A power consensus algorithm for DC microgrids
This work provides a theoretical foundation for distributed power sharing in DC microgrids, addressing the need for scalable and reliable control in renewable energy systems.
The paper proposes a power consensus algorithm for DC microgrids that uses communication among source nodes to adjust injected currents, achieving weighted consensus of power vectors while preserving the weighted geometric mean of source voltages. Convergence is proven via Lyapunov analysis for networks with various load types.
A novel power consensus algorithm for DC microgrids is proposed and analyzed. DC microgrids are networks composed of DC sources, loads, and interconnecting lines. They are represented by differential-algebraic equations connected over an undirected weighted graph that models the electrical circuit. A second graph represents the communication network over which the source nodes exchange information about the instantaneous powers, which is used to adjust the injected current accordingly. This give rise to a nonlinear consensus-like system of differential-algebraic equations that is analyzed via Lyapunov functions inspired by the physics of the system. We establish convergence to the set of equilibria consisting of weighted consensus power vectors as well as preservation of the weighted geometric mean of the source voltages. The results apply to networks with constant impedance, constant current and constant power loads.