OPTIMIZATION FOR SMART GRIDS
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DOCTORAL RESEARCHERS

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Mathieu Besançon
​Ph.D. student in engineering mathematics
514 340-6053 x3926
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mathieu.besancon@polymtl.ca
The integration of renewable energy generation into the power grid requires a higher flexibility on the demand side and motivated the creation of demand response programs. My research focuses on leader-follower frameworks to develop these programs in a robust and scalable way, sharing the benefits between users and grid suppliers.

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Ahmed Chaouachi
Ph.D. candidate in computer science
 514 343-6111 x 8707
ahmed.chaouachi@umontreal.ca
My research is concerned, firstly, with bi-level programming theory to design an optimal involvement strategy of electric vehicles to the Smart grid market. Secondly, I am interested about the message-passing distributed optimization algorithms to make near-optimal real-time decision to co-optimize the operation of Transmission and Distribution power grids profiting from the storage technologies.

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Éloïse Edom
Ph.D. student in industrial engineering
 514 340-6053 x3913
 
eloise.edom@polymtl.ca
My project aims to propose a mixed integer nonlinear optimization approach that takes into account both the standard constraints in maintenance planning for hydropower plants and the nonlinear aspects of the power output function, often linearized in the literature.

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Neda Etebari
​Ph.D. student in engineering mathematics
514-340-6053 x3643
Neda.etebarialamdari@polymtl.ca
Since demand forecasting plays a key role in any revenue management system, robust and accurate predictions are of great importance to the companies. My research focuses on improvement of booking prediction accuracy in railways industry through stable and generalizable machine learning and optimization algorithms. The provided methods can easily be extended to other transportation or hospitality industries.

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Vinicius Neves Motta
Ph.D. student in industrial engineering
514 340-6053 x3926
vinicius.neves-motta@polymtl.ca 

My research interests are stochastic and robust optimization, and mathematical modelling of power grids considering demand response (DR). Currently, I'm working on the problem of optimal management demand contracts of the grid operator and generation contracts, through demand response, of companies considering the topology of the transmission network.

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Mariana Faria Pires Gama Rocha
Ph.D. candidate in i
ndustrial engineering
514 340-6053 x3926
mariana.rocha@polymtl.ca
My research interests are: optimization and mathematical modeling of power systems equipment operation, especially electrical and thermal energy storage devices and renewable related resources, for its optimal integration into electrical and smart grids giving careful consideration to power flow (load flow) methods, short circuit analysis, voltage stability, security analysis, energy price and other market information.

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Julie Sliwak
Ph.D. student 
in engineering mathematics
514 340-6053 x 3926
julie.sliwak@polymtl.ca
My research project consists in solving conic relaxations of Optimal Power Flow problems for large-scale power transmission networks. These problems being originally formulated into complex variables, my research also focuses on polynomial optimization with complex variables and the possible extension of methods to the complex case.

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Mathieu Tanneau
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Ph.D. candidate in
engineering mathematics
514-340-5121 x3388
mathieu.tanneau@polymtl.ca
As the penetration of renewable generation soars, so does the need for a more flexible and decentralized grid. This need can be met by leveraging the potential of Distributed Energy Resources (DERs) including - but not limited to - energy storage, smart appliances, and electric vehicles. My goal is to overcome scalability and heterogeneity challenges raised by DERs. I do so by developing efficient aggregation algorithms which exploit decomposition and parallelization techniques.

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