Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7418127 | Cities | 2016 | 12 Pages |
Abstract
Long term average wind speeds are predicted using a logarithmic vertical wind profile. This employs detailed three-dimensional building data to estimate aerodynamic parameters for the complex urban surface. Solar resource is modelled using a Geographical Information System-based methodology. This establishes the location and geometry of roof structures to estimate insolation, whilst accounting for shading effects from other buildings and terrain features. Project viability for potential installations is assessed in terms of the net present value over the lifespan of the technology and associated Feed-in Tariff incentive. Discounted return on investment is also calculated for all sites. The methodology is demonstrated for a case study of 6794 sites owned by Leeds City Council, UK. Results suggest significant potential for small-scale wind and solar power generation across council assets. A number of sites present a persuasive business case for investment, and in all cases, using the generated electricity on site improves financial viability. This indicates that initial installations should be sited at assets with high electricity demands. Overall, the work establishes a methodology that enables large city-level asset holders to make strategic investment decisions across their entire portfolio, which are based on financial assessment of wind and solar generation potential accurate to the individual asset scale. Such tools could facilitate strategic planning within cities and help to ensure that investment in renewable energy is focused at the most viable sites. In addition, the methodology can assist with asset management at the city scale by identifying sites with a higher market value as a result of their potential for renewable energy generation than otherwise might be estimated.
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Authors
Katrina Adam, Victoria Hoolohan, James Gooding, Thomas Knowland, Catherine S.E. Bale, Alison S. Tomlin,