  We treat the emerging power systems with direct current (DC) MicroGrids,
characterized with high penetration of power electronic converters. We rely on
the power electronics to propose a decentralized solution for autonomous
learning of and adaptation to the operating conditions of the DC Mirogrids; the
goal is to eliminate the need to rely on an external communication system for
such purpose. The solution works within the primary droop control loops and
uses only local bus voltage measurements. Each controller is able to estimate
(i) the generation capacities of power sources, (ii) the load demands, and
(iii) the conductances of the distribution lines. To define a well-conditioned
estimation problem, we employ decentralized strategy where the primary droop
controllers temporarily switch between operating points in a coordinated
manner, following amplitude-modulated training sequences. We study the use of
the estimator in a decentralized solution of the Optimal Economic Dispatch
problem. The evaluations confirm the usefulness of the proposed solution for
autonomous MicroGrid operation.
