Department Chair and Fred W. Finley Distinguished Professor
Electrical and Computer Engineering
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INVESTIGATORS
Jonathan Kimball, Bruce McMillin, Bokang Zhou
FUNDING SOURCE
National Science Foundation, including FREEDM Systems Center
PROJECT DESCRIPTION
In a cyber-physical system (CPS) like a smart power grid, security and stability are both important and challenging to ensure. Analysis in each domain uses different tools and concepts. An invariant is an evaluation function whose truth value indicates the correctness (e.g., stability) of the system. Invariants can be purely cyber, or can be physical and used to constrain the cyber system. Furthermore, related concepts can be used to determine whether information shared in a distributed computing system is correct. In essence, the physical system provides a second information channel that verifies the cyber information channel.
PUBLICATIONS
INVESTIGATORS
Jonathan Kimball; Jacob Mueller
FUNDING SOURCE
National Science Foundation, Department of Energy
PROJECT DESCRIPTION
A microgrid is a relatively small power distribution network, which typically contains a number of renewable energy sources and energy storage devices. Whereas a conventional generator is connected directly to the power grid, renewable energy sources and energy storage devices require switching power converters for interconnection. The fact that they are connected to a microgrid complicates the control design: the grid impedance is higher, the power flow is multi-directional, and both the voltage and the frequency are more variable. Therefore, new analysis and design methods are needed to account for the variability of the system. In addition, system size poses significant challenges, so model order reduction is necessary.
PUBLICATIONS

INVESTIGATORS
Jonathan Kimball, Jacob Mueller, Gilles Mpembele
FUNDING SOURCE
National Science Foundation
PROJECT DESCRIPTION
In a microgrid, both loads and generation are stochastic in nature. The randomness, on top of the inherent weakness of the grid, can lead to instability or operation outside of desired limits. This project has two related thrusts. First, stochastic models of sources and loads are derived from data. Second, the models are used for either deeper data analysis or for design purposes. The models are either ARMA type (autoregressive moving average) or hidden Markov models (HMMs). The analysis includes both system-level stability and operational evaluation using stochastic hybrid systems and nonintrusive load monitoring.
PUBLICATIONS
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