Hybrid alopex based DECRPSO algorithm optimized Fuzzy-PID controller for AGC
This paper is corroborated the hybrid Alopex based DECRPSO algorithm (ADECRPSO) over DE, ADE, PSO, and CRPSO algorithms to pursuit the gain parameters of the PID and Fuzzy PID (FPID) controller. In a two area thermal-hydro-diesel power system, primacy of FPID controller is endorsed with PID controller tuned with assorted techniques. The hybrid ADECRPSO algorithm is affirmed over above mentioned algorithms to tune PID controller in a two area hydro-thermal system. PSO, DE, CRPSO, ADE and ADECRPSO are executed individually to optimize the controller to enhance the transient analysis by conceding undershoot, overshoot, and settling time of the system. The compilation of advantages of alopex based DE and craziness based PSO causes an adequate hybrid algorithm which enhances the performance of Automatic Generation Control (AGC). The step load uprise in area-1 is imposed to observe the activities of AGC. Undeniably, FPID controller optimized by ADECRPSO commits superior performance over PSO, DE, CRPSO, and ADE optimized controller as proposed AGC system. So, the modified mutation of DE by alopex scheme enhances the potentiality to tune the system variables.
Kundur P. S., 2011. Power System Stability and Control, vol. 46, no. 0.
Cohn N., 1957. Tie-Line Bias Control, pp. 1415–1436, 1957.
Fosha E., 1970. Megawatt-Frequency Control Multi area Electric Energy Systems, no. 4, pp. 556–563.
Kumar P., Kothari D. P., and Member S., 2005. Recent Philosophies of Automatic Generation Control Strategies in Power Systems, vol. 20, no. 1, pp. 346–357.
Khodabakhshian A. and Hooshmand R., 2010. A new PID controller design for automatic generation control of hydro power systems, Int. J. Electr. Power Energy Syst., vol. 32, no. 5, pp. 375–382.
Shabani H., Vahidi B., and Ebrahimpour M., 2013. A robust PID controller based on imperialist competitive algorithm for load-frequency control of power systems, ISA Trans., vol. 52, no. 1, pp. 88–95.
Dash P., Saikia L. C., and Sinha N., 2016. Flower Pollination Algorithm Optimized PI-PD Cascade Controller in Automatic Generation Control of a Multi-area Power System, Int. J. Electr. Power Energy Syst., vol. 82, pp. 19–28.
Dash P., Saikia L. C., and Sinha N., 2014. Comparison of performances of several Cuckoo search algorithm based 2DOF controllers in AGC of multi-area thermal system, Int. J. Electr. Power Energy Syst., vol. 55, pp. 429–436.
Sahu R. K., Panda S., Rout U. K., and Sahoo D. K., 2016. Teaching learning based optimization algorithm for automatic generation control of power system using 2-DOF PID controller, Int. J. Electr. Power Energy Syst., vol. 77, pp. 287–301.
Zadeh L. A., 1965. Fuzzy sets, Inf. Control, vol. 8, no. 3, pp. 338–353.
Chown G. A. and Hartman R. C., 1997. Design and experience with a fuzzy logic controller for automatic generation control (AGC), IEEE Trans. Power Syst., vol. 13, no. 3, pp. 352–357.
Yeşil E., Güzelkaya M., and Eksin I., 2004. Self-tuning fuzzy PID type load and frequency controller, Energy Convers. Manag., vol. 45, no. 3, pp. 377–390.
Nayak J. R., Pati T. K., Sahu B. K., and Kar S. K., 2015. Fuzzy-PID controller optimized TLBO algorithm on automatic generation control of a two-area interconnected power system, IEEE Int. Conf. Circuit, Power Comput. Technol. ICCPCT 2015, pp. 4–7.
Sahu B. K., Pati T. K., Nayak J. R., Panda S., and Kar S. K., 2016. A novel hybrid LUS-TLBO optimized fuzzy-PID controller for load frequency control of multi-source power system, Int. J. Electr. Power Energy Syst., vol. 74, pp. 58–69.
Sahu B. K., Pati S., Mohanty P. K., and Panda S.,2015. Teaching-learning based optimization algorithm based fuzzy-PID controller for automatic generation control of multi-area power system, Appl. Soft Comput. J., vol. 27, pp. 240–249.
Sahu R.K., Panda S., and Chandra Sekhar G.T., 2015. A novel hybrid PSO-PS optimized fuzzy PI controller for AGC in multi area interconnected power systems, Int. J. Electr. Power Energy Syst., vol. 64, pp. 880–893.
Nayak J. R., Sahu B. K., and Pati T. K., 2016. Load frequency control of a two-area non-reheat thermal system using Type-2 Fuzzy system optimized DEPSO algorithm, in 2015 International Conference on Energy, Power and Environment: Towards Sustainable Growth, ICEPE 2015, vol. 2, no. 1, pp. 0–4.
Gozde H., Cengiz Taplamacioglu M., and Kocaarslan İ., 2012. Comparative performance analysis of Artificial Bee Colony algorithm in automatic generation control for interconnected reheat thermal power system, Int. J. Electr. Power Energy Syst., vol. 42, no. 1, pp. 167–178.
Guha D., Roy P. K., and Banerjee S., 2016. Load frequency control of interconnected power system using grey Wolf optimization, Swarm Evol. Comput., vol. 27, pp. 97–115.
Dash P., Saikia L. C., and Sinha N., 2015. Automatic generation control of multi area thermal system using Bat algorithm optimized PD-PID cascade controller, Int. J. Electr. Power Energy Syst., vol. 68, pp. 364–372.
Sahu R. K., Panda S., and Pradhan S., 2015. A hybrid firefly algorithm and pattern search technique for automatic generation control of multi area power systems, Int. J. Electr. Power Energy Syst., vol. 64, pp. 9–23.
Nanda J., Mishra S., and Saikia L. C., 2009. Maiden application of bacterial foraging-based optimization technique in multiarea automatic generation control, IEEE Trans. Power Syst., vol. 24, no. 2, pp. 602–609.
Sahu R. K., Panda S., and Pradhan S., 2015. A novel hybrid gravitational search and pattern search algorithm for load frequency control of nonlinear power system, Appl. Soft Comput., vol. 29, pp. 310–327.
Kennedy J. and Eberhart R., 1995. Particle swarm optimization,” Neural Networks, 1995. Proceedings., IEEE Int. Conf., vol. 4, pp. 1942–1948 vol.4.
Ghoshal S. P., 2004. Optimizations of PID gains by particle swarm optimizations in fuzzy based automatic generation control, Electr. Power Syst. Res., vol. 72, no. 3, pp. 203–212.
Panda S., Mohanty B., and Hota P. K., 2013. Hybrid BFOA–PSO algorithm for automatic generation control of linear and nonlinear interconnected power systems, Appl. Soft Comput., vol. 13, no. 12, pp. 4718–4730.
Storn R. and Price K., 1997. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces, J. Glob. Optim., vol. 11, no. 4, pp. 341–359.
Rout U. K., Sahu R.K., and Panda S., 2013. Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system, Ain Shams Eng. J., vol. 4, no. 3, pp. 409–421.
Zhang W. J. and Xie X. F., 2003. DEPSO: Hybrid Particle Swarm with Differential Evolution Operators, Proc. 2003 IEEE Int. Conf. Syst. Man Cybern., vol. 4, no. 1, pp. 3816–3821.
Pati S., Sahu B. K., and Panda S., 2014. Hybrid differential evolution particle swarm optimisation optimised fuzzy proportional–integral derivative controller for automatic generation control of interconnected power system, IET Gener. Transm. Distrib., vol. 8, no. 11, pp. 1789–1800.
Tzanakou E., Michalak R., and Harth E., 1979. The Alopex process: Visual receptive fields by response feedback, Biol. Cybern., vol. 35, no. 3, pp. 161–174.
Leon M., 2017. Alopex-Based Mutation Strategy in Differential Evolution, pp. 1978–1984.
Kar R., Mandal D., Mondal S., and Ghoshal S. P., 2012. Craziness based Particle Swarm Optimization algorithm for FIR band stop filter design, Swarm Evol. Comput., vol. 7, pp. 58–64.
Saha S. K., Kar R., Mandal D., and Ghoshal S. P., 2013. An efficient craziness based particle swarm optimization technique for optimal IIR filter design, Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 8160, pp. 230–231.
Upadhyay P., Kar R., Mandal D., and Ghoshal S. P., 2014. Craziness based particle swarm optimization algorithm for IIR system identification problem, AEU - Int. J. Electron. Commun., vol. 68, no. 5, pp. 369–378.
Nayak J.R., & Shaw B., 2017. Load frequency control of hydro-thermal power system using fuzzy PID controller optimized by hybrid DECPSO algorithm, Int. Jrnl. Of Pure Appl. Math., vol. 114, no. I, pp. 3–6.
Nayak J.R., Shaw B., and Sahu B.K., 2018. Application of adaptive-SOS (ASOS) algorithm based interval type-2 fuzzy-PID controller with derivative filter for automatic generation control of an interconnected power system, Int. J. Engineering Science and Technology. https://doi.org/10.1016/j.jestch.2018.03.010.
Nayak J.R., Shaw B., Das S., and Sahu B.K., 2018. Design of MI fuzzy PID controller optimized by Modified Group Hunting Search algorithm for interconnected power system”, Microsyst. Technol. 3, 1432–1858. https://doi.org/10.1007/s00542-018-3788-3.
Khadanga R. K., & Kumar A., 2017. Hybrid adaptive “gbest”-guided gravitational search and pattern search algorithm for automatic generation control of multi-area power system, IET Generation, Transmission & Distribution, 11(13), 3257–3267.
Sahu R.K., Panda S., & Pradhan S., 2015. A hybrid firefly algorithm and pattern search technique for automatic generation control of multi area power systems, Int. J. Electr. Power Energy Syst., 64, 9–23. https://doi.org/10.1016/j.ijepes.2014.07.013.
Nayak J.R., & Shaw B., 2018. Application of Group Hunting Search Optimized Cascade PD-Fractional Order PID Controller in Interconnected Thermal Power System, 4(3), 22–33. https://doi.org/10.17737/tre.2018.4.3.0047.