28 research outputs found
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