Active fan protection system of wind and light integrated street lamp

Abstract

The invention discloses a fan active protection system of a wind-solar integrated street lamp, and belongs to the technical field of new energy lighting equipment protection. The system comprises a sensing module, a communication module, a decision control module and an execution module. The decision control module is suitable for obtaining the real-time wind speed and the real-time temperature collected by the sensing module and the future forecast wind speed obtained by the communication module from the meteorological platform. Based on the real-time wind speed, the real-time temperature and the future forecast wind speed, triple redundancy protection trigger logic is used for decision judgment; and when any trigger condition is satisfied, generating a protection instruction to drive the execution module to execute a protection action. The problems that an existing protection mechanism is lagged in response, single in dimension and poor in low-temperature adaptability are solved, and the fan is actively protected in advance.

Description

Technical Field

[0001] This application relates to the field of protection technology for new energy lighting equipment, and in particular to an active protection system for the wind turbine of a wind-solar integrated street light. Background Technology

[0002] As a green lighting device that utilizes wind and solar energy for power generation, wind-solar integrated streetlights rely on wind turbines (or simply wind turbines) as one of their core components, which are constantly exposed to complex outdoor environments. In extreme wind conditions, if the wind turbine operates at excessively high speeds, it can cause irreversible mechanical damage to core components such as blades, bearings, and generators, and may even lead to structural failure.

[0003] Most existing wind turbine protection mechanisms rely on a passive, single-dimensional triggering mode. Specifically, the system only monitors wind speed in real time using wind speed sensors, and only activates the braking mechanism to lock the wind turbine when the measured real-time wind speed exceeds a preset fixed threshold. This protection method has several inherent technical defects: First, the response is delayed; the protection action always occurs after the wind turbine has already experienced a huge impact load, failing to provide early prevention. Second, the protection dimension is singular, only considering real-time wind speed and ignoring future weather trends, as well as the risk of freezing and brittle damage to bearings and other metal components that may occur when low temperatures and other environmental factors are coupled with strong winds. Therefore, existing technologies have limited protective effects when dealing with sudden and complex extreme weather events, and are unable to effectively prevent equipment damage and shortened service life. Summary of the Invention

[0004] The purpose of this application is to provide an active protection system for wind turbines in integrated wind and solar streetlights, which aims to solve the technical problems of delayed response, single protection dimension, and poor adaptability to low temperature environment in the existing wind turbine protection mechanism.

[0005] To achieve the above objectives, in a first aspect, this application provides an active protection system for the wind turbine of a wind-solar integrated street light, comprising: The sensing module is suitable for collecting real-time wind speed and real-time temperature data of the environment where the integrated wind and solar streetlights are located. The communication module is suitable for establishing data communication with a remote meteorological platform to obtain meteorological forecast data including future wind speeds; An execution module is adapted to receive protection commands and perform at least one protection action on the wind turbine of the integrated wind and solar street light; and The decision control module is electrically connected to the sensing module, communication module, and execution module, and the decision control module is adapted to: The real-time wind speed and real-time temperature collected by the sensing module are periodically acquired. The weather forecast data is periodically acquired via the communication module, and the future forecast wind speed is extracted from the weather forecast data. Based on the real-time wind speed, the real-time temperature, and the predicted future wind speed, a triple-redundancy protection triggering logic is executed to determine whether a protection command should be generated; and When it is determined that the protection instruction will be generated, the protection instruction will be sent to the execution module.

[0006] Optionally, the triple redundancy protection triggering logic includes: First trigger condition: Determine whether the real-time wind speed is greater than a preset hard protection threshold; The second triggering condition is as follows: It is determined whether the future forecast wind speed within a preset time window in the weather forecast data is not less than the hard protection threshold, and whether the real-time wind speed is greater than a preset soft protection threshold; and The third triggering condition is to determine whether the real-time wind speed is greater than a preset medium wind speed threshold and whether the real-time temperature is less than a preset low temperature protection threshold. Specifically, when at least one of the first triggering condition, the second triggering condition, or the third triggering condition is met, the decision control module determines to generate the protection instruction.

[0007] Optionally, the execution module includes a wind turbine braking mechanism and a bearing heating unit; when the decision control module determines to generate the protection command, the protection command includes at least a braking command for driving the wind turbine braking mechanism to perform a locking action.

[0008] Optionally, the decision control module is further adapted to: when it is determined that the protection command is generated, further determine whether the third triggering condition is met; and if the third triggering condition is met, the protection command further includes a heating command for driving the bearing heating unit to heat the fan bearing.

[0009] Optionally, the value of the soft protection threshold is smaller than the value of the hard protection threshold.

[0010] Optionally, the value of the medium wind speed threshold is greater than the value of the soft protection threshold and less than the value of the hard protection threshold.

[0011] Optionally, the decision control module is further adapted to execute a state recovery logic, which includes: continuously monitoring the real-time wind speed and the weather forecast data when the execution module has performed a protection action; when it is detected that the real-time wind speed is continuously less than a preset recovery threshold within a preset recovery time, and the future forecast wind speeds in the weather forecast data within a preset time window are all less than the hard protection threshold, generating and sending a release command to the execution module to enable the wind turbine to resume normal operation.

[0012] Optionally, the sensing module includes: a three-cup anemometer for measuring the real-time wind speed; and an industrial-grade ambient temperature sensor for measuring the real-time temperature.

[0013] Optionally, the communication module is a 5G / NB-IoT dual-mode communication module to ensure data transmission reliability under different network coverage conditions.

[0014] Optionally, the decision control module acquires the real-time wind speed and the real-time temperature every 30 seconds, and acquires the weather forecast data every 60 minutes.

[0015] Optionally, the preset time window is the next hour.

[0016] The technical solution provided in this application innovatively introduces future weather forecast data as a feedforward signal for decision-making, and combines it with real-time wind speed and temperature data to construct a multi-dimensional, predictive, and proactive protection logic. Compared with existing technologies, this application has the following beneficial effects: 1. Achieved proactive protection in advance: Through a soft triggering mechanism based on future wind speed forecasts, the system can put the wind turbine into a protected state in advance before extreme weather arrives, fundamentally eliminating the delay of the traditional passive response mode and effectively avoiding the core components of the wind turbine from being subjected to peak impact loads.

[0017] 2. Enhanced protection dimensions and robustness: Triple redundancy of triggering logic covers predictable gradual strong winds, unpredictable sudden gusts, and complex risk scenarios involving the coupling of low temperatures and strong winds, making the protection mechanism more comprehensive and reliable.

[0018] 3. Enhanced environmental adaptability of the equipment: A low-temperature composite risk protection was specifically designed, and the linkage bearing heating effectively solved the problem of fan failure caused by bearing freezing and cracking in cold northern regions during winter, significantly extending the service life of the equipment in harsh environments. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a structural block diagram of an active protection system for a wind turbine of a wind-solar integrated street light, provided as an embodiment of this application.

[0021] Figure 2 A flowchart of a wind turbine active protection method provided in an embodiment of this application.

[0022] Figure 3 This is a detailed flowchart of step S200 in the embodiments of this application, namely the triple redundancy protection triggering logic.

[0023] Figure 4 This is a detailed flowchart of step S300 in the embodiments of this application, namely the execution of protection and recovery action decisions.

[0024] Figure 5 This is a schematic diagram illustrating the significant advantages of the protection mechanism of this application in terms of time response compared to the prior art, as shown in the embodiments of this application.

[0025] Figure 6 This is a schematic diagram illustrating the physical deployment relationship of the modules of the active protection system for wind turbines in one embodiment of this application. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0028] Please see Figure 1This application provides an active protection system 100 for wind turbines in a wind-solar integrated street light. In one specific implementation, the system 100 employs a decision-making mechanism that integrates future weather forecasts with real-time monitoring of multiple physical quantities at the current moment. This enables predictive feedforward protection of the wind turbine under extreme weather conditions, effectively avoiding equipment damage caused by response delays. This method solves the technical problems of untimely and incomplete protection caused by passive protection relying solely on a single real-time wind speed threshold in existing technologies, achieving the beneficial effects of significantly improving equipment operational safety and extending service life.

[0029] The system 100 includes a sensing module 110, a communication module 120, a decision control module 130, and an execution module 140.

[0030] The sensing module 110 functions as the system's sensory organ, responsible for high-frequency, multi-dimensional state data acquisition of the local microenvironment surrounding the integrated wind-solar streetlight. In one embodiment, the sensing module 110 includes a high-precision three-cup anemometer and an industrial-grade ambient temperature sensor. The three-cup anemometer is fixed to a bracket on top of the streetlight, ensuring unobstructed sensing of ambient wind. Its internal Hall effect sensor or optocoupler linearly converts the rotational angular velocity of the cups into an electrical signal. The industrial-grade ambient temperature sensor, such as a platinum resistance thermometer (Pt100) encapsulated in a radiation shield, is used to accurately measure the ambient atmospheric temperature. Both sensors are connected to the analog input interface of the decision control module 130 via shielded cables, continuously providing raw analog signals characterizing the current environmental state.

[0031] The communication module 120 serves as a bridge between the system and an external wide-area data network, ensuring the data source for predictive protection. In a preferred embodiment, the communication module 120 employs a dual-mode communication module supporting both 5G and NB-IoT (Narrowband Internet of Things) communication protocols. This design provides redundant and adaptive network connectivity. In areas with 5G network coverage, the system can utilize its high speed and low latency for rapid data interaction; while in remote areas or areas with poor signal coverage, the system can automatically switch to the lower-power, wider-coverage NB-IoT network, ensuring the stability and reliability of the weather forecast data link. The communication module 120 connects to the decision control module 130 via a serial communication interface (such as UART), receiving AT commands from the latter to perform operations such as network connection, data request, and data reception.

[0032] The execution module 140 is the final physical executor of the protection commands, directly implementing protective actions on the wind turbine body. In a specific embodiment, the execution module 140 consists of a wind turbine braking mechanism and a bearing heating unit. The wind turbine braking mechanism can be an electromagnetic power-off brake, which, in the default power-off state, uses an internal spring to lock the brake pads to the wind turbine main shaft, achieving a locking effect; when energized, the electromagnet generates attraction, causing the brake pads to separate and releasing the main shaft. This design ensures that the wind turbine is in a safe braking state even in the event of an unexpected power outage. The bearing heating unit can be one or more flexible carbon fiber heating strips tightly wound around the outer shell of the wind turbine main bearing. Carbon fiber material has the advantages of uniform heating, rapid response, and good weather resistance. The drive circuits of both execution components are connected to the GPIO (General Purpose Input / Output) ports of the decision control module 130, and their power-on / off states are directly controlled by the high and low level signals output by the module.

[0033] The decision control module 130 is responsible for all data processing, logical operations, and control instruction generation. In one embodiment, it consists of a high-performance embedded microcontroller (MCU) or a system-on-a-chip (SoC) based on an ARM Cortex-A9 processor. Internally, it integrates a central processing unit (CPU), random access memory (RAM), flash memory for storing firmware programs, and abundant I / O interfaces, including an analog-to-digital converter (ADC) for processing sensor signals and GPIO ports for controlling the execution module. The decision control module 130 internally runs a pre-programmed control algorithm, the specific flow of which will be described below. Figure 2 To provide a detailed explanation.

[0034] Please see Figure 2 This illustrates the flowchart of the active wind turbine protection method provided in this application embodiment. The method is executed by the decision control module 130 and specifically includes the following steps: S100: Periodic acquisition and synchronization of multi-source environmental data.

[0035] This step forms the data foundation for the entire decision-making process, and its purpose is to ensure that the decision control module 130 can continuously monitor the current and future environmental conditions. This step is broken down into two parallel subtasks.

[0036] S110: Obtain the real-time wind speed and real-time temperature collected by the sensing module.

[0037] The decision control module 130 performs local real-time data acquisition at a relatively high frequency, for example, every 30 seconds. In this sub-step, the ADC channel of the decision control module 130 samples the analog voltage or current signals from the three-cup anemometer and the ambient temperature sensor, respectively. The sampled raw digital values ​​are processed by an internally preset calibration curve or conversion formula and are finally converted into values ​​with standard physical units.

[0038] For example, in a certain acquisition cycle, the current signal output by the wind speed sensor is 12mA. If the sensor's range is 0-60m / s, corresponding to a 4-20mA output, then the decision control module 130 uses a linear transformation formula... Perform calculations, where It is the real-time wind speed. This is the measured current value. Substituting the data, we can obtain... m / s. Similarly, the industrial-grade ambient temperature sensor, as a platinum resistance (Pt100) sensor, has a resistance value that changes with temperature. The decision control module measures this resistance value through a precision bridge circuit, and then obtains a high-precision real-time temperature value by consulting a temperature-resistance correspondence table pre-loaded in flash memory, or by applying the Callendar-Van Dusen equation for precise inverse kinematics according to international standards (such as IEC60751). ,For example ℃. These two calculated values... and The current state is stored in a specially designated "current state area" within the internal RAM of the decision control module 130, so that it can be called up at any time by subsequent logical judgment steps.

[0039] S120: Obtain the weather forecast data via the communication module, and parse the future forecast wind speed from the weather forecast data.

[0040] Unlike high-frequency local data acquisition, remote weather forecast data is acquired at a lower frequency, such as every 60 minutes, to balance data timeliness and communication energy consumption. In this sub-step, the decision control module 130 sends a series of AT commands to the communication module 120 via the UART interface. The first is a network attach command, enabling the communication module to connect to an available 5G or NB-IoT base station. After successful connection, the decision control module 130 sends a constructed HTTP GET request command, the target URL of which points to a national meteorological science data center API endpoint, and includes the street light's preset GPS latitude and longitude coordinates in the URL parameters.

[0041] For example, the HTTP request might be GET / api / v1 / weather / forecast?lon=116.4&lat=39.9. After receiving the request, the weather platform server returns a JSON (JavaScript Object Notation) data packet containing hourly weather forecasts for the next 24 hours or longer. Upon receiving this data packet, the communication module 120 transmits it completely to the decision control module 130 via UART. The JSON parser program inside the decision control module 130 performs syntax analysis on this text data packet, extracting the forecast sequences related to wind speed and temperature. For example, it locates the `hourlyforecast` array and iterates through each object, extracting key-value pairs such as `time: "t+1h", windspeed: "13.5m / s", and temperature: "4.5C". The decision control module 130 then displays the hourly wind speed forecasts for the next 24 hours. and forecast temperature The forecast data is stored in the "forecast data cache" in RAM for later use.

[0042] S200: Decision-making based on triple redundancy protection trigger logic.

[0043] After each update of real-time data in S110, the decision control module 130 immediately initiates this core decision-making step. This step does not employ a single judgment criterion, but rather evaluates three different risk scenarios in parallel and independently, constituting the "triple redundancy protection trigger logic" as described in this application. The purpose of this design is to maximize the coverage and reliability of the protection mechanism, ensuring that any potential threat can be identified in a timely manner.

[0044] S210: Evaluate the first trigger condition.

[0045] The first trigger condition is a real-time monitoring based on absolute risk, acting as the last line of defense for the system. This condition is used to deal with sudden strong gusts that develop extremely rapidly and may not be accurately predicted by meteorological models. The decision control module 130 determines the real-time wind speed currently stored in RAM. Is it greater than a preset hard protection threshold? .

[0046] The hard protection threshold This limit is set based on the mechanical design strength and safety specifications of the wind turbine itself, representing the maximum wind speed at which the wind turbine can operate safely without protection. Exceeding this wind speed will result in an extremely high risk of damage to components such as blades and bearings.

[0047] For example, for a small to medium-sized vertical axis fan, its hard protection threshold is... It can be set to 12 m / s (equivalent to a Force 6 wind). At a certain moment, if the real-time wind speed collected by S110 is... If the speed is m / s, then the decision control module 130 performs a comparison operation. The expression evaluates to True, therefore, the first triggering condition is met. At this point, regardless of whether the other two conditions are met, the system will immediately trigger protection.

[0048] S220: Evaluate the second triggering condition.

[0049] The second triggering condition is the core of this system's predictive feedforward protection, and its logic embodies the idea of ​​"early warning and degraded response." The judgment of this condition is divided into two stages.

[0050] In the first stage, the system enters a "high alert state." The decision control module 130 will consult the data in the "forecast data cache" in RAM to determine whether there is a forecast wind speed within a preset time window, such as the next hour. Greater than or equal to the hard protection threshold If this situation exists, it means the system anticipates an impending extreme windstorm, and a status flag within the system is set to "high alert."

[0051] The second stage involves determining the soft trigger. When the system is in a "high alert state," the decision control module 130 will use a lower soft protection threshold. To match real-time wind speed A judgment is made. The soft protection threshold... The value is significantly smaller than However, it is higher than the average wind speed when the fan is working normally.

[0052] For example, continuing from example S120, the system obtains the forecast wind speed for the next hour as follows: m / s. The decision control module 130 first performs a first-stage judgment: (where 12.0 is) When this condition is met, the system immediately enters a "high alert state." Assuming that after 45 minutes, the wind speed begins to gradually increase, and the real-time wind speed collected by S110 is... m / s. At this point, the decision control module 130 performs the second-stage judgment and... With soft protection threshold (For example, set to 8.0 m / s) for comparison: This condition is also met. Because the conditions in both stages are satisfied, the second triggering condition is determined to be true. It is evident that although the real-time wind speed is far from the dangerous 12 m / s, the system, based on its prediction of the future, has already activated its protection mechanism, perfectly avoiding the impending peak impact.

[0053] S230: Evaluate the third trigger condition.

[0054] The third triggering condition is specifically designed to address the combined risks arising from the coupling of low temperatures and strong winds. Metallic materials exhibit increased brittleness at low temperatures, while the viscosity of lubricating grease increases dramatically. This makes wind turbine bearings highly susceptible to freezing cracks or wear failures when simultaneously subjected to low temperatures and high wind loads. This condition requires both sub-conditions to be met simultaneously.

[0055] The decision control module 130 determines the current real-time wind speed. Is it greater than a preset medium wind speed threshold? Furthermore, it simultaneously determines the current real-time temperature. Is it less than a preset low temperature protection threshold? .

[0056] The medium wind speed threshold Typically, it falls between soft and hard protection thresholds, for example, 10 m / s. The low-temperature protection threshold... The temperature is set according to the materials used in the bearing and the specifications of the lubricating grease, and is usually between 5°C and 0°C.

[0057] For example, on a winter night, the real-time data collected by S110 is m / s, ℃. Assume Set to 10.0 m / s, Set to 5.0℃. Decision control module 130 performs a logical AND operation: ( AND ( Since both subexpressions result in true, the overall logical AND operation is true, and the third triggering condition is satisfied.

[0058] In one embodiment, the determination of the hard protection threshold, soft protection threshold, medium wind speed threshold, and low temperature protection threshold can be based on a systematic method, rather than being arbitrarily set, to ensure the scientific validity and effectiveness of the protection logic. Specifically, the hard protection threshold... The limit operating wind speed can be determined directly from the design safety manual or product specifications provided by the wind turbine manufacturer, and a safety factor can be added. The soft protection threshold... The determination of the wind speed threshold can be based on statistical analysis of historical meteorological data (e.g., hourly wind speed records from the past five years) of the streetlight installation location. By calculating conditional probability, a wind speed value can be set. When the real-time wind speed reaches this value, the probability of a strong wind exceeding the hard protection threshold occurring within a short period of time (e.g., 2 hours) exceeds a preset confidence level (e.g., 70%). This wind speed value can then serve as the soft protection threshold, which is essentially a risk warning signal based on historical experience. The aforementioned moderate wind speed threshold... and low temperature protection threshold Determining the low-temperature protection threshold requires comprehensive consideration of the mechanical properties of the metal materials used in the wind turbine bearings (e.g., bearing steel) and the physicochemical characteristics of the grease. The ductile-brittle transition temperature range of the metal material can be determined by consulting the material handbook, and the low-temperature protection threshold can be set near the upper limit of this range. Simultaneously, based on the low-temperature performance curves provided by the grease supplier, it can be determined at what temperature the viscosity will increase sharply to the point of affecting normal lubrication; this temperature can serve as another basis for setting the low-temperature protection threshold. The medium-speed threshold is the critical wind speed at which sufficient stress can be generated under these low-temperature conditions to induce brittle fracture or accelerate wear; it can be estimated through finite element analysis or empirical formulas.

[0059] In a preferred embodiment, the value of the moderate wind speed threshold is greater than the value of the soft protection threshold and less than the value of the hard protection threshold, i.e., it satisfies... The relationship. This hierarchical threshold setting has clear technical advantages. As the minimum threshold used in response to predictive information, its purpose is to raise the system’s vigilance when risks are still in their infancy, reflecting the lead time for protection. This corresponds to a compound risk that has already occurred and has a clear physical mechanism (low temperature + moderate wind speed). The severity of this risk is higher than that of a purely predicted risk, but lower than that of an impending structural damage risk. Therefore, its corresponding wind speed threshold should be higher than [the threshold value is missing here]. . The highest threshold, representing the last line of defense in the protection system, corresponds to extreme wind forces that could cause direct, catastrophic damage; therefore, its value must be the highest. This gradient setting ensures that the protection system can respond in a differentiated and hierarchical manner based on the nature and urgency of the risk.

[0060] S300: Decision-making and execution of protection and recovery actions.

[0061] This step is the final output stage of the decision-making process, responsible for converting the logical results obtained from the evaluation in S200 into physical control signals for the execution module 140.

[0062] S310: Generate protection instructions.

[0063] The decision control module 130 performs a logical OR operation on the three Boolean results (true or false) obtained from the evaluations in S210, S220, and S230. The characteristic of the logical OR operation is that if any one of the inputs is true, its output is true. This means that if any of the three risk scenarios mentioned above occurs, the protection mechanism of the entire system will be activated. If the result of the logical OR operation is true, the decision control module 130 generates a protection command.

[0064] In addition, the decision control module 130 will specifically check the result of S230. If the result of S230 is true, the generated protection command will not only include the general braking command, but will also include an additional specific heating command.

[0065] S320: Sends the protection command to the execution module.

[0066] The generated protection command is output through the GPIO port of the decision control module 130.

[0067] If the protection command includes a braking command, the GPIO port controlling the wind turbine braking mechanism will switch from a high level (e.g., 3.3V, indicating power-on release) to a low level (0V, indicating power-off lock). The electromagnetic power-off brake will then activate, completely locking the wind turbine main shaft in less than 0.5 seconds.

[0068] If the protection command includes a heating command, the GPIO port of the bearing heating unit will output a high-level signal. This signal will connect the power supply (e.g., 24V DC) to the carbon fiber heating belt through a relay or MOSFET switch. The heating belt will then start to heat the bearing evenly at a power of 80W to maintain its temperature within a safe range.

[0069] S330: Execution state recovery logic.

[0070] When the wind turbine is in a protected state, the decision control module 130 will switch to executing the state recovery logic. It will continuously monitor the real-time wind speed. Wind speed forecast for the next hour The recovery condition is set to: real-time wind speed. Within a preset recovery period (e.g., 10 minutes), the value remains consistently and stably below a preset recovery threshold. (e.g., 6.0 m / s), and at the same time, the forecast wind speed for the next hour. It is also less than the hard protection threshold. These two conditions together ensure that current and future weather conditions are safe enough to allow the protection to be lifted.

[0071] When the recovery conditions are met, the decision control module 130 will generate and send a release command to the execution module 140, which will restore the corresponding GPIO port to its initial state (brake energized and released, heating de-energized and stopped), so that the wind turbine can resume normal wind power generation operation.

[0072] In summary, the wind turbine active protection system for integrated wind-solar streetlights provided in this application introduces future weather forecast data into the decision loop, constructing a soft-triggering mechanism based on predictive feedforward control. This, combined with hard triggering for sudden risks and specialized protection against low-temperature composite risks, forms a three-dimensional, redundant, and intelligent active protection system. This system effectively overcomes the inherent defects of existing technologies, completing protective actions before extreme weather causes substantial damage to the wind turbine, greatly improving the operational reliability and equipment lifespan of integrated wind-solar streetlights. It has significant application value, especially in areas with complex and variable climate conditions.

[0073] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit described above can be implemented in hardware.

[0074] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An active protection system for the wind turbine of a wind-solar integrated street light, characterized in that, include: The sensing module is suitable for collecting real-time wind speed and real-time temperature data of the environment where the integrated wind and solar streetlights are located. The communication module is suitable for establishing data communication with a remote meteorological platform to obtain meteorological forecast data including future wind speeds; An execution module is adapted to receive protection commands and perform at least one protection action on the wind turbine of the integrated wind and solar street light; and The decision control module is electrically connected to the sensing module, communication module, and execution module, and the decision control module is adapted to: The real-time wind speed and real-time temperature collected by the sensing module are periodically acquired. The weather forecast data is periodically acquired via the communication module, and the future forecast wind speed is extracted from the weather forecast data. Based on the real-time wind speed, the real-time temperature, and the future forecast wind speed, a triple redundancy protection triggering logic is executed to determine whether to generate a protection command. as well as When it is determined that the protection instruction will be generated, the protection instruction will be sent to the execution module.

2. The system according to claim 1, characterized in that, The triple redundancy protection triggering logic includes: First trigger condition: Determine whether the real-time wind speed is greater than a preset hard protection threshold; The second triggering condition is as follows: It is determined whether the future forecast wind speed within a preset time window in the weather forecast data is not less than the hard protection threshold, and whether the real-time wind speed is greater than a preset soft protection threshold; and The third triggering condition is to determine whether the real-time wind speed is greater than a preset medium wind speed threshold and whether the real-time temperature is less than a preset low temperature protection threshold. Specifically, when at least one of the first triggering condition, the second triggering condition, or the third triggering condition is met, the decision control module determines to generate the protection instruction.

3. The system according to claim 2, characterized in that, The execution module includes a fan braking mechanism and a bearing heating unit; When the decision control module determines to generate the protection command, the protection command includes at least a braking command for driving the wind turbine braking mechanism to perform a locking action.

4. The system according to claim 3, characterized in that, The decision control module is also adapted to: When it is determined that the protection command is generated, it is further determined whether the third triggering condition is met; and If the third triggering condition is met, the protection command further includes a heating command for driving the bearing heating unit to heat the fan bearing.

5. The system according to claim 2, characterized in that, The value of the soft protection threshold is less than the value of the hard protection threshold.

6. The system according to claim 2, characterized in that, The value of the medium wind speed threshold is greater than the value of the soft protection threshold and less than the value of the hard protection threshold.

7. The system according to claim 2, characterized in that, The decision control module is also adapted to execute a state recovery logic, the state recovery logic including: While the execution module has performed the protection action, the real-time wind speed and the weather forecast data are continuously monitored; When the real-time wind speed is detected to be continuously less than a preset recovery threshold within a preset recovery time, and the future forecast wind speeds within a preset time window in the meteorological forecast data are all less than the hard protection threshold, a release command is generated and sent to the execution module to enable the wind turbine to resume normal operation.

8. The system according to claim 1, characterized in that, The sensing module includes: A three-cup anemometer is used to measure the real-time wind speed; and An industrial-grade ambient temperature sensor is used to measure the real-time temperature.

9. The system according to claim 1, characterized in that, The communication module is a 5G / NB-IoT dual-mode communication module to ensure the reliability of data transmission under different network coverage conditions.

10. The system according to claim 1, characterized in that, The decision control module acquires the real-time wind speed and real-time temperature every 30 seconds, and acquires the weather forecast data every 60 minutes.

Images