Michael David de Souza Dutra
Michael David de Souza Dutra, PhD
michaeldavidsd@gmail.com
Brazil France EUA

Michael David de Souza Dutra I obtained a PhD at Polytechnique Montréal in Mathematics for Engineers under the supervision of professors Miguel F. Anjos and Sébastien Le Digabel.

I was a lecturer at the Département de Sciences de la Décision at HEC, where I taught operational research courses. Currently, I am a Professor at the Universidade Federal de Goiás, where I teach courses related to Logistics and Operational Research.

My research interests are optimization and mathematical modeling. I have been devoting myself to Continuous Optimization and Discrete Optimization, especially in decomposition methods for large scale optimization. Since 2015, I have been working with optimization for smart grids.

Smart grid is a concept for an electricity network that integrates many agents such as generators, consumers, and service providers in such a way to provide electricity sustainably, securely, and economically. In this new network, electricity and information flows from and to each agent. Hence, a consumer, like a house, may generate electricity, use it, and send a possible surplus to the grid. All this brings some questions:

  • Is it profitable, feasible to users (houses, apartments, stores) be a participant in the smart grid?
  • If yes, how should be a transition from current infrastructure for a smart one?
  • If users generate electricity and inject it into the grid at the same time, it may be a problem for the network operation. Hence, how to coordinate them?
  • Electric vehicles may be an alternative to combustion engine vehicles. How to adapt the current infrastructure to insert electric vehicles in the national fleet?
Providing good answers to these questions may be a challenge because nonconvex physical equations are, frequently, needed. Thus, mathematical models to address those questions may pose issues for some optimization methods. I contribute to science by solving these issues.

My other skills are concerned with the improvement of companies' key performance indicators via optimization, simulation and workflow process reformulation.