Wind Farm Layout Optimization Using Genetic Algorithm and Pitch Angle Control
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Date
2021-11
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Addis Ababa University
Abstract
In this study, MATLAB is used to develop wind farm layout optimization and pitch angle control methods
for the wind energy system. The upstream wind turbine reduces the wind speed that passes through the
downwind turbine when numerous wind turbines are arranged in close proximity and at random in a wind
farm. The wake effect is the name for this phenomena. This effect has an impact on the wind farm's energy
production. As a result, while planning and constructing effective wind farms, an optimum layout that takes
into account the wake effect is critical. This research proposes a genetic algorithm-based wind farm layout
optimization methodology for optimal power output while minimizing wake loss. As a result, power output
has increased from 94.25 percent to 96 percent. SIMULINK findings from prior studies for 26, 30, and 32
turbines in a 2000m2 farm area are used to validate this.
The change in wind speed is the other most significant difficulty in wind energy systems.
The power level rises above the authorized safe level when the wind speed exceeds the rated value of the
wind turbine. As a result, the wind turbine rotor is subjected to a highly nonlinear aerodynamic load.
This load causes blade fatigue and vibration, resulting in rotor blade damage. To overcome the load and
manage the quantity of aerodynamic collected power, an Adaptive Fuzzy PID pitch angle controller is
developed in this article. Furthermore, it improved the transient stability of the wind energy system.
When compared to the PID controller, simulations show that the suggested controller is superior in terms of
feasibility, overshoot, and settling time.
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Keywords
Genetic Algorithm, wake effect, Pitch Angle PID controller, Adaptive Fuzzy-PID