An Inter-Laboratory Study of Zn–Sn–Ti–O Thin Films using High-Throughput Experimental Methods
Not Available
14 SOLAR ENERGY↗
Engineering topics
Phillips, Caleb
Publications and source records attributed to Phillips, Caleb.
A data mining approach to estimating rooftop photovoltaic potential in the US
This paper aims to quantify the amount of suitable rooftop area for photovoltaic (PV) energy generation in the continental United States (US). The approach is data-driven, combining Geographic Information Systems analysis of an extensive dataset of Light Detection and Ranging (LiDAR) measurements collected by the Department of Homeland Security with a statistical model trained on these same data. The model developed herein can predict the quantity of suitable roof area where LiDAR data is not available. This analysis focuses on small buildings (1000 to 5000 square feet) which account for more than half of the total available rooftop space in these data (58%) and demonstrate a greater variability in suitability compared to larger buildings which are nearly all suitable for PV installations. This paper presents new results characterizing the size, shape and suitability of US rooftops with respect to PV installations. Overall 28% of small building roofs appear suitable in the continental United States for rooftop solar. Nationally, small building rooftops could accommodate an expected 731 GW of PV capacity and generate 926 TWh/year of PV energy on 4920 km2 of suitable rooftop space which equates to 25% the current US electricity sales.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Automated Algorithms for Band Gap Analysis from Optical Absorption Spectra
As high-throughput combinatorial experimental methods become more common, the technical challenge is shifting from producing materials to dealing with increasingly large datasets. One of the most important metrics to determine suitability of semiconductor materials for various applications is the band gap. This paper discusses automated algorithms for determining band gaps from optical absorption spectra. The algorithms are applied to a database of 34,313 optical absorption spectra, and selected results are compared to published theoretical and experimental band gap data from 16 materials sets. The best algorithm determines the band gaps with an accuracy of 0.37 eV for direct- and 0.93 eV for indirect band gaps for >20,000 spectra.
97 MATHEMATICS AND COMPUTING↗
An open experimental database for exploring inorganic materials
The use of advanced machine learning algorithms in experimental materials science is limited by the lack of sufficiently large and diverse datasets amenable to data mining. If publicly open, such data resources would also enable materials research by scientists without access to expensive experimental equipment. Here, we report on our progress towards a publicly open High Throughput Experimental Materials (HTEM) Database (htem.nrel.gov). This database currently contains 140,000 sample entries, characterized by structural (100,000), synthetic (80,000), chemical (70,000), and optoelectronic (50,000) properties of inorganic thin film materials, grouped in >4,000 sample entries across >100 materials systems; more than a half of these data are publicly available. This article shows how the HTEM database may enable scientists to explore materials by browsing web-based user interface and an application programming interface. This paper also describes a HTE approach to generating materials data, and discusses the laboratory information management system (LIMS), that underpin HTEM database. Finally, this manuscript illustrates how advanced machine learning algorithms can be adopted to materials science problems using this open data resource.
36 MATERIALS SCIENCE↗
OpenOA™, FKA: Wind Plant Performance Project (WP3) Benchmarking
This library provides a framework for working with large timeseries data from wind plants, such as SCADA. Its development has been motivated by the WP3 Benchmarking (PRUF) project, which aims to provide a reference implementation for plant-level performance assessment.
Perr-Sauer, Jordan↗
HTEM-DB API Examples
The HTEM DB is a public database and web application containing measurements of thin film materials collected using "high throughput" (combinatorial) synthesis and measurement processes. This software provides examples of utilizing the HTEM-DB API to access, plot and analyze the data contained therein.
Schwarting, Marcus↗
WIND Toolkit Highly Scalable Data Service (HSDS) API Examples [SWR-18-05]
The WIND Toolkit Highly Scalable Data Service (HSDS) API examples provide example python software notebooks (software) and a javascript visualization that demonstrate use of the HDF Group's HSDS API utilizing data for NREL's WIND Toolkit.
Phillips, Caleb↗
High Throughput Experimental Materials Database
The mission of the High Throughput Experimental Materials Database (HTEM DB) is to enable discovery of new materials with useful properties by releasing large amounts of high-quality experimental data to public. The HTEM DB contains information about materials obtained from high-throughput experiments at the National Renewable Energy Laboratory (NREL).
36 MATERIALS SCIENCE↗
WIND Toolkit Offshore Summary Dataset
This dataset contains summary statistics for offshore wind resources for the continental United States derived from the Wind Integration National Datatset (WIND) Toolkit. These data are available in two formats: GDB - Compressed geodatabases containing statistical summaries aligned with lease blocks (aliquots) stored in a GIS format. These data are partitioned into Pacific, Atlantic, and Gulf resource regions. HDF5 - Statistical summaries of all points in the offshore Pacific, Atlantic, and Gulf offshore regions. These data are located on the original WIND Toolkit grid and have not been reassigned or downsampled to lease blocks. These data were developed under contract by NREL for the Bureau of Oceanic Energy Management (BOEM).
17 WIND ENERGY↗
Using GIS-based methods and lidar data to estimate rooftop solar technical potential in US cities
Not Available
14 SOLAR ENERGY↗
Prediction and characterization of application power use in a high-performance computing environment
Power use in data centers and high-performance computing (HPC) facilities has grown in tandem with increases in the size and number of these facilities. Substantial innovation is needed to enable meaningful reduction in energy footprints in leadership-class HPC systems. In this paper, we focus on characterizing and investigating application-level power usage. We demonstrate potential methods for predicting power usage based on a priori and in situ characteristics. Lastly, we highlight a potential use case of this method through a simulated power-aware scheduler using historical jobs from a real scientific HPC system.
97 MATHEMATICS AND COMPUTING↗
U.S. PV-Suitable Rooftop Resources
This dataset contains zipcode resolution estimates of suitable area on small (1,000-5,000 m^2), medium (5,000-10,000 m^2) and large (>10,000 m^2) buildings' rooftops for PV deployment.
14 SOLAR ENERGY↗
On the Use of Coupled Wind, Wave, and Current Fields in the Simulation of Loads on Bottom-Supported Offshore Wind Turbines during Hurricanes: March 2012 - September 2015
In the United States, potential offshore wind plant sites have been identified along the Atlantic seaboard and in the Gulf of Mexico. It is imperative that we define external conditions associated with hurricanes and severe winter storms and consider load cases for which wind turbines may need to be designed. We selected two hurricanes, Ike (2008) and Sandy (2012), and investigated the effect these tropical storms would have on bottom-supported offshore wind turbines that were hypothetically in or close to their path as they made landfall. For realistic turbine loads assessment, it is important that the coupled influences of the changing wind, wave, and current fields are simulated throughout the evolution of the hurricanes. We employed a coupled model--specifically, the University of Miami Coupled Model (UMCM)--that integrates atmospheric, wave, and ocean components to produce needed wind, wave, and current data. The wind data are used to generate appropriate vertical wind profiles and full wind velocity fields including turbulence; the current field over the water column is obtained by interpolated discrete output current data; and short-crested irregular second-order waves are simulated using output directional wave spectra from the coupled model. We studied two monopile-supported offshore wind turbines sited in 20 meters of water in the Gulf of Mexico to estimate loads during Hurricane Ike, and a jacket space-frame platform-supported offshore wind turbine sited in 50 meters of water in the mid-Atlantic region to estimate loads during Hurricane Sandy. In this report we discuss in detail how the simulated hurricane wind, wave, and current output data are used in turbine loads studies. In addition, important characteristics of the external conditions are studied, including the relative importance of swell versus wind seas, aerodynamic versus hydrodynamic forces, current velocity effects, yaw control options for the turbine, hydrodynamic drag versus inertia forces, and soil-structure interaction effects. A detailed framework is presented that explains how coupled inputs can be included in turbine loads studies during a hurricane. This framework can aid in future efforts aimed at developing offshore wind turbine design criteria and load cases related to hurricanes.
16 TIDAL AND WAVE POWER↗