The 27th of January, 2021, Jérôme De Boeck succesfully defended his thesis titled
From vertical to horizontal structures : New optimization challenges in electricity markets
The jury was composed by:
- Miguel F. Anjos, Professor, University of Edinburgh
- Luce Brotcorne, Directrice de Recherche, INRIA
- Bernard Fortz, Professor, Université Libre de Bruxelles
- Joel Goossens, Professor, Université Libre de Bruxelles
- Martine Labbé, Professor, Université Libre de Bruxelles
- Mathieu Van Vyve, Professor, Université catholique de Louvain
Thesis abstract: The electricity supply chain has seen a strong evolution of its environnement over the past years. Liberalization of electricity markets and new technologies are having a strong influence on how to organize electricity production and transmission. Previous computational methods used in electricity related problems need to be updated in order to follow the evolution of real life constraints.
One classical problem for a generation company (GC) is the Unit Commitment problem (UC) which consists in establishing an electricity production plan over a given time horizon to satisfy a demand in electricity. When first considered, the price of electricity and demands were relatively easy to estimate as national GCs had a monopoly over the market. This problem has been widely studied and solved using Mathematical Programming (MP) methods. Today, the price of electricity can be relatively volatile due to the introduction of deregulated electricity markets and the demand of the market is split among several independent GCs competing on several different markets. When estimating profit, a GC cannot therefore consider solving only a UC problem. There is a need to integrate the uncertainty on the price of electricity and the quantities to produce when a GC must take decisions in order to establish a production plan.
Technology has also led to new conceptual organization in the electricity supply chain through Micro-Grids (MGs). A MG is composed of a group of power consumers which have their own power generation units and optimizes its internal electricity consumption. This concept is possible due to the increasing use of renewable energy sources and the increasing penetration of interconnected devices used in daily life. Still, because renewable energy sources are intermittent and storage devices are still not sufficiently efficient, MGs cannot consider being autonomous regarding electricity production. Therefore, MGs must have external power suppliers to ensure sufficient electricity supply at all time. A GC trading electricity with a MG faces a lot of uncertainty regarding its demand because of the internal management of the MG.
This situation asks again for new computational methods considering the interaction between different actors. We also face an increasing need of reliability in electricity transmission. Optimization problems related to transmission networks have also been studied for a long time as the UC. These optimization problems increasingly tend to consider robustness to deal with reliability issues. In this thesis, several optimization problems considering modern constraints related to the electricity supply chain are studied through MP. Several problems consider interactions between actors and are modelled through bi-level formulations. We illustrate how the difficulties introduced by the evolving context can be used to derive properties of the models considered to reformulate them into mixed integer linear programs. Efficient heuristic methods are obtained inspired by the exact formulations proposed, some of which being applicable to more general problems. An extensive analysis of the performance of the solving methods as well as the influence of the parameters of the problems introduced by modern constraints are presented.
