Development of an evolving digital tool, based on a multi-scale and dynamic energy mapping, for strategic decision making and integrated energy management in Wallonia


Development of an evolving digital tool, based on a multi-scale and dynamic energy mapping, for strategic decision making and integrated energy management in Wallonia

Abstract

The ongoing climate change urges cities, government stakeholders and decision makers to think about different strategies to reduce greenhouse gases and thus energy consumption in buildings. In this case, the Wal-e-Cities-ENR project, which is financed by ERDF and Wallonia Region, addresses the energy challenge of transforming the walloon building stock into a smart built environment. It aims to develop evolving digital tools related to smart energy management of the building stock in Wallonia. The tools are dedicated to multi-scale and dynamic energy mapping as well as statistical analysis of buildings’ energy data for integrated energy management in the transitioning territory of Wallonia. On spatial scale, the representation varies from statistical sectors to urban regions. On time level, the scale of representation varies from an hour to a year. In Wallonia, a lot of buildings are more than 50 years old, poorly insulated and thus energy consuming. Creating these tools will contribute to a better management of buildings energy consumption at the regional scale. In addition, Wal-e-Cities-ECO project, also financed by ERDF and Wallonia Region, aims to dynamically model hourly energy consumption on a given period, using static energy data from ENR through spatialized energy cadastres and also using monitored energy data of selected buildings in Wallonia. The main obectives of the thesis are: assessment of buildings' annual heat consumption (HC), heat demand (HD) and electricity consumption (EC) of the whole Wallonia building stock (residential, tertiary and industrial buildings), on different territorial scales namely statistical sector, municipalities, urban regions and provinces. Next, dynamically model hour by hour the HD and EC of the Wallonia building stock.The obtained results will be accessible to the public via a web platform which is being developed. Afterwards, the statistical analysis, sensitivity analysis and energy forecast up to 2050 is performed. Then, the evolution scenarios and multicriteria decision aid for sustainable strategies will be realized and energy plans established.

Within the LEMA research team, Professor Sigrid Reiter coordinates and scientifically supervises this thesis and Antoinette Marie Reine Nishimwe is working on a doctoral thesis on this project.Here are some of the obtained results:

Screenshot 2021-02-MarieReine

This image has won the Public price in the contest exhibition La Preuve par l'image 2020”.

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