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•A method of extracting five parameter model of a PV module from manusfacutres data is proposed.•Uses adaptive particle swarm optimization (APSO) with barrier constraints.•considered the effect of solar radiation and cell temperature.•Multi-crystalline and mono-crystalline PV modules technologies are investigated.•Comprehensive comparison between APSO methods, genetic algorithm (GA), differential evalution (DE) and salp swarm optimization (SSO) are conducted.

DC microgrids (DCMGs) have the potential to accelerate the restoration of power systems, enhance grid resilience, and mitigate grid disturbances. The proportional integral (PI) controller designed at rated supercapacitor (SC) voltage, in existing battery-SC based hybrid energy storage system (HESS) integrated DCMG, unable to guarantee both steady state and transient performances simultaneously due to variation in SC operating voltage (Vsco). Hence an in-depth investigation of the impact of varying Vscoon DCMG stability is presented. This paper also proposes an inverted zero-lag controller designed at optimum SC voltage, computed using the adaptive particle swarm optimization (APSO) technique, to mitigate bus voltage fluctuations with enhanced stability over a wide range of Vsco. The proposed method succeeded in mitigating ringing and improving the stability of the DCMG with sufficient bandwidth, phase margin and gain margin with 22%–42% reduction in settling time and 15%–55% reduction in peak overshoot compared to the conventional design methods at lower Vsco. The effectiveness of the proposed controller in reducing DC bus voltage ringing and improving the dynamic performance of DCMG is verified through the use of MATLAB/Simulink simulation and real-time simulator OPAL-RT OP4510.