Collaborative and multilevel optimizations of a hybrid railway power substation. (2nd October 2017)

• Record Type: Journal Article
• Authors: Brisset, Stephane; Ogier, Maxime
• Other Names: Laudani Antonino guestEditor.; Fulginei Francesco Riganti guestEditor.; Salvini Alessandro guestEditor.
• Is Part Of: International journal of numerical modelling. Volume 32:Number 4(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-10-02
• Subjects: benders decomposition -- collaborative optimization -- energy storage -- hybrid railway power substation -- multisource systems; Electric networks -- Mathematical models -- Periodicals; Electronics -- Mathematical models -- Periodicals; 621.3011
• DOI: 10.1002/jnm.2289
• Languages: English
• ISSNs: 0894-3370

Abstract

Abstract: Three approaches are proposed for the design of a hybrid railway power substation taking into account the control of the storage system over 1 year. The first one is based on a piecewise linearization of the cost function and solved with linear programming. The others decompose the whole problem in 2 levels with lower dimensionality. Collaborative optimization solves it with a double‐loop scheme while Benders decomposition allows a sequential resolution. This last gives the same solution as linear programming in about 5 times more computing time and can be used with a nonlinear cost function.