Automatic Load Frequency Control in Three Area Power System Using Fuzzy PI Controller
Keywords:
Automatic Load frequency control, Area control error (ACE), Proportional integral derivative (PID) controller, Fuzzy PI Controller Matlab/Simulation.Abstract
In this paper, the dynamic performance of automatic load frequency control of three-area power system is done by using PI Fuzzy controller. When load changes then, there is drift in system frequency and voltage which in turn leads to loss in generation owing to blackouts and line tripping. Main objectives of automatic load frequency control in each area are to supply load demand and to minimize tie-line power deviations, to minimize transient deviations, to improve steady-state error and to match the output power of generator with change in load. Thus, simulation evaluation is done to know the working of ALFC by building Simulink models in single area, two area and three area power system.
References
Indrajeet Pal, Amit Kumar, Load frequency control of Multi Area Power System with PI Controller. IJAREEIE, Vol. 7, Issue 2 Feb 2018
Surya Prakash , Sunil K. Sinha, Automatic Load Frequency Control of Six area’s Hybrid Multi Generation Power System using Neuro-Fuzzy Intelligent Controller, IITE, Vol 64, 2018 issue 4
Sirisha Annam, Dr. K. Radha Rani, J. Srinu Naick, Automatic Generation Control of Three Area Power System with Artificial Intelligent Controllers, IJAREEIE, Vol 6, Issue 8, August 2017
C. Zhang, L. Jiang, Q. H. Wu, Y. He, and M. Wu, ―Delay-dependent robust load frequency control for time delay power systems,‖ IEEE Trans. Power Syst., vol. 28, no. 3, pp. 2192–2201, Aug. 2013.
H. Trinh, T. Fernando, H. H. C. Iu, and K. P. Wong, ―Quasi-decentralized functional observers for the LFC of interconnected power systems,‖ IEEE Trans. Power Syst., vol. 28, no. 3, pp. 3513–3514, Aug. 2013.
S. Saxena and Y. V. Hote, ―Load frequency control in power systems via internal model control scheme and model-order reduction,‖ IEEE Trans. Power Syst., vol. 28, no. 3, pp. 2749–2757, Aug. 2013.
C. Zhang, L. Jiang, Q. H. Wu, Y. He, and M. Wu, ―Delay-dependent robust load frequency control for time delay power systems,‖ IEEE Trans. Power Syst., vol. 28, no. 3, pp. 2192–2201, Aug. 2013.
H. Trinh, T. Fernando, H. H. C. Iu, and K. P. Wong, ―Quasi-decentralized functional observers for the LFC of interconnected power systems,‖ IEEE Trans. Power Syst., vol. 28, no. 3, pp. 3513–3514, Aug. 2013.
S. Saxena and Y. V. Hote, ―Load frequency control in power systems via internal model control scheme and model-order reduction,‖ IEEE Trans. Power Syst., vol. 28, no. 3, pp. 2749–2757, Aug. 2013.
L. Jiang, W. Yao, Q. H. Wu, J. Y. Wen, and S. J. Cheng, ―Delay-dependent stability for load frequency control with constant and time-varying delays,‖ IEEE Trans. Power Syst., vol. 27, no. 2, pp. 932–941, May 2012.
L. Dong, Y. Zhang, and Z. Gao, "A robust decentralized load frequency controller for interconnected power systems," ISA Trans., vol. 51, pp. 410-419, 5, 2012.
R. Arivoli and I. A. Chidambaram, ―CPSO based LFC for a two-area power system with GDB and GRC nonlinearities interconnected through TCPS in series with the tie-line,‖ Int. J. Comput. Applications, vol. 38, no. 7, pp. 1–10, Jan. 2012.
H. Yousef, M. Hamdy, and E. El-Madbouly, ―Robust adaptive fuzzy semi-decentralized control for a class of large-scale nonlinear systems using input-output linearization concept,‖ Int. J. Robust Nonlinear Control, vol. 20, pp. 27–40, 2010
W. Tan, ―Unified tuning of PID load frequency controller for power systems via IMC,‖ IEEE Trans. Power Systems, vol. 25, no. 1, February 2010.
H. Bevrani and T. Hiyama, ―On load-frequency regulation with time delays: Design and real-time implementation,‖ IEEE Trans. Energy Convers., vol. 24, no. 1, pp. 292–300, Mar. 2009.
H. Shayeghi, H. A. Shayanfar, and A. Jalili, ―Load frequency control strategies: A state-of-the-art survey for the researcher,‖ Energy Conversion and Management. vol. 50, pp. 344–353, 2009.
A. Khodabakhshian and M. Edrisi, ―A new robust PID load frequency controller,‖ Control Eng. Practice, vol. 16, pp. 1069–1080, 2008.
S. H. Hosseini and A. H. Etemadi, ―Adaptive neuro-fuzzy inference system based automatic generation control,‖ Electr. Power Syst. Res,, vol. 78, pp. 1230–1239, 2008.
R. L. Williams II and D. A. Lawrence, Linear State-Space Control Design. Hoboken, NJ, USA: Wiley, 2007.
S. Velusami and I. A. Chidambaram, ―Decentralized biasual mode controllers for load frequency control of interconnected power systems considering GDB and GRC non-linearities,‖ Energy Convers. Manag., vol. 48, pp. 1691–1702, 2007.
C.-F. Juang and C.-F. Lu, ―Load-frequency control by hybrid evolutionary fuzzy PI controller,‖ Proc. Inst. Electr. Eng.—Gener., Transm. Distrib., vol. 153, no. 2, pp. 196–204, 2006.
H. Yousef, M. Hamdy, D. Eteim, and E. El-Madbouly, ―Adaptive fuzzy semi-decentralized control for a class of large-scale nonlinear systems with unknown interconnections,‖ Int. J. Robust Nonlinear Control, vol. 16, pp. 687–708, 2006.
H. J. Lee, J. B. Park, and Y. H. Joo, ―Robust load-frequency control for uncertain nonlinear power systems: A fuzzy logic approach,‖ Inf. Sci., vol. 176, pp. 3520–3537, 2006.
Ibraheem, P. Kumar, and D. P. Kothari, ―Recent philosophies of automatic generation control strategies in power systems,‖ IEEE Trans. Power Syst., vol. 20, no. 1, pp. 346–357, Feb. 2005.
H. Bevrani, Y. Mitani, and K. Tsuji, ―Robust decentralised load-frequency control using an iterative linear matrix inequalities algorithm,‖ Proc. Inst. Electr. Eng.—Generation, Transmission and Distribution. vol. 151, no. 3, May 2004.
N. Hoonchareon, C. Ong, and R. A. Kramer, ―Implementation of an ACE1 decomposition method,‖ IEEE Trans. Power Syst., vol. 17, no. 3, pp. 757–761, Aug. 2002.
J. Talaq and F. Al-Basri, ―Adaptive fuzzy gain scheduling for load frequency control,‖ IEEE Trans. Power Syst., vol. 14, no. 1, pp. 145–150, Feb. 1999.
L. X. Wang, Fuzzy System and Control: Design and Stability Analysis. Englewood Cliffs, NJ, USA: Prentice-Hall, 1994.
Downloads
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
