Marko Angjelichinoski

Pietro Danzi, Marko Angjelichinoski, Čedomir Stefanović et al.

In standard implementations of distributed secondary control for DC MicroGrids (MGs), the exchange of local measurements among neighboring control agents is enabled via off-the-shelf wireless solutions, such as IEEE 802.11. However, Denial of Service (DoS) attacks on the wireless interface through jamming prevents the secondary control system from performing its main tasks, which might compromise the stability of the MG. In this paper, we propose novel, robust and secure secondary control reconfiguration strategy, tailored to counteract DoS attacks. Specifically, upon detecting the impairment of the wireless interface, the jammed secondary control agent notifies its peers via a secure, low-rate powerline channel based on Power Talk communication. This triggers reconfiguration of the wireless communication graph through primary control mode switching, where the jammed agents leave the secondary control by switching to current source mode, and are replaced by nonjammed current sources that switch to voltage source mode and join the secondary control. The strategy fits within the software-defined networking framework, where the network control is split from the data plane using reliable and secure side power talk communication channel, created via software modification of the MG primary control loops. The simulation results illustrate the feasibility of the solution and prove that the MG resilience and performance can be indeed improved via software-defined networking approaches.

Marko Angjelichinoski, Pietro Danzi, Čedomir Stefanović et al.

We propose a novel framework for secure and reliable authentication of Distributed Energy Resources to the centralized secondary/tertiary control system of a DC MicroGrid (MG), networked using the IEEE 802.11 wireless interface. The key idea is to perform the authentication using power talk, which is a powerline communication technique executed by the primary control loops of the power electronic converters, without the use of a dedicated hardware for its modem. In addition, the scheme also promotes direct and active participation of the control system in the authentication process, a feature not commonly encountered in current networked control systems for MicroGrids. The PLECS-based simulations verifies the viability of our scheme.

Cedomir Stefanovic, Marko Angjelichinoski, Pietro Danzi et al.

The future smart grid is envisioned as a network of interconnected microgrids (MGs) - small-scale local power networks comprising generators, storage capacities and loads. MGs bring unprecedented modularity, efficiency, sustainability, and resilience to the power grid as a whole. Due to the high share of renewable generation, MGs require innovative concepts for control and optimization, giving rise to a novel class of smart energy applications, in which communications represent an integral part. In this paper, we review power talk, a communication technique specifically developed for direct current MGs, which exploits the communication potential residing within the MG power equipment. Depending on the smart energy application, power talk can be used either as a primary communication enabler, or an auxiliary communication system that provides resilient and secure operation. The key advantage of power talk is that it derives its availability, reliability, and security from the very MG elements, outmatching standard, off-the shelf communication solutions.

Marko Angjelichinoski, Anna Scaglione, Petar Popovski et al.

We propose a decentralized Maximum Likelihood solution for estimating the stochastic renewable power generation and demand in single bus Direct Current (DC) MicroGrids (MGs), with high penetration of droop controlled power electronic converters. The solution relies on the fact that the primary control parameters are set in accordance with the local power generation status of the generators. Therefore, the steady state voltage is inherently dependent on the generation capacities and the load, through a non-linear parametric model, which can be estimated. To have a well conditioned estimation problem, our solution avoids the use of an external communication interface and utilizes controlled voltage disturbances to perform distributed training. Using this tool, we develop an efficient, decentralized Maximum Likelihood Estimator (MLE) and formulate the sufficient condition for the existence of the globally optimal solution. The numerical results illustrate the promising performance of our MLE algorithm.