Optimal selection of LQR parameter using AIS for LFC in a multi-area power system

Muhammad Abdillah, Herlambang Setiadi, Adelhard Beni Reihara, Karar Mahmoud, Imam Wahyudi Farid, Adi Soeprijanto


This paper proposes a method to optimize the parameter of the linear quadratic regulator (LQR) using artificial immune system (AIS) via clonal selection. The parameters of LQR utilized in this paper are the weighting matrices Q and R. The optimal LQR control for load frequency control (LFC) is installed on each area as a decentralized control scheme. The aim of this control design is to improve the dynamic performance of LFC automatically when unexpected load change occurred on power system network. The change of load demands 0.01 p.u used as a disturbance is applied to LFC in Area 1. The proposed method guarantees the stability of the overall closed-loop system. The simulation result shows that the proposed method can reduce the overshoot of the system and compress the time response to steady-state which is better compared to trial error method (TEM) and without optimal LQR control.


linear quadratic regulator (LQR); artificial immune system; clonal selection; load frequency control (LFC)

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R. W. W. Atmaja et al., “Optimal design of PID controller in interconnected load frequency control using hybrid differential evolution- particle swarm optimization algorithm,” in Proceedings of 2014 Seminar on Intelligent Technology and Its Applications, 2014.

I. Robandi, “Desain sistem tenaga modern,” Penerbit Andi Yogyakarta, 2006.

M. A. Mahmud, “An alternative LQR-based excitation controller design for power systems to enhance small-signal stability,“ International Journal of Electrical Power and Energy Systems, Vol. 63, pp. 1-7, 2014. crossref

S. K. Pandey et al., ”A literature survey on load frequency control for conventional and distribution generation power systems,” Renewable and Sustainable Energy Reviews, Vol. 25, pp. 318–34, 2013. crossref

Ibraheem et al., “AGC of two area power system interconnected by AC/DC links with diverse sources in each area,” International Journal of Electrical Power and Energy Systems, Vol. 55, pp. 297–304, 2014. crossref

M. R. Sathya, and M. M. T. 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 and Energy Systems, Vol. 64, pp. 365–74, 2015. crossref

X. Hao, and S. Cai-xin, “Artificial immune network classification algorithm for fault diagnosis of power transformer,” IEEE Transaction on Power Delivery, Vol. 22, pp. 930-935, 2007. crossref

I. Idris and A. Selamat, "Negative selection algorithm in artificial immune system for spam detection," in Proceedings of the 2011 IEEE Software Engineering, pp. 379-382, 2011. crossref

Y. Zhuang et al., “Information security risk assessment dased on artificial immune danger theory,” in Proceedings of the 2009 IEEE Computing in the Global Information Technology, 2009, pp. 169-174. crossref

M. W. Yaw et al., “Optimization of the multi-flow rate mode selection for pneumatic dispensing valve system using clonal selection based artificial immune system algorithm,” in Proceedings of the 2011 IEEE Control System, Computing and Engineering, 2011, pp. 327-331. crossref

L. N. de Castro, and J. Timmis, "Artificial immune system: a novel paradigm to pattern recognition," in Proceeding of SOCO, University of Paisley, UK, pp. 67-84, 2002.

E. Hart et al., “Producing robust schedules via an artificial immune

system,” in Proceedings of the International Conference on Electronic Commerce 1998 (ICEC’98), April 6-9, 1998. crossref

E. Hart, and P. Ross, “An immune system approach to scheduling in changing environments,” in Proceedings of The Genetic and Evolutionary Computation Conference 1999 (GECCO’99), July 13-17, 1999.

Y. Li et al., “Improved immune algorithm for reactive power optimization,” in Proceeding of 2013 IEEE Instrumentation and Measurement, Sensor Network and Automation, 2013, pp. 458-462. crossref

Z. Haybar et al., “Dynamic power system stability improvement on single-machine power system using optimal artificial immune system power system stabilizer (OpAISPSS),” in Proceedings of Seminar Nasional Efisiensi dan konversi Energi, 2006.

H. Maryono et al., ”Coordination of power system stabilizer (PSS) and thyristor controlled series capacitor (TCSC) damping controller using AIS via clonal selection,” in Proceeding of Seminar on Intelligent Technology and Its Applications (SITIA), 2006 (In Indonesian Languange).

T. C. Yang et al., “Decentralized power system load frequency control beyond the limit of diagonal dominance,” International Journal of Electrical Power and Energy Systems, Vol. 24, pp. 173-184, 2002. crossref

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