Design of fuzzy-PID controller with derivative filter and its application using firefly algorithm to automatic generation control

In this study we introduced a heuristic and powerful optimization technique called firefly algorithm to tune the coefficients of fuzzy-PID controller along with derivative filter (FPIDF) for the frequency control of a unified power system with thermal non-reheat type turbine. The response of system is observed under Step Load Perturbation (SLP) of 10% in area 1. The frequency stability analysis is carried on two phases. In the first case the system responses are analyzed by giving a perturbation of 10% in area 1 and in later case the system load is increased by 10% for verifying its robustness. The dynamic response of the FPIDF controllers are observed in terms of minimum undershoots, settling time and maximum overshoots. Further the results obtained by this established method are also compared with those of Bacteria Foraging Optimization (BFO) tuned PI controller and Hybrid BFO-PSO tuned PI controller which are published in previous journals.

[1]  E. S. Ali,et al.  Bacteria foraging optimization algorithm based load frequency controller for interconnected power system , 2011 .

[2]  W. C. Andrews,et al.  THE AMERICAN INSTITUTE OF ELECTRICAL ENGINEERS. , 1901, Science.

[3]  Engin Yesil,et al.  Self tuning fuzzy PID type load and frequency controller , 2004 .

[4]  Hansen Yee,et al.  Self-tuning algorithm for automatic generation control in an interconnected power system , 1991 .

[5]  P. S. Nagendra Rao,et al.  A reinforcement learning approach to automatic generation control , 2002 .

[6]  Sidhartha Panda,et al.  Simulation study for automatic generation control of a multi-area power system by ANFIS approach , 2012, Appl. Soft Comput..

[7]  Babu Narayanan,et al.  POWER SYSTEM STABILITY AND CONTROL , 2015 .

[8]  Lalit Chandra Saikia,et al.  Performance comparison of several classical controllers in AGC for multi-area interconnected thermal system , 2011 .

[9]  Charles E. Fosha,et al.  Optimum Megawatt-Frequency Control of Multiarea Electric Energy Systems , 1970 .

[10]  Haluk Gozde,et al.  Automatic generation control application with craziness based particle swarm optimization in a thermal power system , 2011 .

[11]  Mohammad Ali Abido,et al.  AGC tuning of interconnected reheat thermal systems with particle swarm optimization , 2003, 10th IEEE International Conference on Electronics, Circuits and Systems, 2003. ICECS 2003. Proceedings of the 2003.

[12]  Sidhartha Panda,et al.  Hybrid BFOA-PSO algorithm for automatic generation control of linear and nonlinear interconnected power systems , 2013, Appl. Soft Comput..

[13]  Chung-Fu Chang,et al.  Area load frequency control using fuzzy gain scheduling of PI controllers , 1997 .

[14]  Xin-She Yang,et al.  Firefly algorithm, stochastic test functions and design optimisation , 2010, Int. J. Bio Inspired Comput..

[15]  Na Li,et al.  Connecting Automatic Generation Control and Economic Dispatch From an Optimization View , 2014, IEEE Transactions on Control of Network Systems.

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

[17]  Nathan Cohn,et al.  Some Aspects of Tie-Line Bias Control on Interconnected Power Systems [includes discussion] , 1956, Transactions of the American Institute of Electrical Engineers. Part III: Power Apparatus and Systems.