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Hybrid adaptive ‘gbest’-guided gravitational search and pattern search algorithm for automatic generation control of multi-area power system

Hybrid adaptive ‘gbest’-guided gravitational search and pattern search algorithm for automatic generation control of multi-area power system

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In this research article, a maiden approach of hybrid adaptive ‘gbest’ guided gravitational search and pattern search (hGGSA-PS) optimization method are proposed for load frequency control (LFC) of multi-area interconnected power system considering the nonlinear effect of generation rate constraint (GRC). At first, the two area single stage thermal–thermal power system with conventional proportional integral derivative (PID) controller is analyzed and the parameters of the PID controller are optimized by the proposed technique. Initially, the ‘gbest’ guided gravitational search algorithm (GGSA) using integral time absolute error (ITAE) fitness function is used and then pattern search (PS) technique is employed to fine-tune the obtained best solution from the GGSA. The supremacy of the hGGSA-PS optimized PID controller is presented by comparing its results with other modern soft computing techniques. Later in order to demonstrate the robustness of the proposed controller, the sensitive analysis is performed. Finally, the proposed technique is extended to a two area multi-source power system. The parameters of the controller for each area are optimized using the novel hGGSA-PS technique. From the simulation results, it can be seen that the proposed technique has superior performance than the prior results with lesser settling time and different performance index values.

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