References of "Ernst, Damien"
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See detailOn the Dynamics of the Deployment of Renewable Energy Production Capacities
Fonteneau, Raphaël ULg; Ernst, Damien ULg

in Furze, James N.; Swing, Kelly; Gupta, Anil K. (Eds.) et al Mathematical Advances Towards Sustainable Environmental Systems (2017)

This chapter falls within the context of modeling the deployment of renewable en-ergy production capacities in the scope of the energy transition. This problem is addressed from an energy point of view, i ... [more ▼]

This chapter falls within the context of modeling the deployment of renewable en-ergy production capacities in the scope of the energy transition. This problem is addressed from an energy point of view, i.e. the deployment of technologies is seen as an energy investment under the constraint that an initial budget of non-renewable energy is provided. Using the Energy Return on Energy Investment (ERoEI) characteristics of technologies, we propose MODERN, a discrete-time formalization of the deployment of renewable energy production capacities. Be-sides showing the influence of the ERoEI parameter, the model also underlines the potential benefits of designing control strategies for optimizing the deployment of production capacities, and the necessity to increase energy efficiency. [less ▲]

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See detailDeep Reinforcement Learning Solutions for Energy Microgrids Management
François-Lavet, Vincent ULg; Taralla, David; Ernst, Damien ULg et al

in European Workshop on Reinforcement Learning (EWRL 2016) (2016, December)

This paper addresses the problem of efficiently operating the storage devices in an electricity microgrid featuring photovoltaic (PV) panels with both short- and long-term storage capacities. The problem ... [more ▼]

This paper addresses the problem of efficiently operating the storage devices in an electricity microgrid featuring photovoltaic (PV) panels with both short- and long-term storage capacities. The problem of optimally activating the storage devices is formulated as a sequential decision making problem under uncertainty where, at every time-step, the uncertainty comes from the lack of knowledge about future electricity consumption and weather dependent PV production. This paper proposes to address this problem using deep reinforcement learning. To this purpose, a specific deep learning architecture has been designed in order to extract knowledge from past consumption and production time series as well as any available forecasts. The approach is empirically illustrated in the case of a residential customer located in Belgium. [less ▲]

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See detailThe Green Grid Network and Trading Renewable Energy
Ernst, Damien ULg

Speech/Talk (2016)

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See detailBatteries and disrupting business models for the energy sector
Ernst, Damien ULg; Goka, Olivier

Speech/Talk (2016)

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See detailActive network management for electrical distribution systems: problem formulation, benchmark, and approximate solution
Gemine, Quentin ULg; Ernst, Damien ULg; Cornélusse, Bertrand ULg

in Optimization and Engineering (2016)

With the increasing share of renewable and distributed generation in electrical distribution systems, active network management (ANM) becomes a valuable option for a distribution system operator to ... [more ▼]

With the increasing share of renewable and distributed generation in electrical distribution systems, active network management (ANM) becomes a valuable option for a distribution system operator to operate his system in a secure and cost-effective way without relying solely on network reinforcement. ANM strategies are short-term policies that control the power injected by generators and/or taken off by loads in order to avoid congestion or voltage issues. While simple ANM strategies consist in curtailing temporary excess generation, more advanced strategies rather attempt to move the consumption of loads to anticipated periods of high renewable generation. However, such advanced strategies imply that the system operator has to solve large-scale optimal sequential decision-making problems under uncertainty. The problems are sequential for several reasons. For example, decisions taken at a given moment constrain the future decisions that can be taken, and decisions should be communicated to the actors of the system sufficiently in advance to grant them enough time for implementation. Uncertainty must be explicitly accounted for because neither demand nor generation can be accurately forecasted. We first formulate the ANM problem, which in addition to be sequential and uncertain, has a nonlinear nature stemming from the power flow equations and a discrete nature arising from the activation of power modulation signals. This ANM problem is then cast as a stochastic mixed-integer nonlinear program, as well as second-order cone and linear counterparts, for which we provide quantitative results using state of the art solvers and perform a sensitivity analysis over the size of the system, the amount of available flexibility, and the number of scenarios considered in the deterministic equivalent of the stochastic program. To foster further research on this problem, we make available at http://www.montefiore.ulg.ac.be/~anm/ three test beds based on distribution networks of 5, 33, and 77 buses. These test beds contain a simulator of the distribution system, with stochastic models for the generation and consumption devices, and callbacks to implement and test various ANM strategies. [less ▲]

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See detailLa transition énergétique, l’affaire de tous
Ernst, Damien ULg

Speech/Talk (2016)

Conférence d'ouverture donnée par le Prof . Ernst lors de la soirée de lancement de la saison 2016-2017 de Liège Créative. Accéder à la vidéo de la conférence: https://www.youtube.com/watch?v=2SJ14Sj33bI

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See detailCes robots qui pourraient nous vouloir du mal...
Bouffioux, Michel; Ernst, Damien ULg

Article for general public (2016)

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See detailBenchmarking for Bayesian Reinforcement Learning
Castronovo, Michaël ULg; Ernst, Damien ULg; Couëtoux, Adrien ULg et al

in PLoS ONE (2016)

In the Bayesian Reinforcement Learning (BRL) setting, agents try to maximise the col- lected rewards while interacting with their environment while using some prior knowledge that is accessed beforehand ... [more ▼]

In the Bayesian Reinforcement Learning (BRL) setting, agents try to maximise the col- lected rewards while interacting with their environment while using some prior knowledge that is accessed beforehand. Many BRL algorithms have already been proposed, but even though a few toy examples exist in the literature, there are still no extensive or rigorous benchmarks to compare them. The paper addresses this problem, and provides a new BRL comparison methodology along with the corresponding open source library. In this methodology, a comparison criterion that measures the performance of algorithms on large sets of Markov Decision Processes (MDPs) drawn from some probability distributions is defined. In order to enable the comparison of non-anytime algorithms, our methodology also includes a detailed analysis of the computation time requirement of each algorithm. Our library is released with all source code and documentation: it includes three test prob- lems, each of which has two different prior distributions, and seven state-of-the-art RL algorithms. Finally, our library is illustrated by comparing all the available algorithms and the results are discussed. [less ▲]

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See detailDirect control service from residential heat pump aggregation with specified payback
Georges, Emeline ULg; Cornélusse, Bertrand ULg; Ernst, Damien ULg et al

in Proceedings of the 19th Power Systems Computation Conference (PSCC) (2016, June)

This paper addresses the problem of an aggregator controlling residential heat pumps to offer a direct control flexibility service. The service is defined by a 15 minute power modulation, upward or ... [more ▼]

This paper addresses the problem of an aggregator controlling residential heat pumps to offer a direct control flexibility service. The service is defined by a 15 minute power modulation, upward or downward, followed by a payback of one hour and 15 minutes. The service modulation is relative to an optimized baseline that minimizes the energy costs. The potential amount of modulable power and the payback effect are computed by solving mixed integer linear problems. Within these problems, the building thermal behavior is modeled by an equivalent thermal network made of resistances and lumped capacitances whose parameters are identified from validated models. Simulations are performed on 100 freestanding houses. For an average 4.3 kW heat pump, results show a potential of 1.2 kW upward modulation with a payback of 600 Wh and 150 Wh of overconsumption. A downward modulation of 500 W per house can be achieved with a payback of 420 Wh and 120 Wh of overconsumption. [less ▲]

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See detailA Gaussian mixture approach to model stochastic processes in power systems
Gemine, Quentin ULg; Cornélusse, Bertrand ULg; Glavic, Mevludin ULg et al

in Proceedings of the 19th Power Systems Computation Conference (PSCC'16) (2016, June)

Probabilistic methods are emerging for operating electrical networks, driven by the integration of renewable generation. We present an algorithm that models a stochastic process as a Markov process using ... [more ▼]

Probabilistic methods are emerging for operating electrical networks, driven by the integration of renewable generation. We present an algorithm that models a stochastic process as a Markov process using a multivariate Gaussian Mixture Model, as well as a model selection technique to search for the adequate Markov order and number of components. The main motivation is to sample future trajectories of these processes from their last available observations (i.e. measurements). An accurate model that can generate these synthetic trajectories is critical for applications such as security analysis or decision making based on lookahead models. The proposed approach is evaluated in a lookahead security analysis framework, i.e. by estimating the probability of future system states to respect operational constraints. The evaluation is performed using a 33-bus distribution test system, for power consumption and wind speed processes. Empirical results show that the GMM approach slightly outperforms an ARMA approach. [less ▲]

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See detailThe Rise of Artificial Intelligence
Ernst, Damien ULg

Speech/Talk (2016)

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See detailFurther validation and extensions of the Global Capacity ANnouncement procedure for distribution systems
Cornélusse, Bertrand ULg; Vangulick, David; Glavic, Mevludin ULg et al

in CIRED Workshop Proceedings, Helsinki 14-15 June 2016 (2016, May)

This paper extends the Global Capacity ANnouncement procedure proposed in [5] along two directions. First, two new stopping criteria are considered. Second, annual losses are evaluated using ... [more ▼]

This paper extends the Global Capacity ANnouncement procedure proposed in [5] along two directions. First, two new stopping criteria are considered. Second, annual losses are evaluated using representative days to approximate the injection duration curve. The extensions are validated on an updated model of a real-life system. The emphasis is on the situation in the Walloon region of Belgium considered in the GREDOR project [1]. A way for a DSO to publish Global Capacity ANnouncement computation results is shortly discussed. [less ▲]

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See detailSmart Grids versus Microgrids
Ernst, Damien ULg

Speech/Talk (2016)

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See detailModelling and Emulation of an Unbalanced LV Feeder with Photovoltaic Inverters
López-Erauskin, Ramón; Gyselinck, Johan; Olivier, Frédéric ULg et al

in Proc. of 8th IEEE Benelux Young researchers symposium in Electrical Power Engineering (2016, May)

In this paper, the penetration of grid-connected pho- tovoltaic systems is studied, experimentally tested and compared to simulation results. In particular, how the inverse current flow and unbalance ... [more ▼]

In this paper, the penetration of grid-connected pho- tovoltaic systems is studied, experimentally tested and compared to simulation results. In particular, how the inverse current flow and unbalance situations affect the voltage in the low-voltage grid. Thus, a test platform has been developed for obtaining experimental results with grid-tied commercial inverters. Photo- voltaic arrays are emulated and subjected to different irradiance profiles and the inverters are controlled to produce at different power conditions. A model has been developed in order to repro- duce the same operating conditions and working environment. Simulations are performed with the software PowerFactory and the results compared to the experimental ones. [less ▲]

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See detailCOP21 and Electrical Systems
Ernst, Damien ULg

Speech/Talk (2016)

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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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