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

在印第安人保留地，数以万计的家庭仍然无法接入电网。这种形式的能源贫困与一系列负面的健康、经济和教育结果有关。最近，小规模的太阳能离网电力系统已经安装在保留地的家庭中，提供了适度但有意义的电力供应。但是，需要关键数据来了解系统的性能以及如何对其进行优化。这个NSF项目旨在评估美国土著保留地离网系统的性能，并开发一种新方法来改进其设计，从而降低成本并提高性能。该项目将为部落和非部落土地上的离网电气化实践带来革命性的变化。这将通过创建离网系统的测量数据集，严格分析数据，并开发新的数据驱动设计方法来实现。该项目的智力优势包括创建最大和最全面的电力消耗和环境测量数据集，这些数据来自美国土著保留地的离网系统，并设计了一种基于上下文信息和测量消费模式的新颖设计方法。该项目的更广泛影响包括增加服务不足人口的电力供应，支持两所主要的本科院校的工程教育，以及增加美洲原住民学生参与研究。一个强有力的传播计划包括培训、教程和讲习班材料，目标是美国土著保留地的离网从业人员。该项目将部署数据采集系统，在为期一年的时间里，从美国原住民保留区大约200个住宅离网系统中收集数据。数据集将包括负载、太阳能电池阵列功率、电池组电压、辐照度和温度的测量值。背景数据将通过调查收集。分析包括：对电力消耗进行统计表征和建模，以创建负载概况，评估系统的技术性能，计算可靠性指数，并对停电原因进行编目。该项目开发了一种基于消费回归模型的新型数据驱动设计方法，并将从调查中收集的上下文信息作为解释变量。从可以模拟离网系统的硬件试验台进行的实验室测量将用于验证该方法。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.