Stability Enhancement of a Power System With Wind Generation Using ANN Based STATCOM
This paper examines the impact of a high penetration of Squirrel Cage Induction Generator wind turbines (SCIGs) on the voltage regulation and reactive power compensation on a grid. It shows that SCIGs slow down voltage restoration after a voltage drop and can lead to voltage and rotor speed instability. When the voltage is restored, SCIGs will absorb reactive power and, if the voltage does not return quickly enough, the generator accelerates and consumes larger amounts of reactive power. This situation is exacerbated if the wind turbine is connected to a weak power system. A static synchronous compensator (STATCOM), can be utilised to maintain the voltage profile and to overcome a transient disturbance after faults. However, existing STATCOMs utilise fixed gain PI controllers that are unable to respond when the system is under extreme conditions such as a three phase to ground fault, sudden wind speed changes, load fluctuations and weak grid support. Therefore, in this work, an artificial neural network (ANN) based self-tuning PI controller is proposed. Simulation studies were conducted to demonstrate the effectiveness of the proposed controller in maintaining the system stability under such conditions.