Decentralised energy sources, such as urban wind energy, have a number of well known advantages. However, accurately predicting urban wind resource is notoriously difficult due to the complexity of air flows in the urban boundary layer. Without sufficiently accurate methods of predicting this resource, there is the danger that small-scale turbines will be installed at unsuitable locations, which can be detrimental to the reputation of the wind energy industry. Additionally, viable sites may be overlooked, leading to the under-exploitation of small-scale wind in built areas. In this paper, we use an analytical down-scaling method to produce maps of mean wind speed as a function of height for a number of UK cities, via the use of detailed building data to estimate their aerodynamic characteristics. The predictions are shown to compare well with mean wind speeds measured at various locations, except at some sheltered sites which lie in highly complex regions of flow. We then consider the viability of urban wind energy at the city scale. The results suggest that residential properties in suburban areas are often unsuitable locations for rooftop turbines. However, there are many tall, unsheltered buildings in urban areas upon which turbines could access a substantial wind resource. Preliminary results suggest that in the city of Leeds, UK there are potentially over 8000 suitable turbine locations. These results should be informative for turbine suppliers and customers attempting to assess the viability of potential sites, as well as being instructive for policymakers developing subsidies for small-scale renewable energy projects.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)