Ant lion algorithm for optimized controller gains for power quality enrichment of off-grid wind power harnessing units

The proposed system uses an algorithm that works on the admittance of the system, for estimating the reference values of generated currents for an off-grid wind power harnessing unit (WPHU). The controller controls the voltage and maintains the frequency within the limits while working with both linear and nonlinear loads for varying wind speeds. The admittance algorithm is simple and easy to implement and works very efficiently to generate the triggering signals for the controller of the WPHU. The wind power harnessing unit comprising of a squirrel cage induction generator, a star-delta transformer, a battery storage system and the control unit are modeled using Matlab/Simulink R2019. An isolated transformer with a star-delta configuration connects the load and the generator circuit with the controller to reduce the dc bus voltage and mitigate current in the neutral line. The response of the system during the dynamic loading depends on the best possible compensator proportional-integral (PI) gains. The antlion optimization algorithm is compared with particle swarm optimization and grey wolf optimization and is found to have the advantages of good convergence, high efficiency and fast calculating speed. It is therefore used to extract the optimal values of frequency and voltage PI gains. The simulation results of the control algorithm for the WPHU are validated in a real-time environment in a dSpace1104 laboratory set up. This algorithm is proven to have a quick response, maintain the required frequency, suppress the current harmonics, regulate voltage, help in balancing the load and compensating for the neutral current.