In the News
Harnessing Data and Modern Technology News
The Global Assessment of Electricity in Healthcare Facilities provides a comprehensive update on the status and key actions needed for providing reliable, modern energy to health-care facilities in low- and middle-income countries.
EAP research on using satellite and drone imagery to automatically detect solar PV panels featured in PV Magazine.
Congratulations to the seven winners of the Nicholas Institute Catalyst Grants! We are delighted that this year’s winners includes EAP’s own Rob Fetter, who will be leading ‘Mapping Solar Photovoltaic Arrays Using Unpiloted Aerial Vehicles.’
The Energy Access Project at Duke in collaboration with the Inter-American Development Bank and Sustainable Energy For All, have developed an Energy Access Dividend for Haiti and Honduras with the aim of quantifying the electrification benefits forgone over a country’s business-as-usual electrification transition.
The Energy Access Project at Duke University (EAP) and RTI International cordially invite you attend the convening Data for Development: Using Data Analytics to Accelerate Global Energy Access in Washington, DC on December 6, 2019.
On May 15–17, 2018, more than 100 academic researchers and energy access practitioners gathered at Duke University to discuss critical issues related to energy access as part of the third annual conference for the Sustainable Energy Transitions Initiative (SETI). Presentations by Kyle Bradbury of Duke University, Johannes Urpelainen of Johns Hopkins University, Nathan Williams of Carnegie Mellon University, and Jay Taneja of the University of Massachusetts–Amherst highlighted remarkable advances in energy data analytics, described applications for developing world energy challenges, and outlined remaining data-related hurdles impeding progress on energy access. Energy developers, utilities, planners, and policy makers are often not equipped with the necessary tools to understand the changing landscape of energy delivery options and customer preferences. Researchers and grid operators are often restricted by outdated, unavailable, or biased data in the field. Through innovative methods and analytical tools, such as remote sensing, satellite imagery, and machine learning, data analytics are improving our understanding of energy demand in rural areas, customer needs and expectations, the local availability of energy resources, and the realities of providing electricity to underserved communities. These proceedings present key conference takeaways related to the core theme of energy data analytics.