Abstract
This paper presents the dynamic modeling of an interconnected two equal area of conventional combined cycle gas turbine. In addition, fuzzy logic controllers have been designed and applied to improve speed/load control, temperature control, and air flow control. The coordination between fuzzy- controlled speed signal and fuzzy-controlled temperature control signal has been considered in the design process using fuzzy fuel controller in order to compute the accurate control signal to the fuel system for fast response against the system disturbance. On the other hand, the adaptive neuro-fuzzy inference system (ANFIS) controller is investigated for controlling the model parameter and selection of the proper rule base in order to improve the proposed controller performance. The results demonstrate the superiority of the proposed model with fuzzy logic controller and ANFIS over the conventional model under normal and abnormal conditions. Moreover, the proposed controllers improve effectively the system damping characteristics after a load deviation as the settling time is greatly reduced.
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Acknowledgements
Dr. M. A. Abido would like to acknowledge the support of King Fahd University of Petroleum and Minerals (KFUPM) through the Electrical Power and Energy Systems Research Group.
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Appendix: CCGT
Appendix: CCGT
Table 17 shows the parameter values and the related values of CCGT model.
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Elhosseini, M.A., El Sehiemy, R.A., Salah, A.H. et al. Modeling and control of an interconnected combined cycle gas turbine using fuzzy and ANFIS controllers. Electr Eng 100, 763–785 (2018). https://doi.org/10.1007/s00202-017-0547-x
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DOI: https://doi.org/10.1007/s00202-017-0547-x