Bertrand Cornélusse

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This paper addresses the problem faced by a distribution system operator (DSO) when planning the operation of a network in the short-term. The problem is formulated in the context of high penetration of renewable energy sources (RES) and distributed generation (DG), and when flexible demand is available. The problem is expressed as a sequential(More)
— In this paper we propose a methodology based on supervised automatic learning in order to classify the behaviour of generators in terms of their performance in providing primary frequency control ancillary services. The problem is posed as a time-series classification problem, and handled by using state-of-the-art supervised learning methods such as(More)
Tree based ensemble methods can be seen as a way to learn a kernel from a sample of input-output pairs. This paper proposes a regularization framework to incorporate non-standard information not used in the kernel learning algorithm, so as to take advantage of incomplete information about output values and/or of some prior information about the problem at(More)
In order to operate an electrical distribution network in a secure and cost-efficient way, it is necessary, due to the rise of renewable energy-based distributed generation, to develop Active Network Management (ANM) strategies. These strategies rely on short-term policies that control the power injected by generators and/or taken off by loads in order to(More)
—We propose and analyze a day-ahead reserve market model that handles bids from flexible loads. This pool market model takes into account the fact that a load modulation in one direction must usually be compensated later by a modulation of the same magnitude in the opposite direction. Our analysis takes into account the gaming possibilities of producers and(More)
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