Offshore wind turbine control system based on IEC61499 architecture

Abstract

The application discloses a kind of offshore wind turbine control systems based on IEC61499 architecture, it is related to wind power generation control system technical field, generator insulation monitoring system: the parameter of the insulation resistance value, dielectric loss value and degree of contamination value of generator is collected by sensor, the insulation condition information of monitoring generator is obtained, and the detection is transmitted to linkage communication CPU module as insulation fault signal;The application is in the mode of IEC61499 distributed control architecture, realizes the control system of offshore wind turbine and can distribute the function of subsystem, and adopts linkage communication CPU module to obtain the data between subsystem and carry out the ability of high-speed interaction sharing, uses the subsystem of offshore wind turbine as the function module of IEC61499, improves signal processing efficiency, more more quickly when later iteration and upgrading subsystem, and improve the security of wind turbine operation.

Description

Technical Field

[0001] This invention relates to the field of wind power generation control system technology, specifically to an offshore wind turbine control system based on the IEC61499 architecture. Background Technology

[0002] Currently, the control system of offshore wind turbines adopts the same model as that on land, controlling the turbine by installing a PLC controller at the base of the tower. The PLC collects data from sensors in real time for dynamic logic control. However, due to the traditional control functions and software architecture of the PLC, it cannot support the simultaneous integration of different systems. Since some systems are non-real-time control systems, the original PLC control method cannot be used for unified management. However, considering the special characteristics of the marine environment and the increasing size of wind turbines, and for safety reasons, several intelligent sensors have been installed on offshore wind turbines. These include online corrosion monitoring systems for tower corrosion, online load monitoring systems for blade root loads, and online insulation monitoring systems for generator insulation. Each system is relatively independent and developed using different languages ​​and methods. This presents a limitation in terms of unified maintenance and updates.

[0003] For example, the current control system of offshore wind turbines includes not only the main operation control system, but also auxiliary control systems such as lubrication system, video monitoring system, and blade load monitoring system. Each system is independently controlled and does not have system linkage function. If the blade load of the wind turbine is large, the control system of the offshore wind turbine cannot obtain the signal and cannot perform alarm and control operations. If the current control mode is used continuously, it may lead to safety problems of the wind turbine in the long run.

[0004] The existing technology has the following shortcomings: Therefore, in actual use, the offshore wind power control system based on the IEC61499 architecture has the following shortcomings: because the communication between distributed components is achieved through an event-triggered mechanism, there are data synchronization inconsistencies and signal transmission delays, which may lead to erroneous behavior of the control system, hardware failures or software anomalies that cause performance degradation, thereby causing the subsystem to fail to work properly and destroying the overall stability and function of the control system.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide an offshore wind turbine control system based on the IEC61499 architecture. This invention solves the problems mentioned in the background art by using a distributed control mode, which addresses the issue that offshore wind turbines currently have many intelligent sensors and that the controller of the offshore wind turbine must know in real time whether the current operating status of each sensor has triggered the early warning mode.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a control system for offshore wind turbines based on the IEC61499 architecture, including a generator insulation monitoring system: acquiring parameters such as the insulation resistance value, dielectric loss value, and pollution level value of the generator through sensors, obtaining information on the insulation status of the generator, and transmitting the detected insulation fault signal to the linkage communication CPU module; PLC operation control system: Using a programmable logic controller (PLC), the system collects current, voltage, power, frequency, temperature and vibration parameter signals of the generator, generates generator operation status information, and transmits the detected operation fault signals to the linkage communication CPU module. Unit lubrication control system: Collects temperature, pressure and flow parameters of generator lubricating oil through intelligent sensors, generates unit lubrication status signals, and transmits signals of abnormal unit lubrication to the linkage communication CPU module; Blade load calculation and control system: Sensors are used to monitor the generator blades, collect parameter signals such as wind speed at the blade location, force direction of the blade, and vibration acceleration of the blade, generate blade load status information, transmit the detected blade load status information to the linkage communication CPU module, construct a Bayesian model, and combine it with the mechanical model to calculate the load on the blade. By setting a preset load threshold range, when the load exceeds the threshold, load control is carried out by adjusting the blade angle, motor load and wind turbine speed. Blade lightning strike monitoring system: The system uses intelligent sensors to monitor lightning signals in the environment where the generator blades are located, including the frequency, intensity, and distance of the lightning, as well as the instantaneous temperature state of the blade surface, the blade vibration frequency, and the amplitude of the parameters. It generates blade lightning strike status signals and transmits the detected blade lightning strike status information to the linkage communication CPU module. Linkage communication CPU module: It acquires data signals from the subsystem in real time through the bus interface, synchronizes, shares, and integrates the data, and uses statistical average and threshold judgment algorithms to superimpose and calculate abnormal information transmitted by the subsystem. It comprehensively analyzes and judges the impact of abnormal information, generates level-based abnormal signals, transmits them to the abnormal signal alarm module, and feeds back the abnormal signals to the subsystem for synchronous control. Abnormal signal alarm module: Receives abnormal signals from the integrated subsystem calculated by the linkage communication CPU module and performs alarm processing, including pre-classifying abnormal levels, setting priorities and priority alarm response times based on safety risk assessment.

[0008] Preferably, the generator insulation monitoring system involves installing an insulation resistance sensor on the generator to measure and collect the insulation resistance value of the generator windings. Dielectric loss value and filth value The data collected on the insulation status of the generator is compared and analyzed with preset thresholds, and abnormal signals are evaluated and judged. If the preset safety threshold range for generator insulation monitoring parameters is defined, then the insulation resistance value... Dielectric loss value filth value ; When measuring the insulation resistance value of generator windings If the signal is abnormal, the insulation resistance signal of the generator winding is determined to be abnormal and transmitted to the linkage communication CPU module. When measuring the standard dielectric loss value of generator loss If the generator's dielectric loss signal is abnormal, it will be determined and transmitted to the linkage communication CPU module. When measuring the pollution level of the generator If the generator's pollution level signal is abnormal, it will be determined and transmitted to the linkage communication CPU module.

[0009] Preferably, the PLC operation control system transforms the generator's operation logic control by using control logic algorithms to transform the generator's current, voltage, output power, output frequency, temperature, and vibration parameter data collected by the PLC. The steps for transforming the control logic are as follows: setting the generator's start-stop, speed regulation, and power control operation modes and parameters; The PLC collects data on the generator's operating current, voltage, output power, output frequency, temperature, and vibration parameters and monitors its operating status in real time. When the PLC reads the parameter data and determines whether there are any abnormal conditions such as overload or overtemperature in the generator, it further performs fault detection and load reduction or power cut-off on the generator. The PLC is pre-programmed with overcurrent protection, overvoltage protection, and underfrequency protection control logic to ensure the generator can operate safely. The PLC records and transmits the collected parameter data to the linkage communication CPU module. Through the data sharing function of the linkage communication CPU module, data interaction and coordination with the subsystem can be realized.

[0010] Preferably, the generator lubrication control system collects data on the temperature, pressure, and flow rate of the generator lubricating oil and compares them with preset thresholds. The preset safety threshold range for generator lubrication parameters determines the lubricating oil temperature. Lubricating oil pressure Lubricating oil flow rate It detects abnormalities in the lubricating oil temperature, pressure, and flow parameters, and transmits the detected abnormal signals to the linkage communication CPU module.

[0011] Preferably, a Bayesian model is constructed in the blade load calculation and control system to calculate the conditional probability of the target variable of blade force occurrence based on the observed variables of collected wind speed and wind direction data, and then the Bayesian algorithm formula is used. In the formula, Indicates wind speed. Indicates wind direction. Indicates in a known event In the event of occurrence, The conditional probability of occurrence; Indicates in the event In the event of occurrence, The conditional probability of occurrence; Indicates an event The prior probability of occurrence; Indicates an event The prior probability is used to calculate the posterior probability distribution of the blade force, and the blade load is calculated based on the posterior probability distribution of the blade force, combined with the mechanical model and the structural characteristics of the blade.

[0012] Preferably, the blade lightning strike monitoring system collects parameter data on the impact of rain and lightning on the blade in the environment. Since lightning strikes can cause structural damage, dynamic imbalance, electrical system failure, energy loss and safety hazards, the system integrates and calculates the parameter signals of the blade lightning strike status using a weighted average method to determine the safety status of the blade after the lightning strike.

[0013] Preferably, the linkage communication CPU module receives abnormal signals from the subsystem and performs data synchronization, sharing, and coordination of subsystem communication. Then, it performs superposition calculations on the abnormal information transmitted from the subsystem, using a statistical average algorithm. In the formula, i represents the number of sequences in the subsystem, and X represents the proportion of each abnormal signal in the subsystem. The steps to obtain anomaly information from the statistics subsystem are as follows: Collect abnormal information: Collect abnormal information of the subsystem, including parameter signals that exceed the threshold; Count the number of anomalies in the subsystem: Based on the collected anomaly information, count and calculate the number of different types of anomalies in each system; Calculate the percentage of abnormal information: count the total number of abnormal information in all subsystems, and calculate the percentage of abnormal information in each subsystem in the total number of abnormal information. That is, by dividing the number of abnormal information in each subsystem by the total number of abnormal information, we can get the percentage of abnormal information in each subsystem. Comparison of abnormal information indicators: The proportion of abnormal information in each subsystem is compared and analyzed, and the trend, change and impact status of abnormal information are determined according to the judgment criteria of preset thresholds; Feedback and processing of abnormal information: Based on the abnormal information of each subsystem obtained from statistics, the information is fed back to the offshore wind turbine control system. The abnormal information is analyzed and processed, and the subsystems with abnormal information that cause impact and harm are subject to negative feedback control, thereby regulating parameter changes and notifying operators to take measures to eliminate faults.

[0014] Preferably, the alarm processing method of the abnormal signal alarm module includes pre-classifying abnormal levels, setting priorities and priority alarm response times based on safety risk assessments. The pre-classification of abnormality levels is based on the degree of damage to the wind turbine's operation and the impact of the abnormal signal on the safe operation of the control system, and is divided into four different levels: emergency, warning, attention, and ignore. Safety risk assessment and priority setting: Conduct safety risk assessments on various abnormal signals in the subsystem, and determine the potential impact of each abnormal signal on equipment, personnel and environment based on the characteristics and operating requirements of the subsystem. Then, based on the assessment results, divide the alarm priority into four different levels: high, relatively high, medium and low. Priority alarm response time: Based on the level and priority of the abnormal signal, four different response time requirements are set: emergency shutdown, immediate execution, short-term maintenance, and long-term maintenance.

[0015] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention utilizes an IEC61499 distributed control architecture to enable distributed control of subsystem functions within the control system of offshore wind turbines. It employs a linked communication CPU module to acquire data between subsystems and facilitate high-speed data exchange and sharing. The subsystems of the offshore wind turbine are used as functional modules according to IEC61499 standards, with the offshore wind turbine control system serving as the main control module and the generator insulation monitoring system, PLC operation control system, turbine lubrication control system, blade load calculation control system, and blade lightning strike monitoring system serving as subordinate functional modules. This improves signal processing efficiency, allows for faster iteration and upgrades of subsystems, and enhances the operational safety of the wind turbine.

[0016] This invention employs an abnormal signal alarm module, which increases the consistency of data synchronization and avoids signal transmission delays. The abnormal signal alarm module also enhances the timely reminder of erroneous behavior in the control system, further feeding back to the subsystem for fault verification and adjustment of parameter changes, thereby maintaining the overall stability and functionality of the control system. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0018] Figure 1 This is a block diagram of the offshore wind turbine control system based on the IEC61499 architecture of the present invention.

[0019] Figure 2 This is a flowchart of the linkage abnormality signal judgment of the offshore wind turbine control system of the present invention.

[0020] Figure 3 This is an architecture diagram of the control system for the offshore wind farm of the present invention. Detailed Implementation

[0021] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0022] Example 1 like Figure 1-3 As shown, this invention provides an offshore wind turbine control system based on the IEC61499 architecture, including a generator insulation monitoring system: it acquires parameters such as the generator's insulation resistance value, dielectric loss value, and pollution level value through sensors to obtain information on the generator's insulation status, and transmits the detected insulation fault signal to the linkage communication CPU module. That is, the linkage communication CPU module receives the monitored generator's insulation abnormal signal for data synchronization processing, which is used to link the subsystem signals of the offshore wind turbine control system for signal linkage calculation, and further determine the safety and abnormality of the generator's insulation performance. PLC operation control system: Utilizes a programmable logic controller (PLC) to collect current, voltage, power, frequency, temperature, and vibration parameter signals of the generator, generate generator operating status information, and transmit detected operating fault signals to the linkage communication CPU module for monitoring and controlling the operation of the wind turbine. By receiving data transmitted by the wind turbine during operation, it realizes data processing and communication, status monitoring, fault detection and handling, and scheduling control functions. The unit lubrication control system collects temperature, pressure and flow parameters of the generator's lubricating oil through intelligent sensors, generates a unit lubrication status signal, and transmits the detected abnormal lubrication signal to the linkage communication CPU module. After analyzing the abnormality of the generator's lubricating oil, an alarm signal is issued when an abnormality is detected, notifying the operation and maintenance personnel to carry out inspection and maintenance, in order to reduce the wear and friction of the generator set and extend the service life of the wind turbine equipment. Blade load calculation and control system: Sensors are used to monitor the generator blades, collecting parameter signals such as wind speed at the blade location, force direction of the blade, and vibration acceleration of the blade, generating blade load status information, and transmitting the detected blade load status information to the linkage communication CPU module to build a Bayesian model, and combine it with the mechanical model to calculate the load on the blade. By setting a preset load threshold range, when the load exceeds the threshold, load control is performed by adjusting the blade angle, motor load and wind turbine speed. This is used to adjust the stress state of the blade in real time, keep the blade operating within a safe load range, and thus avoid failures caused by blade damage or overload. Blade lightning strike monitoring system: The system uses intelligent sensors to monitor lightning signals in the environment where the generator blades are located, including the frequency, intensity, and distance of the lightning, as well as the instantaneous temperature state of the blade surface, the blade vibration frequency, and the amplitude of the parameters. It generates blade lightning strike status signals and transmits the detected blade lightning strike status information to the linkage communication CPU module. After real-time monitoring of the blade lightning strike status signals, the system uses lightning warning, installation of conductive equipment, lightning protection devices, and regular inspection and maintenance to control the blades and reduce the risk of lightning strikes, thus protecting the safety and reliability of the blades. Linkage Communication CPU Module: Through the bus interface, the subsystems of the generator insulation monitoring system, PLC operation control system, unit lubrication control system, blade load calculation control system, and blade lightning strike monitoring system transmit data to the linkage communication CPU module. It acquires data signals from the subsystems in real time, synchronizes, shares, and integrates the data, and uses statistical average and threshold judgment algorithms to superimpose and calculate abnormal information transmitted by the subsystems. It comprehensively analyzes and judges the impact of abnormal information, generates level-based abnormal signals, transmits them to the abnormal signal alarm module, and feeds back the abnormal signals to the subsystems for synchronous control, avoiding delays in triggering events and inconsistencies in data signal sharing between subsystems. Abnormal signal alarm module: Receives abnormal signals from the integrated subsystem calculated by the linkage communication CPU module and performs alarm processing, including pre-classifying abnormal levels, setting priorities and priority alarm response times based on safety risk assessment, and comprehensively considering the severity of abnormal signals, safety risks, and response time requirements to ensure that urgent and important abnormal signals can be processed and responded to in a timely manner, thus guaranteeing the safe and stable operation of the control system.

[0023] It should be noted that the generator insulation monitoring system involves installing insulation resistance sensors on the generator to measure and collect the insulation resistance values ​​of the generator windings. Dielectric loss value and filth value The data collected on the insulation status of the generator is compared and analyzed with preset thresholds, and abnormal signals are evaluated and judged. If the preset safety threshold range for generator insulation monitoring parameters is defined, then the insulation resistance value... Dielectric loss value Filth value ; When measuring the insulation resistance value of generator windings If the signal is abnormal, the insulation resistance signal of the generator winding is determined to be abnormal and transmitted to the linkage communication CPU module. When measuring the standard dielectric loss value of generator loss If the generator's dielectric loss signal is abnormal, it will be determined and transmitted to the linkage communication CPU module. When measuring the pollution level of the generator If the generator's pollution level signal is abnormal, it will be determined and transmitted to the linkage communication CPU module.

[0024] It should be noted that the PLC operation control system uses control logic algorithms to transform the generator's operation logic control by collecting data on the generator's current, voltage, output power, output frequency, temperature, and vibration parameters from the PLC. In other words, the PLC can flexibly adjust the control logic and parameters according to different operating conditions and requirements of the wind turbine to adapt to different operational needs and operating scenarios. The steps for transforming the control logic are as follows: setting the operating modes and parameters for generator start-up, speed regulation, and power control; The PLC collects data on the generator's operating current, voltage, output power, output frequency, temperature, and vibration parameters and monitors its operating status in real time. When the PLC reads the parameter data and determines whether there are any abnormal conditions such as overload or overtemperature in the generator, it further performs fault detection and load reduction or power cut-off on the generator. The PLC is pre-programmed with overcurrent protection, overvoltage protection, and underfrequency protection control logic to ensure the generator can operate safely. The PLC records and transmits the collected parameter data to the linkage communication CPU module. Through the data sharing function of the linkage communication CPU module, data interaction and coordination with the subsystem can be realized.

[0025] It should be noted that the generator lubrication control system collects data on the temperature, pressure, and flow rate of the generator lubricating oil and compares it with preset thresholds. The preset safe threshold range for generator lubrication parameters includes the lubricating oil temperature... Lubricating oil pressure Lubricating oil flow rate The system detects abnormalities in lubricating oil temperature, pressure, and flow parameters, transmits these abnormal signals to the linkage communication CPU module, and uses a threshold judgment algorithm to evaluate the parameters. If the parameters exceed the threshold range, the system transmits the information to the abnormal signal alarm module to trigger an alarm, reminding maintenance personnel to take measures such as replacing or adding lubricating oil to control the unit's lubrication.

[0026] It should be noted that a Bayesian model is constructed in the blade load calculation and control system to calculate the conditional probability of the target variable of blade force based on the observed variables of collected wind speed and direction data. This probability is then calculated using the Bayesian algorithm formula. In the formula, Indicates wind speed. Indicates wind direction. Indicates a known event In the event of occurrence, The conditional probability of occurrence; Indicates in the event In the event of occurrence, The conditional probability of occurrence; Indicates an event The prior probability of occurrence; Indicates an event The prior probability is used to calculate the posterior probability distribution of the blade force, and the blade load is calculated based on the posterior probability distribution of the blade force, combined with the mechanical model and the structural characteristics of the blade.

[0027] It should be noted that the blade lightning strike monitoring system collects parameter data on the impact of rain and lightning on the blades. Since lightning strikes can cause structural damage, dynamic imbalance, electrical system failures, energy loss, and safety hazards, the system uses a weighted average method to integrate and calculate the safety status of the blades based on the parameter signals of the lightning strike. Structural damage refers to cracks, scratches, or fractures on the surface or internal structure of the blade caused by a lightning strike, affecting the blade's strength and stability, as well as the normal operation and safety of the wind turbine. Dynamic imbalance refers to the uneven mass distribution of the blade after a lightning strike. Lightning strikes can cause dynamic imbalances, leading to rotational imbalances and increased vibrations, which reduce the overall performance of the wind turbine and shorten blade life. Electrical system failures, caused by lightning strikes, damage sensors and wiring on the blades, preventing the wind turbine's control and monitoring systems from functioning properly and affecting the operation and safety of wind power generation. Energy loss occurs when the blades are struck by lightning; on the one hand, some energy is absorbed and dissipated, resulting in energy loss and reduced efficiency; on the other hand, the high temperatures generated by lightning discharge cause thermal expansion or melting of the blade's covering material, further increasing energy loss. Safety hazards include the risk of fire, explosion, or personal injury that lightning strikes may cause.

[0028] It should be noted that the linkage communication CPU module receives abnormal signals from the subsystem and performs data synchronization, sharing, and coordination for subsystem communication. Therefore, it performs a cumulative calculation on the abnormal information transmitted from the subsystem, using a statistical average algorithm. In the formula, i represents the number of sequences in the subsystem, and X represents the proportion of each abnormal signal in the subsystem. The steps to obtain anomaly information from the statistics subsystem are as follows: Collect abnormal information: Collect abnormal information of the subsystem, including parameter signals that exceed the threshold; Count the number of anomalies in the subsystem: Based on the collected anomaly information, count and calculate the number of different types of anomalies in each system; Calculate the percentage of abnormal information: count the total number of abnormal information in all subsystems, and calculate the percentage of abnormal information in each subsystem in the total number of abnormal information. That is, by dividing the number of abnormal information in each subsystem by the total number of abnormal information, we can get the percentage of abnormal information in each subsystem. Comparison of abnormal information indicators: The proportion of abnormal information in each subsystem is compared and analyzed, and the trend, change and impact status of abnormal information are determined according to the judgment criteria of preset thresholds. Feedback and processing of abnormal information: Based on the abnormal information of each subsystem obtained from statistics, the information is fed back to the offshore wind turbine control system. The abnormal information is analyzed and processed, and the subsystems with abnormal information that cause impact and harm are subject to negative feedback control, thereby regulating parameter changes and notifying operators to take measures to eliminate faults.

[0029] It should be noted that the alarm handling method of the abnormal signal alarm module includes pre-classifying the abnormality level, setting priorities and priority alarm response times based on the safety risk assessment. The pre-classification of abnormal levels is based on the degree of damage to the wind turbine's operation and its impact on the safe operation of the control system. The abnormal signals are divided into four different levels: emergency, warning, attention, and ignore. An audible and visual alarm is used. When the emergency level is reached, the audible and visual alarm will show a continuous red light and a continuous buzzer until the maintenance personnel find the abnormal signal and take measures to resolve the abnormal state, at which point the audible and visual alarm response will end. When a warning level is detected, the audible and visual alarm will display intermittent red lights and intermittent buzzers at intervals of 5-10 minutes each time, until maintenance personnel find the abnormal signal and take measures to resolve the abnormal state, at which point the audible and visual alarm response will end. When the alert level is reached, the audible and visual alarm will display intermittent red light and intermittent buzzer. The audible and visual alarm response will end when the interval between the flashing red light and the buzzer broadcast is 5-10 times. When the neglect level is reached, the audible and visual alarm will display intermittent red light and intermittent buzzer. When the interval between the red light flashing and the buzzer broadcast occurs 1-3 times, the audible and visual alarm response will end. Safety risk assessment and priority setting: Safety risk assessment is conducted on various abnormal signals existing in the subsystem. Based on the characteristics and operating requirements of the subsystem, the potential impact of each abnormal signal on equipment, personnel and environment is determined. Based on the assessment results, the alarm priority is divided into four different levels: high, relatively high, medium and low. Audible and visual alarms are used. When a high priority occurs, the audible and visual alarm will show a continuous red light and a continuous buzzer until the operation and maintenance personnel find the abnormal signal and take measures to resolve the abnormal state, at which point the audible and visual alarm response ends. When a higher priority is detected, the audible and visual alarm will display intermittent red lights and intermittent buzzers, with an interval of 5-10 minutes per time, until the maintenance personnel find the abnormal signal and take measures to resolve the abnormal state, at which point the audible and visual alarm response will end. When the medium priority is reached, the audible and visual alarm will display intermittent red light and intermittent buzzer. When the interval between the red light flashing and the buzzer broadcast occurs 5-10 times, the audible and visual alarm response will end. When a low priority occurs, the audible and visual alarm will display intermittent red light and intermittent buzzer. When the interval between the red light flashing and the buzzer broadcast occurs 1-3 times, the audible and visual alarm response will end. Priority alarm response time: Based on the level and priority of the abnormal signal, four different response time requirements are set: emergency shutdown, immediate execution, short-term repair, and long-term maintenance. For example, for emergency or high-priority abnormal signals, the control system is required to immediately shut down and alarm, while for ignored or low-priority abnormal signals, an alarm signal is used to remind maintenance personnel to respond within a certain time.

[0030] It should be further explained that the linkage communication CPU module has a built-in linkage alarm mechanism. This linkage alarm mechanism sets the abnormal signals monitored and collected by the subsystem as fuzzy alarm signals and inputs these fuzzy alarm signals into the linkage alarm mechanism. The linkage alarm mechanism then performs different output controls according to the operating conditions of the offshore wind turbine. When an abnormal signal is generated in the subsystem, if the linkage alarm mechanism determines that it will not affect the safety of the unit, it will automatically filter out the abnormal signal. Only when the abnormal signal is calculated by the subsystem's statistical averaging algorithm and will affect the safe operation of the unit will the control for that abnormal signal be triggered.

[0031] The embodiments of the offshore wind turbine control system based on the IEC61499 architecture provided in this invention will not be described in detail here.

[0032] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0033] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0034] It should be understood that in the various embodiments of this application, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0035] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0036] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology 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. A control system for offshore wind turbines based on the IEC61499 architecture, characterized in that, Including the generator insulation monitoring system: It collects parameters such as the generator's insulation resistance value, dielectric loss value and pollution degree value through sensors, obtains information on the generator's insulation status, and transmits the detected insulation fault signal to the linkage communication CPU module; PLC operation control system: Using a programmable logic controller (PLC), the system collects signals of current, voltage, power, frequency, temperature and vibration parameters of the generator, generates generator operation status information, and transmits the detected operation fault signals to the linkage communication CPU module. Unit lubrication control system: Collects temperature, pressure and flow parameters of generator lubricating oil through intelligent sensors, generates unit lubrication status signals, and transmits signals of abnormal unit lubrication to the linkage communication CPU module; Blade load calculation and control system: Sensors are used to monitor the generator blades, collect parameter signals such as wind speed at the blade location, force direction of the blade, and vibration acceleration of the blade, generate blade load status information, transmit the detected blade load status information to the linkage communication CPU module, construct a Bayesian model, and combine it with the mechanical model to calculate the load on the blade. By setting a preset load threshold range, when the load exceeds the threshold, load control is carried out by adjusting the blade angle, motor load and wind turbine speed. Blade lightning strike monitoring system: The system uses intelligent sensors to monitor lightning signals in the environment where the generator blades are located, including the frequency, intensity, and distance of the lightning, as well as the instantaneous temperature state of the blade surface, the blade vibration frequency, and the amplitude of the parameters. It generates blade lightning strike status signals and transmits the detected blade lightning strike status information to the linkage communication CPU module. Linkage communication CPU module: It acquires data signals from the subsystem in real time through the bus interface, synchronizes, shares, and integrates the data, and uses statistical average and threshold judgment algorithms to superimpose and calculate abnormal information transmitted by the subsystem. It comprehensively analyzes and judges the impact of abnormal information, generates level-based abnormal signals, transmits them to the abnormal signal alarm module, and feeds back the abnormal signals to the subsystem for synchronous control. The linkage communication CPU module receives abnormal signals from the subsystem and performs data synchronization, sharing, and coordination for subsystem communication. It then performs a superposition calculation on the abnormal information transmitted from the subsystem, employing a statistical average algorithm. In the formula, Represents the sequence number of the subsystem. This is expressed as the proportion of each abnormal signal in the subsystem, where, The steps to obtain anomaly information from the statistics subsystem are as follows: Collect abnormal information: Collect abnormal information of the subsystem, including parameter signals that exceed the threshold; Count the number of anomalies in the subsystem: Based on the collected anomaly information, count and calculate the number of different types of anomalies in each system; Calculate the percentage of abnormal information: count the total number of abnormal information in all subsystems, and calculate the percentage of abnormal information in each subsystem in the total number of abnormal information. That is, by dividing the number of abnormal information in each subsystem by the total number of abnormal information, we can get the percentage of abnormal information in each subsystem. Comparison of abnormal information indicators: The proportion of abnormal information in each subsystem is compared and analyzed, and the trend, change and impact status of abnormal information are determined according to the judgment criteria of preset thresholds. Feedback and processing of abnormal information: Based on the abnormal information of each subsystem obtained from statistics, the information is fed back to the offshore wind turbine control system. The abnormal information is analyzed and processed, and the subsystems with abnormal information that have an impact or hazard are subject to negative feedback control to regulate parameter changes and notify the operators to take measures to eliminate the fault. Abnormal signal alarm module: Receives abnormal signals from the integrated subsystem calculated by the linkage communication CPU module and performs alarm processing, including pre-classifying abnormal levels, setting priorities and priority alarm response times based on safety risk assessment.

2. The offshore wind turbine control system based on the IEC61499 architecture according to claim 1, characterized in that, The blade lightning strike monitoring system collects parameter data on the impact of rain and lightning on the blades in the environment. Since lightning strikes can cause structural damage, dynamic imbalance, electrical system failure, and energy loss, the system integrates and calculates the parameter signals of the blade lightning strike status using a weighted average method to determine the safety status of the blades after the lightning strike.

3. The offshore wind turbine control system based on the IEC61499 architecture according to claim 1, characterized in that, The alarm processing method of the abnormal signal alarm module includes pre-classifying the abnormal level, setting the priority and priority alarm response time according to the safety risk assessment. The pre-classification of the abnormal level is based on the degree of damage to the wind turbine operation and the impact on the safe operation of the control system, and is divided into four different levels: emergency, warning, attention and ignore. Safety risk assessment and priority setting: Conduct safety risk assessments on various abnormal signals in the subsystem, and determine the potential impact of each abnormal signal on equipment, personnel and environment based on the characteristics and operating requirements of the subsystem. Then, based on the assessment results, divide the alarm priority into four different levels: high, relatively high, medium and low. Priority alarm response time: Based on the level and priority of the calculated abnormal signal, four different response time requirements are set: emergency shutdown, immediate execution, short-term maintenance, and long-term maintenance.

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