Quasi-dynamic optimal power sharing in isolated DC microgrids

This paper presents an optimization framework for solving the quasi-dynamic optimal power sharing problem in isolated DC microgrids. Said framework involves estimating the nodal-admittance matrix for a reduced model that includes nodes with inverter-based renewable resources. This estimation is not precise, so the uncertainty in the model is directly addressed in the optimization problem by incorporating robust constraints. Different properties of the estimation and optimization algorithms are mathematically studied, and the simulation results obtained in a test system are outlined, wherein the grid is represented by a full dynamic model and the optimization and control correspond to the proposed quasi-dynamic model. Both theoretical and simulation results demonstrate the high performance of the proposed framework. • Optimization framework for power sharing in isolated DC microgrids. • Estimation of nodal-admittance matrix addresses model uncertainty. • Robust constraints handle estimation inaccuracies in optimization. • High performance demonstrated through theoretical and simulation results.