Le 13/12/2021 par LBrotcorne :

Context and Goal:

Liberalization of electricity markets and new technologies are having a strong influence on how to organize electricity production and transmission.

In this work, we consider the Bidding Problem (BP) of a GC (Generation Companies ) maximizing its profit in coupled day-ahead markets.  The production of the GC is considered high enough to impact the market prices. The model defined in De Boeck et al. integrates a detailed Unit Commitment (UC) formulation of the production planning problem.

The goal of this project consists in relaxing the assumption made in De Boeck et al. that the bids of the competitor are known in advance. More precisely, the first step is to propose stochastic models for bids of the competitors to capture different dependencies (spatial, economic, regional, etc).  Second, the randomness has to be incorporated into the optimization framework. In particular, some type of risk measure has to be added to the formulation to deal with the random parameters that were introduced. The choice will be guided by the need of a risk measure that captures risk aversion of the GC, while at the same time maintaining the structure of the problem so it can be efficiently solved for realistic instances.

The work can be divided into 3 parts:

• Master the model defined in De Boeck et al.
• Define a stochastic model for competitors’ bids. Define scenarios Implement and test the model. 
• Select a risk measure and introduce it into the model. Solve the model and test it on large size instances.

The work will be accompanied and supervised throughout the duration of the internship by Luce Brotcorne, Bernard Fortz and Bernardo Pagnoncelli. Close relations with the doctoral student's work will take place.

Pre-requesities

Bac+5

Knowledge in Linear programming, mixed-integer linear programming

Computational experience in numerical optimization is a must.

While the focus of the work will be in decision making under uncertainty/stochastic programming, no prior knowledge is needed to work in this project. Familiarity with classical models such as two-stage and chance-constrained programming is a plus.
Location

The internship will last 6 months and will start in February/March 2022

Location : INRIA Lille Nord Europe, INOCS Team https://team.inria.fr/inocs/

Application
In order to apply, please send to one of the contacts below, your: (1) Curriculum vitae (2) Motivation letter (3) Transcript of grades of the current year and of the M1 as well as (4) possible letters of recommendation.

Contacts
Luce Brotcorne : Luce.Brotcorne@inria.fr, Directeur de Recherche INRIA, INOCS

Bernard Fortz: Bernard.fortz@ulb.be, Professeur, Université Libre de Bruxelles, INOCS

Bernardo Pagnoncelli : bernardo.pagnoncelli@skema.edu, Professor, SKEMA, Lille

References
[1] J. De Boeck, L. Brotcorne, B. Fortz, Strategic Bidding in Price Coupled Regions, To appear in MMOR in 2022.