Vol 5 Issue 1 January 2018-March 2018
Kavita Nayak, Shraddha Ramani
Abstract:This paper presents the importance of soft computing techniques in Wind Generation System. Since wind speeds typically vary over a wide range, the turbine speed needs to be continuously adjusted so that its power output can be maximized and also it usually leads to better result than those of the conventional controllers. Many researchers have studied and performed the simulations in wind generation system using different soft computing technique. The purpose of the study is to do comparisons of various soft computing techniques used for improvement of wind form model. In wind generation system different techniques like particle swarm optimization, generalized regression neural network (GRNN), fuzzy logic control, genetic algorithm, mean variance optimization algorithm etc. has been used for efficiency optimization and performance enhancement control. The characteristics and merits of these techniques on wind form model is then compared and studied. After studying the different soft computing technique it is found that a system using the fuzzy controller based amongst the other soft computing techniques shows more accurate control performances.
Keywords:Doubly fed induction generator, direct power control, grid side converter, rotor side converter, particle swarm optimization, fuzzy lozzy controller.
Title: Comparative Analysis on Soft Computing Based Wind Farm Model
Author: Kavita Nayak, Shraddha Ramani
ISSN 2349-7815
International Journal of Recent Research in Electrical and Electronics Engineering (IJRREEE)
Paper Publications