Wind power generation optimization system based on big data

Abstract

The invention relates to the technical field of big data and energy management, in particular to a wind power generation optimization system based on big data, which comprises an environment monitoring and early warning module, a windward adjustment module and a power optimization module, and is characterized in that the environment monitoring and early warning module is used for monitoring meteorological parameters in an environment and calculating a meteorological health coefficient; the display module is used for displaying early warning information; the windward adjusting module is used for calculating the horizontal angle variation and the vertical angle variation of the wind direction; the control step length of the horizontal rotation driving motor and the target driving power of the hydraulic pump machine are calculated; the rotating direction of the fan is controlled; the power optimization module is used for performing work grade division; the calculation module is used for calculating the air density and the output power of the motor; and after the working grade of the motor is determined, optimal power adjustment is performed according to the calculated output power of the motor and the upper limit of the output power for determining the working grade of the motor, so that the working stability of the power generation system is ensured while the power generation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of big data and energy management, and in particular to a wind power generation optimization system based on big data. Background Art

[0002] As an important part of renewable energy, the development and utilization of wind energy is of great significance for promoting the optimization of energy structure, reducing environmental pollution and coping with climate change. However, in the practical application of wind power generation systems, existing technologies still face many challenges and shortcomings. In terms of environmental monitoring, traditional wind power generation systems often rely only on simple meteorological sensors to monitor basic meteorological parameters such as wind speed and wind direction, which lacks comprehensiveness and accuracy. This single monitoring method not only fails to capture the profound impact of the complex and changeable meteorological environment on the efficiency of wind power generation, but also fails to provide timely and effective early warning information, thereby increasing the potential risks of system operation. Most existing technologies use fixed or simple mechanical adjustment devices, which are difficult to accurately adjust according to real-time meteorological parameters. Not only this, but also the motor may be overloaded due to excessive wind resistance, affecting the stability and service life of the system. In terms of power optimization, traditional methods often adjust power based on fixed motor parameters and working modes, lacking comprehensive consideration of multiple factors such as different wind speeds, motor heat dissipation efficiency and working temperature. This single regulation strategy not only makes it difficult to achieve optimal power output, but may also cause energy waste and motor performance degradation. The existing technology also lacks a comprehensive management system that can integrate environmental monitoring, windward regulation, and power optimization. The lack of effective data sharing and collaborative work between modules leads to low overall system efficiency and cannot meet the needs of modern wind power generation systems for efficient, stable, and intelligent operation.

[0003] Therefore, a wind power generation optimization system based on big data is proposed. Summary of the invention

[0004] The present invention aims to solve the problem that the current traditional wind power generation system lacks comprehensiveness and is difficult to provide timely and effective early warning information. Most of the existing technologies use fixed or simple mechanical adjustment devices, which are difficult to accurately adjust according to real-time meteorological parameters, reducing the wind energy capture efficiency. There is a lack of comprehensive consideration of multiple factors such as different wind speeds, motor heat dissipation efficiency and operating temperature, making it difficult to achieve optimal power output, and may also cause energy waste and reduced motor performance.

[0005] The technical solution adopted by the present invention to solve its technical problem is:

[0006] A wind power generation optimization system based on big data, including an environmental monitoring and early warning module, a windward adjustment module and a power optimization module.

[0007] The environmental monitoring and early warning module is arranged above the motor, and is used to monitor the meteorological parameters in the environment, and then transmit the monitored meteorological parameter data to the windward adjustment module and the power optimization module respectively; and is used to calculate the meteorological health coefficient according to the air parameters; and is used to compare the calculated meteorological health coefficient with the preset safety threshold range of the meteorological health coefficient; and is used to display early warning information when the meteorological health coefficient is outside the preset safety threshold range of the meteorological health coefficient;

[0008] The windward adjustment module is used to calculate the horizontal angle change and vertical angle change of the wind direction according to the received meteorological parameters after receiving the meteorological parameter data; and to calculate the horizontal rotation drive motor control step length according to the calculated horizontal angle change and the preset horizontal rotation drive motor parameters; and to calculate the target driving power of the hydraulic pump according to the calculated vertical angle change and the preset hydraulic valve working parameters; and to control the direction of the fan according to the calculated horizontal rotation drive motor control step length and the target driving power of the hydraulic pump;

[0009] The power optimization module is used to divide the working levels according to different wind speeds and the heat dissipation efficiency, working temperature and the optimal output power upper limit of the motor of the motor; and after receiving the meteorological parameter data and the meteorological health coefficient, calculate the air density according to the received meteorological parameter data; and calculate the output power of the motor according to the calculated air density, meteorological parameters and meteorological health coefficient and preset motor parameters; and monitor the working temperature of the motor, and then compare the working levels divided according to the horizontal wind speed data and the monitored working temperature of the motor to determine the working level of the motor; and after determining the working level of the motor, perform optimal power regulation according to the calculated output power of the motor and the output power upper limit of the determined working level of the motor.

[0010] Preferably, the environmental monitoring and early warning module includes a timing module, a horizontal wind speed and direction sensing unit, a vertical wind speed and direction sensing unit, a temperature and humidity sensing unit, an air pressure monitoring unit, a Zigbee module and an early warning display module.

[0011] The timing module is used to connect all sensor units and send acquisition signals to all sensor units at regular intervals;

[0012] The horizontal wind speed and direction sensor unit is arranged above the motor, and is used to monitor the horizontal wind direction data and horizontal wind speed data at the fan after receiving the collection signal, and then transmit the monitored horizontal wind direction data and horizontal wind speed data to the Zigbee module;

[0013] The vertical wind speed and direction sensor unit is arranged above the motor, and is used to monitor the vertical wind direction data and vertical wind speed data at the fan after receiving the acquisition signal, and then transmit the monitored vertical wind direction data and vertical wind speed data to the Zigbee module;

[0014] The temperature and humidity sensing unit is arranged in the power generation mast, and is used to monitor the temperature and humidity data in the air after receiving the acquisition signal, and then transmit the monitored temperature and humidity data to the Zigbee module;

[0015] The air pressure monitoring unit is set in the power generation mast, and is used to monitor the air pressure data after receiving the collection signal, and then transmit the monitored air pressure data to the Zigbee module;

[0016] The Zigbee module is used to transmit the horizontal wind direction data, horizontal wind speed data, vertical wind direction data, vertical wind speed data, temperature data, humidity data and air pressure data to the early warning monitoring module after receiving the horizontal wind direction data, horizontal wind speed data, vertical wind direction data, vertical wind speed data, temperature data, humidity data and air pressure data;

[0017] The early warning display module is used to calculate the meteorological health coefficient based on the horizontal wind speed data, vertical wind speed data, temperature data and the preset maximum values ​​of the horizontal wind speed, vertical wind speed and temperature after receiving the horizontal wind speed data, vertical wind speed data and temperature data, and then transmit the meteorological health coefficient to the power optimization unit; and to compare the calculated meteorological health coefficient with the preset safety threshold range of the meteorological health coefficient; and to display early warning information when the meteorological health coefficient is outside the preset safety threshold range of the meteorological health coefficient.

[0018] Preferably, the warning display module includes a data processing unit, a 5G communication module and a mobile warning display unit.

[0019] The data processing unit is used to calculate the meteorological health coefficient according to the horizontal wind speed data, the vertical wind speed data, the temperature data and the maximum values ​​of the preset horizontal wind speed, the vertical wind speed and the temperature after receiving the horizontal wind speed data, the vertical wind speed data and the temperature data, and then transmit the meteorological health coefficient to the power optimization unit; and to compare the calculated meteorological health coefficient with the preset safety threshold range of the meteorological health coefficient; and to generate an early warning signal when the meteorological health coefficient is outside the preset safety threshold range of the meteorological health coefficient, and then transmit the early warning signal to the 5G communication module;

[0020] The 5G communication module is used to transmit the warning signal to the mobile warning display unit after receiving the graphical data packet and the warning signal;

[0021] The mobile warning display unit is used to display warning information after receiving a warning signal.

[0022] Preferably, the calculation formula of the meteorological health coefficient is:

[0023]

[0024] Where MHI is the meteorological health index, ω 1 and ω 2 and ω 3 is the weight coefficient, and ω 1 +ω 2 +ω 3 =1, V h is the horizontal wind speed data, its unit is km / h, is the maximum horizontal wind speed, in km / h, V v is the vertical wind speed data, its unit is km / h, is the maximum vertical wind speed, its unit is km / h, T is the temperature data, its unit is ℃, T max is the maximum temperature, its unit is °C.

[0025] Preferably, the windward adjustment module includes an angle change calculation unit, a motor control step length calculation unit, a hydraulic pump drive power calculation unit and a fan steering control unit;

[0026] The angle variation calculation unit is used to calculate the horizontal angle variation and the vertical angle variation according to the horizontal wind direction data and the vertical wind direction data after receiving the horizontal wind direction data and the vertical wind direction data, and then transmit the calculated horizontal angle variation data and the vertical angle variation data to the motor control step length calculation unit and the hydraulic pump drive power calculation unit respectively;

[0027] The motor control step length calculation unit is used to calculate the horizontal rotation drive motor control step length according to the horizontal angle change amount data, the preset total step length of the horizontal rotation drive motor and the step angle of the horizontal rotation drive motor after receiving the horizontal angle change amount data, and then transmit the calculated horizontal rotation drive motor control step length data to the fan steering control unit;

[0028] The hydraulic pump driving power calculation unit is used to monitor the oil supply pressure detected by the pressure gauge in the hydraulic pipe; and is used to detect the working flow rate per unit time in the hydraulic pipe; and is used to calculate the target driving power of the hydraulic pump according to the vertical angle change, the oil supply pressure in the hydraulic pipe, the working flow rate in the hydraulic pipe and the preset curvature radius of the hydraulic pipe, the inner diameter of the hydraulic push rod, the inner diameter of the hydraulic pipe and the response time of the vertical angle driving device and the working efficiency of the hydraulic pump after receiving the vertical angle change data, and then transmit the calculated target driving power of the hydraulic pump to the fan steering control unit;

[0029] The fan steering control unit is used to adjust the fan steering according to the horizontal rotation drive motor control step data and the target driving power of the hydraulic pump after receiving the horizontal rotation drive motor control step data and the target driving power of the hydraulic pump.

[0030] Preferably, the calculation formulas for the horizontal angle change and the vertical angle change are:

[0031] Δθ 1 =θ 1 -θ′ 1 ;

[0032] Δθ 2 =θ 2 -θ′ 2 ;

[0033] Among them, Δθ 1 is the horizontal angle change, its unit is °, θ 1 Indicates the current horizontal wind direction data, its unit is °, θ' 1 Indicates the horizontal wind direction data of the previous unit time, its unit is °, Δθ 2 is the change in the vertical angle, its unit is °, θ 2 Indicates the current vertical wind direction data, its unit is °, θ' 2 Represents the vertical wind direction data of the previous unit time, and its unit is °.

[0034] Preferably, the calculation formula for the control step length of the horizontal rotation drive motor and the target drive power of the hydraulic pump is:

[0035]

[0036] Among them, T run is the horizontal rotation drive motor control step size, Δθ 1 is the horizontal angle change, its unit is °, θ 0 is the step angle of the horizontal rotation drive motor, in degrees, T total is the preset total step length of the horizontal rotation drive motor, P run is the target driving power of the hydraulic pump, in kW, P v is the oil supply pressure in the hydraulic pipe, its unit is Pa, Δθ 2 is the change in the vertical angle, in degrees, r 1 is the preset inner diameter of the hydraulic pipe, in m, r 0 is the preset inner diameter of the hydraulic push rod, its unit is m, r is the preset radius of curvature of the hydraulic pipe, its unit is m, t is the preset response time of the vertical angle drive device, its unit is s, and η is the preset working efficiency of the hydraulic pump, which is a dimensionless parameter.

[0037] Preferably, the power optimization module includes a working level classification module, an air density calculation unit, an output power calculation unit and a power regulation module.

[0038] The working level division module is used to divide the working level of the motor into level I working level and level II working level according to different wind speeds, the heat dissipation efficiency of the motor, the working temperature and the upper limit of the optimal output power of the motor; and is used to monitor the working temperature of the motor; and is used to compare the working levels divided according to the horizontal wind speed data and the monitored working temperature of the motor after receiving the output power data and the horizontal wind speed data of the motor, determine the working level of the motor, and then transmit the upper limit of the optimal output power of the motor in the corresponding working level to the power regulation module;

[0039] The air density calculation unit is used to calculate the air density according to the atmospheric pressure value and the saturated water vapor pressure value in the temperature data, humidity data and air pressure data after receiving the temperature data, humidity data and air pressure data, and then transmit the calculated air density data to the output power calculation unit;

[0040] The output power calculation unit is used to calculate the output power of the motor according to the air density, horizontal wind speed data, meteorological health coefficient and preset blade radius and wind energy utilization efficiency of the motor after receiving the horizontal wind speed data, meteorological health coefficient and air density data, and then transmit the output power data of the motor to the working level division module and the power regulation module respectively;

[0041] The power regulation module is used to regulate the output power data of the motor to the optimal output power of the motor after receiving the output power data of the motor and the optimal output power of the motor.

[0042] Preferably, the calculation formula of air density is:

[0043]

[0044] Where ρ is the air density in kg / m 3 , P is the atmospheric pressure value, its unit is Pa, T is the temperature data, its unit is ℃, p b is the saturated water vapor pressure value, its unit is Pa, φ is the humidity data, its unit is %.

[0045] Preferably, the calculation formula of the output power of the motor is:

[0046]

[0047] Among them, P w is the output power of the motor, its unit is W, ρ is the air density, its unit is kg / m 3, R is the preset blade radius, its unit is m, V h is the horizontal wind speed data, its unit is km / h, C p is the wind energy utilization factor of the motor, dimensionless, and MHI is the meteorological health index.

[0048] Beneficial effects of the present invention:

[0049] 1. It can monitor multiple meteorological parameters in the environment in real time, such as temperature, humidity, wind speed, wind direction, etc., to achieve comprehensive coverage of the meteorological environment. This not only improves the accuracy of monitoring data, but also provides a reliable data basis for subsequent wind power generation optimization.

[0050] 2.According to the real-time monitored meteorological parameters, the horizontal and vertical angle changes of the wind direction are accurately calculated, and the direction of the fan is controlled accordingly. This precise adjustment method not only improves the efficiency of wind energy capture, but also reduces wind resistance and extends the service life of the motor.

[0051] 3. By comprehensively considering factors such as wind speed, motor heat dissipation efficiency, operating temperature and optimal output power upper limit, the motor's working level is divided, and the optimal power adjustment is performed based on the calculated output power and the corresponding level's output power upper limit.

[0052] 4. By real-time monitoring of the motor's working status and meteorological parameters, the system can promptly detect and warn of potential operating risks, helping operators to take timely measures to avoid failures and ensure the stable operation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments are briefly introduced below. The drawings described below only relate to some embodiments of the present invention, but are not intended to limit the present invention.

[0054] In the attached picture:

[0055] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0056] The concept and technical effects of the present invention will be clearly and completely described below in conjunction with embodiments to fully understand the purpose, features and effects of the present invention.

[0057] See also Figure 1 ,

[0058] A wind power generation optimization system based on big data, including an environmental monitoring and early warning module, a windward adjustment module and a power optimization module.

[0059] The environmental monitoring and early warning module is arranged above the motor, and is used to monitor the meteorological parameters in the environment, and then transmit the monitored meteorological parameter data to the windward adjustment module and the power optimization module respectively; and is used to calculate the meteorological health coefficient according to the air parameters; and is used to compare the calculated meteorological health coefficient with the preset safety threshold range of the meteorological health coefficient; and is used to display early warning information when the meteorological health coefficient is outside the preset safety threshold range of the meteorological health coefficient;

[0060] The windward adjustment module is used to calculate the horizontal angle change and vertical angle change of the wind direction according to the received meteorological parameters after receiving the meteorological parameter data; and to calculate the horizontal rotation drive motor control step length according to the calculated horizontal angle change and the preset horizontal rotation drive motor parameters; and to calculate the target driving power of the hydraulic pump according to the calculated vertical angle change and the preset hydraulic valve working parameters; and to control the direction of the fan according to the calculated horizontal rotation drive motor control step length and the target driving power of the hydraulic pump;

[0061] The power optimization module is used to divide the working levels according to different wind speeds and the heat dissipation efficiency, working temperature and the optimal output power upper limit of the motor of the motor; and after receiving the meteorological parameter data and the meteorological health coefficient, calculate the air density according to the received meteorological parameter data; and calculate the output power of the motor according to the calculated air density, meteorological parameters and meteorological health coefficient and preset motor parameters; and monitor the working temperature of the motor, and then compare the working levels divided according to the horizontal wind speed data and the monitored working temperature of the motor to determine the working level of the motor; and after determining the working level of the motor, perform optimal power regulation according to the calculated output power of the motor and the output power upper limit of the determined working level of the motor.

[0062] In this embodiment, the environmental monitoring and early warning module includes a timing module, a horizontal wind speed and direction sensing unit, a vertical wind speed and direction sensing unit, a temperature and humidity sensing unit, an air pressure monitoring unit, a Zigbee module and an early warning display module.

[0063] The timing module is used to connect all sensor units and send acquisition signals to all sensor units at regular intervals. The timing module is a programmable timer;

[0064] The horizontal wind speed and direction sensing unit is arranged above the motor, and is used to monitor the horizontal wind direction data and horizontal wind speed data at the fan after receiving the acquisition signal, and then transmit the monitored horizontal wind direction data and horizontal wind speed data to the Zigbee module. The horizontal wind speed and direction sensing unit is a three-cup wind speed and direction sensor;

[0065] The vertical wind speed and direction sensing unit is arranged above the motor, and is used to monitor the vertical wind direction data and vertical wind speed data at the fan after receiving the acquisition signal, and then transmit the monitored vertical wind direction data and vertical wind speed data to the Zigbee module. The vertical wind speed and direction sensing unit is a propeller-type wind speed and direction sensor;

[0066] The temperature and humidity sensing unit is set in the power generation mast, and is used to monitor the temperature data and humidity data in the air after receiving the collection signal, and then transmit the monitored temperature data and humidity data to the Zigbee module. The temperature and humidity sensing unit is a temperature sensor and a humidity sensor;

[0067] The air pressure monitoring unit is set in the power generation mast, and is used to monitor the air pressure data after receiving the collection signal, and then transmit the monitored air pressure data to the Zigbee module. The air pressure monitoring unit is an air pressure sensor and a saturated water vapor pressure measuring instrument;

[0068] The Zigbee module is used to transmit the horizontal wind direction data, horizontal wind speed data, vertical wind direction data, vertical wind speed data, temperature data, humidity data and air pressure data to the early warning monitoring module after receiving the horizontal wind direction data, horizontal wind speed data, vertical wind direction data, vertical wind speed data, temperature data, humidity data and air pressure data;

[0069] The early warning display module is used to calculate the meteorological health coefficient based on the horizontal wind speed data, vertical wind speed data, temperature data and the preset maximum values ​​of the horizontal wind speed, vertical wind speed and temperature after receiving the horizontal wind speed data, vertical wind speed data and temperature data, and then transmit the meteorological health coefficient to the power optimization unit; and to compare the calculated meteorological health coefficient with the preset safety threshold range of the meteorological health coefficient; and to display early warning information when the meteorological health coefficient is outside the preset safety threshold range of the meteorological health coefficient.

[0070] In this embodiment, the warning display module includes a data processing unit, a 5G communication module and a mobile warning display unit.

[0071] The data processing unit is used to calculate the meteorological health coefficient according to the horizontal wind speed data, the vertical wind speed data, the temperature data and the maximum values ​​of the preset horizontal wind speed, the vertical wind speed and the temperature after receiving the horizontal wind speed data, the vertical wind speed data and the temperature data, and then transmit the meteorological health coefficient to the power optimization unit; and to compare the calculated meteorological health coefficient with the preset safety threshold range of the meteorological health coefficient; and to generate an early warning signal when the meteorological health coefficient is outside the preset safety threshold range of the meteorological health coefficient, and then transmit the early warning signal to the 5G communication module, and the data processing unit is a processor;

[0072] The 5G communication module is used to transmit the warning signal to the mobile warning display unit after receiving the graphical data packet and the warning signal;

[0073] The mobile warning display unit is used to display warning information after receiving a warning signal. The mobile warning module is a mobile terminal.

[0074] In this embodiment, the calculation formula of the meteorological health coefficient is:

[0075]

[0076] Where MHI is the meteorological health index, ω 1 and ω 2 and ω 3 is the weight coefficient, and ω 1 +ω 2 +ω 3 =1, V h is the horizontal wind speed data, its unit is km / h, is the maximum horizontal wind speed, in km / h, V v is the vertical wind speed data, its unit is km / h, is the maximum vertical wind speed, its unit is km / h, T is the temperature data, its unit is ℃, T max is the maximum temperature, its unit is °C.

[0077] In this embodiment, when ω 1 =0.4,ω 2 =0.3,ω 3 =0.3, V h =50km / h, V v =10km / h, T=25℃,T max When the temperature is =40℃, the meteorological health factor is calculated to be 0.41.

[0078] In this embodiment, the windward adjustment module includes an angle change calculation unit, a motor control step length calculation unit, a hydraulic pump drive power calculation unit and a fan steering control unit;

[0079] The angle variation calculation unit is used to calculate the horizontal angle variation and the vertical angle variation according to the horizontal wind direction data and the vertical wind direction data after receiving the horizontal wind direction data and the vertical wind direction data, and then transmit the calculated horizontal angle variation data and the vertical angle variation data to the motor control step length calculation unit and the hydraulic pump drive power calculation unit respectively. The angle variation calculation unit is a processor;

[0080] The motor control step length calculation unit is used to calculate the horizontal rotation drive motor control step length according to the horizontal angle change amount data, the preset total step length of the horizontal rotation drive motor and the step angle of the horizontal rotation drive motor after receiving the horizontal angle change amount data, and then transmit the calculated horizontal rotation drive motor control step length data to the fan steering control unit. The motor control step length calculation unit is a processor;

[0081] The hydraulic pump driving power calculation unit is used to monitor the oil supply pressure detected by the pressure gauge in the hydraulic pipe; and is used to detect the working flow rate per unit time in the hydraulic pipe; and is used to calculate the target driving power of the hydraulic pump according to the vertical angle change, the oil supply pressure in the hydraulic pipe, the working flow rate in the hydraulic pipe and the preset curvature radius of the hydraulic pipe, the inner diameter of the hydraulic push rod, the inner diameter of the hydraulic pipe and the response time of the vertical angle driving device and the working efficiency of the hydraulic pump after receiving the vertical angle change data, and then transmit the calculated target driving power of the hydraulic pump to the fan steering control unit. The hydraulic pump driving power calculation unit is a processor;

[0082] The fan steering control unit is used to adjust the fan steering according to the horizontal rotation drive motor control step data and the target driving power of the hydraulic pump after receiving the horizontal rotation drive motor control step data and the target driving power of the hydraulic pump. The fan steering control unit is a controller.

[0083] In this embodiment, the calculation formulas for the horizontal angle change and the vertical angle change are:

[0084] Δθ 1 =θ 1 -θ′ 1 ;

[0085] Δθ 2 =θ 2 -θ′ 2 ;

[0086] Among them, Δθ 1 is the horizontal angle change, its unit is °, θ 1 Indicates the current horizontal wind direction data, its unit is °, θ' 1 Indicates the horizontal wind direction data of the previous unit time, its unit is °, Δθ 2 is the change in the vertical angle, its unit is °, θ 2 Indicates the current vertical wind direction data, its unit is °, θ' 2 Represents the vertical wind direction data of the previous unit time, and its unit is °.

[0087] In this embodiment, the calculation formula for the control step length of the horizontal rotation drive motor and the target drive power of the hydraulic pump is:

[0088]

[0089]

[0090] Among them, T run is the horizontal rotation drive motor control step size, Δθ 1 is the horizontal angle change, its unit is °, θ 0 is the step angle of the horizontal rotation drive motor, in degrees, T total is the preset total step length of the horizontal rotation drive motor, P run is the target driving power of the hydraulic pump, in kW, P v is the oil supply pressure in the hydraulic pipe, its unit is Pa, Δθ 2 is the change in the vertical angle, in degrees, r 1 is the preset inner diameter of the hydraulic pipe, in m, r 0 is the preset inner diameter of the hydraulic push rod, its unit is m, r is the preset radius of curvature of the hydraulic pipe, its unit is m, t is the preset response time of the vertical angle drive device, its unit is s, and η is the preset working efficiency of the hydraulic pump, which is a dimensionless parameter.

[0091] In this embodiment, when Δθ 1 =-30°,θ 0 =1.8°, T total =200, the control step length of the horizontal rotation drive motor is calculated to be 531. v =2*107Pa,Δθ 2 =10°, r 1 =0.05m, r=0.1m, r 0 =0.02m, t=0.05s, η=0.85, the target driving power of the hydraulic pump is calculated to be 63kW.

[0092] In this embodiment, the power optimization module includes a working level classification module, an air density calculation unit, an output power calculation unit and a power adjustment module.

[0093] The working level division module is used to divide the working level of the motor into level I working level and level II working level according to different wind speeds, the heat dissipation efficiency of the motor, the working temperature and the upper limit of the optimal output power of the motor; and is used to monitor the working temperature of the motor; and is used to compare the working levels divided according to the horizontal wind speed data and the monitored working temperature of the motor after receiving the output power data and horizontal wind speed data of the motor, determine the working level of the motor, and then transmit the upper limit of the optimal output power of the motor in the corresponding working level to the power regulation module. The working level division module is a big data server;

[0094] The air density calculation unit is used to calculate the air density according to the atmospheric pressure value and the saturated water vapor pressure value in the temperature data, humidity data and air pressure data after receiving the temperature data, humidity data and air pressure data, and then transmit the calculated air density data to the output power calculation unit. The air density calculation unit is a processor;

[0095] The output power calculation unit is used to calculate the output power of the motor according to the air density, horizontal wind speed data, meteorological health coefficient and preset blade radius and wind energy utilization efficiency of the motor after receiving the horizontal wind speed data, meteorological health coefficient and air density data, and then transmit the output power data of the motor to the working level division module and the power regulation module respectively. The output power calculation unit is a processor;

[0096] The power regulating module is used to regulate the output power data of the motor to the optimal output power of the motor after receiving the output power data of the motor and the optimal output power of the motor. The power regulating module is a controller.

[0097] In this embodiment, the comparison method of the working levels divided according to the horizontal wind speed data and the monitored working temperature of the motor is as follows:

[0098]

[0099] Among them, T m is the monitored operating temperature of the motor, in °C, T fir is the first temperature threshold, in °C, T sec is the second temperature threshold, in °C, V h It is the horizontal wind speed data, and its unit is km / h. When the output result is Ⅰ, it is determined to be Level Ⅰ working level, and when the output result is Ⅱ, it is determined to be Level Ⅱ working level.

[0100] In this embodiment, the calculation formula of air density is:

[0101]

[0102] Where ρ is the air density in kg / m 3 , P is the atmospheric pressure value, its unit is kPa, T is the temperature data, its unit is ℃, p b is the saturated water vapor pressure value, its unit is kPa, φ is the humidity data, its unit is %.

[0103] In this embodiment, when P = 100 kPa, T = 20 °C, p b =2kPa, φ=40%, the calculated air density is 1.74kg / m 3 .

[0104] In this embodiment, the calculation formula of the output power of the motor is:

[0105]

[0106] Among them, P w is the output power of the motor, its unit is W, ρ is the air density, its unit is kg / m 3 , R is the preset blade radius, its unit is m, V h is the horizontal wind speed data, its unit is km / h, C p is the wind energy utilization factor of the motor, dimensionless, and MHI is the meteorological health index.

[0107] In this embodiment, when ρ = 1.7 kg / m 3 , R=65m,V w =90km / h, C p =0.4, MHI = 0.4, the calculated output power of the motor is 3.29*10 7 W.

[0108] In summary, the wind power generation optimization system based on big data effectively solves the problems existing in the existing technology by improving the comprehensiveness and accuracy of environmental monitoring, realizing the precision and intelligence of windward adjustment, optimizing power output, and enhancing the stability and reliability of the system, thereby improving the efficiency of wind power generation, system stability and intelligence level.

[0109] The above embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, other embodiments obtained by those skilled in the art without creative work shall all fall within the scope of protection of the present invention.

Claims

1. A wind power generation optimization system based on big data, characterized by: It includes environmental monitoring and early warning module, windward adjustment module and power optimization module. The environmental monitoring and early warning module is arranged above the motor, and is used to monitor the meteorological parameters in the environment, and then transmit the monitored meteorological parameter data to the windward adjustment module and the power optimization module respectively; and is used to calculate the meteorological health coefficient according to the air parameters; and used to compare the calculated meteorological health factor with a preset safety threshold range of the meteorological health factor; and is used to display warning information when the meteorological health factor is outside the preset safety threshold range of the meteorological health factor; The windward adjustment module is used to calculate the horizontal angle change and the vertical angle change of the wind direction according to the received meteorological parameters after receiving the meteorological parameter data; and to calculate the control step length of the horizontal rotation drive motor according to the calculated horizontal angle change and the preset horizontal rotation drive motor parameters; and to calculate the target driving power of the hydraulic pump according to the calculated vertical angle change and the preset hydraulic valve working parameters; and to control the direction of the fan according to the calculated control step length of the horizontal rotation drive motor and the target driving power of the hydraulic pump; The power optimization module is used to divide the working level according to different wind speeds and the heat dissipation efficiency, working temperature and the upper limit of the optimal output power of the motor; and is used to calculate the air density according to the received meteorological parameter data after receiving the meteorological parameter data and the meteorological health coefficient; It is used to calculate the output power of the motor based on the calculated air density, meteorological parameters and meteorological health coefficient and preset motor parameters; it is used to monitor the working temperature of the motor, and then compare the working levels divided according to the horizontal wind speed data and the monitored working temperature of the motor to determine the working level of the motor; and after determining the working level of the motor, it is used to perform optimal power regulation based on the calculated output power of the motor and the output power upper limit of the determined working level of the motor.

2. The wind power generation optimization system based on big data according to claim 1, characterized in that: The environmental monitoring and early warning module includes a timing module, a horizontal wind speed and direction sensing unit, a vertical wind speed and direction sensing unit, a temperature and humidity sensing unit, an air pressure monitoring unit, a Zigbee module and an early warning display module. The timing module is used to connect all sensor units and send acquisition signals to all sensor units at a regular time; The horizontal wind speed and direction sensing unit is arranged above the motor, and is used to monitor the horizontal wind direction data and horizontal wind speed data at the fan after receiving the collection signal, and then transmit the monitored horizontal wind direction data and horizontal wind speed data to the Zigbee module; The vertical wind speed and direction sensor unit is arranged above the motor, and is used to monitor the vertical wind direction data and vertical wind speed data at the fan after receiving the collection signal, and then transmit the monitored vertical wind direction data and vertical wind speed data to the Zigbee module; The temperature and humidity sensing unit is arranged in the power generation mast, and is used to monitor the temperature data and humidity data in the air after receiving the collection signal, and then transmit the monitored temperature data and humidity data to the Zigbee module; The air pressure monitoring unit is arranged in the power generation mast, and is used to monitor the air pressure data after receiving the collection signal, and then transmit the monitored air pressure data to the Zigbee module; The Zigbee module is used to transmit the horizontal wind direction data, horizontal wind speed data, vertical wind direction data, vertical wind speed data, temperature data, humidity data and air pressure data to the early warning monitoring module after receiving the horizontal wind direction data, horizontal wind speed data, vertical wind direction data, vertical wind speed data, temperature data, humidity data and air pressure data; The early warning display module is used to calculate the meteorological health coefficient according to the horizontal wind speed data, the vertical wind speed data, the temperature data and the maximum values ​​of the preset horizontal wind speed, the vertical wind speed and the temperature after receiving the horizontal wind speed data, the vertical wind speed data and the temperature data, and then transmit the meteorological health coefficient to the power optimization unit; and used to compare the calculated meteorological health factor with a preset safety threshold range of the meteorological health factor; It is also used to display warning information when the meteorological health coefficient is outside the preset safety threshold range of the meteorological health coefficient.

3. The wind power generation optimization system based on big data according to claim 2 is characterized in that: The warning display module includes a data processing unit, a 5G communication module and a mobile warning display unit. The data processing unit is used to calculate the meteorological health coefficient according to the horizontal wind speed data, the vertical wind speed data, the temperature data and the maximum values ​​of the preset horizontal wind speed, the vertical wind speed and the temperature after receiving the horizontal wind speed data, the vertical wind speed data and the temperature data, and then transmit the meteorological health coefficient to the power optimization unit; and used to compare the calculated meteorological health factor with a preset safety threshold range of the meteorological health factor; And used to generate a warning signal when the meteorological health coefficient is outside the preset safety threshold range of the meteorological health coefficient, and then transmit the warning signal to the 5G communication module; The 5G communication module is used to transmit the warning signal to the mobile warning display unit after receiving the graphical data packet and the warning signal; The mobile warning display unit is used to display warning information after receiving a warning signal.

4. The wind power generation optimization system based on big data according to claim 3 is characterized in that: The calculation formula of the meteorological health coefficient is: Where MHI is the meteorological health index, ω1, ω2 and ω3 are weight coefficients, and ω1+ω2+ω3=1, V h is the horizontal wind speed data, its unit is km / h, is the maximum horizontal wind speed, in km / h, V v is the vertical wind speed data, its unit is km / h, is the maximum vertical wind speed, its unit is km / h, T is the temperature data, its unit is ℃, T max is the maximum temperature, its unit is °C.

5. The wind power generation optimization system based on big data according to claim 1, characterized in that: The windward adjustment module includes an angle variation calculation unit, a motor control step length calculation unit, a hydraulic pump drive power calculation unit and a fan steering control unit; The angle change amount calculation unit is used to calculate the horizontal angle change amount and the vertical angle change amount according to the horizontal wind direction data and the vertical wind direction data after receiving the horizontal wind direction data and the vertical wind direction data, and then transmit the calculated horizontal angle change amount data and the vertical angle change amount data to the motor control step length calculation unit and the hydraulic pump drive power calculation unit respectively; The motor control step length calculation unit is used to calculate the horizontal rotation drive motor control step length according to the horizontal angle variation data, the preset total step length of the horizontal rotation drive motor and the step angle of the horizontal rotation drive motor after receiving the horizontal angle variation data, and then transmit the calculated horizontal rotation drive motor control step length data to the fan steering control unit; The hydraulic pump driving power calculation unit is used to monitor the oil supply pressure detected by the pressure gauge in the hydraulic pipe; and is used to detect the working flow per unit time in the hydraulic pipe; and used to calculate the target driving power of the hydraulic pump according to the vertical angle change, the oil supply pressure in the hydraulic pipe, the working flow in the hydraulic pipe and the preset curvature radius of the hydraulic pipe, the inner diameter of the hydraulic push rod, the inner diameter of the hydraulic pipe and the response time of the vertical angle driving device and the working efficiency of the hydraulic pump after receiving the vertical angle change data, and then transmit the calculated target driving power of the hydraulic pump to the fan steering control unit; The fan steering control unit is used to adjust the fan steering according to the horizontal rotation drive motor control step data and the target driving power of the hydraulic pump after receiving the horizontal rotation drive motor control step data and the target driving power of the hydraulic pump.

6. The wind power generation optimization system based on big data according to claim 5, characterized in that: The calculation formulas for the horizontal angle change and the vertical angle change are: Δθ1=θ1-θ'1; Δθ2=θ2-θ'2; Among them, Δθ1 is the horizontal angle change, its unit is °, θ1 represents the current horizontal wind direction data, its unit is °, θ'1 represents the horizontal wind direction data of the previous unit time, its unit is °, Δθ2 is the vertical angle change, its unit is °, θ2 represents the current vertical wind direction data, its unit is °, θ'2 represents the vertical wind direction data of the previous unit time, its unit is °.

7. The wind power generation optimization system based on big data according to claim 6 is characterized by: The calculation formula for the control step length of the horizontal rotation drive motor and the target drive power of the hydraulic pump is: Among them, T run is the control step length of the horizontal rotation drive motor, Δθ1 is the horizontal angle change, its unit is °, θ0 is the step angle of the horizontal rotation drive motor, its unit is °, T total is the preset total step length of the horizontal rotation drive motor, P run is the target driving power of the hydraulic pump, in kW, P v is the oil supply pressure in the hydraulic pipe, with the unit of Pa, Δθ2 is the change in the plumb angle, with the unit of °, r1 is the preset inner diameter of the hydraulic pipe, with the unit of m, r0 is the preset inner diameter of the hydraulic push rod, with the unit of m, r is the preset radius of curvature of the hydraulic pipe, with the unit of m, t is the preset response time of the plumb angle drive device, with the unit of s, and η is the preset working efficiency of the hydraulic pump, which is a dimensionless parameter.

8. The wind power generation optimization system based on big data according to claim 1, characterized in that: The power optimization module includes a working level classification module, an air density calculation unit, an output power calculation unit and a power adjustment module. The working level classification module is used to classify the motor working level into level I working level and level II working level according to different wind speeds, the heat dissipation efficiency of the motor, the working temperature and the upper limit of the optimal output power of the motor; And used to monitor the working temperature of the motor; and used to compare the working levels divided according to the horizontal wind speed data and the monitored working temperature of the motor after receiving the output power data and the horizontal wind speed data of the motor, determine the working level of the motor, and then transmit the upper limit of the optimal output power of the motor in the corresponding working level to the power regulation module; The air density calculation unit is used to calculate the air density according to the atmospheric pressure value and the saturated water vapor pressure value in the temperature data, humidity data and air pressure data after receiving the temperature data, humidity data and air pressure data, and then transmit the calculated air density data to the output power calculation unit; The output power calculation unit is used to calculate the output power of the motor according to the air density, horizontal wind speed data, meteorological health coefficient and preset blade radius and wind energy utilization efficiency of the motor after receiving the horizontal wind speed data, meteorological health coefficient and air density data, and then transmit the output power data of the motor to the working level division module and the power regulation module respectively; The power adjustment module is used to adjust the output power data of the motor to the optimal output power of the motor after receiving the output power data of the motor and the optimal output power of the motor.

9. The wind power generation optimization system based on big data according to claim 8, characterized in that: The calculation formula of the air density is: Where ρ is the air density in kg / m 3 , P is the atmospheric pressure value, its unit is Pa, T is the temperature data, its unit is ℃, p b is the saturated water vapor pressure value, its unit is Pa, φ is the humidity data, its unit is %.

10. The wind power generation optimization system based on big data according to claim 9, characterized in that: The calculation formula of the output power of the motor is: Among them, P w is the output power of the motor, its unit is W, ρ is the air density, its unit is kg / m 3 , R is the preset blade radius, its unit is m, V h is the horizontal wind speed data, its unit is km / h, C p is the wind energy utilization factor of the motor, dimensionless, and MHI is the meteorological health index.

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