Renewable generation uncertainty, dynamic load change, and system parameter variation play a significant role in the performance degradation of non-linear multi-microgrid (MMG) systems. As a result, intelligent contro...
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Renewable generation uncertainty, dynamic load change, and system parameter variation play a significant role in the performance degradation of non-linear multi-microgrid (MMG) systems. As a result, intelligent control becomes the need of the hour for assisting superlative attribute- based consistent electric power. The application of marinepredatoralgorithm (MPA)-based cascaded PD-(1+PI) controller for Automatic Generation Control (AGC) of MMG system is a novel work. A maiden attempt of the MPA is proposed to optimize the parameters of the cascaded PD-(1+PI) controller using the integral time absolute error criterion. To demonstrate its superiority, the proposed algorithm is compared to the genetic algorithm, differential evolution, and grey wolf optimization. MPA then applied to conventional controller PID, cascaded PD-PI controller and proposed PD-(1+PI) controller for frequency control in multi-microgrid system. The robustness of the suggested controller is verified over PID and PD-PI controller by taking step and random load perturbation and integrating the renewable sources like solar and wind with their uncertain nature. The simulation of the investigated interconnected microgrid is carried out in MATLAB/SIMULINK environment. Finally, detailed simulation and hardware in the loop experimental results are presented to confirm the practicality of the proposed approach.
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