Abstract
Owing to unpredicted power demand, integration of distributed generators and parametric disparity in the system cause the power system more intricacy which in turn affects the frequency and power fluctuation critically. To mitigate these phenomena, an intelligent and efficient automatic generation control (AGC) is indispensable. Therefore, in this paper, an intelligent and robust controller named fuzzy sliding mode controller (FSMC) has been recommended to tackle the AGC problem in a deregulated power system in the presence of distributed generators effectively. Again, to manifest its dominance over SMC, fuzzy-PID and PID controllers, dynamic response of the deregulated system under Poolco, Bilateral and Contract violation conditions has been evaluated and compared. Further, to support the FSMC controller’s ability, another test model has been taken for the AGC study. The gains of these controllers have been enumerated by Gannet Optimization Algorithm (GOA) subjecting to a minimization problem. Exploration phase of GOA involves two steps, namely U- & V-shaped diving patterns of Gannets and exploitation phase again involves two steps namely sudden rotation and random walk of Gannets. These four steps ensures quick convergence of the objective function to its optimal value. Apart from transient response under different power transaction conditions, parametric uncertainties of the system, solar and wind power variation and abrupt load change have been considered to support the robustness & credibility of FSMC controller. In addition to this, the stability of the proposed model has been analyzed in the frequency domain. Finally, the MATLAB/SIMULINK based transient response has been validated by a real-time simulator using OPAL-RT-4510, Xilinx Kintex-7 FPGA software.
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