Current urban systems have a linear metabolism; they rely on imported resources, which are used inefficiently, and they produce waste flows. Urban areas can become productive and not only consumptive if a well-planned distributed energy system is implemented. Switching to renewables, however, means rethinking today’s urban landscape entirely. Decisions made for the future need to be built on a robust understanding of urban energy systems. There is a need to bring creative perspectives to include local potentials into urban planning and study the energetic gaps and opportunities that can foster a circular metabolism.
This thesis presents a modular energy generation system with an innovative noise-barrier integration feature. This novel concept, formally known as the Energy Wall, is designed to capture the local wind and solar energy resources of urban areas and transform them for urban use while exploiting the benefits of reusing existing urban stock. This paper embarks on a comprehensive assessment of the potential of this system taking a full approach from experimental data to energy and cost modeling. A study area located in Delft, the Netherlands, has provided a solid basis for this research. The base-case Energy Wall module in this area generates per year almost enough energy to supply the annual demand of a residential household. To account for the great diversity of urban environments, the energy supplied by the system is investigated in different scenarios with varying local characteristics. A number of cost reduction opportunities have been identified increasing the appeal of noise-barrier integration. Despite this, the small-wind system faces economic burdens hindering its profitability. Field measurements from sonic anemometers are employed to investigate the wind concentrator effect of a noise-barrier showing an acceleration effect up to 30% depending on flow perpendicularity. The robustness of current vertical wind profile scaling techniques is tested to gauge its reliability within the urban boundary layer. Results have underscored important gaps in the theory of near-surface wind speed prediction methods. The higher complexity and uncertainty of urban wind energy generation has given this research a special focus on understanding why this technology has lagged behind over the recent years and, most importantly, what steps should be taken to change this situation.