Wind turbine generator coordinated control device and method based on Internet of Things

Abstract

The invention discloses a wind turbine generator coordinated control device and method based on the Internet of Things, and belongs to the technical field of wind power generation. The wind turbine generator coordinated control device comprises an information transmission module, an optimal scheduling module, a power control module, a load balancing module and a fault transfer module. Meanwhile, the master server and the slave server are added, flexible switching of the whole communication network can be achieved, optimal adjustment can be conducted on the wind driven generator which is being adjusted at the first time, optimal scheduling can be conducted through the optimal scheduling module, and then power output is rapidly adjusted in cooperation with the power control module. The problem that the conventional PID adjustment duration is too long is solved, the load balancing module and the fault transfer module achieve load balancing through information interaction and cooperation between the generator sets, a fault detection mechanism is established, it is ensured that a standby generator set is switched to in time when a fault occurs, and continuous operation of the system is maintained.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and particularly relates to a wind turbine coordinated control device and method based on the Internet of Things. Background Art

[0002] The coordinated control of wind turbines refers to the information interaction and cooperation among multiple wind turbines. Through coordinated control, stable connection between multiple generators and the power grid can be achieved, and load balancing and fault transfer among generators can be realized. The key to coordinated control lies in information transmission and protocol design to ensure real-time sharing of operating states, control strategies, wind speed predictions, etc. among multiple generators. Coordinated control of wind turbines is widely applied in scenarios such as large-scale wind farms, distributed wind power, and offshore wind power. In large-scale wind farms, load balancing and fault transfer of multiple generators are achieved through coordinated control, improving the reliability and stability of the system. In distributed wind power and offshore wind power, coordinated control helps optimize power generation efficiency and reduce operating costs.

[0003] According to the patent number: CN115324823A, patent name: A wind turbine coordinated control system, which records that "this wind turbine coordinated control method and system can achieve efficient coordinated adjustment by installing a central processing unit, avoiding the inability to quickly adjust when a wind turbine fails and improving the safety performance of the wind turbines in the whole field" and "this wind turbine coordinated control method and system can achieve real-time observation of the state of the wind turbine generator set by installing a real-time acquisition unit, effectively improving the speed of fault discovery and avoiding danger". Those skilled in the art can clearly know that the entire coordinated control system adopts a traditional PID control method, which has the advantages of simple implementation and good stability. However, it lacks in-depth understanding of complex system dynamics and is difficult to cope with the influence of various factors such as wind speed, wind direction, and temperature. Summary of the Invention

[0004] In order to overcome the above deficiencies, the present invention provides a wind turbine coordinated control device and method based on the Internet of Things.

[0005] The present invention achieves the above object through the following technical solutions:

[0006] A wind turbine coordinated control device based on the Internet of Things includes

[0007] An information transmission module that establishes an efficient information transmission mechanism to ensure real-time sharing of operating states, control strategies, and wind speed prediction information among multiple generators;

[0008] An optimized scheduling module that calculates the wind speed of the wind turbines and schedules the operation of each wind turbine in the wind turbine according to the wind speed;

[0009] A power control module, in combination with the wind speed and load changes at the wind turbine, adjusts the blade angle and pitch speed of the generator set to regulate the maximum power output of the wind turbine.

[0010] A load balancing module achieves load balancing through information interaction and cooperation among generator sets, reducing the load on a single generator set.

[0011] A fault transfer module, through information interaction among generator sets, establishes a fault detection mechanism to ensure timely switching to a standby generator set in case of a fault and maintain the continuous operation of the system.

[0012] Preferably, the information transmission module includes a server and a wireless communication module. The servers are wirelessly connected through the wireless communication module. The information transmission network composed of servers is divided into a main server and slave servers. When a certain wind turbine is operating and the optimization scheduling module, power control module, load balancing module, and fault transfer module need to perform calculations and other wind turbine operating parameters need to be collected, the server of this wind turbine will switch to the main server, and the servers of other wind turbines will switch to slave servers, so that this wind turbine can perform optimal adjustment according to the situation of the entire wind turbine group in the first time.

[0013] Preferably, the wireless communication module uses the XMPP communication protocol, an instant messaging protocol based on XML, which has good scalability and flexibility and is suitable for communication between generator sets. By optimizing the message format and transmission mechanism of XMPP, the efficiency of message processing can be improved. The data transmission of the wireless communication module uses data compression technology, which significantly reduces the data transmission volume on the premise of ensuring message integrity.

[0014] Preferably, the optimization scheduling module includes the following steps:

[0015] S11. Measure wind speed data, which includes the initial wind speed and wake wind speed of each wind turbine generator set.

[0016] S12. Calculate wind energy and calculate the total power of the wind based on the wind speed data.

[0017] S13. Establish a prediction model and speculate on the future wind speed by analyzing and modeling historical data based on the calculated wind speed data.

[0018] S14. Optimize the scheduling, compare the historical wind speed data with the existing wind speed data, and select an optimization plan.

[0019] Preferably, the power control module includes the following wind turbine output power algorithm:

[0020]

[0021] Wherein: P is the power output by the wind turbine, ρ is the air density, usually taken as a constant, A is the swept area of the wind turbine, which is proportional to the square of the wind turbine diameter, Cp is the wind energy utilization coefficient, representing the efficiency of the wind turbine in converting wind energy into mechanical energy, which is affected by the pitch angle and the tip speed ratio, and V is the wind speed.

[0022] Preferably, the power control module further includes a blade angle adjustment module. The blade angle adjustment module includes a drive motor, and the drive motor controls the blade of the wind turbine to adjust the angle. After the blade angle adjustment module adjusts the angle, the output power value of the wind turbine needs to approach the power value calculated by the wind turbine output power algorithm.

[0023] Preferably, the load balancing module includes the following steps:

[0024] S21. Predict the output of the wind turbine. By monitoring the wind speed and wind direction, predict the output power of each wind turbine.

[0025] S22. Optimize the load distribution. According to the adjustment of the output power of each wind turbine, perform load optimization distribution.

[0026] Preferably, the fault transfer module includes the following steps:

[0027] S31. Data acquisition. Use sensors installed on key components of the wind turbine generator set, such as vibration sensors, temperature sensors, and oil quality sensors, to collect the operation data of the unit in real time.

[0028] S32. Data analysis. Transmit the collected data to the data processing center. In the data processing center, use the main engine in the wind turbine to analyze and process the collected data to identify abnormal data or fault characteristics.

[0029] S33. Fault diagnosis and transfer. According to the analysis results, perform fault diagnosis on the wind turbine generator set to determine the fault type, location, and cause. At the same time, stop the operation of the faulty wind turbine and start a new wind turbine to work.

[0030] Preferably, it further includes a data monitoring module, which is used to monitor the data of power, wind speed, voltage, current, temperature, humidity, and pressure in the entire wind turbine in real time.

[0031] A method for a coordinated control device of a wind turbine based on the Internet of Things as described above includes the following steps:

[0032] Step 1: Establish an information transmission network, forming an information transmission network with all wind turbines in the wind farm.

[0033] Step 2: Real-time data monitoring. Each wind turbine uses a data monitoring module to monitor various parameters of the wind turbine in real time, and at the same time, real-time data interaction and interconnection are carried out through the information transmission network.

[0034] Step 3: Optimal scheduling of the wind farm. The optimization scheduling module is used to optimize the scheduling of the wind turbines in the entire wind farm.

[0035] Step 4: Power adjustment and output. The power control module is used to adjust the wind turbine to output the corresponding power.

[0036] Step 5: Load balancing and fault transfer. The load balancing module is used to make the wind farm operate in a load-balanced state, and at the same time, the fault transfer module is used to make the wind farm operate stably.

[0037] The beneficial effects of the present invention are as follows: In the wind turbine coordinated control device and method based on the Internet of Things:

[0038] 1. The information transmission module realizes the communication network composed of each wind turbine in the generating set. At the same time, the main server and the slave server are added, which can realize the flexible switching of the entire communication network, enabling the wind turbine being adjusted to perform the optimal adjustment in the first time.

[0039] 2. The optimization scheduling module can perform optimization scheduling, and cooperate with the power control module to quickly adjust the power output, solving the problem of too long adjustment time of the conventional PID regulation.

[0040] 3. The load balancing module and the fault transfer module realize load balancing through the information interaction and cooperation between the generating sets, and establish a fault detection mechanism to ensure that the standby generating set is switched to in time when a fault occurs, maintaining the continuous operation of the system. Description of the Drawings

[0041] The present invention will be described by way of examples with reference to the drawings, where:

[0042] Figure 1 is the step diagram of the present invention;

[0043] Figure 2 is the step diagram of the optimization scheduling module of the present invention;

[0044] Figure 3 is the step diagram of the load balancing module of the present invention;

[0045] Figure 4 is the step diagram of the fault transfer module of the present invention. Detailed Embodiments

[0046] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are all simplified schematic diagrams, only showing the basic structure of the present invention in a schematic manner, so they only show the components related to the present invention.

[0047] As Figure 1 shown, a coordinated control device for wind turbine groups based on the Internet of Things includes

[0048] an information transmission module that establishes an efficient information transmission mechanism to ensure real-time sharing of operating status, control strategies, and wind speed prediction information among multiple generator sets;

[0049] an optimization scheduling module that calculates the wind speed of the wind turbine groups and schedules the operation of each wind turbine in the wind turbine groups according to the wind speed;

[0050] a power control module that combines the wind speed and load changes at the wind turbine to adjust the maximum power output of the wind turbine by adjusting the blade angle and pitch speed of the generator set;

[0051] a load balancing module that realizes load balancing through information interaction and cooperation among the generator sets to reduce the load of a single generator set;

[0052] a fault transfer module that establishes a fault detection mechanism through information interaction among the generator sets to ensure timely switching to a standby generator set in case of a fault and maintain the continuous operation of the system.

[0053] a data monitoring module that is used to monitor the data of power, wind speed, voltage, current, temperature, humidity, and pressure in the entire wind turbine group in real time.

[0054] A method for a coordinated control device for wind turbine groups based on the Internet of Things as described above includes the following steps:

[0055] Step 1: Establish an information transmission network, forming an information transmission network with all the wind turbines in the wind turbine group,

[0056] Step 2: Real-time data monitoring, each wind turbine monitors the various parameters of the wind turbine in real time through the data monitoring module, and at the same time conducts real-time data interaction and intercommunication through the information transmission network,

[0057] Step 3: Optimization scheduling of the wind turbine group, optimizing the scheduling of the wind turbines in the entire wind turbine group through the optimization scheduling module;

[0058] Step 4: Power adjustment and output, adjusting the wind turbine to perform corresponding power output through the power control module;

[0059] Step Five: Load Balancing and Failover. Through the load balancing module, the wind turbine is made to operate in a load-balanced state, and at the same time, through the failover module, the wind turbine operates stably.

[0060] As a specific embodiment, the information transmission module includes a server and a wireless communication module. The servers are wirelessly connected to each other through the wireless communication module. The information transmission network composed of the servers is divided into a primary server and a secondary server. When a certain wind turbine is operating and the optimization scheduling module, power control module, load balancing module, and failover module need to perform calculations, it is necessary to collect the operating parameters of other wind turbines. At this time, the server of this wind turbine will switch to the primary server, and the servers of other wind turbines will switch to the secondary server, so that this wind turbine can perform optimal adjustment according to the situation of the entire wind turbine group in the first time.

[0061] As a specific embodiment, the wireless communication module uses the XMPP communication protocol, an instant messaging protocol based on XML, which has good scalability and flexibility and is suitable for communication between generator sets. By optimizing the message format and transmission mechanism of XMPP, the efficiency of message processing can be improved. The data transmission of the wireless communication module uses data compression technology, which significantly reduces the amount of data transmission on the premise of ensuring the integrity of the message.

[0062] As Figure 2 shown, as a specific embodiment, the optimization scheduling module includes the following steps:

[0063] S11. Measure the wind speed data, where the wind speed data includes the initial wind speed and wake wind speed of each wind turbine generator set;

[0064] S12. Calculate the wind energy, and calculate the total power of the wind according to the wind speed data;

[0065] S13. Establish a prediction model, and speculate on the future wind speed by analyzing and modeling the historical data based on the calculated wind speed data;

[0066] S14. Optimize the scheduling, compare the historical wind speed data with the existing wind speed data, and select an optimization plan.

[0067] As a specific embodiment, the power control module includes the following wind turbine output power algorithm:

[0068]

[0069] Where: P is the power output by the wind turbine, ρ is the air density, usually taken as a constant, A is the swept area of the wind turbine rotor, which is proportional to the square of the wind turbine diameter, Cp is the wind energy utilization coefficient, representing the efficiency of the wind turbine in converting wind energy into mechanical energy, which is affected by the pitch angle and the tip speed ratio, and V is the wind speed.

[0070] As a specific embodiment, the power control module further includes a blade angle adjustment module. The blade angle adjustment module includes a driving motor, and the driving motor controls the blade of the wind turbine to adjust the angle. After the blade angle adjustment module adjusts the angle, the output power value of the wind turbine needs to approach the power value calculated by the wind turbine output power algorithm.

[0071] As Figure 3 shown, as a specific embodiment, the load balancing module includes the following steps:

[0072] S21. Prediction of the output of the wind turbine. By monitoring the wind speed and wind direction, predict the output power of each wind turbine. The wind speed monitoring equipment monitors meteorological conditions such as wind speed and wind direction to provide data support for the prediction of the output of the wind turbine.

[0073] S22. Optimization of load distribution. Adjust the output power of each wind turbine to optimize the load distribution.

[0074] As Figure 4 shown, as a specific embodiment, the fault transfer module includes the following steps:

[0075] S31. Data acquisition. Use sensors installed on key components of the wind turbine generator set, such as vibration sensors, temperature sensors, and oil quality sensors, to collect the operation data of the unit in real time.

[0076] S32. Data analysis. Transmit the collected data to the data processing center. In the data processing center, use the main computer in the wind turbine to analyze and process the collected data to identify abnormal data or fault characteristics.

[0077] S33. Fault diagnosis and transfer. According to the analysis results, conduct fault diagnosis on the wind turbine generator set to determine the fault type, location, and cause. At the same time, stop the operation of the faulty wind turbine and start a new wind turbine to operate.

[0078] Based on the inspiration of the present invention, through the above description, relevant staff can completely make various changes and modifications without departing from the technical idea of this invention. The technical scope of this invention is not limited to the content in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A wind turbine coordinated control device based on the Internet of Things, characterized in that: include Information transmission module, establishes an efficient information transmission mechanism to ensure real-time sharing of operating status, control strategy and wind speed forecast information among multiple generator sets; The optimization scheduling module calculates the wind speed of the wind turbine group and schedules the operation of each wind turbine in the wind turbine group according to the wind speed; The power control module adjusts the maximum power output of the wind turbine by adjusting the blade angle and pitch speed of the generator set in accordance with the wind speed and load changes at the wind turbine. The load balancing module realizes load balancing through information interaction and collaboration between generator sets, thus reducing the load of a single generator set; The fault transfer module establishes a fault detection mechanism through information exchange between generator sets to ensure timely switching to the backup generator set when a fault occurs and maintain the continuous operation of the system.

2. The wind turbine coordinated control device based on the Internet of Things according to claim 1, characterized in that: The information transmission module includes a server and a wireless communication module. The servers are wirelessly connected through the wireless communication module. The information transmission network formed between the servers is divided into a main server and a slave server (when a wind turbine is running and needs to optimize the calculation of the scheduling module, power control module, load balancing module and fault transfer module, it is necessary to collect the operating parameters of other wind turbines. At this time, the server of the wind turbine will switch to the main server, and the servers of other wind turbines will switch to the slave servers, so that the wind turbine can be optimally adjusted according to the situation of the entire wind turbine group at the first time).

3. The wind turbine coordinated control device based on the Internet of Things according to claim 2 is characterized in that: The wireless communication module adopts the XMPP communication protocol, and the data transmission of the wireless communication module adopts data compression technology.

4. The wind turbine coordinated control device based on the Internet of Things according to claim 1, characterized in that: The optimization scheduling module includes the following steps: S11, measuring wind speed data, where the wind speed data includes the initial wind speed and wake wind speed of each wind turbine generator set; S12, calculating wind energy, and calculating the total wind power according to the wind speed data; S13, establishing a prediction model, based on the calculated wind speed data, and then inferring the future wind speed by analyzing and modeling the historical data; S14, optimize the scheduling, compare the historical wind speed data with the existing wind speed data, and select an optimization plan.

5. The wind turbine coordinated control device based on the Internet of Things according to claim 1, characterized in that: The power control module includes the following wind turbine generator output power algorithm: Where: P is the power output of the wind turbine, ρ is the air density, which is usually taken as a constant, A is the swept area of ​​the wind rotor, which is proportional to the square of the wind rotor diameter, Cp is the wind energy utilization coefficient, which indicates the efficiency of the wind turbine in converting wind energy into mechanical energy. It is affected by the pitch angle and the tip speed ratio, and V is the wind speed.

6. The wind turbine coordinated control device based on the Internet of Things according to claim 5 is characterized in that: The power control module also includes a blade angle adjustment module, which includes a drive motor that controls the blade adjustment angle of the wind turbine.

7. The wind turbine coordinated control device based on the Internet of Things according to claim 1, characterized in that: The load balancing module includes the following steps: S21. Wind turbine output prediction: by monitoring wind speed and wind direction, predict the output power of each wind turbine; S22, load distribution optimization, load optimization distribution is performed by adjusting the output power of each wind turbine generator.

8. The wind turbine coordinated control device based on the Internet of Things according to claim 1, characterized in that: The failover module includes the following steps: S31, data collection, using sensors installed on key components of wind turbines, such as vibration sensors, temperature sensors, and oil quality sensors, to collect real-time unit operation data; S32, data analysis, transmitting the collected data to a data processing center, where the collected data is analyzed and processed using a host in the wind turbine to identify abnormal data or fault characteristics; S33, fault diagnosis and transfer, based on the analysis results, the wind turbine generator set is diagnosed to determine the fault type, location and cause, and the faulty wind turbine generator is stopped and a new wind turbine generator is started to operate.

9. The wind turbine coordinated control device based on the Internet of Things according to claim 1, characterized in that: It also includes a data monitoring module, which is used to monitor the power, wind speed, voltage, current, temperature, humidity and pressure data of the entire wind turbine in real time.

10. A method for wind turbine coordinated control device based on Internet of Things according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Establish an information transmission network, and combine all wind turbines in the wind turbine group into an information transmission network. Step 2: Real-time data monitoring: each wind turbine uses a data monitoring module to monitor various parameters of the wind turbine in real time, and at the same time, the data is exchanged in real time through the information transmission network. Step 3: Optimizing the dispatching of wind turbines: optimizing the dispatching of wind turbines in the entire wind turbine group through the optimization dispatching module; Step 4: Power adjustment output, adjusting the wind turbine generator to output corresponding power through the power control module; Step 5: Load balancing and fault transfer. The load balancing module is used to put the wind turbine in a load-balanced working state, and the fault transfer module is used to make the wind turbine work stably.

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