Multiuser Communication through Power Talk in DC MicroGrids

Power talk is a novel concept for communication among control units in MicroGrids (MGs), carried out without a dedicated modem, but by using power electronics that interface the common bus. The information is transmitted by modulating the parameters of the primary control, incurring subtle power deviations that can be detected by other units. In this paper, we develop power talk communication strategies for DC MG systems with arbitrary number of control units that carry out all-to-all communication. We investigate two multiple access strategies: 1) TDMA, where only one unit transmits at a time, and 2) full duplex, where all units transmit and receive simultaneously. We introduce the notions of signaling space, where the power talk symbol constellations are constructed, and detection space, where the demodulation of the symbols is performed. The proposed communication technique is challenged by the random changes of the bus parameters due to load variations in the system. To this end, we employ a solution based on training sequences, which re-establishes the signaling and detection spaces and thus enables reliable information exchange. The presented results show that power talk is an effective solution for reliable communication among units in DC MG systems.Comment: Multiuser extension of the power talk concept. Submitted to IEEE JSA

Distributed Estimation of the Operating State of a Single-Bus DC MicroGrid without an External Communication Interface

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.Comment: Accepted to GlobalSIP 201