Achieving Universal Electricity Access at the Lowest Cost
A comparison of least-cost electrification models
As of 2017, around 1.1 billion people lacked access to electricity. Sustainable Development Goal 7 has put this issue on the global agenda, and as such there has been a growing push to achieve universal access to electricity. Notably efforts around this goal have been advanced by recent declines in the cost of renewable energy technologies, which create the possibility of taking generation directly to unconnected households. For remote, isolated households, consuming small amounts of electricity, such connections are significantly cheaper than extending the grid. For households close to the existing grid, and/or households consuming large amounts of electricity, extending the grid remains the cheapest option for providing electricity.
While new technologies create new opportunities for advancing the goal of universal electrification they also create challenges for planners who have to determine the extent to which they should prioritize investments in grid extension vs. distributed generation, so that they can achieve rural electrification at the lowest possible cost. Answering this question requires the application of spatial models to weigh the distance households are from the existing grid, the amounts of electricity they are likely to consume and the costs of providing that electricity using different infrastructure. Notably, however, these models face serious data problems and rely on computational simplifications in order to address complex dynamics involved in electrification decisions.
This new research backgrounder from Oxfam seeks to compare the published findings from 22 different “least cost electrification models” (these are all the published models thought to currently exist in the literature). The aim of the report is to explain how these models work, the data and computational challenges they face, and how they are resolved, and then to compare the results across different models. The aim is to help electrification advocates use the findings of these models responsibly, and to call for modelers to coordinate efforts to improve understanding of model accuracy.