EN FR
EN FR




Software
Bilateral Contracts and Grants with Industry
Bibliography




Software
Bilateral Contracts and Grants with Industry
Bibliography


Section: Partnerships and Cooperations

International Initiatives

Inria Associate Teams

STEM
  • Title: deciSion Tools for Energy Management (STEM)

  • Inria principal investigator: L. Brotcorne

  • International Partners (Institution - Laboratory - Researcher):

    • Université de Montréal (Canada) - Département d'informatique et recherche opérationnelle - Francois Gilbert

    • Polytechnic School of Montreal (Canada) - Département de mathématique et génie industriel - Michel Gendreau

  • Duration: 2012 - 2014

  • See also: http://dolphin.lille.inria.fr/Dolphin/STEM

  • The economic rise of developing countries, together with the need to meet ever more stringent pollution reduction targets, will increase the stress on the global energy system. Within this framework, the goal of the current project is to develop decision tools for energy management in a context of market deregulation. We will focus on two issues, namely demand management and production planning.

    The first problem is concerned with the efficient management of consumption. More precisely, the short or long term behaviour of customers can be influenced through signals sent by a utility (or several utilities) to the end-users. These signals can take the form of an "optimal" pricing scheme, or yet of devices (timers, automatic switches, etc.) designed to induce an "optimal" behaviour from the users.

    The second issue is concerned with efficient management of sustainable energy production. Indeed the development of renewable energy introduces new parameters in the supply/demand global equilibrium process. The issue is to achieve the right trade-off between costs (production, security) and revenues when determining the daily hydro-electricity generation and storage within an environment where demand is stochastic.

    The first problem is modeled as a bilevel program, the second one as a integer mutli-objective stochastic program. Efficient and effective solution methods are developed and implemented to solve these problems.

Inria International Partners

  • University of Sydney, Australia

  • University of Montreal and Ecole Polytechnique of Montreal, Canada

  • University of Dortmund, Germany

  • ETH Zurich, Switzerland

  • SINTEF, Norway

Participation In International Programs

  • Inria STIC-Tunisie,2011-2013.

  • Inria STIC-Algérie, 2011-2013.

  • CNRS PICS Luxembourg, 2011-1014.