BibTeX
@INCOLLECTION{
Zaoui2008LEP,
author = "Fabrice Zaoui",
title = "Large Electrical Power Systems Optimization Using Automatic Differentiation",
doi = "10.1007/9783540689423_26",
pages = "293302",
abstract = "This paper is an example of an industrial application of a wellknown automatic
differentiation (AD) tool for large nonlinear optimizations in Power Systems. The efficiency of
modern AD tools for computing first and secondorder derivatives of sparse problems, makes its use
now conceivable not only for prototyping models but also for operational softwares in an industrial
context. The problem described here is to compute an electrical network steady state so that
physical and operating constraints are satisfied and an economic criterion optimized. This optimal
power flow problem is solved with an interior point method. Necessary derivatives for the simulator
of the network equations are either handcoded or based on an AD tool, namely ADOLC. This operator
overloading tool has the advantage of offering easytouse drivers for the computation of sparse
derivative matrices. Numerical examples of optimizations are made on large test cases coming from
realworld problems. They allow an interesting comparison of performance for derivative
computations.",
crossref = "Bischof2008AiA",
booktitle = "Advances in Automatic Differentiation",
publisher = "Springer",
editor = "Christian H. Bischof and H. Martin B{\"u}cker and Paul D. Hovland and Uwe
Naumann and J. Utke",
isbn = "9783540689355",
issn = "14397358",
year = "2008",
ad_area = "Optimization",
ad_tools = "ADOLC",
ad_theotech = "Sparsity"
}
