Browsing by Author "Bradbury, Kyle"
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Item Open Access Distributed solar photovoltaic array location and extent dataset for remote sensing object identification.(Scientific data, 2016-12) Bradbury, Kyle; Saboo, Raghav; L Johnson, Timothy; Malof, Jordan M; Devarajan, Arjun; Zhang, Wuming; M Collins, Leslie; G Newell, RichardEarth-observing remote sensing data, including aerial photography and satellite imagery, offer a snapshot of the world from which we can learn about the state of natural resources and the built environment. The components of energy systems that are visible from above can be automatically assessed with these remote sensing data when processed with machine learning methods. Here, we focus on the information gap in distributed solar photovoltaic (PV) arrays, of which there is limited public data on solar PV deployments at small geographic scales. We created a dataset of solar PV arrays to initiate and develop the process of automatically identifying solar PV locations using remote sensing imagery. This dataset contains the geospatial coordinates and border vertices for over 19,000 solar panels across 601 high-resolution images from four cities in California. Dataset applications include training object detection and other machine learning algorithms that use remote sensing imagery, developing specific algorithms for predictive detection of distributed PV systems, estimating installed PV capacity, and analysis of the socioeconomic correlates of PV deployment.Item Open Access Integrating Medium-Voltage Lines into the OnSSET Model for Electrification Planning(2019-04-25) Cathcart, WendellExtending electricity access to the 1 billion people worldwide who live without is a complex and costly undertaking, requiring data-driven methods to inform decision makers. Models for electricity access optimization fill this role by leveraging geospatial data to determine the least cost grid and off-grid electrification options for a region of study. The emergence of modern machine learning techniques coupled with abundant satellite imagery promises to provide a new source of transmission and distribution infrastructure data for electricity access modeling, yet questions persist about how to best integrate this new data into existing models. My work focused on the popular OnSSET model for electrification planning, and I explored updating the model to accommodate new data on the location of Medium-Voltage (MV) transmission infrastructure. In addition to adjusting the core model to incorporate this new class of input data, I built an add-on to optimize grid-extension from MV interconnections. Applying this updated model to a case study in Afghanistan, I found small parameter changes can have large impacts on the electricity planning pathways for a region. Similarly, the inclusion of MV infrastructure has great implications for the feasibility of grid extension.Item Open Access Where Data Science and the Disciplines Meet: Innovations in Linking Doctoral Students With Masters-Level Data Science Education(Harvard Data Science Review) Preiss, Doreet; Sperling, Jessica; Huang, Ryan M; Bradbury, Kyle; Nechyba, Thomas; Calderbank, Robert; Herschlag, Gregory; Borg, Jana Schaich