References of "Boukas, Ioannis"
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See detailSizing and Operation of an Isolated Microgrid with Cold Storage
Dakir, Selmane ULiege; Boukas, Ioannis ULiege; Lemort, Vincent ULiege et al

Scientific conference (2019, June)

Due to the technological developments and the advances of smart control, intermittent production from renewable energy sources can be better exploited locally in the context of a smart microgrid. Energy ... [more ▼]

Due to the technological developments and the advances of smart control, intermittent production from renewable energy sources can be better exploited locally in the context of a smart microgrid. Energy storage has a key role in achieving this task and batteries are the most suitable candidate. In this paper, a complementary solution is presented where excess electricity is used in a cold storage to produce ice which, when melting, supplies the cooling demand. A detailed model of each component is considered in order to simulate the operation of the entire system. The goal of this paper is the derivation of the optimal size of the different components to yield the minimum levelized cost of electricity. The methodology described is applied to a real case study in Marrakesh, and results illustrate that cold storage is able to reduce the total cost of energy in the context of an isolated microgrid. [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)

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See detailIntra-day Bidding Strategies for Storage Devices Using Deep Reinforcement Learning
Boukas, Ioannis ULiege; Ernst, Damien ULiege; Papavasiliou, Anthony et al

in International Conference on the European Energy Market, Łódź 27-29 June 2018 (2018, June)

The problem faced by the operator of a storage device participating in a continuous intra-day (CID) market is addressed in this paper. The goal of the storage device operator is the maximization of the ... [more ▼]

The problem faced by the operator of a storage device participating in a continuous intra-day (CID) market is addressed in this paper. The goal of the storage device operator is the maximization of the cumulative rewards received over the entire trading horizon, while taking into account operational constraints. The energy trading is modeled as a Partially Observable Markov Decision Process. An equivalent state representation and high-level actions are proposed in order to tackle the variable number of the existing orders in the order book. The problem is solved using deep reinforcement learning (RL). Preliminary results indicate that the agent converges to a policy that scores higher total revenues than the ``rolling intrinsic''. [less ▲]

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See detailReal-Time Bidding Strategies from Micro-Grids Using Reinforcement Learning
Boukas, Ioannis ULiege; Ernst, Damien ULiege; Cornélusse, Bertrand ULiege

in Proceedings of CIRED Workshop 2018 (2018, June)

We address the problem faced by the operator of a microgrid participating in a continuous real-time market. The microgrid consists of distributed generation, flexible loads and a storage device. The goal ... [more ▼]

We address the problem faced by the operator of a microgrid participating in a continuous real-time market. The microgrid consists of distributed generation, flexible loads and a storage device. The goal of the microgrid operator is the maximization of the profits over the entire trading horizon, while taking into account operational constraints. The variability of the Renewable Energy Sources (RES) is considered and the energy trading is modeled as a Markov Decision Process. The problem is solved using reinforcement learning (RL). The resulting optimal real time bidding strategy of a microgrid is discussed. [less ▲]

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