Adaptive neuro-fuzzy inference system to improve the power quality of a split shaft microturbine power generation system

OĞUZ Y., Ustun S. V. , YABANOVA İ., Yumurtaci M., Guney I.

JOURNAL OF POWER SOURCES, vol.197, pp.196-209, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 197
  • Publication Date: 2012
  • Doi Number: 10.1016/j.jpowsour.2011.09.057
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED)
  • Page Numbers: pp.196-209
  • Acibadem Mehmet Ali Aydinlar University Affiliated: Yes


This article presents design of adaptive neuro-fuzzy inference system (ANFIS) for the turbine speed control for purpose of improving the power quality of the power production system of a split shaft microturbine. To improve the operation performance of the microturbine power generation system (MTPGS) and to obtain the electrical output magnitudes in desired quality and value (terminal voltage, operation frequency, power drawn by consumer and production power), a controller depended on adaptive neuro-fuzzy inference system was designed. The MTPGS consists of the microturbine speed controller, a split shaft microturbine, cylindrical pole synchronous generator, excitation circuit and voltage regulator. Modeling of dynamic behavior of synchronous generator driver with a turbine and split shaft turbine was realized by using the Matlab/Simulink and SimPowerSystems in it. It is observed from the simulation results that with the microturbine speed control made with ANFIS, when the MTPGS is operated under various loading situations, the terminal voltage and frequency values of the system can be settled in desired operation values in a very short time without significant oscillation and electrical production power in desired quality can be obtained. Crown Copyright (C) 2011 Published by Elsevier B.V. All rights reserved.