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Theses

Optimisation des alimentations électriques des Data Centers

Abstract : Data centers, factories housing thousands of computer servers that work permanently to exchange, store, process data and make it accessible via the Internet. With the digital sector development, their energy consumption, which is largely fossil fuel-based, has grown continuously over the last decade, posing a real threat to the environment. The use of renewable energy is a promising way to limit the ecological footprint of data centers. Nevertheless, the intermittent nature of these sources hinders their integration into a system requiring a high reliability degree. The hybridization of several technologies for green electricity production, coupled with storage devices, is currently an effective solution to this problem. As a result, this research work studies a multi-source system, integrating tidal turbines, photovoltaic panels, batteries and a hydrogen storage system to power an MW-scale data center. The main objective of this thesis is the optimization of a data center power supply, both for isolated sites and grid-connected ones. The first axis of this work is the modeling of the system components using the energetic macroscopic representation (EMR). Energy management strategy based on the frequency separation principle is first adopted to share power between storage devices with different dynamic characteristics. The second axis concerns the optimal sizing of the proposed system, in order to find the best configuration that meets the technical constraints imposed at minimum cost, using particle swarm optimization (PSO) and genetic algorithm (GA). Here, a rules-based energy management technique is used for simplicity and reduced computing time purposes. The last axis focuses on the energy management optimization through GA, taking into account the storage systems degradation in order to reduce their operating costs and extend their lifetime. It should be noted that each axis previously discussed has been the subject of a specific sensitivity analysis, which aims to evaluate the performance of the hybrid system under different operating conditions.
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Submitted on : Monday, March 22, 2021 - 3:25:28 PM
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  • HAL Id : tel-03176623, version 1

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Nouhaila Lazaar. Optimisation des alimentations électriques des Data Centers. Energie électrique. Normandie Université; Université Moulay Ismaïl (Meknès, Maroc), 2021. Français. ⟨NNT : 2021NORMC206⟩. ⟨tel-03176623⟩

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