Approximated and Iterative Power Flow Algorithms for Islanded DC Microgrids

The main approach used to model uncertainties in microgrid planning is the Probabilistic Power Flow (PPF). However, this technique has a high computational cost due to the need to solve a system of nonlinear equations for different scenarios of microgrid operation. This paper aims to propose low-cost computational power flow algorithms to evaluate nodal voltages in islanded Direct Current (DC) microgrids under uncertainty. An approximated power flow is proposed based on the Admittance Summation Method for radial microgrids. In addition, iterative power flow algorithms, previously developed by the authors for Alternating Current (AC) microgrids, have been adapted for DC microgrids. The proposed iterative and approximated algorithms were combined with Monte Carlo Simulation to obtain a PPF method. The proposed methods were tested and vali-dated in relation to the Newton-Raphson Method in DC radial microgrids with 33 and 906 nodes and in DC meshed microgrids with 33 e 144 nodes. The results showed that the developed methods have good accuracy and obtain considerable saving in the computational cost of the PPF.