Abstract
Sustainable and efficient energy solutions are urgently needed to tackle climate change transitioning from current fossil fuel-based energy systems to future renewable-based systems. Energy transformation poses a challenge of a complete rethinking of the energy infrastructures that have to be able to integrate a high share of different fluctuating renewable energies, and still ensure adequate flexibility and reliability to the systems.
The solution has been identified in the holistic approach of the smart energy systems: this view merges measures of energy conservation and saving, integration of a pool of renewable sources, implementation of cutting-edge technologies (e.g. conversion, storage and production), and coordination of electricity, gas, heating, and cooling grids. For this aim, the new generation of district heating has to play its crucial role to achieve an optimal solution not only in the thermal sector but especially for the whole energy system.
By introducing urban renewable smart energy systems, the future district heating has to be able to distribute heat with low heat losses to both high and low energy buildings, to integrate renewable energies, to recovery heat from low-temperature sources, and to work in synergy with other energy grids. Thus, this thesis aims at supporting the development of smart district heating by focusing on modelling aspects with the overall aim to advance our current knowledge of the analysis of smart demand data and the simulation of smart heating grids. This research and its applications utilise energy data of the city of Bozen-Bolzano, and in particular heating demand data of the exchange substations installed in the district heating network. First, sustainable solutions for the design of urban energy systems are analysed, with an emphasis on the integration of renewable sources and the implementation of smart infrastructures, e.g. district heating grids. Second, both the hydraulic and the thermal part of the numerical models for the distribution networks simulations are investigated with particular attention to the demand scheme used. Third, different aspects of the heat demand, such as peaks and load, are analysed through statistical methods for a proper demand characterisation and forecasting.
The main outcomes are: i) a new methodology for the design of 100% renewable smart energy systems at urban level is proposed, and a sustainable perspective for the municipality of Bozen-Bolzano is given; ii) enhancements in distribution network simulations are achieved by means of a new demand scheme implemented into hydraulic solver based on a distributed along network demand, together with a flexible thermal numerical scheme unconditionally stable with any spatial-temporal domain chosen; iii) an in-depth multivariate analysis of heat demand and meteorological variables is proposed for providing useful forecasting information through "ad hoc" developed data-driven procedures. The need to adopt suitable distribution systems models, together with the integration of proper demand forecasting tools, is a crucial challenge for the future development of smart district heating.