Qui ne rêverait pas d’un Hainaut prospère où le taux d’emploi serait à des niveaux jamais atteints ? Qui ne rêverait pas que la Belgique puisse bénéficier de l’énergie produite par ses éoliennes en mer du Nord afin de décarboner…

The research positions are about combining modelling, simulation, optimisation, and machine learning techniques in order to investigate several technical, economic and regulatory aspects induced by major upcoming changes in energy (and in particular, electricity) generation, transmission, distribution and consumption in…

Despite achieving impressive performances on various tasks, modern artificial intelligence (AI) systems have become complex black box models. A growing body of work aspires to open the box and understand its internal functioning. In this new article (Lambrechts et al.,…

The decarbonisation of energy systems is one of the main challenges of our century. Finding the optimal technological mix to achieve that goal is a major concern for policy and decision makers alike. These problems are known as energy system…

Download the paper Summary: Active network management (ANM) of electricity distribution networks include many complex stochastic sequential optimization problems. These problems need to be solved for integrating renewable energies and distributed storage into future electrical grids. In this work, we…

Decarbonising sectors such as aviation, heating and industry has proved difficult via direct electrification. Hence, the synthesis of carbon-neutral fuels and feedstocks from renewable electricity has received much attention in recent years. However, in European countries such as Belgium, the…

The topic of sector coupling and the role it may play in the energy transition has recently received a great deal of attention in European energy policy circles. In particular, power-to-gas technologies, which enable the production of hydrogen via water…

Download the research paper Retailers and major consumers of electricity generally purchase a critical percentage of their estimated electricity needs years ahead on the forward markets. This long-term electricity procurement task consists of determining when to buy electricity so that…

Download the research paper This research paper presents a novel deep reinforcement learning (DRL) solution to the decision-making problem behind algorithmic trading in the stock markets: selecting the appropriate trading action (buy, hold or sell shares) without human intervention. Naturally,…