Optimal multi-scale capacity planning for power-intensive continuous processes under time-sensitive electricity prices and demand uncertainty. Part II: Enhanced hybrid bi-level decomposition
Identifieur interne : 003C76 ( PascalFrancis/Curation ); précédent : 003C75; suivant : 003C77Optimal multi-scale capacity planning for power-intensive continuous processes under time-sensitive electricity prices and demand uncertainty. Part II: Enhanced hybrid bi-level decomposition
Auteurs : Sumit Mitra [États-Unis] ; Jose M. Pinto [États-Unis] ; Ignacio E. Grossmann [États-Unis]Source :
- Computers & chemical engineering [ 0098-1354 ] ; 2014.
Descripteurs français
- Pascal (Inist)
- Planification optimale, Méthode échelle multiple, Capacité production, Gestion production, Réseau électrique, En continu, Temps continu, Offre et demande, Prix vente, Système incertain, Echelle grande, Programmation stochastique, Fonction pénalité, Programmation partiellement en nombres entiers, Problème mixte, Méthode partition, Programmation linéaire, Multiplicateur Lagrange, Investissement, Algorithme parallèle, Modélisation, Etude cas, Economies d'énergie, ., Réseau électrique intelligent.
- Wicri :
- topic : Offre et demande, Investissement.
English descriptors
- KwdEn :
- Case study, Continuous process, Continuous time, Electrical network, Energy savings, Investment, Lagrange multiplier, Large scale, Linear programming, Mixed integer programming, Mixed problem, Modeling, Multiscale method, Optimal planning, Parallel algorithm, Partition method, Penalty function, Production capacity, Production management, Selling price, Smart grid, Stochastic programming, Supply demand balance, Uncertain system.
Abstract
We describe a hybrid bi-level decomposition scheme that addresses the challenge of solving a large-scale two-stage stochastic programming problem with mixed-integer recourse, which results from a multi-scale capacity planning problem as described in Part I of this paper series. The decomposition scheme combines bi-level decomposition with Benders decomposition, and relies on additional strengthening cuts from a Lagrangean-type relaxation and subset-type cuts from structure in the linking constraints between investment and operational variables. The application of the scheme with a parallel implementation to an industrial case study reduces the computational time by two orders of magnitude when compared with the time required for the solution of the full-space model.
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<front><div type="abstract" xml:lang="en">We describe a hybrid bi-level decomposition scheme that addresses the challenge of solving a large-scale two-stage stochastic programming problem with mixed-integer recourse, which results from a multi-scale capacity planning problem as described in Part I of this paper series. The decomposition scheme combines bi-level decomposition with Benders decomposition, and relies on additional strengthening cuts from a Lagrangean-type relaxation and subset-type cuts from structure in the linking constraints between investment and operational variables. The application of the scheme with a parallel implementation to an industrial case study reduces the computational time by two orders of magnitude when compared with the time required for the solution of the full-space model.</div>
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{{Explor lien |wiki= Wicri/Amérique |area= PittsburghV1 |flux= PascalFrancis |étape= Curation |type= RBID |clé= Pascal:14-0165507 |texte= Optimal multi-scale capacity planning for power-intensive continuous processes under time-sensitive electricity prices and demand uncertainty. Part II: Enhanced hybrid bi-level decomposition }}
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