Managing wind resource variation for rooftop turbine placement

Numerous localities have attempted to harness wind resources for electricity generation using roof-integrated wind turbines (RIWTs). Disappointingly, the monitored performance of RIWTs is typically only 5–11% of the designed capacity. Since direct wind measurement is expensive for micro-generation and simplified analytical methods are often insufficiently precise for complex geometries, poor outcomes are not surprising. To combat this, the current study explores the extent to which this deficit is due to poor RIWT placement in the absence of precise wind power information for installation sites and how this may be countered with terrestrial laser scanning-based models for complex structures. This is demonstrated with a cluster of complex suburban buildings with ground elevation changes of up to 4.2 m. Those data were used to populate a computational fluid dynamic model for detailed wind flow field simulation using a Navier–Stokes solver, ANSYS CFX. This approach demonstrated that wind power ranged from 0 to 100% of the capacity factor across the main study rooftop, representing the difference between cost recovery of a €16,500 RIWT in less than 1.5 years and a financially non-viable installation. This study provides a partial explanation for the disappointing results of RIWT installation, as well as a methodology to optimize RIWT placement to avoid non-viable installations and improve cost recovery period predictions.