ANFIS Based Control Design for AGC of a Hydro-hydro Power System with UPFC and Hydrogen Electrolyzer Units

Abstract This paper presents the design of artificial neuro fuzzy inference system (ANFIS) based automatic generation control (AGC) scheme for a two-area hydro-hydro dominating power system. The proposed control scheme is flexible with simple structure and may prove to be a promising tool for considered system in the presence of system non-linearity and for wide range of parametric variations. The ANFIS based control are implemented and the system dynamic responses are obtained considering 1% load disturbance in area-1 and compared with fuzzy and conventional proportional integral (PI) based AGC to show the simplicity and effectiveness of the proposed control. The further improvements in the system dynamic responses with the proposed control are observed by considering the unified power flow control (UPFC) in series with the tie-line and hydrogen aqua electrolyzer units installed at one of the terminal of the control areas. The dynamic performance of the designed control is also evaluated considering the governor dead-band and generation rate constraint (GRC) non-linearity and for wide range of system parametric variations.

[1]  Ramesh C. Bansal.  Overview and literature survey of artificial neural networks applications to power systems (1992 - 2004) , 2006 .

[2]  Aysen Demiroren,et al.  Automatic Generation Control by Using ANN Technique , 2001 .

[3]  Prabhat Kumar,et al.  Current Status of the Indian Power System and Dynamic Performance Enhancement of Hydro Power Systems with Asynchronous Tie Lines , 2003 .

[4]  Rabindra Kumar Sahu,et al.  A hybrid DE–PS algorithm for load frequency control under deregulated power system with UPFC and RFB , 2015 .

[5]  Ramesh C. Bansal,et al.  Bibliography on the fuzzy set theory applications in power systems (1994-2001) , 2003 .

[6]  N. Kamaraj,et al.  Hybrid Neuro Fuzzy approach for automatic generation control in restructured power system , 2016 .

[7]  Gulshan Sharma,et al.  Recurrent ANN based AGC of a two-area power system with DFIG based wind turbines considering asynchronous tie-lines , 2014, 2014 International Conference on Advances in Engineering & Technology Research (ICAETR - 2014).

[8]  Takashi Hiyama,et al.  Intelligent Automatic Generation Control , 2011 .

[9]  I. A. Chidambaram,et al.  Optimized PI+ load–frequency controller using BWNN approach for an interconnected reheat power system with RFB and hydrogen electrolyser units , 2015 .

[10]  Ali Feliachi,et al.  Robust load frequency control using genetic algorithms and linear matrix inequalities , 2003 .

[11]  Tarek Hassan Mohamed,et al.  Decentralized model predictive based load frequency control in an interconnected power system , 2011 .

[12]  Ibraheem,et al.  Recent philosophies of automatic generation control strategies in power systems , 2005, IEEE Transactions on Power Systems.

[13]  Jin Bae Park,et al.  Robust load-frequency control for uncertain nonlinear power systems: A fuzzy logic approach , 2006, Inf. Sci..

[14]  Mohamed Hamdy,et al.  Flatness-based adaptive fuzzy output tracking excitation control for power system generators , 2013, J. Frankl. Inst..

[15]  K. R. Sudha,et al.  Robust decentralized load frequency control of interconnected power system with Generation Rate Constraint using Type-2 fuzzy approach , 2011 .

[16]  Chia-Feng Juang,et al.  Load-frequency control by hybrid evolutionary fuzzy PI controller , 2006 .