Digital Simulation, Design, Comparitive Analysis of Intelligent Controllers in Adjustable Speed Drives for PQ Enhancement

Abstract

Problem statement: This study deals with the analysis, design and comparison between fuzzy and genetic based adjustable speed drives with respect to the parameters which determines the quality of power. Approach: ASD system using fuzzy controllers provide ride-through capability during voltage sags, reduces harmonics, improves power factor and is highly reliable, whereas by using genetic algorithm optimized ASD systems, the harmonic contents and distortion factor are fairly less and the power factor approaches unity. A feasible test is implemented by building a proto-type intelligent ASD, which is designed and controlled on the basis of proposed considerations. It is verified from the practical point of view that both the new approaches are more effective and acceptable to minimize the harmonic distortion and improve the quality of power. Results: Thus GA’s performance outscores over fuzzy in all power quality parameter measures and the proposed optimizing strategies can be applied to any variable-frequency DC-AC inverters, UPSs and ac drives. Conclusion: Finally, it is deduced that GA is the most efficient methodology to improve the power quality of the adjustable speed drives.