A New Predictive Model for More Accurate Electrical Grid Mapping
Data Partner(s): Facebook
Challenge: When planning connectivity deployments in emerging markets, it is important to have a clear picture of where existing power lines are placed. This information helps us make better decisions about where to focus our efforts, how we design the network, and how we source the equipment we’ll need. However, this information in developing countries is often outdated, inaccurate, or too low resolution to be useful.
Solution: To find a more accurate picture using existing resources, Facebook partnered with the Energy Sector Management Assistance Program (ESMAP) at the World Bank, KTH Royal Institute of Technology, World Resources Institute (WRI), and the University of Massachusetts Amherst. A new predictive model was developed for mapping medium-voltage (MV) infrastructure using publicly available data sets. The output of this model for six countries is available on the World Bank’s open energy data repository.
Impact: Local governments, businesses, and nonprofits can use it to understand where people need electricity or where to expand water pumping infrastructure to provide basic services.