Urban wind turbines: a case study for the city of London

Small scale wind turbines are used for localized renewable energy generation. Wind turbine installations in urban locations have had varying success, mainly due to the relative lack of information on the wind regime in those locations. A 6 kW Proven and a 5 kW Quiet Revolution wind turbines were installed on the roof of a residential tower in an urban location. Wind data, power output and energy yield of the turbine were monitored along a whole year, starting from June 2007. Having arrived to Farnborough, UK, in April 2008, I was quickly introduced to wind engineering concepts by GasDynamics Ltd, company which specializes in aero-thermodynamics with emphasis on hypersonic. The company hosts me 5 months long, throughout I have learnt several skills concerning the wind brancah of renewable energies. The whole activity was coordinated by the student exchange program called “Erasmus Placement’. Scheduled tasks involved topics as wind regime assessment for building mounted turbines, several measurements of wind speeds around a number of buildings suited to the installation of turbines and yield prediction through numerical computation. Clearly, the energy yield of a wind turbine is dependent upon the wind resource available at the site. A critical review of current methods of predicting the wind regime was carried out. Measured wind data were compared with the predictions and it was found that the wind speed measured over the test period was lower than predicted. Two methods of predicting wind turbine energy yield were compared with the manufacturer’s estimates. The measured yield was compared with the calculated predictions and the manufacturer estimates and was found to be significantly lower. The average daily energy yield during the test months was approximately 9-11 kWh per day, which is lower than the requirement in a typical one bedroom flat. The measured power output of the turbine was found to be lower than the manufacturer published outputs, across the range of measured wind speeds. Several reasons for this have been identified in the report. The power curve method was identified as giving the closest prediction for energy yield. Some findings of the study are highlighted for continuing the study.