{"id":51424,"date":"2025-08-20T11:23:21","date_gmt":"2025-08-20T15:23:21","guid":{"rendered":"https:\/\/www.uqac.ca\/uqactualites\/?p=51424"},"modified":"2025-09-03T14:37:06","modified_gmt":"2025-09-03T18:37:06","slug":"mohammad-jafari-aminabadi-finissant-au-doctorat-en-ingenierie-soutient-sa-these","status":"publish","type":"post","link":"https:\/\/www.uqac.ca\/uqactualites\/2025\/08\/20\/mohammad-jafari-aminabadi-finissant-au-doctorat-en-ingenierie-soutient-sa-these\/","title":{"rendered":"Mohammad Jafari Aminabadi, finissant au doctorat en ing\u00e9nierie, soutient sa th\u00e8se"},"content":{"rendered":"

Finissant au doctorat en ing\u00e9nierie<\/a>, Mohammad Jafari Aminabadi a effectu\u00e9 sa soutenance de th\u00e8se le 13 ao\u00fbt 2025. Sous la direction de recherche de Sara S\u00e9guin (UQAC) et la codirection d’Issouf Fofana<\/a> (UQAC), sa th\u00e8se a pour titre \u00ab<\/em> Nonlinear programming for stochastic short-term hydropower operations planning considering uncertain prices \u00bb<\/em>.<\/p>\n

Pr\u00e9sid\u00e9 par Martin Otis<\/a> (UQAC), le jury d\u2019\u00e9valuation \u00e9tait compos\u00e9 d’Hugo Tremblay<\/a> (UQAC) et de Pascal C\u00f4t\u00e9 (Rio Tinto).<\/p>\n

\n
R\u00e9sum\u00e9 de la th\u00e8se<\/h5>\n

L\u2019hydro\u00e9lectricit\u00e9 constitue la principale source de production d\u2019\u00e9lectricit\u00e9 tant au Qu\u00e9bec qu\u2019au Canada, jouant un r\u00f4le fondamental dans la s\u00e9curit\u00e9 \u00e9nerg\u00e9tique, la flexibilit\u00e9 du r\u00e9seau et la production durable \u00e0 l\u2019\u00e9chelle nationale. Dans les march\u00e9s de l\u2019\u00e9lectricit\u00e9 concurrentiels, la planification \u00e0 court terme de l\u2019exploitation des centrales hydro\u00e9lectriques implique une prise de d\u00e9cision complexe sous incertitude li\u00e9e aux prix de l\u2019\u00e9lectricit\u00e9, aux contraintes physiques et aux limitations op\u00e9rationnelles. Ces d\u00e9fis exigent le d\u00e9veloppement de mod\u00e8les d\u2019optimisation avanc\u00e9s capables de repr\u00e9senter avec pr\u00e9cision la nature non lin\u00e9aire et stochastique des syst\u00e8mes hydro\u00e9lectriques.<\/p>\n

Cette th\u00e8se propose un cadre d\u2019optimisation non lin\u00e9aire complet pour la planification \u00e0 court terme des op\u00e9rations hydro\u00e9lectriques, structure autour de trois objectifs principaux. Premi\u00e8rement, un mod\u00e8le de programmation non lin\u00e9aire mixte en nombres entiers stochastique en deux \u00e9tapes (MINLP) est formule afin d\u2019optimiser les strat\u00e9gies d\u2019ench\u00e8res horaires dans le march\u00e9 du jour pr\u00e9c\u00e8dent. Ce mod\u00e8le prend en compte la dynamique des r\u00e9servoirs, les combinaisons de turbines et les r\u00e8gles du march\u00e9 dans un contexte d\u2019incertitude des prix. Pour surmonter la complexit\u00e9 de calcul, une m\u00e9thode heuristique it\u00e9rative efficace est d\u00e9velopp\u00e9e, capable de fournir des solutions quasi optimales pour des instances de grande taille.<\/p>\n

Deuxi\u00e8mement, un mod\u00e8le MINLP non lin\u00e9aire est propos\u00e9 pour la planification \u00e0 court terme en tenant compte de la couverture de la demande et des couts de d\u00e9marrage des turbines. Des surfaces de puissance maximale sont utilis\u00e9es pour mod\u00e9liser avec plus de pr\u00e9cision le rendement des turbines. Trois m\u00e9thodes de r\u00e9solution \u2014 une heuristique it\u00e9rative, un algorithme g\u00e9n\u00e9tique et une approche hybride \u2014 sont compar\u00e9es afin d\u2019\u00e9valuer la qualit\u00e9 des solutions et l\u2019efficacit\u00e9 computationnelle. Troisi\u00e8mement, un cadre d\u2019optimisation en deux phases est introduit pour g\u00e9rer les offres par blocs dans le march\u00e9 du jour pr\u00e9c\u00e8dent. Dans la premi\u00e8re phase, un mod\u00e8le MINLP d\u00e9terministe g\u00e9n\u00e8re des profils de production r\u00e9alisables, en tenant compte des couts d\u2019opportunit\u00e9 et des contraintes op\u00e9rationnelles. Dans la deuxi\u00e8me phase, un mod\u00e8le de programmation lin\u00e9aire stochastique en deux \u00e9tapes s\u00e9lectionne la meilleure combinaison de blocs sur la base de diff\u00e9rents scenarios de prix. Les mod\u00e8les propos\u00e9s sont \u00e9valu\u00e9s \u00e0 travers des \u00e9tudes de cas comparatives. Le premier mod\u00e8le est valide \u00e0 l\u2019aide des r\u00e9sultats de l\u2019outil d\u2019optimisation SHOP ; le deuxi\u00e8me est compar\u00e9 \u00e0 un mod\u00e8le de r\u00e9f\u00e9rence MINLP simplifie ; et le troisi\u00e8me est teste face aux strat\u00e9gies d\u2019ench\u00e8res horaires classiques en utilisant des donn\u00e9es r\u00e9elles du march\u00e9. Les r\u00e9sultats montrent une am\u00e9lioration de la repr\u00e9sentation des comportements non lin\u00e9aires, de la planification fond\u00e9e sur des scenarios et de la performance computationnelle. Ces travaux offrent des perspectives pr\u00e9cieuses sur le r\u00f4le de l\u2019optimisation non lin\u00e9aire dans l\u2019exploitation hydro\u00e9lectrique \u00e0 court terme et ouvrent la voie \u00e0 des approches de planification plus adaptatives et sensibles au march\u00e9.<\/p>\n

\n

F\u00e9licitations \u00e0 Mohammad Jafari Aminabadi pour la soutenance de sa th\u00e8se de doctorat!<\/p>\n","protected":false},"excerpt":{"rendered":"

Finissant au doctorat en ing\u00e9nierie, Mohammad Jafari Aminabadi a effectu\u00e9 sa soutenance de th\u00e8se le 13 ao\u00fbt 2025. Sous la direction de recherche de Sara S\u00e9guin (UQAC) et la codirection d’Issouf Fofana (UQAC), sa th\u00e8se a pour titre \u00ab Nonlinear programming for stochastic short-term hydropower operations planning considering uncertain prices \u00bb. Pr\u00e9sid\u00e9 par Martin Otis […]<\/p>\n","protected":false},"author":5,"featured_media":51428,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2913],"tags":[666,21,247,293],"yoast_head":"\r\nMohammad Jafari Aminabadi, finissant au doctorat en ing\u00e9nierie, soutient sa th\u00e8se - UQACtualit\u00e9s<\/title>\r\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\r\n<link rel=\"canonical\" href=\"https:\/\/www.uqac.ca\/uqactualites\/2025\/08\/20\/mohammad-jafari-aminabadi-finissant-au-doctorat-en-ingenierie-soutient-sa-these\/\" \/>\r\n<meta property=\"og:locale\" content=\"fr_CA\" \/>\r\n<meta property=\"og:type\" content=\"article\" \/>\r\n<meta property=\"og:title\" content=\"Mohammad Jafari Aminabadi, finissant au doctorat en ing\u00e9nierie, soutient sa th\u00e8se - UQACtualit\u00e9s\" \/>\r\n<meta property=\"og:description\" content=\"Finissant au doctorat en ing\u00e9nierie, Mohammad Jafari Aminabadi a effectu\u00e9 sa soutenance de th\u00e8se le 13 ao\u00fbt 2025. Sous la direction de recherche de Sara S\u00e9guin (UQAC) et la codirection d’Issouf Fofana (UQAC), sa th\u00e8se a pour titre \u00ab Nonlinear programming for stochastic short-term hydropower operations planning considering uncertain prices \u00bb. 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