of the inverter, reduce faults, prolong the service life of the device, and improve the overall power generation efficiency and economic benefits; active defense not only improves the stability of the device, but also reduces the energy efficiency decline of the device caused by dust accumulation through the self-cleaning function; in the long run, the system will reduce the frequency of device faults and maintenance, thereby reducing operation and maintenance costs; through dynamic correction of the wind-sand prevention structure and the self-cleaning function, the wear of the shell and the sealing element of the inverter will be reduced, and the protection level will be improved; the inverter can work efficiently for a long time in a more severe wind-sand environment, and the erosion of external physical factors on the device is reduced; in summary, the wind-sand monitoring and active defense system has strong intelligence, adaptability, and dynamic optimization capability, effectively prolongs the service life of the device while ensuring the efficient operation of the inverter, reduces maintenance costs, and improves the economic benefits of the entire photovoltaic power station. BRIEF DESCRIPTION OF DRAWINGS

[0026] In order to make the technical solutions in the embodiments of the present application or the prior art clearer, the accompanying drawings needed in the embodiments or prior art description will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments described in the present application, and other drawings can be obtained by those skilled in the art without creative effort on the basis of these drawings.

[0027] Figure 1 The structure diagram of the wind and sand monitoring and active defense system for photovoltaic inverter is shown in the figure. DETAILED DESCRIPTION

[0028] The present application will be described below in conjunction with the accompanying drawings in the present application.

[0029] As Figure 1 shown, the wind and sand monitoring and active defense system for photovoltaic inverter of the present application specifically comprises the following steps:

[0030] The environmental parameter sensing and analysis module acquires the wind and sand environmental parameters, analyzes the characteristics of the wind and sand environmental parameters, and obtains the wind and sand type and the particle kinetic energy value.

[0031] The historical strategy matching module maps the wind and sand type and the particle kinetic energy value to the pre-set coping strategy database, and obtains the historical optimal strategy.

[0032] The real-time flow field calculation module acquires the real-time wind speed data of the area where the photovoltaic inverter is located and the terrain parameters around the equipment, performs flow field numerical simulation calculation on the real-time wind speed data and the terrain parameters around the equipment, and obtains the real-time flow field deviation coefficient.

[0033] The strategy dynamic correction module dynamically corrects the historical optimal strategy based on the real-time flow field deviation coefficient, and obtains the coping optimization strategy.

[0034] The intelligent decision module inputs the coping optimization strategy into the intelligent decision model, and obtains the wind and sand prevention structure parameter instruction and the self-cleaning timing instruction.

[0035] The execution and feedback module performs the wind and sand prevention operation according to the wind and sand prevention structure parameter instruction, feeds back the signal that the protection is in place after completion, and performs the self-cleaning operation according to the self-cleaning timing instruction.

[0036] In this embodiment, the system obtains various parameters in the wind-sand environment in real time through the environmental parameter perception and analysis module, and analyzes the characteristics thereof; it is helpful to master the environmental changes in real time and ensure that the system can quickly make response strategies to avoid the influence of the environment on the inverter; through the historical strategy matching module and the real-time flow field calculation module, the system analyzes and decides in combination with historical data and real-time data; the historical strategy provides the system with the best response measures in the past, and the flow field calculation is corrected according to the real-time wind speed and the environment around the equipment, so that the response strategy is more personalized and dynamic; the strategy dynamic correction module dynamically adjusts the historical strategy on the basis of real-time data; it can optimize the response strategy in real time according to the environmental changes and will not be restricted by outdated strategies; it ensures that the system can always respond to changes in the wind-sand environment, thereby ensuring the stable operation of the inverter; through the intelligent decision-making module, the system can automatically generate wind-sand prevention structure parameter instructions and self-cleaning timing instructions, and accurately operate through the execution and feedback module; it can efficiently perform wind-sand prevention operations while automatically performing self-cleaning, ensuring that the inverter equipment works in a clean state for a long time, reducing the need for manual intervention and improving work efficiency; through monitoring, analysis and response to wind-sand, the system can prevent the equipment from being damaged by wind-sand, and through optimization of wind-sand protection and regular self-cleaning, the system can effectively improve the heat dissipation efficiency of the inverter, reduce faults, prolong the service life of the equipment, and improve the overall power generation efficiency and economic benefits; active defense not only improves the stability of the equipment, but also reduces the energy efficiency decline of the equipment caused by dust accumulation through the self-cleaning function; in the long run, the system will reduce the frequency of equipment failure and maintenance, thereby reducing operation and maintenance costs; through the dynamically corrected wind-sand prevention structure and self-cleaning function, the wear of the shell and sealing elements of the inverter will be reduced, and the protection level will be improved; the inverter can work efficiently for a long time in a more severe wind-sand environment, reducing the erosion of external physical factors on the equipment; in summary, the wind-sand monitoring and active defense system has strong intelligence, adaptability and dynamic optimization capability, which effectively prolongs the service life of the equipment, reduces maintenance costs, and improves the economic benefits of the entire photovoltaic power station while ensuring efficient operation of the inverter.

[0037] In some embodiments of the present application, the environmental parameter perception and analysis module obtains wind-sand environment parameters, analyzes the characteristics of the wind-sand environment parameters, and obtains the wind-sand type and particle kinetic energy value;

[0038] The environmental parameter perception and analysis module mainly consists of a plurality of high-precision sensors and a data analysis processing unit;

[0039] The sensor is a direct tool for obtaining environmental parameters, including a wind speed sensor, a wind direction sensor, a particulate matter concentration sensor, a particulate matter particle size distribution sensor, etc.; the sensors are arranged around and inside the photovoltaic inverter at key positions to ensure that various information of the wind-sand environment can be captured comprehensively and accurately;

[0040] The data analysis processing unit adopts a high-performance microprocessor or a special data acquisition and analysis chip, has powerful data processing capability; responsible for receiving the original data transmitted by the sensor, preprocessing, storage, and using specific algorithms for in-depth analysis of the data, and finally outputting the sand type and particle kinetic energy value;

[0041] The wind and sand environment parameters include:

[0042] Wind speed: Wind speed can affect wind and sand movement and impact force; by real-time monitoring of wind speed at different heights through wind speed sensor, it can understand the distribution of wind and sand in the vertical direction and the size of wind force; in strong wind weather, the wind speed is larger, the sand particles carried have higher kinetic energy, the impact on the inverter is also stronger, and it is more likely to invade the internal equipment and cause damage;

[0043] Wind direction: Wind direction determines the source direction and movement path of wind and sand; accurate grasp of wind direction information can determine which parts of the inverter are more vulnerable to wind and sand invasion, so as to targetedly strengthen the protection measures;

[0044] Particulate matter concentration: Particulate matter concentration reflects the density of dust particles in the air; high concentration of dust environment means that there are a large number of particulate matters around the inverter, increasing the possibility of particle invasion into the internal equipment; by real-time monitoring of concentration changes through particulate matter concentration sensor, it can timely understand the severity of wind and sand;

[0045] Particle size distribution: Different particle sizes of dust particles have different effects on the inverter; small dust particles are more likely to enter the internal equipment through the ventilation port, adhere to the heat sink fins and circuit board, and affect heat dissipation and electrical performance; while larger sand particles may cause direct wear and impact on mechanical parts; the particulate matter particle size distribution sensor can analyze the proportion of different particle sizes, helping the system more accurately assess the potential harm of wind and sand to the inverter;

[0046] The original data collected by the sensor are preprocessed to improve the quality and accuracy of the data; the preprocessing process includes data filtering, denoising, calibration and other operations;

[0047] According to the obtained wind speed, wind direction, particulate matter concentration and particle size distribution parameters, the pre-set rules are used to judge the wind and sand type; the wind and sand type includes blowing sand, floating dust and sandstorm; different types of wind and sand have different characteristics, for example, sandstorm usually accompanies strong wind and high concentration of coarse particle dust, which causes more serious damage to the inverter;

[0048] Particle kinetic energy is an important indicator for measuring the impact of dust particles on inverters. According to the principles of physics, the kinetic energy of a particle is proportional to the square of its mass and velocity. Given the particle size distribution and wind speed, the kinetic energy of particles of different sizes can be calculated using a mathematical model, and these values ​​can be combined to obtain the overall particle kinetic energy value. For particles in each size range, the kinetic energy of particles in that range is calculated based on their mass distribution and wind speed. Then, the kinetic energies of all ranges are weighted and summed to obtain the final particle kinetic energy value.

[0049] In this embodiment, high-precision sensors deployed at key locations can comprehensively and accurately perceive and monitor various parameters of the wind and sand environment. The data analysis and processing unit utilizes a high-performance microprocessor or a dedicated data acquisition and analysis chip, possessing powerful data processing and analysis capabilities. It can efficiently preprocess the raw data collected by the sensors and deeply analyze the data through specific algorithms, ultimately determining the wind and sand type and particle kinetic energy value. Through preset rules, the system can accurately determine the wind and sand type based on parameters such as wind speed, wind direction, particle concentration, and particle size distribution. Different types of wind and sand have different characteristics, and the system can use these characteristics to provide inverse... The system provides more targeted protection strategies for inverters. By calculating the kinetic energy of particles, it can assess the potential hazards of wind and sand to the equipment and provide important references for inverter design, helping to strengthen protective measures and thus improve the inverter's resistance to wind and sand and its service life. By monitoring the wind and sand environment in real time, the system can respond promptly and take corresponding protective measures to reduce the damage of wind and sand to the inverter and extend the service life of the equipment. The wind and sand type and particle kinetic energy analysis results provided by the system can help maintenance personnel better understand the environmental risks faced by the equipment, thereby developing more accurate and efficient maintenance plans and reducing unnecessary equipment failures and downtime.

[0050] In some embodiments of the present invention, for the historical strategy matching module, the wind and sand type and particle kinetic energy value are mapped to a preset response strategy database to obtain the historical optimal strategy.

[0051] The response strategy database includes:

[0052] Correspondence between wind and sand types and corresponding protection strategies: Common wind and sand types are associated with corresponding protection strategies; for example, for blowing sand weather, a strategy of medium-density filters and regular manual cleaning may be adopted; while for sandstorm weather, more stringent protection measures such as high-density filters, adjustable wind deflectors and automatic cleaning systems are required.

[0053] Particle kinetic energy value and strategy correspondence: Different levels are divided according to the size of the particle kinetic energy value, and corresponding protection strategies are formulated for each level; the larger the particle kinetic energy value, the stronger the impact of sand and dust particles on the inverter, requiring a more robust protective structure and a more effective cleaning method; for example, when the particle kinetic energy value is low, a simple filter can be used; when the particle kinetic energy value is high, it is necessary to increase the number of filter layers or use a protective structure with a buffer device.

[0054] Comprehensive Strategy Library: In addition to strategies corresponding to single factors, the database also includes composite strategies that take into account multiple factors such as wind and sand type and particle kinetic energy value;

[0055] Receive the wind and sand type and particle kinetic energy value as input parameters;

[0056] Based on the input wind and sand type and particle kinetic energy value, the module queries and matches in the preset response strategy database. The module uses an efficient search algorithm to quickly locate the historical strategy that best matches the current environmental parameters. The wind and sand type is used as the primary index to find the corresponding sub-database in the database. Then, a secondary search is performed in the sub-database based on the particle kinetic energy value to find the closest historical strategy.

[0057] During the matching process, considering that the actual environmental parameters may differ from the preset values ​​in the database, the module also includes a similarity evaluation unit to perform similarity evaluation; by calculating the similarity between the current environmental parameters and the corresponding parameters of each strategy in the database, the historical strategy with the highest similarity is selected as the output result; the historical optimal strategy includes the initial parameters of the windbreak and sand-proof structure and the initial parameters of the self-cleaning time sequence;

[0058] The initial parameters of the windproof and sandproof structure include the opening and closing angle of the louvers, the material and aperture of the louvers, the adjustment response threshold of the louvers, the protection start threshold of the sealing components, and the angle of the guide ribs.

[0059] The initial parameters for the self-cleaning sequence include the initial air pressure of the pulsed airflow, the duration and interval of the pulsed airflow injection, the distribution of pulsed air holes, the vibration frequency, the vibration duration, and the interval with the sandstorm prevention operation.

[0060] In this embodiment, by performing multi-dimensional strategy matching based on wind and sand type and particle kinetic energy value, more precise protection strategies can be effectively provided for different environmental conditions, improving the protection effect. Through querying and matching historical strategies, the most suitable protection measures can be quickly located, avoiding tedious manual adjustments and repeated trials, saving time and resources. The system, through efficient search algorithms and similarity evaluation mechanisms, can flexibly respond to differences in the actual environment, ensuring the accuracy and practicality of the matching strategies. The module has a self-optimization function based on actual operating conditions and feedback information, continuously improving the accuracy and adaptability of strategy matching and enhancing the long-term stability of the system. By comprehensively considering multiple factors such as wind and sand type and particle kinetic energy value, the system can not only provide protection measures under single conditions but also propose more complex and detailed composite strategies to ensure optimal protection under different conditions. Reasonable protection strategies can effectively reduce the impact of sand and dust particles on equipment, extend equipment lifespan, reduce maintenance costs, and improve the overall stability and reliability of the equipment.

[0061] In some embodiments of the present invention, for the real-time flow field calculation module, real-time wind speed data and terrain parameters around the photovoltaic inverter are obtained, and flow field numerical simulation calculations are performed on the real-time wind speed data and terrain parameters around the equipment to obtain the real-time flow field deviation coefficient.

[0062] The real-time flow field calculation module is mainly used to accurately simulate and calculate the real-time flow field around the photovoltaic inverter equipment. Since the movement of sand and dust is affected by various factors such as wind speed and terrain, the flow field distribution will vary at different times and locations. By calculating the flow field in real time, we can understand the trajectory, velocity distribution and concentration changes of sand and dust particles around the inverter, thereby judging the actual impact of the current sand and dust environment on the inverter, ensuring that the defense system can adjust the protection measures in a timely manner according to the actual situation and improve the protection effect.

[0063] Real-time wind speed data is acquired in real time through wind speed sensors installed in the photovoltaic power station. The wind speed directly affects the movement speed and impact force of sand particles, which in turn affects their erosion and accumulation on the inverter. Under high wind speed conditions, sand particles have greater kinetic energy and are more likely to penetrate into the inverter, damaging the heat sink fins and circuit boards. Under low wind speed conditions, sand particles move relatively slowly and mainly accumulate on the inverter surface, affecting the heat dissipation effect.

[0064] The terrain parameters around the equipment have a significant impact on the flow and distribution of wind and sand. These parameters include terrain height, slope, and obstacle distribution. Different terrains can cause changes in the direction and speed of wind and sand flow, thereby affecting the concentration and trajectory of wind and sand around the inverter.

[0065] Before performing flow field calculations, the computational domain needs to be meshed. Typically, structured or unstructured meshes are used to discretize the computational domain. Structured meshes have a regular topology and are computationally efficient, but they are less adaptable to complex terrain. Unstructured meshes can be flexibly divided according to the complexity of the terrain and are better adapted to complex terrain, but their computational efficiency is relatively low. In practical applications, an appropriate meshing method can be selected based on the complexity of the terrain surrounding the equipment.

[0066] Based on the pre-defined mathematical calculation model and the divided grid, the flow field equations are solved using numerical methods. During the solution process, appropriate boundary conditions and initial conditions need to be set to ensure the accuracy and stability of the calculation results.

[0067] The output of the real-time flow field calculation module is the real-time flow field deviation coefficient. The real-time flow field deviation coefficient reflects the degree of deviation between the current actual flow field and the ideal flow field. The ideal flow field refers to the uniform flow state of air under the condition of no wind and sand interference and terrain influence. The real-time flow field deviation coefficient can be calculated by comparing parameters such as wind speed, wind direction, and wind sand concentration in the actual flow field with the corresponding parameters in the ideal flow field. The larger the deviation coefficient, the more serious the influence of wind and sand and terrain on the current flow field, and the higher the risk of wind and sand erosion faced by the inverter.

[0068] In this embodiment, by calculating the flow field in real time, the dynamic information such as the trajectory, velocity distribution, and concentration changes of wind and sand around the inverter equipment can be accurately understood. This reflects the actual impact of wind and sand on the inverter in real time, avoiding the over-assumption and low-precision judgment of the wind and sand environment in traditional methods. Real-time flow field calculation can provide real-time and accurate data support for the protection system, ensuring that the protection measures can be adjusted in a timely manner according to environmental changes, thereby improving the protection effect, effectively reducing the erosion and accumulation of wind and sand on the inverter, and extending the service life of the equipment. By calculating the real-time flow field deviation coefficient, the degree of deviation between the current flow field and the ideal flow field can be quantitatively assessed, thereby clarifying the challenges faced by the inverter. The larger the deviation coefficient, the higher the risk of wind and sand erosion to the inverter, helping the system to provide early warnings. By selecting an appropriate mesh generation method, the module can flexibly adapt to the influence of different complex terrains on the flow field, ensuring the accuracy of the calculation results. Under complex terrain, unstructured meshes can provide more refined flow field simulations, ensuring that the distribution of wind and sand under different terrain conditions can be reasonably predicted. By comprehensively considering multiple factors such as wind speed and terrain, the flow field calculation model can more comprehensively and realistically reflect environmental conditions, thereby ensuring that the system can more accurately predict and respond to various possible wind and sand changes, reducing the risk caused by prediction errors due to a single factor.

[0069] In some embodiments of the present invention, for the strategy dynamic correction module, the historical optimal strategy is dynamically corrected based on the real-time flow field deviation coefficient to obtain a coping optimization strategy.

[0070] It receives wind and sand environmental parameters, real-time flow field deviation coefficients, wind and sand types, particle kinetic energy values, and historical optimal strategies; it integrates these multi-source data to form a comprehensive dataset.

[0071] Based on the magnitude of the real-time flow field deviation coefficient, the degree of deviation between the current wind and sand environment and the preset ideal state is evaluated, and the deviation degree evaluation result is obtained; different levels of deviation correspond to different correction strategies and intensities;

[0072] Based on the assessment results of the degree of deviation and the dynamic changes of wind and sand environmental parameters, a detailed analysis of the historical optimal strategy is conducted. For cases of slight deviation, only minor adjustments to some parameters in the historical optimal strategy are needed. For cases of moderate deviation, the type of protective measures needs to be adjusted or investment in protective equipment needs to be increased. For cases of severe deviation, the protective strategy needs to be completely changed and a completely new protective scheme needs to be adopted.

[0073] The revised and optimized response strategy was evaluated to determine whether it could effectively address the current sandstorm environment.

[0074] In this embodiment, by receiving real-time wind and sand environment parameters and flow field deviation coefficients, changes in the current environment can be rapidly assessed, allowing for timely adjustments to the strategy to avoid delayed responses and ensure the continuity of the protective effect. Integrating multiple data sources such as wind and sand environment, particle kinetic energy, and wind and sand type forms a comprehensive dataset, providing a more accurate basis for strategy modification and enhancing the scientific rigor and rationality of the strategy. Based on the deviation assessment results, the historically optimal strategy is modified at different levels, with corresponding correction measures implemented for different deviation levels, ensuring the effectiveness of the modified strategy and the rational allocation of resources. The protective strategy is flexibly adjusted according to the dynamic changes in the wind and sand environment; whether fine-tuning existing parameters or completely changing the protection scheme, the strategy can always maintain its optimal state under different wind and sand environments. Through precise dynamic correction, excessive or insufficient protective measures can be avoided when dealing with different wind and sand environments, thereby improving the efficiency of the protective effect and reducing unnecessary costs.

[0075] In some embodiments of the present invention, for the intelligent decision-making module, the response optimization strategy is input into the intelligent decision-making model to obtain wind and sand prevention structure parameter instructions and self-cleaning timing instructions;

[0076] The intelligent decision-making model generates specific windbreak structure parameter instructions based on the input optimization strategy and a pre-set rule base for windbreak structure parameters. When the wind and sand type is fine sand with high particle kinetic energy, and the real-time flow field deviation coefficient indicates that the movement direction of the sand particles is relatively concentrated, the model will adjust the opening angle of the windbreak structure according to the corresponding relationship in the rule base, so that it can more effectively block the intrusion of sand particles. If the wind and sand type is coarse sand, the model may instruct to increase the filter density of the windbreak structure to filter out larger sand particles. The windbreak structure parameter instructions include, but are not limited to, the tilt angle of the windbreak plate, the pore size of the filter screen, and the opening degree of the ventilation opening.

[0077] The generation of self-cleaning timing instructions needs to consider multiple factors, including the degree of accumulation of sand particles on the inverter surface, the performance and energy consumption of the self-cleaning equipment, and the operating schedule of the photovoltaic power station. The intelligent decision-making model will predict the accumulation rate and amount of sand particles on the inverter surface based on the real-time monitored sand environment parameters and the inverter's operating status. When the accumulation amount reaches a preset threshold, the model will generate reasonable self-cleaning timing instructions by combining the working efficiency and energy consumption of the self-cleaning equipment.

[0078] In this embodiment, by comprehensively considering real-time environmental parameters such as wind and sand type, particle kinetic energy, and flow field deviation coefficient, the parameters of the wind and sand protection structure can be precisely adjusted to ensure its optimal protective effect under different wind and sand environments. Simultaneously, the model also rationally schedules the self-cleaning equipment based on the accumulation of wind and sand particles on the inverter surface and equipment performance, ensuring cleaning operations are performed at the most suitable time, thereby improving the operating efficiency of the photovoltaic power station and extending equipment lifespan. By considering multiple factors, appropriate self-cleaning timing instructions are generated to avoid energy waste caused by over-cleaning. The beneficial effect of this step is that through intelligent decision-making and real-time monitoring, the wind and sand protection and self-cleaning process are optimized, which not only improves the protection capability and operating efficiency of the photovoltaic power station but also reduces maintenance costs and energy consumption.

[0079] In some embodiments of the present invention, the execution and feedback module performs wind and sand protection operation according to the wind and sand protection structure parameter instructions, and after completion, provides a signal feedback that the protection is in place, and executes the self-cleaning timing instructions to perform self-cleaning operation.

[0080] The sand-proof structure is adjusted based on the parameters transmitted from the intelligent decision-making module. The execution and feedback module precisely controls each component of the sand-proof structure. For sand-proof plates with adjustable angles, the module drives the corresponding electric actuator to adjust them to a specific tilt angle according to the instructions, thereby changing the trajectory of sand particles and reducing the possibility of particles entering the inverter. If the instructions require adjusting the opening degree of the ventilation opening, the module controls the baffle of the ventilation opening to achieve the specified opening degree, ensuring the inverter's heat dissipation requirements while blocking the intrusion of sand as much as possible.

[0081] When the wind and sand protection structure parameter command involves the adjustment of the seals, the module will activate the seal strengthening device; for some expandable sealing strips, the module will control the inflation device to fill the sealing strip with an appropriate amount of gas, so that it expands and fits tightly against the gaps in the inverter's casing, enhancing the sealing effect and preventing wind and sand from penetrating through the gaps.

[0082] According to the self-cleaning sequence instructions, the execution and feedback module will start the self-cleaning equipment at the specified time. For systems that use high-pressure air guns for cleaning, the module will control the opening and closing time of the air guns, as well as the spray pressure and angle of the air guns. The air guns will spray the inverter's casing, heat sink fins, and other parts along a preset path to blow off the sand and dust attached to them. If a brush is used for cleaning, the module will drive the brush to clean the surface of the equipment at a certain speed and movement trajectory to ensure that sand and dust can be completely and thoroughly removed.

[0083] The cleaning process is monitored and adjusted in real time during the self-cleaning operation. Sensors installed on the cleaning equipment acquire parameters such as the air gun's spray pressure and the brush's rotation speed, and compare them with the parameters set in the self-cleaning sequence instructions. If any deviation is detected, the module will adjust the operating parameters of the cleaning equipment in a timely manner to ensure that the self-cleaning operation can be carried out according to the predetermined requirements and achieve good cleaning results.

[0084] In this embodiment, by precisely controlling each component of the sand-proof structure, the trajectory of sand particles can be effectively altered, reducing the likelihood of sand entering the inverter and ensuring long-term stable operation of the equipment. Adjustments to the seals, particularly the application of expandable sealing strips, achieve a tighter seal, preventing sand from entering through equipment gaps and improving the equipment's resistance to sand intrusion. The self-cleaning function automatically activates according to a timing command, using a high-pressure air gun or brush to thoroughly remove sand and dust from the equipment surface and heat sink fins, reducing the negative impact of sand on heat dissipation and long-term use. During self-cleaning, the operating status of the cleaning equipment is monitored in real time, and equipment parameters are compared and adjusted to ensure accurate cleaning and achieve ideal cleaning results, avoiding any abnormalities that could affect equipment performance. Regular self-cleaning and sand-proofing operations prevent sand accumulation from damaging the inverter and other equipment, extending equipment lifespan and reducing maintenance costs.

[0085] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A wind and sand monitoring and active defense system for photovoltaic inverters, characterized in that, include: The environmental parameter sensing and analysis module acquires wind and sand environmental parameters, performs characteristic analysis on these parameters, and obtains wind and sand type and particle kinetic energy value. The historical strategy matching module maps wind and sand types and particle kinetic energy values ​​to a preset response strategy database to obtain the best historical strategy. The real-time flow field calculation module acquires real-time wind speed data and terrain parameters around the photovoltaic inverter, performs flow field numerical simulation calculations on the real-time wind speed data and terrain parameters around the equipment, and obtains the real-time flow field deviation coefficient. The strategy dynamic correction module dynamically corrects the historical best strategy based on the real-time flow field deviation coefficient to obtain an optimized strategy. The intelligent decision-making module inputs the response optimization strategy into the intelligent decision-making model to obtain wind and sand protection structure parameter instructions and self-cleaning timing instructions; The execution and feedback module performs wind and sand protection operations according to the wind and sand protection structure parameter instructions. After completion, it provides a signal feedback that the protection is in place and executes the self-cleaning sequence instructions to perform self-cleaning operations.

2. The wind and sand monitoring and active defense system for photovoltaic inverters according to claim 1, characterized in that, The environmental parameter sensing and analysis module also includes a data analysis and processing unit for performing characteristic analysis on wind and sand environmental parameters.

3. The wind and sand monitoring and active defense system for photovoltaic inverters according to claim 1, characterized in that, Aeolian environmental parameters include wind speed, wind direction, particulate matter concentration, and particulate matter size distribution.

4. The wind and sand monitoring and active defense system for photovoltaic inverters according to claim 1, characterized in that, The types of wind and sand include blowing sand, dust, and sandstorms.

5. The wind and sand monitoring and active defense system for photovoltaic inverters according to claim 1, characterized in that, The response strategy database includes the correspondence between wind and sand types and strategies, the correspondence between particle kinetic energy values ​​and strategies, and a comprehensive strategy database.

6. The wind and sand monitoring and active defense system for photovoltaic inverters according to claim 5, characterized in that, By mapping wind and sand types and particle kinetic energy values ​​to a pre-defined database of coping strategies, the best historical strategies can be obtained. It receives the wind and sand type and particle kinetic energy value as input parameters for the response strategy database; Use the sandstorm type as a primary index to find the corresponding sub-database in the database; A secondary search is performed in the sub-library based on the particle kinetic energy value to find the closest historical strategy as the historical optimal strategy.

7. The wind and sand monitoring and active defense system for photovoltaic inverters according to claim 1, characterized in that, The historical strategy matching module also includes a similarity evaluation unit, which is used to calculate the similarity between the wind and sand environment parameters and the corresponding parameters of each strategy in the database, and select the historical strategy with the highest similarity as the output result.

8. The wind and sand monitoring and active defense system for photovoltaic inverters according to claim 6, characterized in that, The historical optimal strategy includes the initial parameters of the windbreak structure and the initial parameters of the self-cleaning time sequence.

9. The wind and sand monitoring and active defense system for photovoltaic inverters according to claim 8, characterized in that, The initial parameters of the windproof and sandproof structure include the opening and closing angle of the louvers, the material and aperture of the louvers, the adjustment response threshold of the louvers, the protection start threshold of the sealing components, and the angle of the guide ribs.

10. The wind and sand monitoring and active defense system for photovoltaic inverters according to claim 8, characterized in that, The initial parameters of the self-cleaning sequence include the initial air pressure of the pulse airflow, the pulse airflow injection duration and interval, the pulse air hole distribution, the vibration frequency, the vibration duration, and the interval with the sandstorm prevention operation.

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