On the Impact of Wireless Jamming on the Distributed Secondary Microgrid Control

The secondary control in direct current microgrids (MGs) is used to restore the voltage deviations caused by the primary droop control, where the latter is implemented locally in each distributed generator and reacts to load variations. Numerous recent works propose to implement the secondary control in a distributed fashion, relying on a communication system to achieve consensus among MG units. This paper shows that, if the system is not designed to cope with adversary communication impairments, then a malicious attacker can apply a simple jamming of a few units of the MG and thus compromise the secondary MG control. Compared to other denial-of-service attacks that are oriented against the tertiary control, such as economic dispatch, the attack on the secondary control presented here can be more severe, as it disrupts the basic functionality of the MG

A power consensus algorithm for DC microgrids

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.Comment: Abridged version submitted to the 20th IFAC World Congress, Toulouse, Franc

Two-Stage Consensus-Based Distributed MPC for Interconnected Microgrids

In this paper, we propose a model predictive control based two-stage energy management system that aims at increasing the renewable infeed in interconnected microgrids (MGs). In particular, the proposed approach ensures that each MG in the network benefits from power exchange. In the first stage, the optimal islanded operational cost of each MG is obtained. In the second stage, the power exchange is determined such that the operational cost of each MG is below the optimal islanded cost from the first stage. In this stage, a distributed augmented Lagrangian method is used to solve the optimisation problem and determine the power flow of the network without requiring a central entity. This algorithm has faster convergence and same information exchange at each iteration as the dual decomposition algorithm. The properties of the algorithm are illustrated in a numerical case study