A Novel Droop Control Model for Optimizing Standalone DC Microgrid Operation Considering Load and Renewable Uncertainties

Maintaining stable bus voltage and accurate current sharing among distributed generators (DGs) are key challenges in DC microgrids, often with conflicting control goals. Improved current sharing can lead to increased voltage deviation due to unequal line resistances, while minimizing voltage deviation can cause imbalance in current distribution. Conventional droop control methods use fixed droop resistance, which limits their flexibility. This paper proposes an enhanced droop control model that adaptively adjusts droop resistance based on real-time load conditions and incorporates economic objectives into the control strategy. Unlike traditional approaches, the proposed method considers generation cost alongside current sharing and voltage regulation. To address the uncertainties introduced by variable solar and wind power, as well as fluctuating load demand, a scenario-based analytical method is used. A multi-objective marine predator optimization algorithm is developed to achieve optimal operation of the microgrid. The proposed model is evaluated on modified 6-bus and 33-bus systems and a microgrid integrated with a scheduled battery energy management system. Comparative results with other optimization methods demonstrate that the proposed approach achieves better tradeoffs among control accuracy, cost-efficiency, and robustness under uncertainty.