The problem: The global development community lacks a credible way to measure and track progress toward modern energy for growth. Traditional electricity access metrics, like binary electrification, fall short of capturing the true scope of energy poverty and thus have limited use for driving infrastructure investment at the scale needed to catalyze economic growth. The Energy for Growth Hub introduced the Modern Energy Minimum (MEM) as a more ambitious metric, defined as 1,000 kWh of electricity consumption per person per year. This comprises 300 kWh per person used at home plus a national average of 700 kWh per person of non-residential use. The economy-wide component is easily measurable at the country-scale with current data. But measuring how many residences use above or below 300 kWh (or any threshold) is currently impossible because utilities do not share such data and no organizations report electricity consumption data at the scale and level of detail needed (until now).
Our approach: deploying large-scale machine learning systems and remote sensing data to track granular electricity consumption. We’re working as part of a consortium including the IEA, Power Africa, MIT, UMass Amherst, e-GUIDE, and Project InnerSpace to develop state-of-the-art geospatial machine learning systems to estimate building-level electricity demand and electricity access rates. We train these systems using sparse metered consumption datasets and leverage a variety of remote sensing datasets. This novel approach enables us to develop and update accessible, detailed electricity consumption datasets year over year, and ultimately track progress toward the MEM. We released building-level estimates for three pilot countries in March via the Open Energy Maps web platform and are aiming to expand our efforts to low- and middle-income countries (LMICs) globally.
Why it matters: what gets measured gets managed. Economic and human development does not end with electricity access. As more LMICs approach basic energy access using a binary metric, we need to aim higher. Just as the fight against income-based poverty tracks people at $2.15 per day for extreme poverty and also at $3.85 and $6.85 (and possibly will start tracking at $25/day too), energy poverty also needs additional steps up the ladder. Only in doing so can we mobilize global resources to reduce energy poverty and drive economic development. Building credible methods to track progress on the MEM is the first step in realizing this ambition. In fact, once the Open Energy Maps dataset is complete, it could provide a new progress indicator for the next round of Sustainable Development Goal 7.
Much more to come soon, but here’s a preview of the tool.
Our map depicts building-level electricity demand estimates that we are scaling globally. Building colors correspond to expected values for electricity demand, where blue and green buildings represent lower-demand buildings, and yellow and red buildings represent higher-demand buildings.