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Theses

Aide à la décision multicritère pour l’optimisation de scénarios de production énergétique via l’utilisation de données spatiales

Abstract : Currently, lack of electricity is a major global issue around the world due to the increase in power demand, that’s why implementation of renewable energy(RE) is an important alternative solution to feed our electricity needs, reducing Green House Gases (GHG) emissions to fight climate change and to mitigate the dependency on fossil fuels resources. So, (RE) transition planning is an essential ongoing strategy to feed our demand needs whether the network is grid-connected or off-grid in rural areas. Most countries have already begun to reinforce its energy infrastructure to be fed from sustainable (RE) resources but the limited potential resources could halt such deployment. So, integration of different renewable energy resources to the power network is a major challenge to secure the stability of the grid and the implementation of efficient (RE) systems requires strong decision making support to encourage investments. Thus, (RE) planning should be evaluated from the techno-economic-socio-environmental criteria. This thesis highlights the main concept of 100 % renewable energy transition by the end of 2030 in French Guiana where there is a challenge in the development of the energetic scenario by 2030 and the current energy production facilities cannot feed the increase in power demand within limited resources. As a summary, this thesis handles this research question: how to optimize different energy production scenarios combining different RE resources of maximum production at minimal costs in order to satisfy the energy needs taking into account the spatio-temporal dimensions of the problem and data?
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https://tel.archives-ouvertes.fr/tel-03200903
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Submitted on : Friday, April 16, 2021 - 11:14:08 PM
Last modification on : Saturday, April 17, 2021 - 3:28:28 AM

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  • HAL Id : tel-03200903, version 1

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Nadeem Alkurdi. Aide à la décision multicritère pour l’optimisation de scénarios de production énergétique via l’utilisation de données spatiales. Physique [physics]. Université de Guyane, 2020. Français. ⟨NNT : 2020YANE0006⟩. ⟨tel-03200903⟩

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