Section: Contracts and Grants with Industry

Contracts with Industry

ANR projects

• N. Champagnat is member of the ANR MANEGE (Modèles Aléatoires eN Écologie, Génétique et Évolution, started in 2009 under the direction of S. Méléard, Ecole Polytechnique) whose aim is to provide methodological and conceptual advances in the study of stochastic processes modeling ecology, population genetics and evolution of life. This work is sustained by regular exchanges with biologists from several teams in France. In addition, the three working groups that operate in each of the three poles of the MANEGE project (Paris, Palaiseau, Marseille) gather all local probabilistic interests in the issues of this project. http://www.cmap.polytechnique.fr/~anr-manege/index_en.html

• N. Champagnat is member of the ANR MODECOL (Using mathematical MODeling to improve ECOLogical services of prairial ecosystems, started in 2009 under the direction of C. Mony, Univ. Rennes 1), whose goal is to develop computational ecological modeling of terrestrial plants communities via the simulation of a prairie in relation with environmental data. This project focuses on developing an original tool-box that takes advantage of complementary mathematical disciplines (partial differential equations, individual-based stochastic modelling...) to assess ecological problems. Simulations will be extensively processed using distributed computing and webcomputing. Our target application concerns the setup of herbal strips around intensive cereal fields for purificating water from extra nitrate and pesticides, imposed by the European Common Agricultural Policy. http://ecobio.univ-rennes1.fr/modecol/gb/description.php

• S. Herrmann, D. Talay and E. Tanré are member of the ANR MANDy (Mathematical Analysis of Neuronal Dynamics, started in 2009 under the direction of M. Thieullen, Univ. Paris 6). This project, which gathers mathematicians and neuroscientists, aims at developing mathematically rigorous approaches to neuroscience considering single neurons as well as interconnected neuronal populations. Our target is to conduct the mathematical analysis of existing models where there is still much work to be done and to enrich the modelling by proposing new models. See http://www.proba.jussieu.fr/pageperso/thieullen/MANDy/accueil.html for a more complete description of this project.

• P.-E. Jabin is member of the ANR MONUMENTALG (MOdélisation mathématique et simulations NUMériques pour la dégradation biologique des MONUMENTs et pour la prolifération des ALGues) on the dispersion of toxic algae, starting in 2010 (dirercted by M. Ribot, Univ. Nice – Sophia Antipolis). http://math.unice.fr/~ribot/anr.html

• A. Lejay is member of the ANR ECRU (Exploration des Chemins RUgueux, 2009–2011), whose aim is is to explore new directions in the field of rough paths (directed by M. Gubinelli, Univ. Paris Dauphine). http://www.ceremade.dauphine.fr/~mgubi/ecru/index.html

• A. Lejay is member of the ANR SIMUDMRI (Simulation du signal d'IRM diffusion dans tissus biologiques) which started in November 2010 (directed by Jing-Rebecca Li, INRIA Rocquencourt).

Contracts with ADEME

Participants : Mireille Bossy, El Hadj Aly Dia, Jacques Morice, Laurent Violeau.

Local modeling for the wind velocity

Since 2005, M. Bossy was member of a collaboration with the Laboratoire de Météorologie Dynamique (Université Paris 6, École Polytechnique, École Normale Supérieure), funded by the French Environment and Energy Management Agency (ADEME), concerning the modeling and the simulation of local wind energy resources. We collaborate with P. Drobinski. This year was the last year of the second phase of this collaboration started in October 2007, with two other partners: A. Rousseau (Moise team, INRIA Grenoble – Rhône-Alpes) and F. Bernardin (CETE Clermont-Ferrand).

We investigated a new numerical simulation method for the downscaling in CFD, with a strong orientation in applications to meteorology, particularly for the simulation of wind at small scales. The local model that we propose consists in modeling the fundamental equations of fluid motion by a stochastic Lagrangian model describing the behaviour of a fluid particle.

Because of the both Lagrangian and stochastic nature of our model, it is discretized thanks to an interacting particle system, combining a time Euler scheme for stochastic differential equations and a Monte–Carlo approximation method

This model called SDM (Stochastic Downscaling Method) is adapted from previous works introduced by S.B. Pope [41] (see http://sdm.gforge.inria.fr/Accueil/index.en.php ).

This year, we worked on the comparison of the SDM model (endowed with a physical geostrophic forcing and a wall log law) with simulations obtained with a LES method (Méso-NH code) for the atmospheric boundary layer (from 0 to 750 meters in the vertical direction), in the neutral case.

This work allowed to deeply understand the contribution of each elements of the Lagrangian model in terms of the turbulence production and dissipation, we analysed the returns of various closure parametrisation approaches, including viscosity turbulent approach. We also investigated anisotropic effect, with the introduction of a GLM model in SDM (see [41] ), in particular the isotropic relaxation case. We gave our conclusions as a part of the final report for ADEME [28] , http://hal.inria.fr/hal-00646422/en . A paper is in preparation.

Carbon value and carbon tax in the context of renewable energies deployment

Since January 2009, M. Bossy was member of a collaboration funded by the French Environment and Energy Management Agency (ADEME), involving the Center for Applied Mathematics (CMA) at Mines ParisTech, and Coprin and Tosca teams at INRIA Sophia Antipolis. It focuses on a short term carbon value derived from the so-called financial carbon market, the European Union Emission Trading Scheme (EU ETS), which is a framework for GHG emissions reduction in European industry.

The objective of this project is to study the compatibility and complementarity of a carbon tax and a target for renewable energy deployment. As a first step, we are developing a method for assessing the EU ETS value. We consider the constraints related to emission allowances distributed through national plans of allocation (NAP) and the mechanisms of taxes that are taking place. The work will focus on electricity producers, key players in the market in its first phase (NAP-I, 2005-2007). The impact of the Renewable Energies park of the electricity producers on their own carbon value will be particularly studied.

We have selected the financial concept of indifference price as a relevant methodology to assess the European Union Emission Trading Scheme (EU ETS) value. In this setting, modelling strategies of production and emission of market quotas rely on stochastic optimal control problems and associated Hamilton-Jacobi-Bellman equations.

This year, we worked on the calibration (with EPEX Spot data) of the selected panel of electricity spot price models, as input of the indifference price solver. We also added the reduction cases (studied in our collaboration with CMA-MinesParisTech mentioned above) into the solver and we started to implement the 3D case solver, required for some electricity spot price models. We used the current version of CarbonQuant to compare a tax situation with the allowances market situation.

We also continued the study of a game theoretic approach based on the Nash equilibrium concept for the coupled electricity and carbon markets (see the 2011 Activity Report of the Coprin team).

Industrial contracts

• Tosca Nancy starts a working group with the SME Alphability on risk measures and rare events in finance.

• The contract between Tosca and GDF-Suez on the hedging of power plants ended in January.

• In collaboration with V. Reutenauer (CA-CIB) D. Talay and E. Tanré worked on the contract with CA-CIB (ex-CALYON), which concerned

  • the study of the liquidity risk in the interest rate options market;

  • the minimization of the hedging error in interest rates Gaussian models by means of strategies designed in an effective way by using stochastic optimization algorithms.

  This contract ended this year.