Thursday, 12 June 2014: 11:30 AM
Queens Ballroom (Queens Hotel)
Francis C. Emejeamara, University of Leeds, Leeds, West Yorkshire, United Kingdom; and A. S. Tomlin and J. T. Millward-Hopkins

Although power generation via small wind turbines within the urban environment holds great promise, it faces several challenges including insufficient or sparse assessment of urban wind resources, and developing effective commercial gust control solutions suitable for urban wind operations. Evaluating the performance of small scale wind turbines within the urban environment will require an estimation of the total energy available to it, which depends not only on mean wind speeds but also on short term fluctuations in the wind. This additional energy is usually under-represented when using mean wind speeds from say hourly data typically obtained from standard weather stations, but it could be captured using gust tracking control algorithms. In this work high resolution wind measurements at seven potential turbine sites within the urban and suburban environment are used to assess the additional energy available within short term wind fluctuations by calculating the excess energy coefficient (EEC). By developing a relationship between turbulence intensities (T.I.) and the EEC, an analytical methodology for predicting the total wind energy available at potential turbine sites is proposed based on measured or modelled mean wind speed and turbulence levels. Sensitivity analysis of the calculation of T.I. and EEC with respect to the raw data resolution is demonstrated and it is shown that this should be representative of the response time of the turbine in question. Where this is the case then T.I. can be used to provide accurate estimates of the excess energy available to the turbine. The EEC calculations are then integrated into an analytical methodology for the calculation of wind speed and turbulence profiles at different heights within a UK city which is based on specifying the aerodynamic characteristics of the urban surface based on detailed surface morphological data. Results highlight the potential for mapping the turbulence intensities and cumulative wind energy available to selected turbines at different heights within a typical urban city.
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