A multiscale framework for predicting distributed renewable thermal energy integration - Monsalvete Alvarez de Uribarri, Pilar (2020)
With the increase in energy demand in cities and the growing need to mitigate the anthropogenic impact on climate, the interest in understanding the energy flows in cities has risen in recent decades. This thesis aims to contribute towards the development of useful and flexible tools which help to understand the energy flows in cities. It is specifically focused on the building sector, with emphasis on thermal energy performance and the potential of renewable energy integrated into district heating systems. The participation on the development of an adaptive urban energy modelling tool that, on the one side tackles different levels of complexity of the energy system according to the scope of analysis and on the other side, can adjust the models to the data available is presented. This thesis describes a dynamic building demand model that can be used for urban energy modelling thanks to the automation of input data setting and its flexibility to adapt to different levels of data resolution. Likewise, the thesis contributes to the improvement of a District Heating Network model by developing a methodology to avoid artificial diffusion and wave delay in network pipes. In this way, the dynamics of the fluid inside pipes can be reproduced, which is crucial when introducing very intermittent elements to the system, such as thermal solar panels or the buildings themselves. The workflow followed by the tools where the models have been integrated is also explained, paying attention to its modular structure and the input data preprocessing. Finally, the thesis presents two case studies that show the performance and the potential of the developed models and the tools where they are embedded. In the first case study, the capacity of the building model to adapt to two different levels of detail of the input data is shown. In contrast, the second case study focuses on the DHN model and how it can be used to study the impact of connecting distributed supply sources, which are very common in renewable applications.