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    Wind farm site selection using a GIS based Multicriteria technique in Tororo district.

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    Undergraduate dissertation (1.520Mb)
    Date
    2021-12-23
    Author
    Namanda, Judith
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    Abstract
    Due to the global tension on climate change, many countries such as Uganda have resorted to the adaption of alternative renewable resources such as wind energy for the transition of a decarbonized economies. Uganda is endowed with numerous substantial renewable resources wind energy inclusive for production and electricity services. Wind energy is a promising renewable resource alternative because of its advantages including but not limited to, reduces carbon dioxide gases and it’s a clean energy source. However, the spread of wind energy has spatial impacts that cause adverse concerns on the land scape, wildlife and noise levels. In addition the establishment of wind farms also negatively impact the environment and this is usually caused by the sub-optimal sitting of the wind farms. This report therefore presents the wind farm site suitability analysis using multi-criteria decision making (MCDM) approach based on geographic information system (GIS). However, wind farms site election is not only dependent on wind speed but there are other underlying criteria/parameters that play an important role in the process. The objectives of this research was to identify these parameters/factors and integrate them with a GIS to identify the suitable sites for wind farm sitting. Parameters used in this study were based on the literature, an analytical hierarchy process (AHP) was employed to assign appropriate weights to the criteria according to their relative importance. These weighted criteria were combined using the overlay function in a GIS software. As a result of the total area 0.01% was identified as not being suitable and 1.36% as most suitable. This research recommends that more research is done to increase on the availabity of information about the wind energy resources areas and the development of wind data centers for collection of wind speed data.
    URI
    http://hdl.handle.net/20.500.12281/12739
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    • School of Built Environment (SBE) Collection

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