Galley Proof 10/05/2019; 11:13 File: his–1-his190269.tex; BOKCTP/ljl p. 1 International Journal of Hybrid Intelligent Systems -1 (2019) 1–10 1 DOI 10.3233/HIS-190269 IOS Press Implementation of bio-inspired optimization algorithms in state feedback control of power system Anju G. Pillai ∗ , Elizabeth Rita Samuel and A. Unnikrishnan Department of Electrical and Electronics Engineering, Rajagiri School of Engineering and Technology, Kerala, India Abstract. Automatic Generation Control (AGC) is an important tool to ensure the stability and reliability of power systems. For stable operation of power systems, the frequency of the system should be reserved within the nominal value. Towards this, the estimation of states is of supreme implication. In this paper, a comparison is made on the estimation of the states using Kalman estimator method and optimal control approach to the Automatic Generation Control (AGC) of an isolated power system. The performance of optimized Linear Quadratic Regulator (LQR) in pole placement is compared with Kalman estimator. Optimization algorithms such as Genetic Algorithm and Particle Swarm Optimization are used to optimize positive definite matrices Q and R, weighting matrices of a LQR controller. Kalman estimator estimates the states of the system by measuring only one output signal which in this paper is mentioned as the change in frequency for the system considered. The comparison is made on the basis of the mean of the variances of the output, using the mentioned approaches. Study is conducted under different noise levels for independent Monte Carlo simulations. Modeling of an isolated power system is done using Simulink/MATLAB. Keywords: Automatic Generation Control (AGC), Genetic Algorithm (GA), Linear Quadratic Regulator (LQR), Particle Swarm Optimization (PSO), kalman estimator, single area power system 1. Introduction 1 Automatic Generation Control (AGC) in a power 2 system is meant to ensure the reliable operation of 3 the system. It is well known that any load change in 4 the system results in frequency deviation [1]. The pri- 5 mary responsibility of AGC is to attain the equilib- 6 rium state by sustaining the nominal frequency of the 7 system. Large frequency deviations can cause dam- 8 ages to the equipment, overload transmission lines, de- 9 grade load performance and negatively affect the per- 10 formance of system protection schemes. Deviation in 11 frequency can also affect the stability of the system, in 12 due course. In order to maintain the stability of the sys- 13 * Corresponding author: Anju G. Pillai, Department of Electrical and Electronics Engineering, Rajagiri School of Engineering and Technology, Kerala, India. E-mail: anjugpillai@gmail.com. tem, imbalances between the load and generation has 14 to be corrected well in time to prevent frequency devi- 15 ation beyond limits. The practice of controlling the fre- 16 quency, resolved by adjusting the production of gener- 17 ating units in response to the load demand, is termed 18 as Automatic Generation Control (AGC). AGC is also 19 stated as Load Frequency Control (LFC) [1]. 20 In power system operation and control, AGC is gain- 21 ing prominence, ever since the electrical power system 22 has started becoming more complex with the inclusion 23 of randomly varying load in different areas, resulting 24 in the rapid variation of the frequency related to the 25 area. In normal cases, the generators working in corre- 26 sponding area will often adjust their power generation 27 to compensate for the frequency variation [2]. 28 To minimize the frequency deviation of the system, 29 AGC functions by varying the power generation [2]. 30 When the power generation is greater than the demand 31 then the frequency of the system increases and vice 32 1448-5869/19/$35.00 c  2019 – IOS Press. All rights reserved uncorrected proof version