References of "Ernst, Damien"
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See detailHarnessing the flexibility of energy management systems: a retailer perspective
Mathieu, Sébastien ULiege; Manuel de Villena Millan, Miguel ULiege; Vermeulen, Eric et al

in Proceedings PowerTech 2019 (2019, June)

The business of electricity retailing is changing following the current evolution of the electricity system. An example of such an evolution is the increasing number of clients installing sophisticated ... [more ▼]

The business of electricity retailing is changing following the current evolution of the electricity system. An example of such an evolution is the increasing number of clients installing sophisticated energy management systems controlling the production or consumption of a large variety of devices as, for instance, photovoltaic panels with storage solutions. These systems, if managed properly, may provide flexibility to the electricity system to which they are connected, typically by means of an intermediary such as a retailer. Retailers could transfer such flexibility in consumption/production of electricity to the day-ahead and intraday electricity markets, trade it with other balance responsible parties, or use it to participate in the imbalance market. This paper defines an interaction model between a retailer and its clients, based on generic flexibility bids over multiple market periods. The defined interaction model relies on smart meters for registering the trades of electricity and requires no modification of the current rules and regulations of the European electricity system. The concept of flexibility is defined with respect to a baseline, which is negotiated and agreed upon between the retailer and each client. This baseline can be modified by the client following an update mechanism, which must comply with certain security checks by the retailer in order to make sure it is not fraudulent. Any deviations from the quarter-hourly comparison between expected and actual production/consumption are invoiced at a discounted price. [less ▲]

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See detailComplementarity Assessment of South Greenland Katabatic Flows and West Europe Wind Regimes
Radu, David-Constantin ULiege; Berger, Mathias ULiege; Fonteneau, Raphaël ULiege et al

in Energy (2019), 175

Current global environmental challenges require vigorous and diverse actions in the energy sector. One solution that has recently attracted interest consists in harnessing high-quality variable renewable ... [more ▼]

Current global environmental challenges require vigorous and diverse actions in the energy sector. One solution that has recently attracted interest consists in harnessing high-quality variable renewable energy resources in remote locations, while using transmission links to transport the power to end users. In this context, a comparison of western European and Greenland wind regimes is proposed. By leveraging a regional atmospheric model specifically designed to accurately capture polar phenomena, local climatic features of southern Greenland are identified to be particularly conducive to extensive renewable electricity generation from wind. A methodology to assess how connecting remote locations to major demand centres would benefit the latter from a resource availability standpoint is introduced and applied to the aforementioned Europe-Greenland case study, showing superior and complementary wind generation potential in the considered region of Greenland with respect to selected European sites. [less ▲]

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See detailL’écologie authentique, stade avancé de la civilisation technologique
de Salle, Corentin; Ernst, Damien ULiege

Article for general public (2019)

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See detailDamien Ernst: "La technologie sauvera la planète"
Wolff, Geoffrey; Ernst, Damien ULiege

Article for general public (2019)

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See detailAuthentic ecology as an advanced stage of technological civilization
de Salle, Corentin; Ernst, Damien ULiege

E-print/Working paper (2019)

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See detailBlockchain: A novel approach for the consensus algorithm using Condorcet Voting procedure
Vangulick, David ULiege; Cornélusse, Bertrand ULiege; Ernst, Damien ULiege

in Proceedings of the IEEE International Conference on Decentralized Applications and Infrastructures (2019, April)

The blockchain technology allows interested parties to access a common register, the update, and integrity of which are collectively managed in a decentralized manner by a network of actors. It is the ... [more ▼]

The blockchain technology allows interested parties to access a common register, the update, and integrity of which are collectively managed in a decentralized manner by a network of actors. It is the consensus protocol that ensures a common and unambiguous update of transactions by creating blocks of transactions for which integrity, veracity, and consistency are guaranteed through geographically distributed nodes. Bitcoin, the first popular blockchain concept, introduced the Proof of Work consensus based on work validation, and has been extended to thousands of participants. Despite its success and its large use in other crypto-currencies, Proof of Work’s disadvantages are a high latency, a low transaction rate, and a high energy expenditure, making it a less-than-perfect choice for many applications. In addition the validation of transactions is not carried out with a definite temporality. For Bitcoin, it takes on average 10 minutes to create a block. However, for certain use cases such as auctions or the exchange of energy, there is a need for this temporality. The purpose of this article is to propose a new type of consensus that is faster, less energy-consuming and that can be synchronized with a time reference. The core of the reflection is the use of the Condorcet voting mechanism to determine the miner. [less ▲]

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See detailTariff simulator
Manuel de Villena Millan, Miguel ULiege; Fonteneau, Raphaël ULiege; Ernst, Damien ULiege

Speech/Talk (2019)

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See detailDécret favorisant le développement des communautés d’énergie renouvelable
Ernst, Damien ULiege

Speech/Talk (2019)

Detailed reference viewed: 337 (15 ULiège)
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See detailOn overfitting and asymptotic bias in batch reinforcement learning with partial observability
François-Lavet, Vincent ULiege; Rabusseau, Guillaume; Pineau, Joelle et al

E-print/Working paper (2019)

This paper provides an analysis of the tradeoff between asymptotic bias (suboptimality with unlimited data) and overfitting (additional suboptimality due to limited data) in the context of reinforcement ... [more ▼]

This paper provides an analysis of the tradeoff between asymptotic bias (suboptimality with unlimited data) and overfitting (additional suboptimality due to limited data) in the context of reinforcement learning with partial observability. Our theoretical analysis formally characterizes that while potentially increasing the asymptotic bias, a smaller state representation decreases the risk of overfitting. This analysis relies on expressing the quality of a state representation by bounding L1 error terms of the associated belief states. Theoretical results are empirically illustrated when the state representation is a truncated history of observations, both on synthetic POMDPs and on a large-scale POMDP in the context of smartgrids, with real-world data. Finally, similarly to known results in the fully observable setting, we also briefly discuss and empirically illustrate how using function approximators and adapting the discount factor may enhance the tradeoff between asymptotic bias and overfitting in the partially observable context. [less ▲]

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See detailVoiture électrique : 697.612 km pour devenir verte ! Vrai ou faux ?
Ernst, Damien ULiege

E-print/Working paper (2019)

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See detailElectric car: 697,612 km to become green! True or false?
Ernst, Damien ULiege

E-print/Working paper (2019)

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See detailEnergiespecialist Damien Ernst: 'We hoeven helemaal niet minder energie te verbruiken'
Renard, Han; Ernst, Damien ULiege

Article for general public (2019)

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See detailIntroducing neuromodulation in deep neural networks to learn adaptive behaviours
Vecoven, Nicolas ULiege; Ernst, Damien ULiege; Wehenkel, Antoine ULiege et al

E-print/Working paper (2019)

In this paper, we propose a new deep neural network architecture, called NMD net, that has been specifically designed to learn adaptive behaviours. This architecture exploits a biological mechanism called ... [more ▼]

In this paper, we propose a new deep neural network architecture, called NMD net, that has been specifically designed to learn adaptive behaviours. This architecture exploits a biological mechanism called neuromodulation that sustains adaptation in biological organisms. This architecture has been introduced in a deep-reinforcement learning architecture for interacting with Markov decision processes in a meta-reinforcement learning setting where the action space is continuous. The deep-reinforcement learning architecture is trained using an advantage actor-critic algorithm. Experiments are carried on several test problems. Results show that the neural network architecture with neuromodulation provides significantly better results than state-of-the-art recurrent neural networks which do not exploit this mechanism. [less ▲]

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See detailEvaluating the Evolution of Distribution Networks under Different Regulatory Frameworks with Multi-Agent Modelling
Manuel de Villena Millan, Miguel ULiege; Fonteneau, Raphaël ULiege; Gautier, Axel ULiege et al

E-print/Working paper (2019)

In the context of increasing decentralised electricity generation, this paper evaluates the effect of different regulatory frameworks on the evolution of distribution networks. This problem is addressed ... [more ▼]

In the context of increasing decentralised electricity generation, this paper evaluates the effect of different regulatory frameworks on the evolution of distribution networks. This problem is addressed by means of agent based modelling in which the interactions between the agents of a distribution network, and an environment are described. The consumers and the distribution system operator are the agents, which act in an environment that is composed by a set of rules. For a given environment, we can simulate the evolution of the distribution network by computing the actions of the agents at every time step of a discrete time dynamical system. We assume the electricity consumers are rational agents that may deploy distributed energy installations. The deployment of such installations may alter the remuneration mechanism of the distribution system operator. By modelling this mechanism, we may compute the evolution of the electricity distribution tariff in response to the deployment of distributed generation. [less ▲]

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See detailImpact of gate closure time on the efficiency of power systems balancing
Petitet, Marie; Perrot, Marie; Mathieu, Sébastien ULiege et al

in Energy Policy (2019), 129

This paper focuses on market design options for operational balancing management in self-dispatch electric power systems. In particular, it investigates the most relevant timing for the balancing gate ... [more ▼]

This paper focuses on market design options for operational balancing management in self-dispatch electric power systems. In particular, it investigates the most relevant timing for the balancing gate closure, when competitors' decisions on the setting of controllable assets are neutralized and this responsibility is simultaneously transferred to the system operator. This discussion is central in the development and implementation of the European Electricity Balancing Guideline. Based on a multi-level simulation tool with a realistic modelling of short-term power system operations, this paper proposes the first quantitative assessment of postponing the balancing gate closure time from 1 h to 15 min ahead of the imbalance settlement period. For different environments (energy mix, power plant capabilities, outages, etc), the results highlight that postponing the balancing gate closure time from 1 h to 15 min increases the operational cost of the system. Based on robust and scalable results, we show that this difference is mainly due to a better coordination of the available resources by the central decision maker. [less ▲]

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See detailA Deep Reinforcement Learning Framework for Continuous Intraday Market Bidding
Boukas, Ioannis ULiege; Ernst, Damien ULiege; Théate, Thibaut ULiege et al

E-print/Working paper (2019)

Detailed reference viewed: 126 (23 ULiège)