Adaptive droop control strategy for minimization of circulating current and effective power sharing in DC microgrid

Information from the abstract

Purpose The reliable integration of multiple renewable energy sources into autonomous DC microgrid requires effective power sharing to ensure stable operation. Conventional droop control schemes often face issues, such as loop current sharing and inadequate voltage regulation. This paper introduces an adaptive droop control strategy that dynamically tunes the control parameters to enhance the current distribution and suppress circulating currents under variable operating conditions. Design/Methodology/Approach The strategy uses an adaptive droop coefficient tuned through a modified Droop Index (DI), improving response under varying loads. A 96 V, 1.5 kW solar–battery-based autonomous DC microgrid is modeled and simulated in MATLAB/Simulink along with real-time experimental simulator to validate the approach for four operating scenarios. Findings The findings indicate that the proposed approach confirms a substantial enhancement in current sharing accuracy and suppresses circulating currents compared to conventional droop control. It maintains DC bus voltage to 96 V during dynamic load variations, ensuring stable and reliable operation. Practical implications This approach eliminates circulating currents and improves power sharing in real-time DC microgrid systems. Social implications Enhanced microgrid reliability promotes clean energy access and resilience for communities transitioning to renewable power. Originality/value This study introduces a DI-based adaptive droop strategy that dynamically adjusts droop coefficients in real-time without requiring high-bandwidth communication among converters. The proposed method simultaneously improves current-sharing accuracy and minimizes circulating currents, and its effectiveness is validated through both simulations and real-time hardware-in-the-loop testing using the OPAL-RT platform.

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Related topics: Microgrid Control and Optimization · Advanced Battery Technologies Research · Smart Grid Energy Management