In power production the renewable energy resources especially wind systems gains much attention in the recent past years. Low Voltage Ride-Through (LVRT) is one of the ultimate governing grid connection prerequisites to be met by Wind Energy Conversion Systems (WECS). Low voltage ride through prerequisite demands management of the mismatch in voltage due to uncertain conditions, which is a challenge for the WECS. Moreover the voltage dips or voltage sag is the utmost prominent power quality issue in power system. In order to maintain the power quality in power system while the usage of Permanent Magnet Synchronous Generator (PMSG) in WECS, a controller circuit can be used. Here the controlling of PMSG is given by the controllers ANFIS (Adaptive Neuro Fuzzy Inference System) and CANFIS (Coactive Neuro Fuzzy Inference System) both are tuned by the hybrid artificial intelligence techniques particle swarm optimization and genetic algorithm. Both controller techniques are used for the LVRT improvement and the performance of the controllers are compared. From the comparison the CANFIS tuned by GAPSO performance is proved to be the best one for the power quality improvement in wind energy conversion system
Volume 11 | 06-Special Issue
Pages: 955-970