WSEAS Transactions on Power Systems


Print ISSN: 1790-5060
E-ISSN: 2224-350X

Volume 13, 2018

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.



Model Predictive Control of Nonlinear Interconnected Hydro-Thermal System Load Frequency Control Based Bat Inspired Algorithm

AUTHORS: M. Elsisi, M. A. S. Aboelela, M. Soliman, W. Mansour

Download as PDF

ABSTRACT: Bat Inspired Algorithm (BIA) has recently been explored to develop a novel algorithm for distributed optimization and control. This paper proposes a Model Predictive Control (MPC) of Load Frequency Control (LFC) based BIA to enhance the damping of oscillations in a two-area power system. A two-area hydro-thermal system is considered to be equipped with Model Predictive Control (MPC). The proposed power system model considers generation rate constraint (GRC), dead band, and time delay imposed to the power system by governorturbine, thermodynamic process, and communication channels. BIA is utilized to search for optimal controller parameters by minimizing a time-domain based objective function. The performance of the proposed controller has been evaluated with the performance of the conventional PI controller based integral square error technique , and PI controller tuned by GA in order to demonstrate the superior efficiency of the proposed MPC tuned by BIA. Simulation results emphasis on the better performance of the proposed BIA-based MPC compared to PI controller based on GA and conventional one over wide range of operating conditions, and system parameters variations.

KEYWORDS: Bat Inspired Algorithm (BIA), Load Frequency Control (LFC), Model Predictive Control (MPC).

REFERENCES:

[1] P. Kundur, Power system stability and control, McGraw-Hill; 1994.

[2] H, Saadat, power system analysis, Tata McgrawHill, 2002.

[3] O.I. Elgard, Electrical Energy System theory: an Introduction, McGraw-Hill, New Delhi, 2005.

[4] P, Surya, and S. K. Sinha, “Load frequency control of three area interconnected hydro-thermal reheat power system using artificial intelligence and PI controllers,” International Journal of Engineering, Science and Technology, vol. 4, no. 1, pp. 23-37, 2012.

[5] O. I. Elgerd and C. E. Fosha, “Optimum megawattfrequency control of multiarea electric energy systems,” IEEE Trans. Power App. Syst., vol. PAS89, no. 4, pp. 556–563, Apr. 1970.

[6] C. E. Fosha and O. I. Elgerd , “The megawattfrequency control problem-A new approach via optimal control theory,” IEEE Trans. Power App. Syst., vol. PAS-89, no. 4, pp. 563–577, Apr. 1970.

[7] B, Ahmed, and AM Abdel Ghany, “Performance Analysis and Comparative Study of LMI-Based Iterative PID Load-Frequency Controllers of a Single-Area Power System,” WSEAS TRANSACTIONS on POWER SYSTEMS, vol. 5, no. 2, pp. 85-97, 2010.

[8] S. P. Ghoshal and S. K. Goswami, “Application of GA based optimal integral gains in fuzzy based active power-frequency control of nonreheat and reheat thermal generating systems,” Elect. Power Syst. Res.,vol. 67, pp. 79–88, 2003.

[9] S. P. Ghoshal, “Application of GA/GA-SA based fuzzy automatic generation control of a multi-area thermal generating system,” Elect. Power Syst. Res., vol. 70, pp. 115–127, 2004.

[10] Li. Pingkang, , Zhu Hengjun, and Li Yuyun “Genetic algorithm optimization for AGC of multiarea power systems” TENCON'02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering. Vol. 3. IEEE, 2002.

[11] H. Golpira and H. Bevrani “Application of GA optimization for automatic generation control design in an interconnected power system,” Energy Conversion and Management vo1. 52, no. 5, pp. 2247-2255 , 2011.

[12] Y. L. Abdel-Magid, M. A.Abido “AGC tuning of interconnected reheat thermal systems with particle swarm optimization,” Proc. of the 2003 10th IEEE international conference on electronics, circuits and systems, vol. 1; 2003. pp. 376–9.

[13] H. Gozde, M. C. Taplamacioglu, I. Kocaarslan, and M. A. Senol,“ Particle swarm optimization based PI-controller design to load–frequency control of a two area reheat thermal power system,” J Therm Sci Technol, vol. 30, no. 1, pp. 13-21, 2010.

[14] P, Saravuth, et al, “Design of Optimal Fuzzy Logic based Pl Controller using Multiple Tabu Search Algorithm for Load Frequency Control,” International Journal of Control Automation and Systems, vol. 4, no. 2, pp. 155-164, 2006.

[15] H. Shabani, B. Vahidi, and M. Ebrahimpour, “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, Jan. 2013.

[16] E. S. Ali, and S. M. Abd-Elazim, “Bacteria foraging optimization algorithm based load frequency controller for interconnected power system,” Int. J Electr. Power Energy Syst., vol. 33, no. 3, pp. 633–638, 2011.

[17] E. S. Ali, and S. M. Abd-Elazim, “BFOA based design of PID controller for two area Load Frequency Control with nonlinearities,” Electrical Power and Energy Systems vol. 51, pp. 224–231, 2013.

[18]J. Nanada, S. Mishra, and L. C. Saika, “Maiden application of Bacterial foraging-based optimization technique in multi-area automatic generation control,” IEEE Trans. Power Syst., vol. 24, no. 2, pp. 602-609, May 2009.

[19] E. Camacho and C. Bordons, Model Predictive Control, 2nd ed., Berlin, Germany : Springer, 2004.

[20] D. Rerkpreedapong, N., Atic, and A. Feliachi, “Economy oriented model predictive load frequency control,” in Proc. 2003 Power engineering conf. on large engineering systems, pp. 12-16.

[21] L. Kong and L. Xieo, “A New Model Predictive Control Scheme-based load frequency control,” in Proc. 2007 IEEE International Conf on Cntrl and Automation, pp. 2514-18.

[22] AN. Venkat, IA. Hiskens, JB. Rawlings, and SJ. Wright, “Distributed MPC strategies with application to power system automatic generation control,” IEEE Trans Control Syst Technology, vol. 16, no. 6, pp. 1192-1206, 2008.

[23] TH. Mohamed, H. Bevrani, AA. Hassan, and T. Hiyama, “Decentralized model predictive based load frequency control in an interconnected power system,” Energy Convers Manage, vol. 52, no. 2, pp. 1208-1214, 2011.

[24] Y, Xin-She, “A new metaheuristic bat-inspired algorithm,” Nature inspired cooperative strategies for optimization (NICSO 2010). Springer Berlin Heidelberg, pp.65-74, 2010.

[25] E. S. Ali, “Optimization of power system stabilizers using BAT search algorithm,” International Journal of Electrical Power & Energy Systems, vol. 6, no. 1, pp. 683- 690, 2014.

[26] M. R. Sathya, and M. Mohamed Thameem Ansari, “Load frequency control using Bat inspired algorithm based dual mode gain scheduling of PI controllers for interconnected power system,” International Journal of Electrical Power & Energy Systems, vol. 64, pp. 365-374, 2015.

[27]J.M. Maciejowski, Predictive control with constraints, Prenctice Hall, 2002.

[28] A. Bemporad, M. Morari, and N.L. Ricker, “The MPC simulink library,” Tech. Rep. AUT01-08, Automatic Control Laboratory, ETH, Zurich, Switzerland, 2000.

[29] S. C. Tripathy, R. Balasubramanian, and PS Chandramohanan Nair, “Effect of superconducting magnetic energy storage on automatic generation control considering governor deadband and boiler dynamics,” Power Systems, IEEE Transactions on, vol. 7, no. 3, pp.1266-1273, 1992.

[30]B. Anand, A. Ebenezer Jeyakumar, “Fuzzy logic based load frequency control of hydrothermal system with non-linearities,” International Journal of Electrical and Power Engineering, vol. 3, no. 2, pp. 112-118, 2009.

WSEAS Transactions on Power Systems, ISSN / E-ISSN: 1790-5060 / 2224-350X, Volume 13, 2018, Art. #10, pp. 99-107


Copyright © 2018 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

Bulletin Board

Currently:

The editorial board is accepting papers.


WSEAS Main Site