Adaptive Metaheuristic Moth-Flame Optimized Droop Control Method for DC Microgrids
Elvin Yusubov, Lala Bekirova
Abstract
This paper presents an adaptive virtual resistance (droop) control technique by using the metaheuristic moth-flame optimization (MFO) technique to achieve near-optimal power and current sharing with minimal voltage deviation among DC-DC converters of a DC microgrid. One of the major control challenges, which exist in DC microgrids, is unequal power/current sharing as a result of the non-ideal converter properties and parasitic resistances which increase the stress levels on DC-DC converters thereby reducing their efficient lifetime. Conventional, non-adaptive droop control methods are employed to balance the load currents between the converters by changing the voltage reference proportionally. Another major issue with these strategies is the cause of voltage deviation to balance the load currents. Although these conventional methods are quite popular and simple to implement, their robustness reduces under dynamic voltage and load current changes. To confront these issues, a droop control method whose droop gains are adaptively adjusted to balance the output currents while maintaining the voltage within acceptable ranges. Simulation results demonstrate the superiority of the proposed approach over the traditional strategies.