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WindLogics Inc. | Date: 2015-10-14

A voltage pattern analysis system and method may automate aspects of the process of mapping or assigning utility meters to a specific transformer or other distribution node by identifying misassociated meters and correcting a system-wide transformer assignment or distribution node assignment. When a meters voltage signal does not correlate well with other meters voltage signals on the same transformer, the meter is likely misassociated to that transformer. A pairwise voltage signal correlation may be computed for all meters assigned to a transformer and a voltage signal correlation for every transformer in the system, or a subset thereof, may be imputed. Individual meter correlations may then be compared with the transformer correlation. For meters identified as misassociation candidates, transformers or other distribution nodes within a specified radius may be considered for reassignment of the meter.

Baingana B.,WindLogics Inc. | Giannakis G.B.,University of Minnesota
IEEE Transactions on Signal Processing | Year: 2017

Contagions, such as the spread of popular news stories, or infectious diseases, propagate in cascades over dynamic networks with unobservable topologies. However, 'social signals,' such as product purchase time, or blog entry timestamps are measurable, and implicitly depend on the underlying topology, making it possible to track it over time. Interestingly, network topologies often 'jump' between discrete states that may account for sudden changes in the observed signals. The present paper advocates a switched dynamic structural equation model to capture the topology dependent cascade evolution, as well as the discrete states driving the underlying topologies. Conditions under which the proposed switched model is identifiable are established. Leveraging the edge sparsity inherent to social networks, a recursive ℓ1-norm regularized least-squares estimator is put forth to jointly track the states and network topologies. An efficient first-order proximal-gradient algorithm is developed to solve the resulting optimization problem. Numerical experiments on both synthetic data and real cascades measured over the span of one year are conducted, and test results corroborate the efficacy of the advocated approach. © 2016 IEEE.

Beltran-Przekurat A.,University of Colorado at Boulder | Pielke R.A.,University of Colorado at Boulder | Eastman J.L.,WindLogics Inc. | Coughenour M.B.,Colorado State University
International Journal of Climatology | Year: 2012

A fully coupled atmospheric-biospheric regional climate model, GEMRAMS, was used to evaluate potential effects of land-use/land-cover changes (LULCC) on near-surface atmosphere over a southern South American domain at seasonal time scales. In GEMRAMS, leaf area index and canopy conductance are computed based on modelled temperature, solar radiation, and the water status of the soil and air, allowing a two-way interaction between canopy and atmosphere. Several austral spring-early summer simulations were conducted using land cover representing current (i.e. agricultural landscape), natural (i.e. before European settlement), and afforestation scenarios for three periods associated with El Niño-Southern Oscillation (ENSO) conditions. The shift to agriculture resulted in a generalized increase in albedo, reducing the available energy at the near-surface. (Correction added on 21 September 2011 after original online publication: in the preceding sentence the word 'decrease' was corrected to 'increase'.) The energy partitioning between latent and sensible heat fluxes changed, leading to distinct temperature responses. A shift from grass to agriculture led to cooler and wetter near-surface atmospheric conditions. Warmer temperatures resulted from the conversion of wooded grasslands or forest to agriculture. The LULCC-induced signal was spatially heterogeneous and with a seasonal component associated with vegetation phenology. A significant decrease in maximum temperatures in the southern and central Pampas led to a decrease in the diurnal temperature range. Basing on some observational studies in this region our results suggest a potential strong influence of LULCC on the maximum temperatures in central Argentina in summer. Afforestation resulted overall in cooler temperatures. For both LULCC scenarios the direction of the energy fluxes and temperature changes remained in general the same in two extreme ENSO years, although for some vegetation conversions the signal reversed direction. Overall, the impacts were enhanced during a dry year, but the response also depended on the vegetation types involved in the conversion. The effects on precipitation were insignificant in the agriculture-conversion scenario and a general increase was found in the afforested scenario. © 2011 Royal Meteorological Society.

Olivetti E.,University of Trento | Veeramachaneni S.,WindLogics Inc. | Nowakowska E.,Multivariate Statistics Group
Pattern Recognition | Year: 2012

Research in cognitive neuroscience and in braincomputer interfaces (BCI) is frequently concerned with finding evidence that a given brain area processes, or encodes, given stimuli. Experiments based on neuroimaging techniques consist of a stimulation protocol presented to a subject while his or her brain activity is being recorded. The question is then whether there is enough evidence of brain activity related to the stimuli within the recorded data. Finding a link between brain activity and stimuli has recently been proposed as a classification task, called brain decoding. A classifier that can accurately predict which stimuli were presented to the subject provides support for a positive answer to the question. However, it is only the answer for a given data set and the question still remains whether it is a general rule that will apply also to new data. In this paper we try to reliably answer the neuroscientific question about the presence of a significant link between brain activity and stimuli once we have the classification results. The proposed method is based on a Beta-Binomial model for the population of generalization errors of classifiers from multi-subject studies within the Bayesian hypothesis testing framework. We present an application on nine brain decoding investigations from a real functional magnetic resonance imaging (fMRI) experiment about the relation between mental calculation and eye movements. © 2011 Elsevier Ltd. All rights reserved.

Karstens C.D.,Iowa State University | Gallus Jr. W.A.,Iowa State University | Lee B.D.,WindLogics Inc. | Finley C.A.,WindLogics Inc.
Journal of Applied Meteorology and Climatology | Year: 2013

In this study, aerial imagery of tornado damage is used to digitize the falling direction of trees (i.e., tree fall) along the 22 May 2011 Joplin, Missouri, and 27 April 2011 Tuscaloosa-Birmingham, Alabama, tornado tracks. Normalized mean patterns of observed tree fall from each tornado's peak-intensity period are subjectively compared with results from analytical vortex simulations of idealized tornado-induced tree fall to characterize mean properties of the near-surface flow as depicted by the model. A computationally efficient method of simulating tree fall is applied that uses a Gumbel distribution of critical tree-falling wind speeds on the basis of the enhanced Fujita scale. Results from these simulations suggest that both tornadoes had strong radial near-surface winds. A few distinct tree-fall patterns are identified at various locations along the Tuscaloosa-Birmingham tornado track. Concentrated bands of intense tree fall, collocated with and aligned parallel to the axis of underlying valley channels, extend well beyond the primary damage path. These damage patterns are hypothesized to be the result of flow acceleration caused by channeling within valleys. Another distinct pattern of tree fall, likely not linked to the underlying topography, may have been associated with a rear-flank downdraft (RFD) internal surge during the tornado's intensification stage. Here, the wind field was strong enough to produce tornado-strength damage well beyond the visible funnel cloud. This made it difficult to distinguish between tornado- and RFD-related damage and thus illustrates an ambiguity in ascertaining tornado-damage-path width in some locations. © 2013 American Meteorological Society.

Lee B.D.,WindLogics Inc. | Finley C.A.,WindLogics Inc. | Karstens C.D.,Iowa State University
Monthly Weather Review | Year: 2012

Mobile mesonet sampling in the hook echo/rear-flank downdraft (RFD) region of a tornadic supercell near Bowdle, South Dakota, provided the opportunity to examine RFD thermodynamic and kinematic attributes and evolution. Focused analysis of the fifth low-level mesocyclone cycle that produced two significant tornadoes including a violent tornado, revealed four RFD internal surge (RFDIS) events. RFDISs appeared to influence tornado development, intensity, and demise by altering the thermodynamic and kinematic character of the RFD region bounding the pretornadic and tornadic circulations. Significant tornadoes developed and matured when the RFD, modulated by internal surges, was kinematically strong, only weakly negatively buoyant, and very potentially buoyant. In contrast, the demise of the Bowdle tornado was concurrent with a much cooler RFDIS that replaced more buoyant and far more potentially buoyantRFD air near the tornado. This surge also likely contributed to a displacement of the tornado from the storm updraft. Development of the first tornado and rapid intensification of the Bowdle tornado occurred when an RFDIS boundary convergence zone interacted with the pretornadic and tornadic circulations, respectively. In the latter case, a strong vertical vortex sheet along an RFDIS boundary appeared to be a near-surface cyclonic vorticity source for the tornado. A downdraft closely bounding the right flank of the developing first tornado and intensifying Bowdle tornado provided some of the inflow to these circulations. For the Bowdle tornado, parcels were also streaming toward the tornado from its immediate east and northeast. A cyclonic-anticyclonic vortex couplet was observed during a portion of each significant tornado cycle. ©2012 American Meteorological Society.

WindLogics Inc. | Date: 2014-06-04

A system and method is disclosed for calculating potential power generation for a wind farm, the wind farm including a plurality of wind turbines. The system and method include measuring the power generated by the wind farm; acquiring turbine data from at least a subset of the plurality of wind turbines, the wind turbine data including local wind speed and power generated at the local wind speed; acquiring wind resource data for the wind farm, the wind resource data including wind speed; generating a power curve from the turbine data and the wind resource data, the power curve plotting the relationship between wind speed and power generated; calculating power lost due to availability, subcurve, and curtailment, the power loss calculated for at least said subset of turbines; and aggregating the power lost in order to determine an aggregate power loss for the wind farm.

News Article | January 10, 2011

The World's #1 Renewable Energy Network for News, Information, and Companies.

News Article | April 15, 2015

RESTON, Va.--(BUSINESS WIRE)--The Utility Variable-Generation Integration Group (UVIG) announced individuals from the following organizations as recipients of its 2015 Annual Achievement Awards: California ISO (CAISO), PacifiCorp, U.S. Department of Energy, Renewable Energy Consulting Services (RECS), National Renewable Energy Laboratory (NREL), SRA International (SRAI), New West Technologies (NWT), GE, Clean Power Research (CPR), National Oceanic and Atmospheric Administration (NOAA), WindLogics, SUNY Albany, Energy Systems Consulting Services (ESCS), Great River Energy, and Midwest ISO. UVIG President Steve Beuning will present the awards at a reception during its 2015 Spring Technical Workshop and Annual Meeting to be held in Minneapolis, Minnesota, April 21-23. The citation for the awards to Steve Berberich, Mark Rothleder, Karen Edson, and Stacey Crowley of CAISO; Natalie Hocken, Sarah Edmonds, and Stefan Bird of PacifiCorp, reads, “For leadership in the design, development, and deployment of the Energy Imbalance Market in the Western Interconnection.” The citation for the awards to Jose Zayas of DOE, Ed DeMeo of RECS, Jessica Lin-Powers and Eric Lantz of NREL, Edward Eugeni of SRAI, and Richard Tusing of NWT, reads, “For leadership and vision in leading the Wind Vision effort to show the role of wind power in a clean energy future.” The citation for the awards to Kara Clark of NREL, Nick Miller, Miaolei Shao, and Slobodan Pajic of GE, reads, “For leadership in improving the understanding of power system dynamics in WECC under high variable generation conditions.” The citation for the award to Tom Hoff of CPR, reads, “For ongoing contributions to solar forecasting that enable improved integration of PV plant output into power system operations.” The citation for the awards to Melinda Marquis and Jim Wilczak of NOAA, Joel Cline of DOE, Cathy Finley of WindLogics, and Jeff Freedman of SUNY Albany, formerly of AWS Truepower, reads, “For contributions to improve wind energy forecasts through the Wind Forecast Improvement Project.” The citation for the awards to Matt Schuerger of ESCS, Jared Alholinna of Great River Energy, and Dick Piwko, Douglas Welsh, and Rob D’Aquila of GE, reads, “For leadership in planning and executing the Minnesota Renewable Integration and Transmission Study.” The citation for the award to Dale Osborn of Midwest ISO, reads, “For leadership in applying VSC HVDC transmission planning to improving power system operations and renewables integration.” According to UVIG’s Beuning, this year’s slate of honorees reflects the core missions for the organization: “All of these recipients have provided leadership and extended the science and understanding of integrating wind and solar generation into utility power systems. Not only has there been an expansion of the state of the art of how to integrate variable generation, but there has been significant work undertaken in understanding application of variable generation in a variety of utility operating environments and business models. As President of UVIG, it gives me great pleasure to announce these awards and to congratulate the recipients.” UVIG will also honor Beuning of Xcel Energy, Jim Blatchford of California ISO, and Tom Komjathy of DTE Energy for their service on its Board of Directors. The Utility Variable-Generation Integration Group, previously known as the Utility Wind Integration Group (UWIG), was established in 1989 to provide a forum for the critical analysis of wind and solar technology for utility applications and to serve as a source of credible information on the status of wind and solar technology and deployment. The group’s mission is to accelerate the development and application of good engineering and operational practices supporting the appropriate integration of variable generation for utility applications through the coordinated efforts and actions of its members, in collaboration with the U.S. Department of Energy, its National Renewable Energy Laboratory and utility research organizations. UVIG currently has over 175 members from the United States, Canada, Europe, and Asia, including investor-owned, public power, and rural electric cooperative utilities; transmission system operators; and associate member corporate, government, and academic organizations. For more information, visit the UVIG web site at

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