Small-signal modeling based hybrid optimized current and voltage controller for unbalanced DC microgrid

This article mainly focuses on the analysis and design of a dynamic hybrid optimized controllers for unbalanced DC microgrid. Small-signal model analysis of unidirectional boost converter (UBC) and bidirectional converter (BDC) is discussed to get the efficient performance not discussed earlier. The hybrid controller manages the power between BDC and solar with UBC during the unequal loading. The problem associated with nonlinear solar I-V curve effect is expressed by dynamic resistance. It is affected by parametric variation as the operation point of I-V curve, temperature, and solar irradiance. The slower transient response of PI voltage and the current controller is not an effective solution for parametric variations. To address this, a simple hybrid genetic algorithms (GA) based closed current and voltage-controlled loop is designed using proportional-integral (PI) controller. Small-signal model with consideration of dynamic resistance in solar model with UBC connected to BDC fed DC microgrid is described for nonlinear structure. The closed-loop stability of GA-based voltage and the current PI controller are verified under the deviation of load parameters using a bode plot. It covers the overshoot, time response, oscillation, and dynamic stability under the parametric variations. GA PI controller has fast response comparison to Ziegler Nichol's method as settling time, peak overshoot, rise time, and more stable. The comparison of these two methods is described under fixed and variable loading for microgrid by MATLAB/Simulink. Detailed case study for dynamic operation is verified for unequal loading between the system and dc load.

Automated summary

This article focuses on the analysis and design of a dynamic hybrid optimized controllers for unbalanced DC microgrid. The study discusses small-signal model analysis of unidirectional boost converter (UBC) and bidirectional converter (BDC) to improve performance, as well as a genetic algorithm-based closed current and voltage-controlled loop design to address parameter variations affecting controller response speed.