Master Thesis : Sizing of renewable energy production and storage solutions for increasing the energy autonomy of tertiary buildings
Bessemans, Pauline
Promotor(s) : Cornélusse, Bertrand ; gerkens, Guillaume
Date of defense : 4-Sep-2023/5-Sep-2023 • Permalink : http://hdl.handle.net/2268.2/18259
Details
Title : | Master Thesis : Sizing of renewable energy production and storage solutions for increasing the energy autonomy of tertiary buildings |
Translated title : | [fr] Dimensionnement de solutions de production et de stockage d'énergies renouvelables pour augmenter l'autonomie énergétique de bâtiments tertiaires |
Author : | Bessemans, Pauline |
Date of defense : | 4-Sep-2023/5-Sep-2023 |
Advisor(s) : | Cornélusse, Bertrand
gerkens, Guillaume |
Committee's member(s) : | Louveaux, Quentin
Ernst, Damien |
Language : | English |
Number of pages : | 82 |
Keywords : | [en] Sizing algorithm [en] Optimization [en] Renewable energies [en] Microgrids [en] Data analysis |
Discipline(s) : | Engineering, computing & technology > Computer science |
Target public : | Researchers Student General public |
Institution(s) : | Université de Liège, Liège, Belgique |
Degree: | Master : ingénieur civil en science des données, à finalité spécialisée |
Faculty: | Master thesis of the Faculté des Sciences appliquées |
Abstract
[en] The access to electricity as renewable as possible is increasingly in demand. Sometimes, the connection to the public is either impossible or not wanted. Therefore, the local network must equip itself with electrical production and storage solutions. This master's thesis aims to develop and implement an algorithm for sizing production and storage solutions for the electricity supply of tertiary buildings while minimizing the use of fossil energy sources. Three versions of a model were formulated: one considering a long-term investment project with variation in the demand over the year, one restricting itself to yearly data, and a final one modeling the annual demand thanks to representative days. Two objective functions have been defined and used in these three models: the maximization of the installation's Net Present Value with a penalization on the use of fuel and the minimization of the CO2 emissions linked to the project. The different combinations of these three models and two objective functions have been applied to five cases with various consumption profiles. The model with a one-year horizon with a minimization of the CO2 emissions performs best. Further developments and improvements as the integration of additional production and storage solutions or the consideration of the electric vehicles' consumption and batteries worth to be explored.
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