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The output of photovoltaic (PV) systems is significantly impacted by the vagaries of ambient temperature, solar irradiance, and environmental fluctuations. To achieve the utmost attainable power from PV systems, it is desired to be efficient at the maximum power point in diverse weather climates. Maximum power point tracking (MPPT) is used to schedule a designated location from where the highest power can be harvested. In the context of solar photovoltaic systems connected with DC microgrid platforms, this study introduces a recently developed drone squadron optimization (DSO) scheme that tracks the global maximum power point under PSCS difficulties. Furthermore, an exhaustive comparative analysis has been presented among particle swarm optimization (PSO), cuckoo search algorithm (CUSA), and grey wolf optimization (GWO) under different operating environments to endorse the supremacy of the nominated technique. The suggested method performs noticeably faster than many other methods currently in use, and in addition to offering the highest power, it can also use bidirectional power flow regulation in both constant and variable air conditions. Lastly, an MPPT system interfaced with the DC microgrid based on DSO ensures a sustainable and reliable architecture to provide at load in low power generating situations. [ABSTRACT FROM AUTHOR]

Summary: The intermittent nature of renewable energy generation and the variable AC and DC loads are major factors that offer great challenges in power management for AC/DC hybrid microgrids. In this context, this paper presents a coordinated AC frequency vs DC voltage control (CFVC) scheme for managing contemporary renewable energy‐based hybrid AC/DC microgrids. The proposed control strategy enables appropriate power interactions between the AC and DC subgrids while sharing power fluctuations in a coordinated way. Both the AC and DC subgrids support each other in accordance with their normalized relative changes in AC frequency and DC voltage, respectively. The proposed CFVC scheme is designed using fractional‐order‐proportional‐integral‐derivative (FOPID) controllers, and bacterial‐foraging optimization (BFO) method is employed for calculating the design parameters, viz. the controller gains and set‐point orders. A typical photovoltaic (PV) wind‐battery‐based hybrid AC/DC microgrid is modelled and investigated, and the usefulness of the proposed scheme is validated under the renewable energy variations and load perturbations. [ABSTRACT FROM AUTHOR]