Modeling And Simulating A Wind Energy System Engineering Essay

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We are well aware of the fact that energy can be changed from one form to another. Wind inherently possesses large reservoirs of energy which when converted to other more useable forms of energy as termed as wind power. Wind energy has been stated to be one of the most green and sustainable forms of energy and has been used for centuries to generate or substitute electricity. According to estimates made by different prominent institutions, if wind energy is efficiently utilized it can generate electricity equivalent to about 20% of the world's energy demand whereas the dilemma of the present is that only 1% of that vast potential is being exploited.

The equipment used for the extraction of useful energy from wind is termed as a wind turbine. Each turbine may have varying electricity generation potential which is dominantly controlled by the size of the system. By a general convention, a large wind turbine would probably be able to generate hundreds of megawatts of electric energy which can prove to be sufficient to power hundreds of houses. Alternatively a system may be categorized as a smaller system if it has electricity generation potential close to 100 kW and turbines of such a magnitude may generally be employed for powering small businesses or separate houses. They may also prove useful for powering sailboat batteries or in place of backup generators.

Furling control is generally employed as a check on small wind turbines to control the mechanical power from over speeding. As the rotor starts furling (going against the wind direction) the speed of the wind reduces. As a result, the amount of aerodynamic power picked up by the wind turbine reduces. Furling control presents an economical way of exercising control of the small wind turbines.

Sometimes small wind turbines are powered by permanent magnet generators and efficient control of the load can aid coordination of the speed of these small turbines. Tip speed ratio control method may be employed in order to investigate the highest level of output that can be obtained.

The project investigates the performance of steady-state and its impact on the small wind turbine based on furling control. Also demonstrates a number of simulation studies, carried out on Matlab/Simulink, through using blocks and tools from SimPowerSystems toolbox. It is primarily used to analyze control methods and the models generated by the incorporation of a furling control. Previous studies has collaborated that by using the power system blocks, simulation time is large enough. However, this project will aim to reduce the simulation time, with the implementation of Simulink blocks. Lastly, a wind energy system has been designed and simulated by the use of Simulink to further judge the results of the use of a furling control.

SOFTWARE REPRESENTATION

In order to carry out simulation for the wind turbine systems, a number of simple models were developed and then input into Matlab/Simulink1. Separate models were prepared for each block. Individual models have been created for the various electrical components such as induction generator and element models, transmission model, aerodynamic model and wind models etc.

The initial design of the software development is illustrated in Figure 3.

Figure 3: Wind turbine model

WIND TURBINE MODELING

By designing mathematical models for various system and sub-systems, one can usually develop advanced level methodologies which can then aid the process of comprehending system behavior or planning a developed application. Even with all its inherent imperfections, an efficient model can help in arriving at fruitful conclusions. Wind turbines, which incorporate a number of sub-systems, are innately dynamic systems with a number of time constraints namely; wind, rotor, generator, power electronics, transformers etc.

The wind turbine model is based on the steady-state power characteristics of the turbine. The total power detained from a wind turbine is precise to every turbine and is administered by Ref.

Pwind = 0.5. ρ.v³.A (3)

Where Cp is the turbine power coefficient (b is the blade pitch angle and l is the tip-speed ratio), Pm is the mechanical output power of the turbine, A the turbine swept area, vw the wind speed and r is the air density. Tip-speed ratio is characterized as;

Pwind = 0.5. ρ.v³.A (4)

Where O its rotational speed and R is the turbine radius

The characteristics of Cp_l, for different principles of the pitch angle b, have been shown in Figure 4. According to the figure, there is one particular value of l at which the system possesses maximum efficiency. Additionally, "wind power vs. turbine rotor speed" curves have been demonstrated in the form of Figure 5.

For every wind speed, the point at which the greatest power is generated closely matches the single one value of the turbine speed. By the implementation of a changeable speed control, the speed of the wind turbine can be kept in order when wind speed changes. This is fairly in contrast to the constant exercise of control over speed thus enabling the system to function at the peak of the curve.

Figure 4: Cp_l characteristics, for different values of the pitch angle.

The mechanical output power of the turbine is specified by

Pwind = 0.5. ρ.v³.A (5)

Where Tm is the mechanical torque at the turbine side. The wind turbine mechanical characteristics are expressed in the next formula:

Pwind = 0.5. ρ.v³.A (6)

Where J is the turbine moment of inertia and Tg is the load.

SIMULINK MODEL

Figure 6 demonstrates the model that has been developed in Matlab/Simulink. The wind turbine model has been developed as a subsystem block in Simulink. In conjunction with the other mechanisms for simulation, the wind turbine model has been incorporated as a part of the overall power generation system. The figure given below highlights the fundamental prototyping components: the generator, wind simulation, site input power, wind system data, and wind system output power.

Figure 5: Output power characteristic of the turbine

Figure 6: Wind turbine system simulation

Simulation results

Figure 7: Wind turbine rotor speed

Figure 8: Wind speed Furling Angle

Figure 9: Asynchronous generator current output

Figure 10: The tip speed control Power output of the load

Figure 3 shows the wind system model using tip speed ratio control. Figure 4 and 5 displays the simulation results of the model. Variable speed data,obtained from the Bureau of Meteorology, has been applied to the model after a steady condition of 10 seconds has been attained. The simulation initially starts at a time interval od 1 second but as it proceeds further a steady- state is realized after about 10 seconds have passed. Similarly it can be observed that initially the fuling angle and the rotor speed show an ascending trend but are contained within a time of 10 seconds. (Figure 3)

Conclusion

This research has justified the usabilityof furling control method for small wind turbines. Modeling and the control of a wind turbine by making use of furling dynamics has been outlined and simulated. The analysis was undertaken by using an illustration of a battery charging system.

Results of the simulation pertaining to the output power were displayed alongwith the furling angle of the system. Additionally, a case study for the use of a furling control with a wind turbine system was discussed.

Acknowledgment

It is with a very deep sense of indebtedness that I express my profound gratitude to my supervisor Dr. Thurai Vinay for his being a constant source of inspiration, offering his invaluable suggestions and guidance through out the project.

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