Case study: Sub-Saharan Africa electrification planning
- Client: World Bank
- Consultant: Village Infrastructure Angels (VIA)
- Start date: May 2021
- Completion: July 2021
Problem:
In the face of rural electrification challenges in Sub-Saharan Africa (SSA), the World Bank needed a reliable GIS-based model that would enable a rapid analysis of electrification strategies across 46 countries in SSA. The key was identifying the most efficient way to connect off-grid buildings with energy sources, balancing between extending the existing grid, building isolated mini-grids, and employing solar home systems in the least populated areas.
Solution:
VIA, with over 20 years of experience in GIS modeling, employed illustreets’ innovative, low-code spatial analytics, and reporting platform. Utilizing the software’ robust mapping and data analysis capabilities, VIA was able to run large-scale spatial analyses and visualizations at speed and scale.
This enabled them to import and use High-Resolution Settlement Layer (HRSL) data, representing 102.7 million buildings across SSA, to determine potential electrification strategies. The analysis employed the concept of “Critical Distance”, a measure used to decide which households should be connected into grids and which should be served by isolated solar home systems.
They used the mathematical concept of a minimum spanning tree, enabling them to connect all off-grid buildings with the least length of cable possible, optimizing resources and costs.
Results:
With the help of illustreets, VIA rapidly produced detailed analysis results for 46 SSA countries. They estimated that of the 102.7 million buildings, 50% are already reached by electricity (51.34 million), leaving the same number yet to be connected. The data also highlighted that off-grid populations could potentially be serviced by a significantly lower number of isolated mini-grids than previous estimates, suggesting a large market for solar home systems.
The online mapping tool enabled inspection of results for each country, allowing potential developers to identify suitable projects based on their preferences.
illustreets allows for inspection of the results for each of the 46 countries, and the market share of technologies can vary widely compared to the continental average. For example, Sudan and Gambia have the lowest share of SHS, estimated at 4-5%, while Zimbabwe and Namibia have the highest SHS share at 50-70%. The maps can be queried using various parameters (number of buildings per grid, length of line per grid, etc.) to help find grids that suit a developers’ preference, and the least length of line per grid are likely to be the least cost grids and thus the most profitable to develop first, helping with prioritization. A spatial filter can also be used to cut out a small area of interest, keeping the size of datafiles small and manageable.
Conclusion
The use of illustreets provided a cost-effective, efficient, and scalable solution to the significant challenge of electrification planning in SSA. The platform enabled rapid, large-scale data analysis and visualization, providing crucial insights into off-grid electrification strategies and proving to be an invaluable tool for stakeholders in the energy access sector.
Considering the immense size of the dataset and limited time available to process a huge amount of data, 46 countries analysis was done at an unprecedented speed and accuracy. It may have cost around $10 million processing 46 countries separately at this level of detail, doing things the old way, which now cost the client less than $100,000 when using illustreets.
