Wind power master control system based on safe and credible software and hardware platform

Abstract

The invention discloses a wind power master control system based on a safe and credible software and hardware platform, which belongs to the technical field of wind power generation and comprises a data acquisition module, a data analysis module, a monitoring result judgment module, an abnormal unit optimization control module and a data backup module. According to the invention, the data acquisition module acquires the operation monitoring parameters of the wind turbine generator in real time, and the operation monitoring parameters are processed by the data analysis module to obtain the operation monitoring evaluation value, so that the operation state of the wind turbine generator is accurately judged, and accurate monitoring and timely early warning of the wind turbine generator are realized; the problem that in the prior art, a wind power master control system is insufficient in safety performance and reliability is effectively solved, and the safe operation level and the fault handling capacity of a wind power plant are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a wind power master control system based on a safe and reliable software and hardware platform. Background Art

[0002] With the rapid development of wind power generation, the requirements for the safety, reliability and intelligence level of wind farm master control systems are increasing. The wind power master control system refers to the core system responsible for monitoring and controlling the operation of wind turbines in the wind power field.

[0003] The existing wind power master control system determines the operating mode of the wind turbine by monitoring the grid status (especially the grid frequency), and adjusts the output of the wind turbine accordingly to achieve active support for the grid or by optimizing the communication and data exchange between the internal controllers of the wind turbine.

[0004] For example, the invention patent announcement with announcement number: CN111594384B announces a control method and main control system for a voltage source wind turbine, including: determining the operating mode of the wind turbine based on whether the power grid is in a large frequency disturbance condition; when the wind turbine operates in the current source operating mode, based on the generator torque command output by the variable speed and pitch control loop and the generator torque command required for the support frequency output by the power grid frequency active support control loop, determining the generator torque output command sent to the converter and the operating mode of the wind turbine; when the wind turbine operates in the voltage source operating mode, based on the generator torque command output by the variable speed and pitch control loop and the generator torque required for virtual synchronization, determining the generator torque output command sent to the converter and the operating mode of the wind turbine.

[0005] For example, the control system of the integrated linkage between the central control of a wind farm and the main control of a wind turbine unit, as announced in the invention patent publication number CN114233572B, includes: a tower base controller, a cabin controller, a yaw inverter, a pitch inverter, a power converter, an anemometer, a control panel, an internal optical fiber communication bus and a data acquisition server; the tower base controller and the cabin controller realize integrated control of the tower base controller and the cabin controller by means of an internal optical fiber communication bus, and at the same time, the cabin controller acts as a coupler to realize data interaction of multiple interfaces and protocols of the yaw inverter, pitch inverter, power converter and anemometer.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] The management and data storage methods of wind power master control systems in the existing technology are generally single, and fail to effectively classify and distinguish normal data from abnormal data, ignore the differences in data properties, and find it difficult to efficiently identify and handle potential risks and abnormal conditions. As a result, the existing wind power master control systems have problems with insufficient safety performance and reliability. Summary of the invention

[0008] The embodiments of the present application solve the problems of insufficient safety performance and reliability of wind power master control systems in the prior art by providing a wind power master control system based on a secure and reliable software and hardware platform, and achieve accurate monitoring and timely warning of wind turbines.

[0009] The embodiment of the present application provides a wind power master control system based on a secure and trusted software and hardware platform, including: a data acquisition module, which is used to collect the operation monitoring parameters of the wind turbine in real time through the edge intelligent master control sensor hub connected to the secure and trusted software and hardware platform; a data analysis module, which is used to analyze the operation monitoring parameters of the wind turbine to obtain the deviation state evaluation index of the wind turbine, thereby processing to obtain the operation monitoring category, and the operation monitoring category is: normal wind turbine, abnormal wind turbine and wind turbine failure; a monitoring result judgment module, which is used to save the operation monitoring parameters of the wind turbine to the master control cloud platform when the operation monitoring category is that the wind turbine is normal, and When the operation monitoring category is that the wind turbine is abnormal, the wind turbine is recorded as an abnormal unit and optimized and controlled. When the operation monitoring category is that the wind turbine fails, an early warning is issued and the wind turbine is controlled to enter a safety protection mode. The abnormal unit optimization control module is used to track and monitor the abnormal unit, analyze and obtain the optimization control execution parameters of the abnormal unit, and optimize and control the abnormal unit through the main control cloud platform. The data backup module is used to count the operation monitoring parameters of the abnormal unit and obtain the parameters of the currently available backup storage locations, thereby screening and obtaining the adapted backup storage location, and transmitting the operation monitoring parameters of the abnormal unit to the adapted backup storage location for backup storage.

[0010] Furthermore, the edge intelligent main control sensor hub connected through the secure and trusted hardware and software platform collects the operation monitoring parameters of the wind turbine in real time; the operation monitoring parameters specifically include: the blade deviation angle of the wind turbine, output power, main shaft speed, main shaft inclination, generator temperature, yaw angle, power factor and oil level.

[0011] Furthermore, the deviation state evaluation index of the wind turbine group is obtained by analyzing the operation monitoring parameters of the wind turbine group. The specific method is: obtaining an operation monitoring target set of the wind turbine group, the operation monitoring target set of the wind turbine group including: a blade deviation angle target value, an output power target value, a main shaft speed target value, a main shaft inclination target value, a generator temperature target value, a yaw angle target value, a power factor target value and an oil level height target value; analyzing the operation monitoring target set of the wind turbine group with the operation monitoring parameters of the wind turbine group to obtain the deviation state evaluation index of the wind turbine group; the deviation state evaluation index of the wind turbine group is used to characterize the degree of abnormal operation of the wind turbine group.

[0012] Furthermore, the deviation state evaluation index of the wind turbine is obtained, and the specific method is as follows:

[0013]

[0014] Where R represents the deviation state evaluation index of the wind turbine, e represents the natural constant, R1 represents the structural control evaluation value of the wind turbine, R2 represents the performance control evaluation value of the wind turbine, μ1 represents the influence weight of the structural control evaluation value, and μ2 represents the influence weight of the performance control evaluation value.

[0015] Furthermore, the deviation state evaluation index of the wind turbine group is obtained by analyzing the operation monitoring parameters of the wind turbine group, and the operation monitoring category is obtained by processing. The specific process is: obtain the first deviation state evaluation threshold of the wind turbine group and the second deviation state evaluation threshold of the wind turbine group preset in the database; based on the deviation state evaluation index of the wind turbine group, and compare with the first deviation state evaluation threshold of the wind turbine group and the second deviation state evaluation threshold of the wind turbine group, if the deviation state evaluation index of the wind turbine group is above the first deviation state evaluation threshold of the wind turbine group, then the operation monitoring category is wind turbine failure; if the deviation state evaluation index of the wind turbine group is less than the first deviation state evaluation threshold of the wind turbine group and is above the second deviation state evaluation threshold of the wind turbine group, then the operation monitoring category is wind turbine abnormality; if the deviation state evaluation index of the wind turbine group is less than the second deviation state evaluation threshold of the wind turbine group, then the operation monitoring category is normal wind turbine.

[0016] Furthermore, the tracking and monitoring of abnormal units specifically includes: obtaining real-time external environmental parameters through an edge intelligent main control sensor hub connected by a secure and trusted hardware and software platform; obtaining an external environmental target set preset in a database, the external environmental target set including: external environmental wind speed target value, external atmospheric pressure target value, external environmental temperature target value and external environmental humidity target value; obtaining an environmental matching degree by comparing the real-time external environmental parameters with the external environmental target set; screening and obtaining a deviation state evaluation index of the abnormal unit based on the deviation state evaluation index of the wind turbine unit; obtaining an environmental target matching degree preset in the database, and fusing and analyzing the environmental matching degree, environmental target matching degree, the deviation state evaluation index of the abnormal unit and the first threshold of the deviation state evaluation of the wind turbine unit to obtain a tracking control reference index of the abnormal unit; the real-time external environmental parameters include: real-time external environmental wind speed, real-time external atmospheric pressure, real-time external environmental temperature and real-time external environmental humidity; the environmental matching degree is used to characterize the matching degree of the current operating environment of the abnormal unit; the tracking control reference index of the abnormal unit is used to characterize the execution complexity of the optimization control of the abnormal unit.

[0017] Furthermore, the analysis obtains the optimized control execution parameters of the abnormal unit, specifically including: obtaining each tracking control reference index interval preset in the database and the operating adjustment parameters corresponding to each tracking control reference index interval, matching the tracking control reference index of the abnormal unit with each tracking control reference index interval; if the tracking control reference index of the abnormal unit is within a certain tracking control reference index interval, then obtaining the operating adjustment parameters corresponding to the tracking control reference index interval as the optimized control execution parameters of the abnormal unit.

[0018] Furthermore, the currently available parameters of each backup storage location specifically include: remaining space capacity of each backup storage location, remaining space capacity ratio, disk read and write speed, disk average trouble-free time, and disk average fault repair time.

[0019] Furthermore, the screening to obtain the adapted backup storage location and transmitting the operation monitoring parameters of the abnormal unit to the adapted backup storage location for backup storage specifically includes: processing to obtain the backup storage effect evaluation value of each backup storage location according to the parameters of each backup storage location, thereby screening to obtain the best backup storage location; the backup storage effect evaluation value of each backup storage location is used to characterize each backup storage effect. Based on the backup storage effect evaluation value of each backup storage location, the backup storage location corresponding to the maximum backup storage effect evaluation value is obtained as the adapted backup storage location, and the operation monitoring parameters of the abnormal unit are backed up and stored in the adapted backup storage location.

[0020] Furthermore, it also includes a data security and encryption module, which is used to use an encryption algorithm to transmit the operation monitoring parameters of the wind turbine set stored in the main control cloud platform and the operation monitoring parameters of the abnormal unit in the data backup module, and save them in the main control cloud platform and the data backup module respectively, and set access permission management.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0022] 1. The wind power main control system based on a safe and reliable software and hardware platform provided by the present invention collects the operation monitoring parameters of the wind turbine in real time through the data acquisition module, and obtains the operation monitoring evaluation value through processing by the data analysis module, so as to accurately judge the operation status of the wind turbine, and then realizes the precise monitoring and timely early warning of the wind turbine, effectively solves the problem of insufficient safety performance and reliability of the wind power main control system in the prior art, and improves the safe operation level and fault response capability of the wind farm.

[0023] 2. The present invention tracks and monitors abnormal units through the abnormal unit optimization control module, and analyzes and obtains abnormal unit optimization control execution parameters based on real-time external environmental parameters and a preset external environmental target set, thereby realizing intelligent optimization control of abnormal units and improving the power generation efficiency and energy utilization rate of wind farms.

[0024] 3. The present invention sets up a data security and encryption module to encrypt and transmit the operation monitoring parameters of the wind turbine group stored in the main control cloud platform and the data backup module, and sets up access permission management, thereby ensuring the security and confidentiality of the data, thereby preventing the risk of data leakage and illegal access, and further providing reliable protection for the data security of the wind farm. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A schematic diagram of the structure of a wind power master control system based on a secure and reliable software and hardware platform provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] The embodiment of the present application solves the problem of insufficient safety performance and reliability of wind power master control systems in the prior art by providing a wind power master control system based on a secure and reliable software and hardware platform. The data acquisition module is used to collect the operation monitoring parameters of the wind turbine in real time through the edge intelligent master control sensor hub connected to the secure and reliable software and hardware platform; the data analysis module is used to analyze the deviation state evaluation index of the wind turbine according to the operation monitoring parameters of the wind turbine, and obtain the operation monitoring category thereby, and the operation monitoring category is: normal wind turbine, abnormal wind turbine and faulty wind turbine; the monitoring result judgment module is used to save the operation monitoring parameters of the wind turbine to the master control cloud platform when the operation monitoring category is normal wind turbine. When the operation monitoring category is that the wind turbine is abnormal, the wind turbine is recorded as an abnormal unit and optimized and controlled. When the operation monitoring category is that the wind turbine fails, an early warning is issued and the wind turbine is controlled to enter the safety protection mode; the abnormal unit optimization control module is used to track and monitor the abnormal unit, analyze and obtain the optimization control execution parameters of the abnormal unit, and optimize and control the abnormal unit through the main control cloud platform; the data backup module is used to count the operation monitoring parameters of the abnormal unit and obtain the parameters of the currently available backup storage locations, thereby screening and obtaining the adapted backup storage location, and transmitting the operation monitoring parameters of the abnormal unit to the adapted backup storage location for backup storage, thereby realizing accurate monitoring and timely early warning of the wind turbine.

[0027] The technical solution in the embodiment of the present application is to solve the problem that the above-mentioned wind power master control system has insufficient safety performance and reliability. The overall idea is as follows: through the data acquisition module, it is used to collect the operation monitoring parameters of the wind turbine in real time through the edge intelligent master control sensor hub connected to the secure and trusted hardware and software platform; the data analysis module is used to analyze the deviation state evaluation index of the wind turbine according to the operation monitoring parameters of the wind turbine, and thereby obtain the operation monitoring category, and the operation monitoring category is: normal wind turbine, abnormal wind turbine and faulty wind turbine; the monitoring result judgment module is used to save the operation monitoring parameters of the wind turbine to the master control cloud platform when the operation monitoring category is normal wind turbine, and in the operation monitoring When the measurement category is that the wind turbine is abnormal, the wind turbine is recorded as an abnormal unit and optimized and controlled. When the operation monitoring category is a wind turbine failure, an early warning is issued and the wind turbine is controlled to enter a safety protection mode; the abnormal unit optimization control module is used to track and monitor the abnormal unit, analyze and obtain the abnormal unit optimization control execution parameters, and optimize the abnormal unit through the main control cloud platform; the data backup module is used to count the operation monitoring parameters of the abnormal unit, and obtain the parameters of each currently available backup storage location, thereby screening and obtaining the adaptive backup storage location, and transmitting the operation monitoring parameters of the abnormal unit to the adaptive backup storage location for backup storage, so as to achieve accurate monitoring and timely early warning of the wind turbine.

[0028] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0029] like Figure 1 As shown, it is a structural schematic diagram of a wind power main control system based on a secure and trusted software and hardware platform provided in an embodiment of the present application. The wind power main control system based on a secure and trusted software and hardware platform provided in an embodiment of the present application includes: a data acquisition module, which is used to collect the operation monitoring parameters of the wind turbine in real time through an edge intelligent main control sensor hub connected to the secure and trusted software and hardware platform; a data analysis module, which is used to analyze the deviation state evaluation index of the wind turbine according to the operation monitoring parameters of the wind turbine, and thereby obtain the operation monitoring category, and the operation monitoring category is: normal wind turbine, abnormal wind turbine and wind turbine failure; a monitoring result judgment module, which is used to judge the operation of the wind turbine when the operation monitoring category is normal. The monitoring parameters are saved to the main control cloud platform. When the operation monitoring category is that the wind turbine is abnormal, the wind turbine is recorded as an abnormal unit and optimized control is performed. When the operation monitoring category is a wind turbine failure, an early warning is issued and the wind turbine is controlled to enter the safety protection mode; the abnormal unit optimization control module is used to track and monitor the abnormal unit, analyze the abnormal unit optimization control execution parameters, and optimize the abnormal unit through the main control cloud platform; the data backup module is used to count the operation monitoring parameters of the abnormal unit and obtain the parameters of the currently available backup storage locations, thereby screening and obtaining the adapted backup storage location, and transmitting the operation monitoring parameters of the abnormal unit to the adapted backup storage location for backup storage.

[0030] In this embodiment, through a secure and reliable software and hardware platform, it is closely connected to the edge intelligent main control sensor hub, and various operation monitoring parameters of the wind turbine can be collected in real time and accurately. The collected operation monitoring parameters are deeply analyzed to evaluate the operating status of the unit, and the unit is divided into three categories: normal, abnormal or faulty. This is conducive to timely discovery of potential problems and provides strong support for subsequent monitoring and control. Through the monitoring result judgment module, through intelligent monitoring and judgment, it can ensure that the unit operates in a safe and stable state, effectively reducing the probability of accidents. Optimization control through the abnormal unit optimization control module can maximize the operating efficiency and reliability of the unit and reduce maintenance costs. The data backup module provides a strong guarantee for data security, and can ensure the integrity and availability of data even in extreme cases.

[0031] It should be noted that the safety protection mode is an important emergency response mechanism. When a serious fault occurs in a wind turbine, a series of preset protection measures are automatically taken to prevent the fault from further deteriorating, ensure personnel safety, reduce equipment damage, and maintain the overall stable operation of the wind farm. These measures include: stopping the operation of all rotating parts of the wind turbine (such as blades, generators, etc.), automatically isolating the connection between the faulty unit and the power grid, preventing the fault current from impacting the power grid, and protecting the faulty unit from the impact of power grid anomalies, providing a safe electrical environment for subsequent maintenance work, and locking the remote and local operation interface of the wind turbine, allowing only maintenance personnel with specific permissions to intervene through specific security channels, and recording in detail the changes in various parameters before and after the fault occurs, including fault time, fault code, and related monitoring parameters. Automatically send fault alarm information to the preset maintenance team or management personnel, including fault type and location.

[0032] Furthermore, the edge intelligent main control sensor hub connected by a secure and trusted hardware and software platform collects the operation monitoring parameters of the wind turbine in real time; the operation monitoring parameters specifically include: the wind turbine blade deviation angle, output power, main shaft speed, main shaft inclination, generator temperature, yaw angle, power factor and oil level.

[0033] In this embodiment, the edge intelligent main control sensor hub connected by a secure and trusted hardware and software platform collects the operation monitoring parameters of the wind turbine in real time. The edge intelligent main control sensor hub includes connections: angle sensors, power meters, speed sensors, tilt sensors, acceleration sensors, gyroscopes, temperature sensors, yaw motors, oil level sensors, and power quality analyzers, and monitors the blade deviation angle in real time through the angle sensors installed on the blades of the wind turbine. The output power is obtained through a power measuring instrument (such as a power meter or a power sensor), the main shaft speed is obtained through a speed sensor, the main shaft inclination is obtained through a tilt sensor (such as an acceleration sensor or a gyroscope), the generator temperature is obtained through a temperature sensor, the yaw system of the wind turbine (such as a yaw motor) obtains the yaw angle, the power factor is obtained through power monitoring equipment (such as a power quality analyzer), and the oil level is obtained through an oil level sensor.

[0034] Furthermore, the deviation state evaluation index of the wind turbine is obtained by analyzing the operation monitoring parameters of the wind turbine set, and the specific method is: obtaining the operation monitoring target set of the wind turbine set, the operation monitoring target set of the wind turbine set including: blade deviation angle target value, output power target value, main shaft speed target value, main shaft inclination target value, generator temperature target value, yaw angle target value, power factor target value and oil level height target value; analyzing the operation monitoring target set of the wind turbine set with the operation monitoring parameters of the wind turbine set to obtain the deviation state evaluation index of the wind turbine set; the deviation state evaluation index of the wind turbine set is used to characterize the degree of abnormal operation of the wind turbine set.

[0035] In this embodiment, the deviation state evaluation index of the wind turbine is obtained by obtaining the operation monitoring parameters of the wind turbine and analyzing them, taking into account the mutual influence between these parameters, for example: the blade deviation angle directly affects the ability of the wind wheel to capture wind energy. If the deviation angle is too large, the blades may block each other, resulting in energy loss; if the deviation angle is too small, the wind energy may not be fully captured. The output power is proportional to the main shaft speed and is regulated by the blade deviation angle. At the same time, the increase in output power will cause the temperature of the generator to rise, and equipment failure will also cause the temperature to rise, resulting in abnormal output power. The main shaft speed will lead to an increase in output power, but it may also cause the temperature of the generator to rise and mechanical wear to increase. The main shaft inclination will affect the stability and safety of the wind turbine. Excessive inclination will cause vibration and imbalance of the unit, and excessive generator temperature may cause equipment failure and performance degradation. The yaw angle determines the degree to which the wind turbine is facing the wind head-on, affecting the efficiency of wind energy capture. The optimized yaw angle can increase the output power and main shaft speed. The change in output power will cause a change in power factor. Too low an oil level will aggravate the increase in generator temperature and the wear of the main shaft. Too high an oil level will limit the heat dissipation effect of the oil and cause the equipment to overheat.

[0036] Furthermore, the deviation state evaluation index of the wind turbine is obtained, and the specific method is as follows:

[0037]

[0038] Where R represents the deviation state evaluation index of the wind turbine, e represents the natural constant, R1 represents the structural control evaluation value of the wind turbine, R2 represents the performance control evaluation value of the wind turbine, μ1 represents the influence weight of the structural control evaluation value, and μ2 represents the influence weight of the performance control evaluation value.

[0039] In this embodiment, the structural control evaluation value of the wind turbine generator set is obtained by:

[0040]

[0041] Wherein, R1 represents the structural control evaluation value of the wind turbine, θ1 represents the blade deviation angle of the wind turbine, Δθ1 represents the target value of the blade deviation angle, θ2 represents the main shaft inclination of the wind turbine, Δθ2 represents the target value of the main shaft inclination, θ3 represents the yaw angle of the wind turbine, Δθ3 represents the target value of the yaw angle, H1 represents the oil level of the wind turbine, and ΔH1 represents the target value of the oil level.

[0042] It should be noted that the blade deviation angle of a wind turbine refers to the angular deviation between the blade and the axis of rotation. If the blade deviation angle is too large, the blades may block each other, resulting in energy loss. Conversely, if the angle is too small, the wind rotor may not be able to fully capture wind energy. The yaw angle of a wind turbine refers to the angle between the axis of rotation of the wind turbine (or the plane of the wind rotor) and the wind direction. When the yaw angle is too large, the wind rotor cannot fully capture wind energy, resulting in reduced power generation efficiency. A yaw angle that is too large will also increase the torque and stress on the wind rotor, affecting the operating stability and life of the wind rotor.

[0043] The performance control evaluation value of the motor group is obtained by:

[0044]

[0045] In the formula, R2 represents the performance control evaluation value of the wind turbine, e represents the natural constant, and P r Indicates the output power handling value, V r Indicates the spindle speed processing value, T r Indicates the generator temperature processing value, W r Indicates the power factor processing value.

[0046] It should be noted that the power factor processing value refers to the ratio of active power to apparent power in the AC circuit, and its value range is from 0 to 1. The generator temperature is not negative during operation. Where P r represents the output power processing value, P1 represents the output power of the wind turbine, ΔP1 represents the output power target value, Where V r The spindle speed processing value, V1 represents the spindle speed of the wind turbine, ΔV1 represents the spindle speed target value, Where, T r represents the generator temperature processing value, T1 represents the generator temperature of the wind turbine, ΔT1 represents the generator temperature target value, Where W r represents the power factor processing value, W1 represents the power factor of the wind turbine, and ΔW1 represents the power factor target value.

[0047] It should be noted that the structural control evaluation value influence weight represents the numerical value of the influence degree of the structural control evaluation value on the deviation state evaluation index of the wind turbine generator set. When used, the influence weight corresponding to the structural control evaluation value can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the structural control evaluation value and the structural control evaluation value influence weight form a mapping set, and the real-time structural control evaluation value is input into the mapping set to obtain the influence weight corresponding to the structural control evaluation value, and the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The performance control evaluation value influence weight represents the numerical value of the influence degree of the performance control evaluation value on the deviation state evaluation index of the wind turbine generator set. When used, the influence weight corresponding to the performance control evaluation value can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the performance control evaluation value and the performance control evaluation value influence weight form a mapping set, and the real-time performance control evaluation value is input into the mapping set to obtain the influence weight corresponding to the performance control evaluation value, and the mapping relationship can be a one-to-one correspondence or a many-to-one relationship.

[0048] Furthermore, the deviation state evaluation index of the wind turbine group is analyzed according to the operation monitoring parameters of the wind turbine group, and the operation monitoring category is obtained by processing. The specific process is: obtain the first deviation state evaluation threshold of the wind turbine group and the second deviation state evaluation threshold of the wind turbine group preset in the database; based on the deviation state evaluation index of the wind turbine group, and compare with the first deviation state evaluation threshold of the wind turbine group and the second deviation state evaluation threshold of the wind turbine group, if the deviation state evaluation index of the wind turbine group is above the first deviation state evaluation threshold of the wind turbine group, then the operation monitoring category is wind turbine failure; if the deviation state evaluation index of the wind turbine group is less than the first deviation state evaluation threshold of the wind turbine group and is above the second deviation state evaluation threshold of the wind turbine group, then the operation monitoring category is wind turbine abnormality; if the deviation state evaluation index of the wind turbine group is less than the second deviation state evaluation threshold of the wind turbine group, then the operation monitoring category is normal wind turbine.

[0049] Furthermore, the abnormal units are tracked and monitored, specifically including: obtaining real-time external environmental parameters through an edge intelligent main control sensor hub connected by a secure and trusted hardware and software platform; obtaining an external environmental target set preset in a database, the external environmental target set including: external environmental wind speed target value, external atmospheric pressure target value, external environmental temperature target value and external environmental humidity target value; obtaining an environmental matching degree by comparing the real-time external environmental parameters with the external environmental target set; based on the deviation state evaluation index of the wind turbine unit, the deviation state evaluation index of the abnormal unit is screened and obtained; obtaining an environmental target matching degree preset in the database, and fusing and analyzing the environmental matching degree, environmental target matching degree, the deviation state evaluation index of the abnormal unit and the first threshold of the deviation state evaluation of the wind turbine unit to obtain a tracking control reference index for the abnormal unit; the real-time external environmental parameters include: real-time external environmental wind speed, real-time external atmospheric pressure, real-time external environmental temperature and real-time external environmental humidity; the environmental matching degree is used to characterize the matching degree of the current operating environment of the abnormal unit; the tracking control reference index of the abnormal unit is used to characterize the execution complexity of the optimization control of the abnormal unit.

[0050] In this embodiment, the environment matching degree is obtained by:

[0051]

[0052] In the formula, E represents the environmental matching degree, e represents the natural constant, S v Indicates the real-time external environment wind speed, ΔS v Indicates the target value of ambient wind speed, W f Indicates the real-time external atmospheric pressure, ΔW f Represents the target value of external atmospheric pressure, W v Indicates the real-time external ambient temperature, ΔW v Indicates the external ambient temperature target value, H v Indicates the real-time external environment humidity, ΔH v represents the target value of external environment humidity, β1 represents the real-time external environment wind speed influence weight, β2 represents the real-time external environment temperature influence weight, β3 represents the real-time external atmospheric pressure influence weight, and β4 represents the real-time external environment humidity influence weight.

[0053] It should be noted that the real-time external environment wind speed can be obtained by real-time monitoring of the high-precision wind speed sensor of the wind farm, the real-time external atmospheric pressure can be obtained by real-time monitoring of the meteorological tower through the air pressure sensor, the real-time external environment temperature can be obtained by real-time detection of the temperature at the location of the meteorological tower by the temperature sensor, and the real-time external environment humidity can be obtained by real-time detection of the humidity at the location of the meteorological tower by the humidity sensor.

[0054] The environmental matching degree is obtained by analyzing the real-time external environmental wind speed, real-time external atmospheric pressure, real-time external environmental temperature and real-time external environmental humidity. The mutual influence between these parameters is taken into account. For example, changes in wind speed may affect the distribution of atmospheric pressure. In strong wind weather, the increase in wind speed will lead to a decrease in local atmospheric pressure. At the same time, changes in atmospheric pressure will also affect the size and direction of wind speed. When the wind speed is high, air flow will accelerate the loss of heat, thereby reducing the ambient temperature. On the contrary, when the wind speed is low, the air flow is slow, the heat is not easy to dissipate, and the ambient temperature will be relatively high. When the wind speed is high, air flow will accelerate the diffusion and evaporation of water vapor, thereby reducing the ambient humidity. On the contrary, when the wind speed is low, the air flow is slow, the water vapor is not easy to diffuse, and the ambient humidity will be relatively high. As the temperature rises, the movement of gas molecules in the atmosphere intensifies, resulting in a decrease in atmospheric pressure. Changes in atmospheric pressure will affect the content and distribution of water vapor in the air; on the other hand, changes in ambient humidity may also have an impact on atmospheric pressure. As the temperature rises, the water vapor content in the air increases, causing the ambient humidity to rise. When the temperature reaches a certain level, the water vapor in the air reaches saturation and begins to condense into water droplets or dew, thereby reducing the ambient humidity. In addition, changes in ambient humidity will also affect the perception and distribution of ambient temperature.

[0055] The real-time external environment wind speed influence weight represents the numerical value of the influence degree of the real-time external environment wind speed on the environmental matching degree. When used, the influence weight corresponding to the real-time external environment wind speed can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the real-time external environment wind speed and the real-time external environment wind speed influence weight form a mapping set, and the real-time external environment wind speed is input into the mapping set to obtain the influence weight corresponding to the real-time external environment wind speed, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The real-time external environment temperature influence weight represents the numerical value of the influence degree of the real-time external environment temperature on the environmental matching degree. When used, the influence weight corresponding to the real-time external environment temperature can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the real-time external environment temperature and the real-time external environment temperature influence weight form a mapping set, and the real-time external environment temperature is input into the mapping set to obtain the influence weight corresponding to the real-time external environment temperature, wherein the mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The real-time external atmospheric pressure influence weight represents the numerical value of the influence degree of the real-time external atmospheric pressure on the environmental matching degree. When used, the influence weight corresponding to the real-time external atmospheric pressure can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the real-time external atmospheric pressure and the real-time external atmospheric pressure influence weight form a mapping set, and the real-time external atmospheric pressure is input into the mapping set to obtain the influence weight corresponding to the real-time external atmospheric pressure. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The real-time external environment humidity influence weight represents the numerical value of the influence degree of the real-time external environment humidity on the environmental matching degree. When used, the influence weight corresponding to the real-time external environment humidity can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the real-time external environment humidity and the real-time external environment humidity influence weight form a mapping set, and the real-time external environment humidity is input into the mapping set to obtain the influence weight corresponding to the real-time external environment humidity. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship.

[0056] The tracking control reference index of the abnormal unit is obtained by:

[0057]

[0058] In the formula, L represents the reference index of tracking control of abnormal units, E represents the environmental matching degree, ΔE represents the environmental target matching degree, R represents the deviation state evaluation index of wind turbines, and Y r Indicates the first threshold for evaluating the deviation state of the wind turbine.

[0059] Furthermore, the optimization control execution parameters of the abnormal unit are obtained by analysis, specifically including: obtaining each tracking control reference index interval preset in the database and the operating adjustment parameters corresponding to each tracking control reference index interval, matching the tracking control reference index of the abnormal unit with each tracking control reference index interval; if the tracking control reference index of the abnormal unit is within a certain tracking control reference index interval, then obtaining the operating adjustment parameters corresponding to the tracking control reference index interval as the optimization control execution parameters of the abnormal unit.

[0060] In this embodiment, it should be noted that the abnormal unit optimization control execution parameters include: rotor speed adjustment value, generator speed adjustment value, pitch angle adjustment value, generator temperature adjustment value and yaw angle adjustment value. Obtain each tracking control reference index interval preset in the database and its corresponding operation adjustment parameter, and then accurately match the tracking control reference index of the abnormal unit with each tracking control reference index interval to determine the most suitable operation adjustment parameter for the current abnormal condition as the optimization control execution parameter, which can greatly save resources. In the large-scale operation of a wind farm, if all units are tested indiscriminately, it will not only consume a lot of time and manpower and material resources, but also increase equipment wear and energy consumption due to frequent operation. By accurately implementing policies only for units with problems, unnecessary waste of resources is avoided. Once the abnormal unit is identified, it can quickly match the corresponding optimization control execution parameters and immediately implement adjustments, so as to restore the normal operation of the unit in the shortest time, which not only reduces the power generation loss caused by fault shutdown, but also improves the overall operation efficiency and reliability of the wind farm.

[0061] Furthermore, the currently available parameters of each backup storage location specifically include: the remaining space capacity of each backup storage location, the remaining space capacity ratio, the disk read and write speed, the disk average trouble-free time, and the disk average fault repair time.

[0062] In this embodiment, the remaining space capacity can be obtained by using a management tool or a command line tool to obtain the remaining space capacity of the storage device. The remaining space capacity ratio can be obtained by calculating the ratio of the remaining space capacity to the total capacity, or the above-mentioned file system management tool or command line tool can be used to directly view the ratio. The disk read and write speed can be measured using disk performance testing software (such as CrystalDiskMark hard disk detection tool, HD Tune hard disk detection tool, etc.). The average trouble-free time of the disk can be obtained by searching the historical actual operation records, and the average fault repair time of the disk can be obtained by searching the historical actual operation records.

[0063] It should be noted that the backup storage effect evaluation value of each backup storage location is obtained by analyzing the parameters of each currently available backup storage location (remaining space capacity of each backup storage location, remaining space capacity ratio, disk read and write speed, disk average time between failures, and disk average time to repair failures) in consideration of the mutual influence between these parameters. For example, when the remaining space capacity is small, the disk read and write speed will be affected. Maintaining a small remaining space capacity for a long time will have a negative impact on the life of the disk, because the disk needs more write operations to manage the limited space, which increases the wear and failure risk of the disk. Faster read and write speeds can shorten data access time and improve system response speed and throughput. Longer disk average time between failures means that the disk is less likely to fail, thereby improving storage reliability. Shorter disk average time to repair failures can reduce failure downtime and improve availability.

[0064] Furthermore, screening is performed to obtain an adaptive backup storage location, and the operation monitoring parameters of the abnormal unit are transmitted to the adaptive backup storage location for backup storage, specifically including: according to the parameters of each backup storage location, the backup storage effect evaluation value of each backup storage location is processed, and the optimal backup storage location is obtained by screening; the backup storage effect evaluation value of each backup storage location is used to characterize each backup storage effect. Based on the backup storage effect evaluation value of each backup storage location, the backup storage location corresponding to the maximum backup storage effect evaluation value is obtained as the adaptive backup storage location, and the operation monitoring parameters of the abnormal unit are backed up and stored in the adaptive backup storage location.

[0065] In this embodiment, the backup storage effect evaluation value of each backup storage location is obtained by:

[0066]

[0067] In the formula, Z represents the backup storage effect evaluation value of each backup storage location, C i represents the remaining space capacity of the i-th backup storage location, i represents the number of the backup storage location, i=1,2,...,I, I represents the total number of backup storage locations, Indicates the average remaining space capacity of the backup storage location, B i Indicates the remaining space capacity ratio of the i-th backup storage location, Indicates the average remaining space capacity ratio of the backup storage location, V i represents the disk read and write speed of the i-th backup storage location, Indicates the average disk read and write speed of the backup storage location, T i represents the mean time between failures of the disks in the i-th backup storage location, Indicates the average disk MTBF of the backup storage location. Indicates the average failure repair time of the disk in the backup storage location, Q i represents the average disk failure repair time of the i-th backup storage location, γ1 represents the impact weight of the average remaining space capacity, γ2 represents the impact weight of the average remaining space capacity ratio, γ3 represents the impact weight of the average disk read and write speed, γ4 represents the impact weight of the average disk failure-free time, and γ5 represents the impact weight of the average disk failure repair time.

[0068]

[0069] It should be noted that the average remaining space capacity impact weight represents the numerical value of the impact degree of the average remaining space capacity on the backup storage effect evaluation value of each backup storage location. When used, the impact weight corresponding to the average remaining space capacity can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the average remaining space capacity and the average remaining space capacity impact weight form a mapping set, and the real-time average remaining space capacity is input into the mapping set to obtain the impact weight corresponding to the average remaining space capacity. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The average remaining space capacity ratio impact weight represents the numerical value of the impact degree of the average remaining space capacity ratio on the backup storage effect evaluation value of each backup storage location. When used, the impact weight corresponding to the average remaining space capacity ratio can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the average remaining space capacity ratio and the average remaining space capacity ratio impact weight form a mapping set, and the real-time average remaining space capacity ratio is input into the mapping set to obtain the impact weight corresponding to the average remaining space capacity ratio. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The average disk read / write speed impact weight represents the numerical value of the impact degree of the average disk read / write speed on the backup storage effect evaluation value of each backup storage location. When used, the impact weight corresponding to the average disk read / write speed can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the average disk read / write speed and the average disk read / write speed impact weight form a mapping set. The real-time average disk read / write speed is input into the mapping set to obtain the impact weight corresponding to the average disk read / write speed. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The average disk fault repair time impact weight represents the numerical value of the impact degree of the average disk fault repair time on the backup storage effect evaluation value of each backup storage location. When used, the impact weight corresponding to the average disk fault repair time can be directly obtained from the database. The corresponding relationship can be a pre-set mapping relationship. For example, the average disk fault repair time and the average disk fault repair time impact weight form a mapping set. The real-time average disk fault repair time is input into the mapping set to obtain the impact weight corresponding to the average disk fault repair time. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship. The disk mean time between failures impact weight represents the numerical value of the impact degree of the disk mean time between failures impact weight on the backup storage effect evaluation value of each backup storage location. When used, the impact weight corresponding to the disk mean time between failures impact weight can be directly obtained from the database, and the corresponding relationship can be a pre-set mapping relationship. For example, the disk mean time between failures impact weight and the disk mean time between failures impact weight form a mapping set, and the real-time disk mean time between failures impact weight is input into the mapping set to obtain the impact weight corresponding to the disk mean time between failures impact weight. The mapping relationship can be a one-to-one correspondence or a many-to-one relationship.

[0070] Furthermore, it also includes a data security and encryption module, which is used to use an encryption algorithm to transmit the operation monitoring parameters of the wind turbine set stored in the main control cloud platform and the operation monitoring parameters of the abnormal unit in the data backup module, and save them in the main control cloud platform and the data backup module respectively, and set access permission management.

[0071] In this embodiment, the operation monitoring parameters of the wind turbine generator set stored in the main control cloud platform and the data backup module are stored in the initial cache area of ​​the adapted backup storage location in plain text, and are recorded as temporary data; the temporary data is encrypted using a symmetric encryption algorithm to generate ciphertext data and a symmetric encryption key; an asymmetric encryption algorithm is used in the wind power main control system to generate an asymmetric key pair, the asymmetric key pair including a public key and a private key; the public key pair is used to encrypt to obtain encrypted key data, and the encrypted key data is transmitted to the data backup module. When the data backup module receives the encrypted key data, the encrypted key data is encrypted using the private key. Decryption is performed to obtain a symmetric encryption key, and the symmetric encryption key is stored in an encrypted form in the backup module; the encrypted ciphertext data is stored in the main control cloud platform and the data backup module respectively, and an access rights management mechanism is set up to perform different degrees of access control on the operation monitoring parameters of the wind turbine according to the user's authority level. When the user requests to access the encrypted data, the wind power main control system verifies the user's access rights. If the access rights verification is passed, the stored symmetric encryption key is called to decrypt the ciphertext data and the decrypted data is displayed to the user. If the access rights verification is not passed, it will not be displayed. By providing multi-level data encryption and secure communication, the integrity and confidentiality of the data during transmission and storage are ensured, and the energy conversion efficiency and operation stability are improved through real-time optimization control of wind turbines.

[0072] It should be noted that storing the operation monitoring parameters of the wind turbine set in the main control cloud platform instead of uploading it to the data backup module can reduce unnecessary data transmission. Storing the operation monitoring parameters of the unit in the data backup module is convenient for quickly locating and analyzing the cause of the fault for timely processing. Through targeted backup and optimizing the data processing process, the waste of resources can be reduced.

[0073] To sum up, this embodiment collects the operation monitoring parameters of the wind turbine in real time through the data acquisition module, and obtains the operation monitoring evaluation value through processing by the data analysis module, so as to accurately judge the operation status of the wind turbine, and then realizes precise monitoring and timely early warning of the wind turbine, effectively solves the problem of insufficient safety performance and reliability of the wind power main control system in the prior art, and improves the safe operation level and fault response capability of the wind farm.

[0074] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0075] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0076] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0077] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0078] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0079] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A wind power master control system based on a secure and reliable software and hardware platform, characterized by: include: The data acquisition module is used to collect the operation monitoring parameters of the wind turbine in real time through the edge intelligent master control sensor hub connected to the secure and trusted hardware and software platform; A data analysis module is used to analyze the wind turbine generator set operation monitoring parameters to obtain the deviation state evaluation index of the wind turbine generator set, thereby obtaining the operation monitoring category, wherein the operation monitoring category is: normal wind turbine generator set, abnormal wind turbine generator set and faulty wind turbine generator set; The monitoring result judgment module is used to save the operation monitoring parameters of the wind turbine set to the main control cloud platform when the operation monitoring category is that the wind turbine set is normal; when the operation monitoring category is that the wind turbine set is abnormal, the wind turbine set is recorded as an abnormal unit and optimized control is performed; when the operation monitoring category is that the wind turbine set is faulty, an early warning is performed and the wind turbine set is controlled to enter a safety protection mode; The abnormal unit optimization control module is used to track and monitor the abnormal units, analyze and obtain the optimization control execution parameters of the abnormal units, and optimize the abnormal units through the main control cloud platform; The data backup module is used to count the operation monitoring parameters of abnormal units and obtain the parameters of each currently available backup storage location, thereby screening to obtain the adapted backup storage location, and transmitting the operation monitoring parameters of the abnormal units to the adapted backup storage location for backup storage.

2. The wind power master control system based on a secure and reliable software and hardware platform as claimed in claim 1, characterized in that: The edge intelligent master control sensor hub connected through the secure and trusted hardware and software platform collects the operation monitoring parameters of the wind turbine in real time; The operation monitoring parameters specifically include: blade deviation angle, output power, main shaft speed, main shaft inclination, generator temperature, yaw angle, power factor and oil level of the wind turbine.

3. The wind power master control system based on a secure and reliable software and hardware platform as claimed in claim 1, characterized in that: The specific method for analyzing the wind turbine generator set's operating monitoring parameters to obtain the wind turbine generator set's deviation state assessment index is as follows: Acquire an operation monitoring target set of a wind turbine generator set, wherein the operation monitoring target set of the wind turbine generator set includes: a blade deviation angle target value, an output power target value, a main shaft speed target value, a main shaft inclination target value, a generator temperature target value, a yaw angle target value, a power factor target value, and an oil level height target value; The wind turbine operation monitoring target set and the wind turbine operation monitoring parameters are analyzed to obtain the wind turbine deviation state evaluation index; The deviation state evaluation index of the wind turbine generator set is used to characterize the degree of abnormal operation of the wind turbine generator set.

4. The wind power master control system based on a secure and reliable software and hardware platform as claimed in claim 1, characterized in that: The deviation state evaluation index of the wind turbine is obtained. The specific method is as follows: Where R represents the deviation state evaluation index of the wind turbine, e represents the natural constant, R1 represents the structural control evaluation value of the wind turbine, R2 represents the performance control evaluation value of the wind turbine, μ1 represents the influence weight of the structural control evaluation value, and μ2 represents the influence weight of the performance control evaluation value.

5. The wind power master control system based on a secure and reliable software and hardware platform as claimed in claim 1, characterized in that: The deviation state evaluation index of the wind turbine generator set is obtained by analyzing the operation monitoring parameters of the wind turbine generator set, and the operation monitoring category is obtained by processing. The specific process is as follows: Obtaining a first threshold value for evaluating a deviation state of a wind turbine set and a second threshold value for evaluating a deviation state of a wind turbine set preset in a database; Based on the deviation state assessment index of the wind turbine generator set, and compared with the first deviation state assessment threshold of the wind turbine generator set and the second deviation state assessment threshold of the wind turbine generator set, if the deviation state assessment index of the wind turbine generator set is above the first deviation state assessment threshold of the wind turbine generator set, then the operation monitoring category is a wind turbine generator fault; If the deviation state assessment index of the wind turbine generator set is less than the first deviation state assessment threshold of the wind turbine generator set and is above the second deviation state assessment threshold of the wind turbine generator set, the operation monitoring category is abnormality of the wind turbine generator set; If the deviation state assessment index of the wind turbine generator set is less than the second deviation state assessment threshold of the wind turbine generator set, the operation monitoring category is that the wind turbine generator set is normal.

6. The wind power master control system based on a secure and reliable software and hardware platform as claimed in claim 1, characterized in that: The tracking and monitoring of abnormal units specifically includes: Acquire real-time external environment parameters through the edge intelligent master control sensor hub connected by a secure and trusted hardware and software platform; Obtaining an external environment target set preset in a database, wherein the external environment target set includes: an external environment wind speed target value, an external atmospheric pressure target value, an external environment temperature target value, and an external environment humidity target value; The environmental matching degree is obtained by comparing the real-time external environmental parameters with the external environmental target set; Based on the deviation state evaluation index of the wind turbine generator set, the deviation state evaluation index of the abnormal unit is screened and obtained; Obtain the environmental target matching degree preset in the database, and fuse and analyze the environmental matching degree, environmental target matching degree, deviation state evaluation index of abnormal units and the first threshold value of deviation state evaluation of wind turbine units to obtain the tracking control reference index of abnormal units; The real-time external environment parameters include: real-time external environment wind speed, real-time external atmospheric pressure, real-time external environment temperature and real-time external environment humidity; The environmental matching degree is used to characterize the matching degree of the current operating environment of the abnormal unit; The tracking control reference index of the abnormal unit is used to characterize the execution complexity of the optimization control of the abnormal unit.

7. The wind power master control system based on a secure and reliable software and hardware platform as claimed in claim 6, characterized in that: The analysis obtains the abnormal unit optimization control execution parameters, which specifically include: Obtain each tracking control reference index interval preset in the database and the operating adjustment parameters corresponding to each tracking control reference index interval, match the tracking control reference index of the abnormal unit with each tracking control reference index interval; if the tracking control reference index of the abnormal unit is within a certain tracking control reference index interval, obtain the operating adjustment parameters corresponding to the tracking control reference index interval as the abnormal unit optimization control execution parameters.

8. The wind power master control system based on a secure and reliable software and hardware platform as claimed in claim 7, characterized in that: The currently available parameters of each backup storage location specifically include: the remaining space capacity of each backup storage location, the remaining space capacity ratio, the disk read and write speed, the disk average failure-free time, and the disk average failure repair time.

9. The wind power master control system based on a secure and reliable software and hardware platform as claimed in claim 8, characterized in that: The screening to obtain an adapted backup storage location and transmitting the operation monitoring parameters of the abnormal unit to the adapted backup storage location for backup storage specifically includes: According to the parameters of each backup storage location, the backup storage effect evaluation value of each backup storage location is processed to obtain the best backup storage location through screening; The backup storage effect evaluation value of each backup storage location is used to characterize each backup storage effect. Based on the backup storage effect evaluation values ​​of each backup storage location, the backup storage location corresponding to the maximum backup storage effect evaluation value is obtained as the adaptive backup storage location, and the operation monitoring parameters of the abnormal unit are backed up and stored in the adaptive backup storage location.

10. The wind power master control system based on a secure and reliable software and hardware platform as claimed in claim 1, characterized in that: It also includes a data security and encryption module, which is used to use encryption algorithms to transmit the operation monitoring parameters of the wind turbine sets stored in the main control cloud platform and the operation monitoring parameters of the abnormal units in the data backup module, and save them in the main control cloud platform and the data backup module respectively, and set access permission management.

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