Multi-scale and dynamic energy mapping for strategic decision making and integrated energy management in Wallonia
Antoinette Marie Reine NISHIMWE will defend her PhD thesis in Architecture and Urban Planning, entitled: “Multi-scale and dynamic energy mapping for strategic decision making and integrated energy management in Wallonia” on December 05th 2022 at 15h (Sart Tilman Campus, in B31, Salle du Conseil).
Summary
In the context of smart cities, this doctoral thesis addresses the energy challenge linked to existing building stocks, by proposing methods and tools for estimating and analysing their energy consumption on the territorial scale, in combination with multi-scale and dynamic energy mapping. The methodologies and tools developed and validated are applied to the entire stock of buildings in Wallonia, which includes more than 1.7 million buildings. The research methodology is based on the combination of different advanced scientific methods and tools (deep literature review, GIS mapping, statistical analysis, energy models, AI models, forecast scenarios, buildings monitoring, models calibration and validation). The results should help implement smart energy management in large building stocks. Most importantly, the developed models and used data can be updated, and the methodologies are transferable for other regions and countries.
Résumé
Dans le contexte de la création de villes intelligentes, cette thèse répond au défi énergétique lié aux parcs bâtis existants, en proposant des méthodes et outils d’estimation, d’analyse et de cartographie énergétique multi-échelle et dynamique à l’échelle territoriale. Les méthodes et outils développés et validés sont appliqués au stock complet de bâtiments de la Wallonie, qui comprend plus de 1,7 million de bâtiments. La méthodologie de recherche est basée sur la combinaison de différentes méthodes scientifiques et d’outils de pointe (revue approfondie de la littérature, cartographie SIG, analyses statistiques, modèles énergétiques, modèles d’IA, scénarios futurs, monitoring de bâtiments, calibration et validation de modèles). Les résultats visent à favoriser la mise en œuvre d’une gestion intelligente de l'énergie au sein de larges stocks de bâtiments. Plus important encore, les modèles développés et les données utilisées peuvent être mis à jour et les méthodologies sont transférables à d'autres régions et pays.
Jury members of the doctoral thesis
Prof. Dr. Sigrid REITER University of Liège, Belgium - Supervisor
Prof. Dr. Shady ATTIA University of Liège, Belgium - President
Prof. Dr. Mario COOLS University of Liège, Belgium - Member
Prof. Dr. Pierre DEWALLEF University of Liège, Belgium - Member
Prof. Dr. Mindjid MAÏZIA University of Tours, France - Member
Dr. Anne-Françoise MARIQUE University of Liège, Belgium - Member
Prof. Dr. Griet VERBEECK University of Hasselt, Belgium – Member
Publications
- ORBI: https://orbi.uliege.be/ph-search?uid=U228922
- Nishimwe A.M.R., Reiter S., (2021). Building heat consumption and heat demand assessment, characterization, and mapping on a regional scale: A case study of the Walloon building stock in Belgium. Renew Sustain Energy Rev 2021; 135:110170. doi: 10.1016/j.rser.2020.110170.
- Nishimwe A.M.R., Reiter S., (2022). Using Artificial Intelligence Models and Degree-Days Method to Estimate the Heat Consumption Evolution of a Building Stock Until 2050: A Case Study in a Temperate Climate of the Northern Part of Europe. Cleaner and Responsible Consumption 2022; 5: 100069. doi: 10.1016/j.clrc.2022.100069.
- Nishimwe A.M.R., Reiter S, (2021). Estimation, analysis and mapping of electricity consumption of a regional building stock in a temperate climate in Europe. Energy Build 2021; 253:111535. doi: 10.1016/j.enbuild.2021.111535.
- Nematchoua M.K., Nishimwe A.M.R., Reiter S., (2021). Towards nearly zero-energy residential neighbourhoods in the European Union: A case study. Renew Sustain Energy Rev 2021; 135:110198. doi: 10.1016/j.rser.2020.110198.