Example Code
Overview
As the importance of environmental protection and sustainable growth increases, wind energy, a clean and renewable energy, attracts increasing attention. The doubly-fed induction generator (DFIG)-based wind power system is one of the main wind turbine systems because of the system’s ability to improve wind power system efficiency and to reduce costs. Designing and researching more effective controllers for this system is a hot topic. This article introduces the doubly-fed wind power system and describes how the LabVIEW Control Design and Simulation Module can help you design controllers for this complex system.
Introduction to a Wind Power System
The following figure shows the main components of a wind power system.
Figure 1. A Wind Power System and its Main Components
The main components of this system are the wind turbine, the mechanical drive train, the generator, the power grid, and the controller. The wind turbine converts the kinetic energy of the wind into mechanical energy. The generator converts the mechanical energy into electrical energy. The controller is the “brain” of the system. It ensures that the whole system works as expected.
The mechanical power Pmech is extracted from the wind. The following formula describes Pmech:
Pmech = 0.5 ρπR2v3Cp(λ,Ѳ)
where Pmech is the mechanical power
ρ is the air density
R is the turbine’s radius
v is the wind speed
Cp is the power coefficient
λ is the tip speed ratio
Ѳ is the pitch angle
λ is defined as:
where ωm is the turbine rotation speed
R is the turbine’s radius
v is the wind speed
The extracted mechanical power Pmech is proportional to the cube of the wind speed v. The power coefficient Cp affect Pmech. Cp is a function of the tip speed ratio λ and of the pitch angle Ѳ. λ describes the ratio between the system rotational speed ωm and v. Ѳ is the angle between the wind flow direction and the turbine blade. Increasing Ѳ moves the blades out of the wind, thereby reducing the effective wind area.
Figure 2 describes how Ѳ and λ affect Cp.
Figure 2. Cp as a Function of the Pitch Angle Ѳ and of the Tip Speed Ratio λ
In the previous figure, the blue lines are the power coefficients depending on Ѳ and λ. Physically, the greater the pitch angle, the smaller the effective wind area. On figure 2 you can see that as a consequence, the greater the pitch angle, the smaller the power coefficient. For one particular pitch angle, there exists an optimal tip speed ratio that maximizes the power coefficient Cp. The red dot in figure 2 corresponds to the optimal wind energy utilization point.
The Challenges of Designing a Wind Power System Controller: Variable-Speed, Constant-Frequency Operation
Compared with other power generation systems, some unique features of the wind power system make designing the controller challenging. To better utilize wind energy and make wind energy competitive with other forms of energy from an economical perspective, it is desirable to operate the turbine at its most efficient point. In the previous figure, the red circle represents the point at which the turbine operates most efficiently. To operate the turbine efficiently requires keeping the tip speed ratio at its optimal value. So when the wind speed changes, the system rotation speed should change correspondingly to keep the tip speed ratio at its optimal value. The rotational speed of the generator is directly proportional to the frequency of the generated electricity. However, the power grid only accepts fixed frequency (60 Hz in US) electricity. So the variable-speed, constant-frequency requirement is a big challenge for the wind turbine controller’s design.
The Ideal Operation Curve of the Wind Turbine
Wind turbines operate in a certain range of wind speed. When the wind speed is less than normal, usually 12 meters per second (m/s), the turbine extracts less energy than the rated power. In this case, the turbine is expected to operate at its most efficient point by using the variable-speed, constant-frequency operation and to extract as much energy as possible. When the wind speed is greater than normal, the turbine must limit its energy utilization to keep the extracted energy at the maximum allowable level. Otherwise, if the turbine generates too much energy, the over-load might damage the whole turbine system. Usually the controller leverages the pitch angle control to limit the power absorption. Figure 3 shows this ideal operation curve. You can see the power optimization phase, below 12 m/s, and the power limitation phase above 12 m/s.
Figure 3. Ideal Operation Curve of a Wind Turbine
Doubly-Fed Induction Generator Based Wind Turbine System
The DFIG-based wind turbine system is one of the main variable-speed wind power systems. Figure 4 displays its system diagram.
Figure 4. System Diagram of a DFIG-Based Wind Turbine System
In figure 4, Pmech is the extracted mechanical power
Ptotal is the total generated electrical power
Ps is the power from the stator to the grid
Pr is the power from the rotor to the grid
ωr is the rotor rotational speed
ωs is the synchronous speed
One characteristic of the DFIG-based wind turbine system is the bidirectional power flow of the rotor. When ωr >ωs, the power flows from the rotor to the power grid. When ωr <ωs, the rotor absorbs the energy from the power grid.
Similar to a traditional power system, the stator of the generator directly connects to the power grid. Unlike in the traditional power system, the rotor of the generator connects to the power grid through power electronic converters. So in this system, the energy is delivered to the power grid not only by the stator, but also by the rotor. Hence, this system is called “doubly-fed”.
These power electronic converters adjust the frequency and amplitude of the rotor voltage. The control of the rotor voltage allows this system to operate at a variable-speed while still producing constant frequency electricity.
LabVIEW Control Design and Simulation Module – A Tool to Research and Study the Wind Power System
For systems like the wind power system, researchers and engineers are unlikely to test and verify control algorithms directly on the real system because of cost and safety concerns. One alternative to a real system is to design and verify control strategies on a numerical simulation environment.
The LabVIEW Control Design and Simulation Module provides a numerical simulation environment to help study the wind power dynamic system. You can design and verify your controller with this environment. National Instruments also provides case study examples of the doubly-fed wind power system. These examples can be the starting point for research work on this kind of system.
Figure 5 is an example of a simulation diagram of the doubly-fed wind power system.
Figure 5. Simulation Diagram of the Doubly-Fed Wind Power System Using the LabVIEW Control Design and Simulation Module
Controller Design and Verification
According to figure 3, the goal in designing the controller is to achieve the ideal operation curve. The controller consists of two parts. The first part is the master controller. The second part is the generator controller. Figure 6 displays this architecture.
Figure 6. Architecture of the Controller
During the power optimization stage, the master controller adjusts the system rotation speed to keep the optimal tip speed ratio. The speed regulation works by controlling the power of the generator. During the wind power limitation stage, the master controller regulates the pitch angle to limit the wind power utilization.
The generator controller is in charge of accurately controlling the active power of the system. The generator controller adopts the stator flux oriented vector control strategy [1]. This strategy converts the generator’s current and voltage into a reference frame which rotates at the synchronous speed. The d axis of this reference frame aligns with the stator flux vector. Figure 7 displays the strategy’s vector graph. 
Figure 7. Vector Graph of the Stator Flux Oriented Vector Control Strategy
In figure 7, ωr is the rotor rotational speed
ωs is the synchronous speed
The relationship between the power and the current becomes linear in this rotating frame. The set point of the power can convert into the set point of the current. The linear relationship between the power and the current makes the control less difficult.
Figure 8 shows the generator controller diagram.
Figure 8. Block Diagram of the Generator Controller
The controller first converts the current and voltage into the rotating reference frame. On figure 8, you can observe that the VIs in the left red circle perform the transform. Then the controller performs Proportional Integral (PI) control in the rotating reference frame. The controller then transforms the voltage signals back to the original frame, which you can observe on figure 8 as being performed by the VIs in the right red circle.
Examples of Controller Design and Verification
Power Optimization
You can verify the controller’s behavior in the power optimization stage. Figure 9 shows how the doubly-fed wind turbine system reacts to a change in the wind speed, from 8.5m/s to 10.5m/s.
Figure 9. Reaction of the Doubly-Fed Wind Turbine System to a Change in Wind Speed in the Power Optimization Stage
The graph Ir.a (p.u.) indicates the rotor's current in phase A, referring to the three phases, A, B and C existing in a three-phase current. This current is represented in p.u, which means “per unit”, or that the values have been normalized.
As you can see on the generator speed graph on figure 9, the controller reacts quickly to adjust the rotational speed of the generator so that the controller can keep the tip speed ratio at its optimal value. The graph Ir.a (p.u.) shows how the rotor current frequency changes with the rotational speed of the generator. The graph Ir.a (p.u.) also verifies that the frequency of the rotor current is proportional to the deviation of the generator speed from the normal speed (1 p.u.). When the generator speed is close to 1 p.u. at 4.5 seconds (Time = 4.5), the rotor current Ir.a (p.u.) nearly becomes a DC current. Eventually the two power graphs Pr (p.u.) and Ps (p.u.) show that as the wind speed increases, the power that arrives to the power grid increases.
Power Limitation
Figure 10 verifies the controller’s behavior in the power limitation stage. The pitch angle graph shows that the controller reacts quickly to adjust the pitch angle in order to limit the wind power utilization when the wind speed is greater than 12m/s.
Figure 10. Reaction of the Doubly-Fed Wind Turbine System to a High Wind Speed in the Power Limitation Stage
As the pitch angle increases, the power coefficient Cp decreases correspondingly. After the speed transient which takes place between Time=1 and Time=5, the controller maintains the rotational speed of the generator and the power coefficient at their maximum allowable values.
Conclusion
This article briefly introduces the doubly-fed wind power system and describes how you can design and verify its controller using the LabVIEW Control Design and Simulation Module. The examples of the doubly-fed wind power system are available in this module. To access the examples, open the LabVIEW graphical development environment. In the NI Example Finder window, select Toolkits and Modules»Control and Simulation»Electrical Machine.
You can download an evaluation copy of the LabVIEW Control Design and Simulation Module.
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Reference
[1] Pena R., Clare J.C., Asher G.M., May 1996. “Doubly fed induction generator using back-to-back PWM converters and its application to variable-speed wind-energy generation”. IEEE Proc.- Electr. Power Appl. Vol. 143, No.3.
Example code from the Example Code Exchange in the NI Community is licensed with the MIT license.
