HEC Montréal, Canada, 6 - 8 mai 2013

Journées de l'optimisation 2013

HEC Montréal, Canada, 6 — 8 mai 2013

Horaire Auteurs Mon horaire

WA11 Modèles stochastiques et optimisation en énergie / Stochastic Models and Optimization in Energy

8 mai 2013 10h30 – 12h10

Salle: Gérard Parizeau

Présidée par Somayeh Moazeni

3 présentations

  • 10h30 - 10h55

    Risk Management in Energy Storage Planning

    • Somayeh Moazeni, prés., Princeton University
    • Warren Powell, Princeton University
    • Belgacem Bouzaiene-Ayari, Princeton University

    An optimal policy for a finite planning horizon, among some energy source, energy carrier electricity, and a battery storage is sought to satisfy the electricity load and minimize the expected cost (and risk) of the system. We present a stochastic optimization framework for the problem, and develop a novel tractable parallel computational stochastic dynamic programming technique based on the direct policy search method and a parallel multi-start pattern search derivative free optimization. Impacts of the underlying non-stationary stochastic processes of the electricity price and load on the minimum expected cost energy flow structure, its associated expected cost and Value-at-Risk are then extensively discussed.

  • 10h55 - 11h20

    Decision-Support in the Hydro Energy Market: A Stochastic Approach with Risk Aversion Measures

    • Michel Gendreau, prés., Polytechnique Montréal
    • Raphael E.C. Gonçalves, Polytechnique Montréal

    We present a stochastic approach for decision-support in the hydro energy market. For that, we consider risk aversion metrics based on the Conditional Value-at-Risk (CVaR), which can provide more coherent decisions and allow the decision-maker to add its risk perception into the model formulation. We present a case study based on an academic example of the Hydro-Québec (HQ) trading market environment.

  • 11h20 - 11h45

    ANNULÉE/CANCELLED: SMART-ISO: Modeling Uncertainty in Renewable Sources of Energy

    • Marcos Leone-Filho, prés., Princeton University
    • Warren Powell, Princeton University
    • Hugo Simao, Princeton University

    We present a stochastic modeling framework that allows for the analysis of the integration of high levels of renewable sources of energy (e.g. wind and solar) into a large transmission system. It is comprised of a multi-scale optimization and simulation system, including a day-ahead and an hour-ahead unit commitment models and a real-time simulation model. We will illustrate the application of the system through some preliminary results of an off-shore wind integration study.