Multicriteria GIS modeling of wind and solar farms in Colorado

The majority of electricity and heat in Colorado comes from coal and natural gas; however, renewable energy sources will play an integral role in the state's energy future. Colorado is the 11th windiest state and has more than 250 sunny days per year. The objectives of this research are to: 1) determine which landcover classes are affiliated with high wind and solar potential; and 2) identify areas that are suitable for wind and solar farms using multicriteria GIS modelling techniques. Renewable potential (NREL wind speed measurements at 50 m above the ground and NREL annual insolation data), landcover, population density, federal lands, and distance to roads, transmission lines, and cities were reclassified according to their suitability. Each was assigned weights based on their relative importance to one another. Superb wind classes are located in high alpine areas. Unfortunately, these areas are not suitable for large-scale wind farm development due to their inaccessibility and location within a sensitive ecosystem. Federal lands have low wind potential. According to the GIS model, ideal areas for wind farm development are located in northeastern Colorado. About 41 850 km(2) of the state has model scores that are in the 90-100% range. Although annual solar radiation varies slightly, inter-mountain areas receive the most insolation. As far as federal lands, Indian reservations have the greatest solar input. The GIS model indicates that ideal areas for solar development are located in northwestern Colorado and east of Denver. Only 191 km(2) of the state had model scores that were in the 90-100% range. These results suggest that the variables used in this analysis have more of an effect at eliminating non-suitable areas for large-scale solar farms: a greater area exists for suitable wind farms. However, given the statewide high insolation values with minimal variance, solar projects may be better suited for small-scale residential or commercial projects. (c) 2010 Elsevier Ltd. All rights reserved.