Design of Optimal Linear Quadratic Gaussian (LQG) Controller for Load Frequency Control (LFC) using Genetic Algorithm (G.A) in Power System
(International Journal of Engineering Works)
Vol. 5, Issue 3, PP. 40-49, March 2018
Load Frequency Control, Linear Quadratic Regulator, Linear Quadratic Gaussian, Kalman Filter, Genetic Algorithm
Nowadays power demand is increasing continuously and the biggest challenge for the power system is to provide good quality of power to the consumer under changing load conditions. When real power changes, system frequency gets affected while reactive power is dependent on variation in voltage value. For satisfactory operation the frequency of power system should be kept near constant value. Many techniques have been proposed to obtain constant value of frequency and to overcome any deviations. The Load Frequency Control (LFC) is used to restore the balance between load and generation by means of speed control. The main goal of LFC is to minimize the frequency deviations to zero. LFC incorporates an appropriate control system which is having the capability to bring the frequency of the Power system back to original set point values or very near to set point values effectively after the load change. This can be achieved by using a conventional controller like PID but the conventional controller is very slow in operation. Modern and optimal controllers are much faster and they also give better output response than conventional controllers. Linear Quadratic Regulator (LQR) is an advanced control technique in feedback control systems. It’s a control strategy based on minimizing a quadratic performance index. In despite of good results obtained from this method, the control design is not a straight forward task due to the trial and error involved in the selection of weight matrices Q and R. In this case, it may be hard to tune the controller parameters to obtain the optimal behaviour of the system. The difficulty to determine the weight matrices Q and R in LQR controller is solved using Genetic Algorithm (G.A). In this research Paper, G.A based LQG controller which is the combination of LQR and Kalman Filter is feedback in LFC using MATLAB/SIMULINK software package. Reduction in frequency deviations and settling time was successfully achieved by using LQG Controller with LFC based on G.A.
- Muddasar Ali: Lecturer & Researcher, Faculty of Electrical Engineering, Wah Engineering College (WEC), University of Wah, Pakistan. Email:email@example.com, Cell: +92-332-5417228
- Syeda Tahreem Zahra: Electrical Engineer & Researcher, Department of Electrical Engineering, University of Engineering & Technology (U.E.T), Taxila, Pakistan.
- Khadija Jalal: Lecturer & Electrical Engineer, Faculty of Electrical Engineering, Army Public College of Management & Science (APCOMS), Rawalpindi, Pakistan.
- Ayesha Saddiqa: Lab Engineer & MSc Scholar, Faculty of Electrical Engineering, Army Public College of Management & Science (APCOMS), Rawalpindi, Pakistan.
- Muhammad Faisal Hayat: Lab Engineer & MSc Scholar, Faculty of Electrical Engineering, Wah Engineering College (WEC), University of Wah, Pakistan.
Muddasar Ali, Syeda Tahreem Zahra, Khadija Jalal, Ayesha Saddiqa, Muhammad Faisal Hayat, "Design of Optimal Linear Quadratic Gaussian (LQG) Controller for Load Frequency Control (LFC) using Genetic Algorithm (G.A) in Power System" International Journal of Engineering Works, Vol. 5, Issue 3, PP. 40-49, March 2018.
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