Double stage controller optimization for load frequency stabilization in hybrid wind-ocean wave energy based maritime microgrid system

The momentum towards reduction of greenhouse gas emissions by reduced use of conventional source in marine power networks as well as significant development of renewable energy resources (RRs) have been the motivating factors for inclusion RRs in hybrid maritime microgrid system (HMμGS) and investigation of consequent frequent control mechanism. This article presents an approach of load frequency control in an independent HMμGS consisting of wind driven generation (WDG), Archimedes wave power generation (AWPG), marine biodiesel generator (MBG), solid-oxide fuel cell (SOFC) energy units, heat pump (HP) and freezer (FZR). The stability of the HMμGS model have been evaluated through the rigorous tests considering non-availability of renewable resources, concurrent random generation of AWPG, load demand, real recorded data of WDG. Comparative performance of several controllers such as PID, PID with filter (PIDN) and PI-(1 + PD) controller are presented with their parameters optimized using genetic algorithmic technique (GA), particle swarm technique (PSO), firefly algorithmic technique (FA), cultural algorithmic technique (CA) and the recent metaheuristic grasshopper algorithmic technique (GOA). The proposed frequency control strategy of HMμGS model is benchmarked by comparative statistical assessment and decision indicators. Finally, sensitivity assessment of GOA tuned PI-(1 + PD) controller under uncertain parametric variations such as; variation of WDG gain, droop factor (R), inertia constant (M) and loading without reoptimizing the optimal base condition values is conducted as an evidence of the sturdiness of the proposed frequency control strategy. The analysis of the results shows that the proposed GOA optimized PI-(1 + PD) control strategy perform much better than other control schemes.