Award Announcement - Collaborative Research: RUI: Data-Driven Analysis, Modeling, and Design of Off-Grid Power Systems on Tribal Lands

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Award Materials

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Access to the power grid has remained out of reach for tens of thousands of homes on Native American reservations. This form of energy poverty is associated with a wide range of negative health, economic, and educational outcomes. Recently, small-scale solar-powered off-grid electrical systems have been installed in homes on reservations, providing modest but meaningful access to electricity. However, crucial data is needed to understand how the systems perform and how they can be optimized. This NSF project aims to assess how off-grid systems on Native American reservations perform and to develop a novel method to improve their design, resulting in lower costs and enhanced performance. The project will bring transformative change to the practice of off-grid electrification on tribal and non-tribal lands. This will be achieved by creating a dataset of measurements taken from the off-grid systems, rigorously analyzing the data, and developing a new data-driven design methodology. The intellectual merits of the project include creating the largest and most comprehensive dataset of electricity consumption and environmental measurements from off-grid systems on Native American reservations and devising a novel design methodology based contextual information and measured consumption patterns. The broader impacts of the project include increasing electricity access among underserved populations, supporting engineering education at two predominately undergraduate institutions, and increasing participation of Native American students in research. A robust dissemination plan includes trainings, tutorials, and workshop materials targeting off-grid practitioners on Native American reservations.

This project will deploy data acquisition systems to collect data from approximately 200 residential off-grid systems on Native American reservations over a yearlong period. The dataset will include measurements of load, solar array power, battery bank voltage, irradiance, and temperature. Contextual data will be collected through surveys. The analyses include: statistically characterizing and modeling the electricity consumption to create load profiles, assessing the systems’ technical performance, computing reliability indices, and cataloging outage causes. The project develops a novel data-driven design methodology based on regression models of consumption, with contextual information collected from surveys as explanatory variables. Laboratory measurements taken from hardware testbeds that can emulate off-grid systems will be used to validate the methodology.