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Volume 6 Issue 2
Mar.  2019

IEEE/CAA Journal of Automatica Sinica

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K. Jagatheesan, B. Anand, Sourav Samanta, Nilanjan Dey, Amira S. Ashour and Valentina E. Balas, "Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm," IEEE/CAA J. Autom. Sinica, vol. 6, no. 2, pp. 503-515, Mar. 2019. doi: 10.1109/JAS.2017.7510436
Citation: K. Jagatheesan, B. Anand, Sourav Samanta, Nilanjan Dey, Amira S. Ashour and Valentina E. Balas, "Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm," IEEE/CAA J. Autom. Sinica, vol. 6, no. 2, pp. 503-515, Mar. 2019. doi: 10.1109/JAS.2017.7510436

Design of a Proportional-Integral-Derivative Controller for an Automatic Generation Control of Multi-area Power Thermal Systems Using Firefly Algorithm

doi: 10.1109/JAS.2017.7510436
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  • Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is mea sured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control, automatic generation control (AGC) plays a crucial role. In this paper, multi-area (Five areas: area 1, area 2, area 3, area 4 and area 5) reheat thermal power systems are considered with proportional-integral-derivative (PID) controller as a supplemen tary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm (FFA). The experimental results demonstrated the comparison of the proposed system performance (FFA-PID) with optimized PID controller based genetic algorithm (GA PID) and particle swarm optimization (PSO) technique (PSO PID) for the same investigated power system. The results proved the efficiency of employing the integral time absolute error (ITAE) cost function with one percent step load perturbation (1% SLP) in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot/undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.


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