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Publications associées (74)
Multi-agent reinforcement learning with graph convolutional neural networks for optimal bidding strategies of generation units in electricity markets
Finding optimal bidding strategies for generation units in electricity markets would result in higher profit. However, it is a challenging problem due to the system uncertainty which is due to the lack of knowledge of the strategies of other generation uni ...
PERGAMON-ELSEVIER SCIENCE LTD2023Connecting Hodge and Sakaguchi-Kuramoto through a mathematical framework for coupled oscillators on simplicial complexes
Phase synchronizations in models of coupled oscillators such as the Kuramoto model have been widely studied with pairwise couplings on arbitrary topologies, showing many unexpected dynamical behaviors. Here, based on a recent formulation the Kuramoto model ...
NATURE PORTFOLIO2022D-Cliques: Compensating for Data Heterogeneity with Topology in Decentralized Federated Learning
Anne-Marie Kermarrec, Erick Lavoie
The convergence speed of machine learning models trained with Federated Learning is significantly affected by non-independent and identically distributed (non-IID) data partitions, even more so in a fully decentralized setting without a central server. In ...
2022A Modular Multilevel Converter with a Clamping Switch for Quasi-Three-Level Operation
The required module capacitances of modular multilevel converters can be significantly reduced in comparison to conventional operation modes when quasi-two-level operation is applied. Unfortunately, the output voltage distortion becomes similar to those of ...
IEEE2021Robust optimization of power grid with distributed generation and improved reliability
Amarasinghage Tharindu Dasun Perera, Zhengchao Wang
Uncertainties of demand, generation and component outage can lead to black-outs in the grid. This study proposes an optimization algorithm (based on Benders Decomposition (BD)) to optimize a Power Transmission System (PTS) that is robust to aforementioned ...
ELSEVIER SCIENCE BV2019