Research Associate
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My research interests focus on the application of different optimization techniques to problems in smart grids, specifically for the demand side for smart buildings. In this context I take the user perspective to achieve a trade-off between demand satisfaction and cost reduction while ensuring the grid requirements through demand response programs.
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Postdoctoral Researchers
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I have worked on network design problems, focusing on applications in telecommunications. Namely, I am interested in integer programming and decomposition methods. I am currently working on a project with Prof. Miguel Anjos and Prof. Bernard Gendron, that will simultaneously address the problem of locating electrical vehicles charging stations, and of setting the price of energy used in those stations.
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Doctoral Researchers
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Thibault Barbier
Ph.D. candidate in industrial engineering 514 340-6053 x3644 thibault.barbier@polymtl.ca |
My research focuses on optimization and simulation for revenue management problems. In order to ensure better revenues, I develop models and methods to tackle more complex demand behaviors while respecting a time window for solving. I am working with Prof. Miguel Anjos, Prof. Gilles Savard and the company Expretio specialist in revenue management for transportation.
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Mathieu Besançon
Ph.D. student in engineering mathematics 514 340-6053 x3926 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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Christian Bingane
Ph.D. candidate in engineering mathematics 514-340-6053 x3925 christian.bingane@polymtl.ca |
My research interests are: optimal power flow in power network and conic optimization. I am concerned with using linear programming, second-order cone programming or semidefinite programming to provide guaranteed global optimal solution to the optimal power flow problem for a large-scale electrical grid.
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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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Michael David de Souza Dutra
Ph.D candidate in engineering mathematics 514 340-6053 x3644 michaeldavidsd@gmail.com |
Following the strong trend of smart homes, home automation can be seen more and more in modern homes and apartments. We can remotely control appliances and obtain consumer data. But instead of just controlling and visualizing data, could we produce money in this context? I believe so. Developing a scheduler to relate residential energy production to the residential power consumption of the various residential appliances without loss of comfort and optimizing budgeting is one of my PhD's goals.
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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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William Ferreira
Ph.D. student in industrial engineering 514 340-5121 x6047 william.ferreira@polymtl.ca |
My research interest focus on the application of mathematical optimization techniques to industrial engineering problems, seeking overall operational excellence. I'm currently working with multi-floor facility layout problems.
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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. student in industrial 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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Jesús A. Rodríguez
Ph.D candidate in engineering mathematics 514 340-6053 x3644 jesus.rodriguez@gerad.ca |
I'm interested in the application of optimization techniques and game theory for planning and scheduling problems under uncertainty. In particular, we are developing mathematical programming models and solution methods for scheduling maintenance of generators in hydropower systems. In addition, we are applying multilevel optimization and equilibrium models for generator capacity expansion planning of interconnected power systems.
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Vilmar Jefte Rodrigues de Sousa
Ph.D candidate in engineering mathematics 514 340-6053 x3913 vilmar.de.sousa@gerad.ca |
We consider the maximum k-cut problem that consists in partitioning the vertex set of an undirected graph into k subsets such that the sum of weights of edges joining vertices in different subsets is maximized. Initially, we focus on strengthening conic relaxations by combining SDP with LP cutting planes
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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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Masters Researchers
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Mathilde K. Bourque
Masters student in energy engineering 514-340-6053 x3925 mathilde.k-bourque@polymtl.ca |
With the added information provided by smart meters, bad data detection will be crucial to have a robust state estimation of the grid. My research project focuses on adjusting traditional state estimation optimization algorithms to ensure convergence and correct information.
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My project aims to extend the idea of the aggregation of a large number of small DR capacities. As the availability of the loads will be under a significant uncertainty, this problem can be viewed as a stochastic problem.
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Florian Pedroli
Masters student in energy engineering |
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Residential demand response program have been shown to have a huge potential to balance the integration of renewable energy and to shift load from peak to low demand period. My research project consists of defining the possible business model of a water-heaters aggregator. I will look for what technical and economical viable offer can be proposed, using amoung others the mean field game theory.
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Coming soon.
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The aim of my research project is to develop an optimization-based approach to improve the energy system of the future smart cities. I am especially interested in modelling different types of buildings, considering technical features and integrating different technologies, such as distributed generation, batteries, thermal storage, solar electrical vehicles and demand response.
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