References of "François-Lavet, Vincent"
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See detailTowards the Minimization of the Levelized Energy Costs of Microgrids using both Long-term and Short-term Storage Devices
François-Lavet, Vincent ULg; Gemine, Quentin ULg; Ernst, Damien ULg et al

in Smart Grid: Networking, Data Management, and Business Models (2016)

This chapter falls within the context of the optimization of the levelized energy cost (LEC) of microgrids featuring photovoltaic panels (PV) associated with both long-term (hydrogen) and short-term ... [more ▼]

This chapter falls within the context of the optimization of the levelized energy cost (LEC) of microgrids featuring photovoltaic panels (PV) associated with both long-term (hydrogen) and short-term (batteries) storage devices. First, we propose a novel formalization of the problem of building and operating microgrids interacting with their surrounding environment. Then we show how to optimally operate a microgrid using linear programming techniques in the context where the consumption and the production are known. It appears that this optimization technique can also be used to address the problem of optimal sizing of the microgrid, for which we propose a robust approach. These contributions are illustrated in two different settings corresponding to Belgian and Spanish data. [less ▲]

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See detailImitative Learning for Online Planning in Microgrids
Aittahar, Samy ULg; François-Lavet, Vincent ULg; Lodeweyckx, Stefan et al

in Woon, Wei Lee; Zeyar, Aung; Stuart, Madnick (Eds.) Data Analytics for Renewable Energy Integration (2015, December 15)

This paper aims to design an algorithm dedicated to operational planning for microgrids in the challenging case where the scenarios of production and consumption are not known in advance. Using expert ... [more ▼]

This paper aims to design an algorithm dedicated to operational planning for microgrids in the challenging case where the scenarios of production and consumption are not known in advance. Using expert knowledge obtained from solving a family of linear programs, we build a learning set for training a decision-making agent. The empirical performances in terms of Levelized Energy Cost (LEC) of the obtained agent are compared to the expert performances obtained in the case where the scenarios are known in advance. Preliminary results are promising. [less ▲]

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See detailHow to Discount Deep Reinforcement Learning: Towards New Dynamic Strategies
François-Lavet, Vincent ULg; Fonteneau, Raphaël ULg; Ernst, Damien ULg

in NIPS 2015 Workshop on Deep Reinforcement Learning (2015, December)

Using deep neural nets as function approximator for reinforcement learning tasks have recently been shown to be very powerful for solving problems approaching real-world complexity. Using these results as ... [more ▼]

Using deep neural nets as function approximator for reinforcement learning tasks have recently been shown to be very powerful for solving problems approaching real-world complexity. Using these results as a benchmark, we discuss the role that the discount factor may play in the quality of the learning process of a deep Q-network (DQN). When the discount factor progressively increases up to its final value, we empirically show that it is possible to significantly reduce the number of learning steps. When used in conjunction with a varying learning rate, we empirically show that it outperforms original DQN on several experiments. We relate this phenomenon with the instabilities of neural networks when they are used in an approximate Dynamic Programming setting. We also describe the possibility to fall within a local optimum during the learning process, thus connecting our discussion with the exploration/exploitation dilemma. [less ▲]

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See detailElectricity storage with liquid fuels in a zone powered by 100% variable renewables
Léonard, Grégoire ULg; François-Lavet, Vincent ULg; Ernst, Damien ULg et al

in Proceedings of the 12th International Conference on the European Energy Market - EEM15 (2015)

In this work, an electricity zone with 100% renewables is simulated to determine the optimal sizing of generation and storage capacities in such a zone. Using actual wind output data, the model evaluates ... [more ▼]

In this work, an electricity zone with 100% renewables is simulated to determine the optimal sizing of generation and storage capacities in such a zone. Using actual wind output data, the model evaluates the economic viability of a power-to-fuel storage technology that combines water electrolysis, CO2 capture and methanol synthesis. The main advantage of using methanol as an energy carrier is that liquid fuels are suitable for (long-term) energy storage thanks to their high energy density. The levelized electricity cost projection by 2050 equals 83.4 €/MWh in the base case configuration. The effects of storage round-trip efficiency and the storage unit lifetime are quantified and their impacts on the electricity cost discussed. Additional benefits of using methanol as a fuel substitute may be taken into account in further work. [less ▲]

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See detailUsing approximate dynamic programming for estimating the revenues of a hydrogen-based high-capacity storage device
François-Lavet, Vincent ULg; Fonteneau, Raphaël ULg; Ernst, Damien ULg

in IEEE Symposium Series on Computational Intelligence (2014)

This paper proposes a methodology to estimate the maximum revenue that can be generated by a company that operates a high-capacity storage device to buy or sell electricity on the day-ahead electricity ... [more ▼]

This paper proposes a methodology to estimate the maximum revenue that can be generated by a company that operates a high-capacity storage device to buy or sell electricity on the day-ahead electricity market. The methodology exploits the Dynamic Programming (DP) principle and is specified for hydrogen-based storage devices that use electrolysis to produce hydrogen and fuel cells to generate electricity from hydrogen. Experimental results are generated using historical data of energy prices on the Belgian market. They show how the storage capacity and other parameters of the storage device influence the optimal revenue. The main conclusion drawn from the experiments is that it may be advisable to invest in large storage tanks to exploit the inter-seasonal price fluctuations of electricity. [less ▲]

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See detailSimple connectome inference from partial correlation statistics in calcium imaging
Sutera, Antonio ULg; Joly, Arnaud ULg; François-Lavet, Vincent ULg et al

in Proceedings of Connectomics 2014 (ECML 2014) (2014, June)

In this work, we propose a simple yet effective solution to the problem of connectome inference in calcium imaging data. The proposed algorithm consists of two steps. First, processing the raw signals to ... [more ▼]

In this work, we propose a simple yet effective solution to the problem of connectome inference in calcium imaging data. The proposed algorithm consists of two steps. First, processing the raw signals to detect neural peak activities. Second, inferring the degree of association between neurons from partial correlation statistics. This paper summarises the methodology that led us to win the Connectomics Challenge, proposes a simplified version of our method, and finally compares our results with respect to other inference methods. [less ▲]

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See detailEstimating the revenues of a hydrogen-based high-capacity storage device: methodology and results
François-Lavet, Vincent ULg; Fonteneau, Raphaël ULg; Ernst, Damien ULg

in Proceedings des 9èmes Journée Francophones de Planification, Décision et Apprentissage (2014, May)

This paper proposes a methodology to estimate the maximum revenue that can be generated by a company that operates a high-capacity storage device to buy or sell electricity on the day-ahead electricity ... [more ▼]

This paper proposes a methodology to estimate the maximum revenue that can be generated by a company that operates a high-capacity storage device to buy or sell electricity on the day-ahead electricity market. The methodology exploits the Dynamic Programming (DP) principle and is specified for hydrogen-based storage devices that use electrolysis to produce hydrogen and fuel cells to generate electricity from hydrogen. Experimental results are generated using historical data of energy prices on the Belgian market. They show how the storage capacity and other parameters of the storage device influence the optimal revenue. The main conclusion drawn from the experiments is that it may be interesting to invest in large storage tanks to exploit the inter-seasonal price fluctuations of electricity. [less ▲]

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See detailAn Energy-Based Variational Model of Ferromagnetic Hysteresis for Finite Element Computations
François-Lavet, Vincent ULg; Henrotte, François; Stainier, Laurent ULg et al

in Journal of Computational & Applied Mathematics (2013), 246

This paper proposes a macroscopic model for ferromagnetic hysteresis that is well-suited for finite element implementation. The model is readily vectorial and relies on a consistent thermodynamic ... [more ▼]

This paper proposes a macroscopic model for ferromagnetic hysteresis that is well-suited for finite element implementation. The model is readily vectorial and relies on a consistent thermodynamic formulation. In particular, the stored magnetic energy and the dissipated energy are known at all times, and not solely after the completion of closed hysteresis loops as is usually the case. The obtained incremental formulation is variationally consistent, i.e., all internal variables follow from the minimization of a thermodynamic potential. [less ▲]

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See detailVectorial Incremental Nonconservative Consistent Hysteresis model
François-Lavet, Vincent ULg; Henrotte, François; Stainier, Laurent ULg et al

in Hogge, Michel; Van Keer, Roger; Malengier, Benny (Eds.) et al Proceedings of the 5th International Conference on Advanded COmputational Methods in Engineering (ACOMEN2011) (2011, November)

This paper proposes a macroscopic model for ferromagnetic hysteresis that is well-suited for finite element implementation. The model is readily vectorial and relies on a consistent thermodynamic ... [more ▼]

This paper proposes a macroscopic model for ferromagnetic hysteresis that is well-suited for finite element implementation. The model is readily vectorial and relies on a consistent thermodynamic formulation. In particular, the stored magnetic energy and the dissipated energy are known at all times, and not solely after the completion of closed hysteresis loops as is usually the case. The obtained incremental formulation is variationally consistent, i.e., all internal variables follow from the minimization of a thermodynamic potential. [less ▲]

Detailed reference viewed: 103 (14 ULg)