SESO 2016 Winter School
Smart Energy and Stochastic Optimization
on
Numerical Methods for Multistage Stochastic Optimization:
Application to Energy Storage Management

2 to 7 November 2016

P. Carpentier1, J.-P. Chancelier, M. De Lara and V. Leclère2
ENSTA ParisTech and École des Ponts ParisTech


Image ensta                                                  Image ecole_ponts_CMJN

Abstract:

Energy companies witness a rapidly changing landscape: increase of intermittent, variable and spatially distributed power sources (wind, sun); expansion of markets and actors at all spatial and temporal scales; penetration of telecom technologies (smart grids). These new factors challenge the management of energy systems and impact the practice of optimization, towards more stochastic and more decentralized optimization. Data on energy demand and on meteorological conditions will be more and more abundant. How to formulate mathematical optimization problems that take into account the variability of data? What are the proper formats to feed such data in optimization problems? What are optimization methods adapted to storage management problems? How to handle multiple stocks? Are there ways to decentralize an optimal solution to local agents? These are the type of questions addressed in the SESO 2016 Winter Course Numerical Methods for Multistage Stochastic Optimization: Application to Energy Storage Management.

The SESO Smart Energy and Stochastic Optimization events -- International Thematic Weeks and Winter Courses -- offer to the academic community and to industrials the state of the art of optimization in the energy transition. Mid-year, the SESO International Thematic Week alternates tutorials, scientific workshops and an industry day; it is aimed at a mixed public, in academy and in industry. End of year, the SESO Winter Course alternates courses and computer sessions; it is aimed at a mixed public, in academy and in industry. The academic organizers are ENSTA ParisTech and École des Ponts ParisTech, with the financial support of the Gaspard Monge Program for Optimization and operations research (PGMO).

Keywords: energy transition, renewables, intermittency, flexibility, storage, decentralization, optimization

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Eligibility/Pre-requisites.


Computer and software.



Contents

pdf version of this document


1 Wednesday 2 November 2016:
Two-stage Stochastic Programming
-- at ENPC ParisTech

2 Thursday 3 November 2016:
Stochastic Dynamic Programming
-- at ENPC ParisTech

3 Friday 4 November:
Dual Approximate Dynamic Programming (DADP)
-- at ENPC ParisTech

4 Monday 7 November 2016:
Stochastic Dual Dynamic Programming (SDDP)
-- at ENSTA ParisTech



Footnotes

... Carpentier1
pierre.carpentier@ensta-paristech.fr
...ère2
delara@cermics.enpc.fr