BibTeX
@INCOLLECTION{
         Zaoui2008LEP,
       author = "Fabrice Zaoui",
       title = "Large Electrical Power Systems Optimization Using Automatic Differentiation",
       doi = "10.1007/978-3-540-68942-3_26",
       pages = "293--302",
       abstract = "This paper is an example of an industrial application of a well-known automatic
         differentiation (AD) tool for large non-linear optimizations in Power Systems. The efficiency of
         modern AD tools for computing first- and second-order 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 hand-coded or based on an AD tool, namely ADOL-C. This operator
         overloading tool has the advantage of offering easy-to-use drivers for the computation of sparse
         derivative matrices. Numerical examples of optimizations are made on large test cases coming from
         real-world 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 = "978-3-540-68935-5",
       issn = "1439-7358",
       year = "2008",
       ad_area = "Optimization",
       ad_tools = "ADOL-C",
       ad_theotech = "Sparsity"
}