Improving Load Frequency Control of Multi-Area Power System by Considering Uncertainty by Using Optimized Type 2 Fuzzy Pid Controller with the Harmony Search Algorithm

Authors: Mehrdad Mahmudizad, Roya Ahmadi Ahangar

Abstract:

This paper presents the method of designing the type 2 fuzzy PID controllers in order to solve the problem of Load Frequency Control (LFC). The Harmony Search (HS) algorithm is used to regulate the measurement factors and the effect of uncertainty of membership functions of Interval Type 2 Fuzzy Proportional Integral Differential (IT2FPID) controllers in order to reduce the frequency deviation resulted from the load oscillations. The simulation results implicitly show that the performance of the proposed IT2FPID LFC in terms of error, settling time and resistance against different load oscillations is more appropriate and preferred than PID and Type 1 Fuzzy Proportional Integral Differential (T1FPID) controllers.

Keywords: Load Frequency Control, Fuzzy-PID controller, Type 2 fuzzy system, Harmony Search algorithm.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1126291

References:

[1] P. Subbaraj, K. Manickavasagam, Automatic generation control of multi-area power system using fuzzy logic controller, European Transactions on Electrical Power 18 (2008) 266–280.
[2] C.S. Chang, W. Fu, Area load frequency control using fuzzy gain scheduling of PI controllers, Electric Power Systems Research 42 (2) (1997) 145–152.
[3] N. Jaleeli, L.S. VanSlyck, D.N. Ewart, L.H. Fink, A.G. Hoffmann, Understanding automatic generation control, IEEE Transactions on Power Systems 7 (3) (1992) 1106–1112.
[4] J. Talaq, F. Al-Basri, Adaptive fuzzy gain scheduling for load frequency control, IEEE Transactions on Power Systems 14 (1) (1999) 145–150.
[5] O.I. Elgerd, Electric Energy Systems Theory: An Introduction, McGraw-Hill, Q4 1971.
[6] E. Yesil, M. Guzelkaya, I. Eksin, Self-tuning fuzzy PID-type load and frequency controller, Energy Conversion and Management 45 (3) (2004) 377–390.
[7] U. Kumar, R. Sahu , S. Panda, " Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system", Ain Shams Engineering Journal, Vol. 4, pp.409 -421, 2013.
[8] Hamed Shabani, Behrooz Vahidi, Majid Ebrahimpour, cA robust PID controller based on imperialist competitive algorithm for load-frequency control of power systems", ISA Transactions, Vol.52, pp. 88-95, 2013.
[9] E.S. Ali, S.M. Abd-Elazim, "BFOA based design of PID controller for two area Load Frequency Control with nonlinearities", International Journal of Electrical Power & Energy Systems, Vol.51, pp. 224-231, 2013.
[10] K. Naidu, H. Mokhlis, A.H.A. Bakar, "Multiobjective optimization using weighted sum Artificial Bee Colony algorithm for Load Frequency Control", International Journal of Electrical Power & Energy Systems, Vol.55, pp. 657-667, 2014.
[11] Rabindra Kumar Sahu, Sidhartha Panda, Umesh Kumar Rout, "DE optimized parallel 2-DOF PID controller for load frequency control of power system with governor dead-band nonlinearity", International Journal of Electrical Power & Energy Systems, Vol.49, pp. 19-33, 2013.
[12] K. R. M. Vijaya Chandrakala, S. Balamurugan, K. Sankaranarayanan, " Variable structure fuzzy gain scheduling based load frequency controller for multisource multi area hydro thermal system", International Journal of Electrical Power & Energy Systems, Vol. 53, pp. 375-381, 2013.
[13] H. A. Yousef, K. AL-Kharusi, M. H. Albadi, " Load Frequency Control of a Multi-Area Power System: An Adaptive Fuzzy Logic Approach", IEEE Trans. on power system, pp. 1-9, 2014.
[14] O. Abedinia, M.S. Naderi, A. Ghasemi, " Robust LFC in deregulated environment: Fuzzy PID using HBMO", The 10Th international conference on Environment and Electrical Engineering (EEEIC), pp. 1-4, 2011.
[15] H. Bevrani, M. Yasunori, T. Kiichiro, Sequential design of decentralized load frequency controllers using mu synthesis and analysis, Energy Conversion and Management 45 (6) (2004) 865–881.
[16] L.A. Zadeh, The concept of a linguistic variable and its applicate to approximate reasoning-I, Information Sciences 8 (1975) 199–249.
[17] N.N. Karnik, J.M. Mendel, Q. Liang, Type-2 fuzzy logic systems, IEEE Transactions on Fuzzy Systems 7 (6) (1999) 643–658.
[18] P.Z. Lin, C.M. Lin, C.F. Hsu, T.T. Lee, Type-2 fuzzy controller using a sliding-mode approach for application to DC–DC converters, IEE Proceedings – Electric Power Applications 152 (6) (2005) 1482–1488.
[19] S. Barkati, E.M. Berkouk, M.S. Boucherit, Application of type-2 fuzzy logic con-troller to an induction motor drive with seven-level diode-clamped inverter and controlled infeed, Electrical Engineering 90 (2008) 347–359.
[20] Q. Liang, J.M. Mendel, Interval type-2 fuzzy logic systems: theory and design, IEEE Transactions on Fuzzy Systems 8 (5) (2000) 535–550.
[21] J.M. Mendel, Uncertain Rule-Based Fuzzy Logic: Introduction and New Directions, Prentice Hall, USA, 2000.
[22] H. Hagras, Type-2 FLCs: a new generation of fuzzy controllers, IEEE Computational Intelligence Magazine 2 (1) (2007) 30–43.
[23] Power System Operation and Control by N. V. Ramana Published by Pearson, 2010, N. V. RamanaProfessor and Head, Department of Electrical and Electronics Engineering, JNTU College of Engineering, Jagityal, Karimnagar (D), Andhra Pradesh
[24] O. Castillo, L. Aguilar, N. Cázarez, S. Cárdenas, Systematic design of a stable type-2 fuzzy logic controller, Applied Soft Computing 8 (3) (2008) 1274–1279.
[25] http://www.matlabsite.com/4491/fvrp108-pid-tuning-using-fuzzy-logic-video-tutorial.html.
[26] M. Galluzzo, B. Cosenza, A. Matharu, Control of a nonlinear continuous bioreactor with bifurcation by a type-2 fuzzy logic controller, Computers & Chemical Engineering 32 (12) (2008) 2986–2993.
[27] H. Wu, J.M. Mendel, Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems, IEEE Transactions on Fuzzy Systems 10 (5) (2002) 622–639.
[28] D. Wu, An overview of alternative type-reduction approaches for reducing the computational cost of interval type-2 fuzzy logic controllers, in: Proceedings of IEEE International Conference on Fuzzy Systems, FUZZ-IEEE’2012, 2012, pp. 1–8.
[29] C.F. Juang, C.H. Hsu, Reinforcement interval type-2 fuzzy controller design by online rule generation and q-value-aided ant colony optimization, IEEE Trans-actions on Systems, Man, and Cybernetics, Part B: Cybernetics 39 (6) (2009) 1528–1542.
[30] Lee, K. S. and Geem, Z. W., (2005), “A New Meta-Heuristic Algorithm for Continuous Engineering Optimization: Harmony Search Theory and Practice,” Computer Methods in Applied Mechanics and Engineering, 194, pp. 3902-3933.