Comparative Analysis of Low Voltage Ride Through Techniques of DFIG Connected to Grid using AI Techniques

Abstract

The requirement for clean and eco-friendly energy initiated the production of renewable energy. Wind energy promises attractive features such as bulk power production and reduced maintenance cost. Advancement of technologies in the field of wind turbines and generators made the gates open for attractive investments. Adjustable-speed wind turbines tied to Doubly Fed Induction Generators (DFIG) became the most excellent choice of power utilities due to their low-cost power converters and four-quadrant control of useful and wattless powers. The ability to extract a high amount of power for a specified wind speed is a major advantage of DFIG which attracted Power system Operators (PSOs). Low voltage ride-through and wattless Spower support to the grid are estimated and compared using conventional PI controllers, Artificial Neural Network (ANN), and Random Forest Optimization (RFO) algorithm.