AIMS Energy (Apr 2021)
Analysis of power generating plants and substations for increased Uganda's electricity grid access
Abstract
Uganda is endowed with a number of energy generation sources, however; these sources are spread out or scattered throughout the country. This makes transmission of power from the generating stations expensive. This paper aims at assessing the possibility of reduced cost through increasing substations instead of electricity generation plants through use of Geo pandas and spatial informatics techniques. Power substation data that included coordinates and power ratings, data for Uganda districts, major roads and towns together with population were imported in the jupyter notebook using python and plotting was done to generate a map of power stations in Uganda. The power generating plants, substation, district and population stored data in jupter notebook was retrieved and visualised in GIS where buffering was done in order to determine the area covered by the substations. The point layer of current power substations and plants was buffered at a defined radius to get the current unserved area scenario map for Uganda. As a result of this preliminary work, specific areas were targeted for investment and optimized supply systems was established, which included proposed new power substations. Four power substations were proposed to serve areas without access to the grid and a map showing new sited power stations in unserved areas (densely populated) was generated. Net present worth method was used in the economic analysis to determine whether it makes economic sense in extending transmission lines to serve places without access to electricity vis a vis constructing more power plants. It was observed that extending the grid to selected substations was relatively cheaper as compared to constructing power plants since the economic analysis showed a positive net present worth of USD 63.6 million. Since Uganda has surplus electricity generated, it is better to invest in the transmission lines to serve areas without electricity.
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