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Hafen, Ryan P.

Publications and source records attributed to Hafen, Ryan P..

9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Methods and apparatus of analyzing electrical power grid data

Apparatus and methods of processing large-scale data regarding an electrical power grid are described. According to one aspect, a method of processing large-scale data regarding an electrical power grid includes accessing a large-scale data set comprising information regarding an electrical power grid; processing data of the large-scale data set to identify a filter which is configured to remove erroneous data from the large-scale data set; using the filter, removing erroneous data from the large-scale data set; and after the removing, processing data of the large-scale data set to identify an event detector which is configured to identify events of interest in the large-scale data set.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Tessera: Open source software for accelerated data science

Extracting useful, actionable information from data can be a formidable challenge for the safeguards, nonproliferation, and arms control verification communities. Data scientists are often on the “front-lines” of making sense of complex and large datasets. They require flexible tools that make it easy to rapidly reformat large datasets, interactively explore and visualize data, develop statistical algorithms, and validate their approaches—and they need to perform these activities with minimal lines of code. Existing commercial software solutions often lack extensibility and the flexibility required to address the nuances of the demanding and dynamic environments where data scientists work. To address this need, Pacific Northwest National Laboratory developed Tessera, an open source software suite designed to enable data scientists to interactively perform their craft at the terabyte scale. Tessera automatically manages the complicated tasks of distributed storage and computation, empowering data scientists to do what they do best: tackling critical research and mission objectives by deriving insight from data. We illustrate the use of Tessera with an example analysis of computer network data.

Sego, Landon H.↗
DOE OSTI2014

Joint Seasonal ARMA Approach for Modeling of Load Forecast Errors in Planning Studies

To make informed and robust decisions in the probabilistic power system operation and planning process, it is critical to conduct multiple simulations of the generated combinations of wind and load parameters and their forecast errors to handle the variability and uncertainty of these time series. In order for the simulation results to be trustworthy, the simulated series must preserve the salient statistical characteristics of the real series. In this paper, we analyze day-ahead load forecast error data from multiple balancing authority locations and characterize statistical properties such as mean, standard deviation, autocorrelation, correlation between series, time-of-day bias, and time-of-day autocorrelation. We then construct and validate a seasonal autoregressive moving average (ARMA) model to model these characteristics, and use the model to jointly simulate day-ahead load forecast error series for all BAs.

Power system planning, Operations, Probabilistic m↗
DOE OSTI2014

Distance Restraints from Crosslinking Mass Spectrometry: Mining a Molecular Dynamics Simulation Database to Evaluate Lysine-Lysine Distances

Integrative structural biology models the structures of protein complexes that are intractable by classical structural methods (because of extreme size, dynamics, or heterogeneity) by combining computational structural modeling with data from experimental methods. One such method is chemical cross-linking mass spectrometry (XL-MS), in which cross-linked peptides, derived from a covalently cross-linked protein complex and identified by liquid chromatography-mass spectrometry, pinpoint protein residues close in three-dimensional space. The commonly used lysine-reactive N-hydroxysuccinimide ester reagents disuccinimidylsuberate (DSS) and bis(sulfosuccinimidyl)suberate (BS3) have a linker arm that is 11.4 Å long when fully extended. However, XL-MS studies on proteins of known structure frequently report cross-links that exceed this distance. Typically, a tolerance of ~3 Å is added to the theoretical maximum to account for this observation, with little justification for the value chosen. We used the Dynameomics database, a repository of high-quality molecular dynamics simulations of 807 proteins representative of all protein folds, to investigate the change in lysine-lysine distances resulting from native-state dynamics on the time-scale of tens of nanoseconds. We conclude that observed cross-links are consistent with a protein structure if the distance between cross-linked lysine Nζ atoms is less than the cross-linker length plus 11.3 Å. For DSS or BS3, this corresponds to a Cα to Cα distance of 30.4 Å. This analysis provides a theoretical basis for the widespread practice of adding a tolerance to the crosslinker length when comparing XL-MS results to structures, and indicates the appropriate values of an XLMS derived distance constraint to use in structural modeling.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2014

Power Grid Data Analysis with R and Hadoop

This book chapter presents an approach to analysis of large-scale time-series sensor information based on our experience with power grid data. We use the R-Hadoop Integrated Programming Environment (RHIPE) to analyze a 2TB data set and present code and results for this analysis.

Hafen, Ryan P.↗
DOE OSTI2013

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

Lu, Ning↗
DOE OSTI2013

Trelliscope: A System for Detailed Visualization in Analysis of Large Complex Data

Visualization plays a critical role in the statistical model building and data analysis process. Data analysts, well-versed in statistical and machine learning methods, visualize data to hypothesize and validate models. These analysts need flexible, scalable visualization tools that are not decoupled from their analysis environment. In this paper we introduce Trelliscope, a visualization framework for statistical analysis of large complex data. Trelliscope extends Trellis, an effective visualization framework that divides data into subsets and applies a plotting method to each subset, arranging the results in rows and columns of panels. Trelliscope provides a way to create, arrange and interactively view panels for very large datasets, enabling flexible detailed visualization for data of any size. Scalability is achieved using distributed computing technologies coupled with . We discuss the underlying principles, design, and scalable architecture of Trelliscope, and illustrate its use on three analysis projects in the domains of proteomics, high energy physics, and power systems engineering.

Hafen, Ryan P.↗
DOE OSTI2012

Lumen Maintenance Testing of the Philips 60-Watt Replacement Lamp L Prize Entry

This paper describes testing conducted to evaluate the Philips' L Prize award winning 60-watt LED replacement product's ability to meet the lifetime/lumen maintenance requirement of the competition, which was: "having 70 percent of the lumen value under subparagraph (A) [producing a luminous flux greater than 900 lumens] exceeding 25,000 hours under typical conditions expected in residential use." A custom test apparatus was designed and constructed for this testing and a statistical approach was developed for use in evaluating the test results. This will be the only publicly available, third-party data set of long-term LED product operation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗