References of "Fonteneau, Raphaël"
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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 detailOn overfitting and asymptotic bias in batch reinforcement learning with partial observability
François-Lavet, Vincent; Rabusseau, Guillaume; Pineau, Joëlle et al

in Journal of Artificial Intelligence Research (2019), 65

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 detailThe Role of Power-to-Gas and Carbon Capture Technologies in Cross-Sector Decarbonisation Strategies
Berger, Mathias ULiege; Radu, David-Constantin ULiege; Fonteneau, Raphaël ULiege et al

E-print/Working paper (2019)

This paper proposes an optimisation-based framework to tackle long-term centralised planning problems of multi-sector, integrated energy systems including electricity, hydrogen, natural gas, synthetic ... [more ▼]

This paper proposes an optimisation-based framework to tackle long-term centralised planning problems of multi-sector, integrated energy systems including electricity, hydrogen, natural gas, synthetic methane and carbon dioxide. The model selects and sizes the set of power generation, energy conversion and storage as well as carbon capture technologies minimising the cost of supplying energy demand in the form of electricity, hydrogen, natural gas or synthetic methane across the power, heating, transportation and industry sectors whilst accounting for policy drivers, such as energy independence, carbon emissions reductions targets, or support schemes. The usefulness of the model is illustrated in a case study evaluating the potential of sector coupling via power-to-gas and carbon capture technologies to achieve deep decarbonisation targets in the Belgian context. Results, on the one hand, indicate that power-to-gas can only play a minor supporting role in cross-sector decarbonisation strategies in Belgium, as electrolysis plants are generally deployed in moderate quantities whilst methanation plants do not appear in any studied scenario. On the other hand, given the limited renewable potential, post-combustion and direct air carbon capture technologies clearly play an enabling role in any decarbonisation strategy. [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

in Energies (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 detailTariff simulator
Manuel de Villena Millan, Miguel ULiege; Fonteneau, Raphaël ULiege; Ernst, Damien ULiege

Speech/Talk (2019)

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See detailCritical Time Windows for Renewable Resource Complementarity Assessment
Berger, Mathias ULiege; Radu, David-Constantin ULiege; Fonteneau, Raphaël ULiege et al

E-print/Working paper (2018)

This paper proposes a systematic framework to assess the complementarity of renewable resources over arbitrary geographical scopes and temporal scales which is particularly well-suited to exploit very ... [more ▼]

This paper proposes a systematic framework to assess the complementarity of renewable resources over arbitrary geographical scopes and temporal scales which is particularly well-suited to exploit very large data sets of climatological data. The concept of critical time windows is introduced, and a spatio-temporal criticality indicator is proposed, consisting in a parametrised family of scalar indicators quantifying the complementarity between renewable resources in both space and time. The criticality indicator is leveraged to devise a family of optimisation problems identifying sets of locations with maximum complementarity under arbitrary geographical deployment constraints. The applicability of the framework is shown in a case study investigating the complementarity between the wind regimes in continental western Europe and southern Greenland, and its usefulness in a power system planning context is demonstrated. Besides showing that the occurrence of low wind power production events can be significantly reduced on a regional scale by exploiting diversity in local wind patterns, results highlight the fact that aggregating wind power production sites located on different continents may result in a lower occurrence of system-wide low wind power production events and indicate potential benefits of intercontinental electrical interconnections. [less ▲]

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See detailCentralised Planning of National Integrated Energy System with Power-to-Gas and Gas Storages
Berger, Mathias ULiege; Radu, David-Constantin ULiege; Fonteneau, Raphaël ULiege et al

in Proceedings of the 11th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (Medpower2018) (2018, November)

This paper proposes an optimisation-based framework to tackle long-term centralised planning problems of integrated energy systems with bi-directional electricity-gas carriers coupling under various ... [more ▼]

This paper proposes an optimisation-based framework to tackle long-term centralised planning problems of integrated energy systems with bi-directional electricity-gas carriers coupling under various policy constraints. The framework is leveraged to gain insight into possible configurations of the future Belgian energy system, and identify the cost-optimal energy mix as well as short and long-term storage requirements to satisfy CO2 emissions reductions and energy security targets. Results shed light on the economics of a transition to a low-carbon energy system and reveal the potential of power-to-gas and storage in gas form to help achieve ambitious emissions reduction goals. [less ▲]

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See detailDistributed Control of Photovoltaic Units in unbalanced LV Distribution Networks to Prevent Overvoltages
Olivier, Frédéric ULiege; Fonteneau, Raphaël ULiege; Mathieu, Sébastien ULiege et al

in Proc. of the 6th IEEE International Conference on Smart Energy Grid Engineering (SEGE 2018) (2018, August 12)

As more and more photovoltaic units are being installed, some LV networks have already attained their maximum hosting capacity, i.e. the maximum amount of distributed energy resources that they can ... [more ▼]

As more and more photovoltaic units are being installed, some LV networks have already attained their maximum hosting capacity, i.e. the maximum amount of distributed energy resources that they can accommodate during regular operations without suffering problems, such as overvoltages. As an alternative to network reinforcement, active network management (ANM) can, to a certain extent, increase their hosting capacity by controlling the power flows. In the framework of ANM, a distributed control scheme was previously presented. It makes use of a distress signal sent by each participating unit, when its terminal voltage is higher than 1.1 p.u. All units then proceed to absorb the maximum reactive power available. If the problem is not resolved, the units proceed to active power curtailment. This paper extends this control scheme to the case of unbalanced three-phase four-wire distribution networks with single- and/or three-phase inverters. The control scheme works by first partitioning the inverters into four groups, three for the single-phase inverters (one for each phase), and one for the three-phase converters. Each group then independently applies a distributed algorithm similar to the one previously presented. Their performance are then compared to those of two reference schemes, an on-off algorithm that models the default behaviour of PV inverters when there is an overvoltage, and the other one based on an unbalanced OPF. Its resulting total curtailed energy always lies between the two, with the on-off algorithm presenting the poorest performance, and the proposed algorithm losing its edge when the network is strongly unbalanced. [less ▲]

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See detailPhase Identification of Smart Meters by Clustering Voltage Measurements
Olivier, Frédéric ULiege; Sutera, Antonio ULiege; Geurts, Pierre ULiege et al

in Proceedings of the XX Power Systems Computation Conference (PSCC 2018) (2018, June)

When a smart meter, be it single-phase or threephase, is connected to a three-phase network, the phase(s) to which it is connected is (are) initially not known. This means that each of its measurements is ... [more ▼]

When a smart meter, be it single-phase or threephase, is connected to a three-phase network, the phase(s) to which it is connected is (are) initially not known. This means that each of its measurements is not uniquely associated with a phase of the distribution network. This phase information is important because it can be used by Distribution System Operators to take actions in order to have a network that is more balanced. In this work, the correlation between the voltage measurements of the smart meters is used to identify the phases. To do so, the constrained k-means clustering method is first introduced as a reference, as it has been previously used for phase identification. A novel, automatic and effective method is then proposed to overcome the main drawback of the constrained k-means clustering, and improve the quality of the clustering. Indeed, it takes into account the underlying structure of the low-voltage distribution networks beneath the voltage measurements without a priori knowledge on the topology of the network. Both methods are analysed with real measurements from a distribution network in Belgium. The proposed algorithm shows superior performance in different settings, e.g. when the ratio of single-phase over three- phase meters in the network is high, when the period over which the voltages are averaged is longer than one minute, etc. [less ▲]

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See detailModelling of three-phase four-wire low-voltage cables taking into account the neutral connection to the earth
Olivier, Frédéric ULiege; Fonteneau, Raphaël ULiege; Ernst, Damien ULiege

in Proc. of CIRED Workshop 2018 (2018, June)

Local energy communities (LECs) usually occur at the level of low-voltage distribution networks, which are inherently unbalanced due to single-phase household appliances and distributed generation. To ... [more ▼]

Local energy communities (LECs) usually occur at the level of low-voltage distribution networks, which are inherently unbalanced due to single-phase household appliances and distributed generation. To simulate and optimise the behaviour of an LEC, the three phases and neutral must be modelled explicitly. This paper aims at numerically assessing the influence of the modelling of the earth and the connection between the neutral and the earth, in terms of voltages and currents. The simulations are performed on an existing Belgian low-voltage feeder supplying 19 houses, which are all equipped with a smart meter measuring the mean voltage, current, and active and reactive power every minute for each phase. The simulations show that the explicit modelling of the earth using Carson's equations has a moderate effect on the simulation results. In particular, it creates differences in the simulations that are around ten-times smaller than the errors between simulations and measurements. [less ▲]

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See detailA multi-agent system approach to model the interaction between distributed generation deployment and the grid
Manuel de Villena Millan, Miguel ULiege; Gautier, Axel ULiege; Fonteneau, Raphaël ULiege et al

in Proc. of CIRED Workshop 2018 (2018, June)

This paper introduces a multi-agent dynamical system of the interaction between electricity consumers, the electricity distribution system operator, and the technological (generation, storage) and ... [more ▼]

This paper introduces a multi-agent dynamical system of the interaction between electricity consumers, the electricity distribution system operator, and the technological (generation, storage) and regulatory (tariff design, incentive schemes) environments. For any type of environment, our dynamical system simulates the evolution of the deployment of distributed electricity generation, as well as the evolution of the cost of distribution. The system relies on the assumption that individual electricity consumers behave statistically as rational agents, who may invest in optimised distributed renewable energy installations, if they are cost-efficient compared to the retail electricity tariff. The deployment of these installations induces a change in the aggregated net consumption and generation of the users of a distribution network. By modelling the cost recovery mechanism of the distribution system operator, the system simulates the evolution of the retail electricity tariff in response to such a change in the aggregated consumption and production. [less ▲]

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See detailExploring Regulation Policies in Distribution Networks through a Multi-Agent Simulator
Manuel de Villena Millan, Miguel ULiege; Fonteneau, Raphaël ULiege; Gautier, Axel ULiege et al

in Proc. of YRS2018 (2018, May)

This paper presents a multi-agent simulator that describes the interactions between the agents of a distribution network (DN), and an environment. The agents are the users of the DN and the electricity ... [more ▼]

This paper presents a multi-agent simulator that describes the interactions between the agents of a distribution network (DN), and an environment. The agents are the users of the DN and the electricity distribution system operator. The environment is the set of rules (tariff design, technology costs, or incentive schemes) that impacts the agents interactions. For a given environment, we can simulate the evolution of the agents and the environment itself. We assume the electricity consumers are rational agents that may deploy distributed renewable energy installations if they are cost-efficient compared to the retail electricity tariff. The deployment of such installations may alter the cost recovery scheme of the distribution system operator, by inducing a change in the way the user use of the grid. By modelling the cost recovery mechanism of the distribution system operator, the system simulates the evolution of the retail electricity tariff in response to such a change in the aggregated consumption and production. [less ▲]

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See detailForeseeing New Control Challenges in Electricity Prosumer Communities
Olivier, Frédéric ULiege; Marulli, Daniele; Ernst, Damien ULiege et al

in Proc. of the 10th Bulk Power Systems Dynamics and Control Symposium – IREP’2017 (2017, August)

This paper is dedicated to electricity prosumer communities, which are groups of people producing, sharing and consuming electricity locally. This paper focuses on building a rigorous mathematical ... [more ▼]

This paper is dedicated to electricity prosumer communities, which are groups of people producing, sharing and consuming electricity locally. This paper focuses on building a rigorous mathematical framework in order to formalise sequen- tial decision making problems that may soon be encountered within electricity prosumer communities. After introducing our formalism, we propose a set of optimisation problems reflecting several types of theoretically optimal behaviours for energy exchanges between prosumers. We then discuss the advantages and disadvantages of centralised and decentralised schemes and provide illustrations of decision making strategies, allowing a prosumer community to generate more distributed electricity (compared to commonly applied strategies) by mitigating over- voltages over a low-voltage feeder. We finally investigate how to design distributed control schemes that may contribute reaching (at least partially) the objectives of the community, by resort in to machine learning techniques to extract, from centralised solution(s), decision making patterns to be applied locally. First empirical results show that, even after a post-processing phase so that it satisfies physical constraints, the learning approach still performs better than predetermined strategies targeting safety first, then cost minimisation. [less ▲]

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See detailReinforcement Learning for Electric Power System Decision and Control: Past Considerations and Perspectives
Glavic, Mevludin ULiege; Fonteneau, Raphaël ULiege; Ernst, Damien ULiege

in The 20th World Congress of the International Federation of Automatic Control, Toulouse 9-14 July 2017 (2017, July)

In this paper, we review past (including very recent) research considerations in using reinforcement learning (RL) to solve electric power system decision and control problems. The RL considerations are ... [more ▼]

In this paper, we review past (including very recent) research considerations in using reinforcement learning (RL) to solve electric power system decision and control problems. The RL considerations are reviewed in terms of speci c electric power system problems, type of control and RL method used. We also provide observations about past considerations based on a comprehensive review of available publications. The review reveals the RL is considered as viable solutions to many decision and control problems across di erent time scales and electric power system states. Furthermore, we analyse the perspectives of RL approaches in light of the emergence of new-generation, communications, and instrumentation technologies currently in use, or available for future use, in power systems. The perspectives are also analysed in terms of recent breakthroughs in RL algorithms (Safe RL, Deep RL and path integral control for RL) and other, not previously considered, problems for RL considerations (most notably restorative, emergency controls together with so-called system integrity protection schemes, fusion with existing robust controls, and combining preventive and emergency control). [less ▲]

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See detailAutomatic phase identification of smart meter measurement data
Olivier, Frédéric ULiege; Ernst, Damien ULiege; Fonteneau, Raphaël ULiege

in Proceedings of the 24th International Conference and Exhibition on Electricity Distribution, CIRED 2017 (2017, June)

This paper highlights the importance of the knowledge of the phase identification for the different measurement points inside a low-voltage distribution network. Besides considering existing solutions, we ... [more ▼]

This paper highlights the importance of the knowledge of the phase identification for the different measurement points inside a low-voltage distribution network. Besides considering existing solutions, we propose a novel method for identifying the phases of the measurement devices, based exclusively on voltage measurement correlation. It relies on graph theory and the notion of maximum spanning tree. It has been tested on a real Belgian LV network, first with simulated unbalanced voltage for which it managed to correctly identify the phases of all measurement points, second, on preliminary data from a real measurement campaign for which it shows encouraging results. [less ▲]

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See detailA few reinforcement learning stories
Fonteneau, Raphaël ULiege

Speech/Talk (2017)

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