Dynamic performance enhancement can often be formulated as a dynamic embedded optimization problem. The associated cost function quantifies performance, and involves dynamically evolving state variables. The dynamic model is embedded within the constraints. The seminar will develop this formulation, and provide a number of power system based examples. Power systems exhibit intrinsic interactions between continuous dynamics and discrete events, and so form an important application area for hybrid systems. Optimization algorithms must contend with non-smooth response. It will be shown that for a large class of problems, the cost function is smooth even though the underlying dynamic response is non-smooth. When that is not the case, shooting methods provide a means of identifying conditions that separate smooth regions of the cost function. These conditions correspond to grazing bifurcations, and will be discussed in the seminar.
Ian Hiskens is a Professor of Electrical and Computer Engineering at the University of Wisconsin-Madison. He received the B.Eng.(Elec.) and B.App.Sc.(Math.) degrees from the Central Queensland University, Rockhampton, Australia in 1980 and 1983 respectively, and a PhD degree from the University of Newcastle, Australia in 1991. He has held prior appointments with the Queensland Electricity Supply Industry from 1980 to 1992, the University of Newcastle from 1992 to 1999, and the University of Illinois at Urbana-Champaign from 1999 to 2002. His major research interests lie in the area of power system analysis, in particular system dynamics, security, and numerical techniques. Other research interests include the dynamics and control of nonlinear and hybrid systems.
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