Electrification planning in Zimbabwe : A GIS-based approach
In Zimbabwe, the access to electricity is significantly low, especially in rural areas. This inhibits the economic and social development of the country. In order to tackle energy poverty, the government aims at improving the electrification rate from around 40 % to 100 % by 2040.
The objective of this study is to investigate the optimal electrification pathways for Zimbabwe, in order to achieve its energy access goals and support the sustainable energy transition in the country.
The electrification analysis was accomplished by using the Open Source Spatial Electrification Toolkit (ONSSET) developed by Division of Energy System Analysis at The Royal Institute of Technology, Stockholm. A geographic information system operator was fed with open source data. The data was processed and utilized as input in a Visual Basic model in Microsoft Excel. Along with assumptions on population growth, diesel price and cost for renewable energy technologies and the grid, several scenarios were developed and assessed. The model ultimately provided an estimation of the total investment and capacity requirements, the lower possible levelized cost of electricity achieved per settlement and the optimal geospatial distribution among the suggested technological solutions.
The results show that the grid will become more important with higher electricity consumption. When the cost of the grid increases, the optimal technology solution will be more stand-alone technologies in the low demand scenarios and more mini grid and stand-alone in the high demand scenarios. The total investment costs vary between 29.10 and 83.67 billion USD and the total added capacity between 494.42 to 2,769.27 MW for the chosen scenarios.
The Open Source Spatial Electrification Toolkit can hence be used to investigate probable outcome in order to achieve the energy target in Zimbabwe by 2040. The model presents the total investment cost, the levelized cost of electricity and the technology distribution and a visualization of the results gives a clear view of the possible outcomes in the future and can be used as recommendations for stakeholders engaged in energy planning.
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