Wind Turbine Simulink models that are developed on the basis of several purposes and requirements are assisted well by matlabproject.org developers. By considering specific factors of wind energy frameworks, we list out a few diverse wind turbine Simulink models, including explanations and overviews:

1. Basic Wind Turbine Model

Explanation: The power output of a wind turbine is simulated through this basic model on the basis of wind speed.

Major Elements:

• Aerodynamic power estimation
• Power output visualization (utilizing Scope)
• Wind speed input (with a Constant or Sine Wave block)
• Generator model

Significant Parameters:

• Air density
• Rotor radius
• Power coefficient

2. Wind Turbine with Pitch Control

Explanation: To enhance power output and adapt the blade angle, we build this model that includes a pitch control framework.

Major Elements:

• Blade element model
• Wind speed input
• Generator model
• Pitch control system (PID controller)

Significant Parameters:

• Pitch angle
• Anticipated power output
• Control gains

3. Wind Turbine with MPPT (Maximum Power Point Tracking)

Explanation: In order to improve energy capture, this model utilizes a method of MPPT (maximum power point tracking).

Major Elements:

• Generator model
• MPPT controller
• Wind speed input
• Power output tracking

Significant Parameters:

• Power and speed reference
• MPPT algorithm parameters

4. Wind Turbine with Doubly-Fed Induction Generator (DFIG)

Explanation: For grid combination and variable speed regulation, a doubly-fed induction generator is employed in this model.

Major Elements:

• Converter control framework
• DFIG model
• Wind speed input
• Grid linkage

Significant Parameters:

• Converter control gains
• Stator and rotor parameters

5. Wind Turbine with Full Converter

Explanation: A wind turbine model specifically for grid combination, which encompasses a full converter framework.

Major Elements:

• Generator model
• Full converter model
• Grid interface
• Wind speed input

Significant Parameters:

• Grid voltage and frequency
• Converter effectiveness

6. Offshore Wind Turbine Model

Explanation: With a focus on marine platform impacts, this model depicts the simulation of an offshore wind turbine.

Major Elements:

• Offshore support structure
• Hydrodynamic load model
• Wave input
• Wind turbine model

Significant Parameters:

• Turbine height and support structure parameters
• Wave features

7. Small-Scale Wind Turbine for Residential Use

Explanation: For the purpose of residential power generation, this model is particularly developed, which involves a small-scale wind turbine.

Major Elements:

• Battery storage framework
• Small wind turbine model
• Wind speed input
• Residential load model

Significant Parameters:

• Household load pattern
• Battery capacity

8. Wind Turbine with Energy Storage System

Explanation: A model of wind turbine created for stabilizing power output, which is integrated with an energy storage framework.

Major Elements:

• Battery storage framework
• Wind turbine model
• Wind speed input
• Grid interface

Significant Parameters:

• Storage capacity
• Battery charge/discharge effectiveness

9. Wind Farm Model

Explanation: This efficient model depicts the simulation of a wind farm including grid combination and several turbines.

Major Elements:

• Power collection network
• Several wind turbine models
• Wind speed changes
• Grid interface

Significant Parameters:

• Farm layout
• Number of turbines

10. Wind Turbine with Yaw Control

Explanation: To match the wind turbine with the direction of the wind, a wind turbine model encompasses yaw control.

Major Elements:

• Wind direction sensor
• Yaw control framework
• Wind speed input
• Turbine model

Significant Parameters:

• Control gains
• Yaw rate

11. Vertical Axis Wind Turbine (VAWT) Model

Explanation: It represents a vertical axis wind turbine and simulates its dynamics and power generation.

Major Elements:

• Generator model
• VAWT aerodynamic model
• Wind speed input
• Power output visualization

Significant Parameters:

• Blade design parameters
• Rotor height and diameter

12. Wind Turbine Fault Detection Model

Explanation: In order to identify and examine faults in the processes of wind turbines, this model is mainly developed.

Major Elements:

• Wind turbine model
• Fault identification method
• Alarm framework
• Fault settings

Significant Parameters:

• Sensor accuracy
• Fault thresholds

13. Wind Turbine Load Mitigation System

Explanation: A model concentrating on minimizing mechanical stress on the turbine by including a load mitigation framework.

Major Elements:

• Wind turbine model
• Load mitigation control framework
• Wind speed input
• Mechanical load sensors

Significant Parameters:

• Stress thresholds
• Load mitigation control parameters

14. Wind Turbine Grid Integration with Power Quality Control

Explanation: Combination of a wind turbine into a power grid is the major consideration of this model that also aims to assure power quality.

Major Elements:

• Power quality control framework
• Wind turbine model
• Harmonic assessment
• Grid interface

Significant Parameters:

• Grid voltage and frequency
• Power quality principles

15. Hybrid Wind-Solar Power Generation System

Explanation: For a hybrid renewable energy framework, this robust model integrates solar and wind power generation.

Major Elements:

• Solar PV model
• Wind turbine model
• Grid interface
• Energy management framework

Significant Parameters:

• Wind speed
• Solar irradiance
• Energy management principles

How to simulate wind turbine using Simulink?

Simulation of a wind turbine is examined as a compelling as well as challenging process that must be carried out by following numerous procedures. To build and execute a wind turbine simulation using Simulink, we provide a procedural instruction in an explicit way:

1. Introduction to Wind Turbine Simulation

Generally, various elements are encompassed in the simulation of wind turbine and they are:

• Aerodynamic Model: Communication among the turbine blades and the wind is specified in this element.
• Mechanical Model: It denotes the gearbox and the rotor dynamics.
• Electrical Model: This element simulates the power electronics and the generator.
• Control System: The functionalities of a turbine are handled by this framework. It could include speed control and pitch control.

2. Arranging Simulink Platform

• Initially, we have to open the MATLAB tool. By entering simulink in the MATLAB command window, initiate the Simulink.
• From the Simulink start page, choose “Blank Model” to develop a novel model.

3. Develop the Aerodynamic Model

• Drag and Drop Blocks:
  • Select Simscape > Simscape Components > Thermal > Gas from the Simulink Library Browser.
  • For designing the blade aerodynamics and wind input, append blocks like Blade Element and Wind Profile.
• Configure Wind Profile:
  • To simulate diverse wind speeds periodically, we plan to utilize the Wind Profile block.
  • For clarity, the wind speed pattern has to be specified through a Sine Wave or a Signal Builder block.
• Blade Aerodynamics:
  • In order to depict the aerodynamic forces on the blades, employ a Function Block.
  • For aerodynamic power, describe the function PaeroP_{aero}Paero: Paero=12⋅ρ⋅A⋅v3⋅Cp(λ,β)P_{aero} = \frac{1}{2} \cdot \rho \cdot A \cdot v^3 \cdot C_p(\lambda, \beta)Paero=21⋅ρ⋅A⋅v3⋅Cp(λ,β), in which ρ\rhoρ denotes air density, vvv specifies the wind speed, AAA indicates the rotor area, CpC_pCp is the power coefficient, β\betaβ signifies the blade pitch angle, and λ\lambdaλ is the tip speed ratio.

4. Create the Mechanical Model

• Include Mechanical Blocks:
  • For the Rotor and Gearbox, append blocks from Simscape > SimMechanics > Second Generation > Body Elements.
• Rotor Dynamics:
  • To design the rotor inertia, we utilize a Rotational Inertia block.
  • As a means to depict the aerodynamic torque, link a torque source.
• Gearbox:
  • The transmission among the generator and the rotor has to be simulated through the utilization of a Gearbox block.
  • The gear ratio must be specified and linked to the generator and rotor.

5. Build the Electrical Model

• Append Electrical Components:
  • Specifically for the Power Electronics and Generator, include blocks from Simscape > Electrical > Specialized Power Systems.
• Generator Model:
  • To depict the generator, employ an Induction Generator or Synchronous Machine block.
  • Through a Mechanical Rotational Interface, link the generator to the mechanical model.
• Power Electronics:
  • In order to transform the produced AC power to DC, append a Three-Phase inverter.
  • To simulate grid combination or power utilization, link it to a Grid or Load model.

6. Implement the Control Framework

• Encompass Control Blocks:
  • For Logic Operations and PID Controllers, include blocks from Simulink > Discrete or Continuous libraries.
• Pitch Control:
  • To adapt the blade pitch angle regarding wind speed changes, a pitch control framework has to be applied with a PID Controller.
  • As a means to regulate the power coefficient CpC_pCp, the controller must be linked to the aerodynamic model.
• Speed Regulation:
  • The rotor speed should be preserved at an ideal level by utilizing a speed control loop.
  • To keep constant power output and handle generator torque, apply control logic.

7. Set up the Simulation Platform

• Add Scope and Display Blocks:
  • In order to visualize major parameters such as rotor speed, wind speed, power, and generator output, append Scope and Display blocks from Simulink > Sinks.
• Set Simulation Parameters:
  • Then, select Simulation > Model Configuration Parameters.
  • For adequate preciseness, fix the solver to ode45. The beginning and end times have to be established.

8. Link and Execute the Simulation

• Link All Blocks:
  • It is important to make sure that all the blocks are linked in an appropriate manner. To assure data flows across the framework based on the anticipations, verify the inputs and outputs of every element.
• Execute the Simulation:
  • To initiate the simulation, choose the “Run” button.
  • Track the performance of the framework by utilizing the display and scope blocks.

Sample Simulink Model Structure

Based on the arrangement of Simulink model, we provide a concise overview:

• Aerodynamic Subsystem:
  • Wind Profile (Sine Wave)
  • Blade Element (Function Block)
  • Aerodynamic Power Calculation
• Mechanical Subsystem:
  • Gearbox (Gear Ratio)
  • Rotor (Rotational Inertia)
  • Mechanical Shaft
• Electrical Subsystem:
  • Inverter (Three-Phase Inverter)
  • Generator (Synchronous Machine)
  • Load/Grid Connection
• Control Subsystem:
  • Speed Control (Speed Feedback Loop)
  • Pitch Control (PID Controller)
  • Torque Control

Instance of MATLAB Code for Simulink Initialization

In MATLAB, set the wind turbine parameters before executing the Simulink model by considering the following instance of code snippet:

% Wind turbine parameters

rho = 1.225; % Air density (kg/m^3)

blade_length = 40; % Blade length (m)

rotor_area = pi * blade_length^2; % Rotor swept area (m^2)

Cp_max = 0.45; % Maximum power coefficient

% Wind speed profile

time = 0:10:3600; % Time vector (s)

wind_speed = 10 + 2 * sin(2 * pi * time / 3600); % Wind speed (m/s)

% Simulation settings

simTime = 3600; % Simulation time (s)

set_param(‘wind_turbine_model’, ‘StopTime’, num2str(simTime));

% Run the simulation

sim(‘wind_turbine_model’);

% Plot results

figure;

subplot(2,1,1);

plot(time, wind_speed);

xlabel(‘Time (s)’);

ylabel(‘Wind Speed (m/s)’);

title(‘Wind Speed Profile’);

subplot(2,1,2);

plot(time, rotor_speed);

xlabel(‘Time (s)’);

ylabel(‘Rotor Speed (rpm)’);

title(‘Rotor Speed Over Time’);

9. Examine and Enhance the Simulation

• Review Outcomes:
  • For rotor speed, generator power, wind speed, and other major parameters, examine the scope outputs.
  • Particularly for further enhancement, detect potential areas or any performance challenges.
• Improve Parameters:
  • To improve performance, alter the gear ratio, or the parameters have to be adapted in the PID controller.
  • As a means to assess the impacts of the alterations, re-execute the simulation.
• Check the Model:
  • To check the preciseness of the model, the simulation outcomes must be compared using actual-world data or principles.

Wind Turbine Simulink Projects

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1. Stochastic unit commitment to determine frequency response ramp rate including wind turbines with synthetic inertia and virtual synchronous generator
2. Semi-supervised adversarial discriminative learning approach for intelligent fault diagnosis of wind turbine
3. Optimum geometry of seashell-shaped wind turbine rotor: Maximizing output power and minimizing thrust
4. Study of air compressibility effects on the aerodynamic performance of the IEA-15 MW offshore wind turbine
5. Hydrodynamic analysis of the combined structure of offshore monopile wind turbine foundation and aquaculture cage
6. Towards optimal reliability-based design of wind turbines towers using artificial intelligence
7. A comprehensive multi-objective optimization study for the aerodynamic noise mitigation of a small wind turbine
8. Research on bearing behavior of secant piled bucket foundation for onshore wind turbines
9. Investigation of bamboo-based vertical axis wind turbine blade under static loading
10. Feasibility study of a steel-UHPFRC hybrid tower for offshore wind turbines
11. Integrated design of aerodynamic and anti-flutter performance of offshore wind turbine airfoil based on full information cooperative game method
12. Control and dynamic analysis of a 10 MW floating wind turbine on a TetraSpar multi-body platform
13. One year monitoring of an offshore wind turbine: Variability of modal parameters to ambient and operational conditions
14. Experimental study on mitigating vibration of floating offshore wind turbine using tuned mass damper
15. A novel fault diagnosis method for wind turbine based on adaptive multivariate time-series convolutional network using SCADA data
16. Lateral vibration control of monopile supported offshore wind turbines with toroidal tuned liquid column dampers
17. Numerical and experimental validation of vortex generator effect on power performance improvement in MW-class wind turbine blade
18. Preliminary design and dynamic analysis of constant tension mooring system on a 15 MW semi-submersible wind turbine for extreme conditions in shallow water
19. Spectral ensemble sparse representation classification approach for super-robust health diagnostics of wind turbine planetary gearbox
20. Paired ensemble and group knowledge measurement for health evaluation of wind turbine gearbox under compound fault scenarios