LQR Tuning Using AIS for Frequency Oscillation Damping


Muhammad Abdillah(1*), Teguh Aryo Nugroho(2), Herlambang Setiadi(3)

(1) Department of Electrical Engineering Faculty of Industrial Technology Universitas Pertamina
(2) Department of Electrical Engineering Faculty of Industrial Technology Universitas Pertamina
(3) Department of Engineering Faculty of Vocational Universitas Airlangga
(*) Corresponding Author


Commonly, primary control, i.e. governor, in the generation unit had been employed to stabilize the change of frequency due to the change of electrical load during system operation. But, the drawback of the primary control was it could not return the frequency to its nominal value when the disturbance was occurred. Thus, the aim of the primary control was only stabilizing the frequency to reach its new value after there were load changes. Therefore, the LQR control is employed as a supplementary control called Load Frequency Control (LFC) to restore and keep the frequency on its nominal value after load changes occurred on the power system grid. However, since the LQR control parameters were commonly adjusted based on classical or Trial-Error Method (TEM), it was incapable of obtaining good dynamic performance for a wide range of operating conditions and various load change scenarios. To overcome this problem, this paper proposed an Artificial Immune System (AIS) via clonal selection to automatically adjust the weighting matrices, Q and R, of LQR related to various system operating conditions changes. The efficacy of the proposed control scheme was tested on a two-area power system network. The obtained simulation results have shown that the proposed method could reduce the settling time and the overshoot of frequency oscillation, which is better than conventional LQR optimal control and without LQR optimal control.


Governor; LQR; LFC; AIS

Full Text:



P.S.R. Murty, Electrical Power Systems, 1st ed., Butterworth-Heinemann, United Kingdom: Elsevier, 2017.

A. Soeprijanto, M. Abdillah, D.F.U. Putra, Mardlijah, and Rusilawati, “Power System Stabilizer Based on Interval Type 2 Fuzzy Sliding Mode Controller for Oscillation Damping on 500kV Java-Bali Electrical Power System, “J. Electrical Systems,” Special Issue 3, pp. 1-11, 2015.

I.B.G. Manuaba, M. Abdillah, A. Priyadi, and M.H. Purnomo, “Coordinated Tuning of PID-based PSS and AVR Using Bacterial Foraging-PSOTVAC-DE Algorithm,” Control and Intelligent Systems, Vol. 43, No. 3, pp. 1-9, 2015.

S. Saxena, “Load Frequency Control Strategy via Fractional-order Controller and Reduced-order Modeling,” International Journal of Electrical Power & Energy Systems, Vol. 104, pp. 603-614, Jan. 2019.

D. Antunes and W.P.M. Heemels, “Linear Quadratic Regulation of Switched Systems Using Informed Policies,” IEEE Transactions on Automatic Control, Vol. 62, No. 6, pp. 2675-2688, Jun. 2017.

G.P. Prajapat, N. Senroy, and I.N. Kar, “Stability Enhancement of DFIGbased Wind Turbine System Through Linear Quadratic Regulator,” IET Generation, Transmission & Distribution, Vol. 12, No. 6, pp. 1331-1338, 2018.

O. Baghani, “Solving State Feedback Control of Fractional Linear Quadratic Regulator Systems Using Triangular Functions,” Communications in Nonlinear Science and Numerical Simulation, Vol. 73, pp. 319-337, July 2019.

A.K. Singh and B.C. Pal, Dynamic Estimation and Control of Power Systems, 1st ed., Cambridge, USA: Academic Press, 2018.

N. Arab, B. Kedjar, A. Javadi, and K. Al-Haddad, “A Multifunctional Single-Phase Grid-Integrated Residential Solar PV Systems Based on LQR Control,” IEEE Transactions on Industry Applications, Vol. 55, No. 2, pp. 2099-2109, March 2019.

H. Asadi, S. Mohamed, C.P. Lim, and S. Nahavandi, “Robust Optimal Motion Cueing Algorithm Based on the Linear Quadratic Regulator Method and a Genetic Algorithm,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 47, No. 2, pp. 238-254, Feb. 2016.

L.B.P. Nascimento, V.P. Pinto, and M.A.B. Amora, “Harmony Search Algorithm with Adaptive Parameters to Optimize the Linear Quadratic Regulator Design,” IEEE Latin America Transactions, Vol. 16, No. 7, pp. 1862-1869, Jul. 2018.

F.T.S. Silva, L.R. Araujo, and D.R.R. Penido, “Optimal Substation Placement in Distribution Systems Using Artificial Immune Systems,” IEEE Latin America Transactions, Vol. 16, No. 2, pp. 505-513, Feb. 2018.

T. Wakui, M. Hashiguchi, K. Sawada, and R. Yokoyama, “Two-stage Design Optimization Based on Artificial Immune System and Mixedinteger Linear Programming for Energy Supply Networks,” Energy, Vol. 170, pp. 1228-1248, March 2019.

W. Zang, Z. Wang, D. Jiang, and X. Liu, “A Kernel-based Intuitionistic Fuzzy C-Means Clustering Using Improved Multi-objective Immune Algorithm,” IEEE Access, Vol. 7, pp. 84565-84579, June 2019.

D. Corus, P.S. Oliveto, and D. Yazdan, “Artificial Immune Systems can Find Arbitrarily Good Approximations for the NP-hard Number Partitioning Problem,” Artificial Intelligence, Vol. 274, pp. 180-196, September 2019.

M. Caetano, A. Zacharakis, I. Barbancho, and L.J. Tardon, “Leveraging Diversity in Computer-aided Musical Orchestration with an Artificial Immune System for Multi-modal Optimization,” Swarm and Evolutionary Computation, Vol. 50, pp. 1-46, Nov. 2019.

I.A. Carvalho and M.A. Ribeiro, “A Node-depth Phylogenetic-based Artificial Immune System for Multi-objective Network Design Problems,” Swarm and Evolutionary Computation, Vol. 50, pp. 1-52, Nov. 2019.

H. Saadat, Power System Analysis, 2nd ed., New York, USA: McGraw-Hill, 2004.

F. Lewis, Optimal Control, Hoboken, USA: John Wiley & Sons, Inc, 1986.

L.N. de Castro and F.J. Von Zuben, “Learning and Optimization Using the Clonal Selection Principle,” IEEE Transaction on Evolutionary Computation, Vol. 6, No. 3, pp. 239-251, 2002.

DOI: https://doi.org/10.22146/ijitee.51192

Article Metrics

Abstract views : 1296 | views : 943


  • There are currently no refbacks.

Copyright (c) 2020 IJITEE (International Journal of Information Technology and Electrical Engineering)

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

ISSN  : 2550-0554 (online)

Contact :

Department of Electrical engineering and Information Technology, Faculty of Engineering
Universitas Gadjah Mada

Jl. Grafika No 2 Kampus UGM Yogyakarta

+62 (274) 552305

Email : ijitee.ft@ugm.ac.id