General Electric Company

Lockheed Martin Corporation

Morpho Detection, Inc.

Robert August Kaucic

Ricardo Scott Avila

Paulo Ricardo Mendonca

Jiucai Zhang

Charles Clarence Hicks, Jr

Sam T Liu

Leng Mao

Patrick Osae Djan-Sampson

Matthew William Turek

Richard Hayes Cutright

Joshua Webb

Zhaohui Harry Sun

Joseph Manuel Portaz

Herman Wiegman

Peter Henry Tu

Samit Kumar Basu

Xiaoye Wu

James Vradenburg Miller

David James

Ali Can

Forrest Frank Hopkins

Joseph Leagrand Mundy

Necip Doganaksoy

Zhanpan Zhang

Subhankar Ghosh

Hongyan Liu

Peter Michael Edic

Glen William Brooksby

William E Lorensen

James Walter LeBlanc

Colin Richard Wilson

Francis Howard Little

Mert Geveci

Xiaoming Liu

William Robert Ross

Harry Israel Ringermacher

Bruno De Man

Deborah Joy Walter

Patrick Joseph Howard

Donald Robert Howard

Paulo Ricardo Dos Santos Mendonca

William Macomber Leue

Colin Craig McCulloch

John Brandon Laflen

Yanyan Wu

Xiaodong Tao

Manoharan Venugopal

Hullas Sehgal

Timothy Patrick Kelliher

Mahesh Kumar Asati

Daniel J Blezek

Megha Navalgund

John Charles Janning

Rajashekar Venkatachalam

Fei Zhao

Matthew Edward Dragovich

Jay Zhiqiang Cao

Tony Chishao Pan

Abhirup Mondal

Eric Scott Foster

Prakash Mandayam Comare

Tony Chi-shao Pan

Shannon Lee Hastings

The system and method described herein relate to production of power from the wind farm that incorporate tunable power production forecasts for optimal wind farm performance, where the wind farm power production is controlled at least in part by the power production forecasts. The system and method use a tunable power forecasting model to generate tunable coefficients based on asymmetric loss function applied on actual power production data, along with tuning factor(s) that tune forecast towards under forecasting or over forecasting. The power production forecasts are generated using the tunable coefficientsand power characteristic features that are derived from actual power production data. The power production forecasts are monitored for any degradation, and a control action to regenerate the coefficients or retune the model is undertaken if degradation is observed.

System and method for controlling power production from a wind farm

The present disclosure is directed to a system and method for forecasting a farm-level power output of a wind farm having a plurality of wind turbines. The method includes collecting actual operational data and/or site information for the wind farm. The method also includes predicting operational data for the wind farm for a future time period. Further, the method includes generating a model-based power output forecast based on the actual operational data, the predicted operational data, and/or the site information. In addition, the method includes measuring real-time operational data from the wind farm and adjusting the power output forecast based on the measured real-time operational data. Thus, the method also includes forecasting the farm-level power output of the wind farm based on the adjusted power output forecast.

System and method for forecasting power output of a wind farm

Systems and methods of controlling a dispatch operation of an energy storage system are provided. In particular, a degradation value of a present dispatch state of an energy storage system can be determined. The present dispatch state can specify one or more energy storage units presently coupled to the system. The degradation value can be determined based at least in part on one or more operating parameters, such as temperature, open circuit voltage, charge or discharge current, and/or contactor life. The degradation value can then be compared against one or more degradation values associated with one or more candidate dispatch states. A dispatch state can then be selected based on the comparison. One or more energy storage units can be selectively coupled to the energy storage system based at least in part on the selected dispatch state.

Controlling a dispatch operation of an energy storage system

The present disclosure is directed to a system and method for calibrating state-of-charge (SOC) of an energy storage device. The method includes monitoring, via a battery management system, at least one of an accumulated capacity of the energy storage device after a first SOC calibration or a time period after the first SOC calibration. Another step includes determining, via the battery management system, whether at least one of the accumulated capacity or the time period is above a predetermined threshold. If at least one of the accumulated capacity or the time period is above a predetermined threshold, then the method includes charging, via the battery management system, the energy storage device for a specified duration until the energy storage device reaches a second SOC calibration.

System and method for calibrating battery state of charge

Systems and methods for charging a plurality of battery strings are provided. The individual string current of each of the individual battery strings can be monitored and used to regulate a charging output provided by the charger. For instance, the output voltage of charger can be controlled as part of a closed loop control system based on the individual string current of the battery string under the constraint of an individual string current limit and/or a charging voltage limit. As the charging voltage of the charger increases as a result of the closed loop control based on the individual string current, other battery strings can be coupled to the charger when the charging voltage provided by the charger exceeds a battery string voltage associated with the battery string.

String current limited battery charging control

In one aspect, a method of performing a passive maintenance operation on an energy storage farm may generally include receiving data associated with a maintenance schedule for each energy storage system in the plurality of energy storage systems, identifying at least one energy storage system as a charge contributor based at least in part on the data associated with the maintenance schedule, identifying at least one energy storage system as a discharge contributor based at least in part on the data associated with the maintenance schedule, and controlling the operation of the energy storage farm such that power distribution in the energy storage farm is biased so as to increase the state of charge of the charge contributor(s) prior to increasing the state of charge of the discharge contributor(s).

Performing passive maintenance on an energy storage farm

Systems and methods for controlling an energy storage system to provide for delivery of multiple grid services are provided. Grid service requests can be categorized into a plurality of priority tiers. Power demands associated with the grid service requests can be allocated to enforce the prioritization scheme of the priority tiers. For instance, power demands associated with grid service requests in higher priority tiers can be given preference over power demands associated with grid service requests in lower priority tiers. Multiple grid service requests can be categorized within the same priority tier. In addition, the energy storage system can be controlled not only give priority to grid services requests categorized in the higher priority tiers, but also to manage the state of charge of the system to ensure that there is sufficient reserve capacity to meet power demands of the grid service requests categorized in the higher priority tiers.

Delivery of multiple grid services with energy storage system

In one aspect, a method of distributing power among a plurality of energy storage systems in an energy storage farm may generally include receiving a power distribution input associated with a power amount to be received by or delivered from the energy storage farm, determining an initial power value for each energy storage system based at least in part on a state of charge associated with the energy storage system, determining an unallocated power value for the energy storage farm based at least in part on the received power request and the initial power values of the energy storage systems, determining an updated power value for each energy storage system based at least in part on the unallocated power value, and controlling the operation of the energy storage farm such that each energy storage system delivers or receives an amount of power equal to its determined updated power value.

Power distribution in energy storage farms

The present disclosure is directed to a system and method for controlling an energy storage device by more accurately detecting an end-of-discharge voltage of the energy storage device. More specifically, in one embodiment, the method includes determining an end-of-discharge voltage threshold for the energy storage device. Another step includes filtering the end-of-discharge voltage threshold via a filter. The method also includes adjusting a time constant of the filter based on at least one voltage-current condition. Still a further step includes comparing the filtered end-of-discharge voltage threshold and a terminal voltage of the energy storage device. Based on the comparison, the method includes determining a change of state of the energy storage device. Thus, the energy storage device can be controlled based on the change of state.

System and method for detecting battery end of discharge

A system for detecting faint perturbations of interest in an image is described. The system includes a memory comprising the image, and a processor. The processor is configured to estimate a local mean and variance for each of a plurality of pixels in the image, analyze a local region of the image, an image mean, and an image variance using a filter bank, thereby generating a plurality of response vectors, determine a likelihood of a local perturbation in the image using a probability distribution based on the plurality of response vectors, and make a classification decision of the local perturbation. The probability distribution is calculated, for each of the plurality of response vectors, based on a response of each of the plurality of response vectors to the estimated local mean and variance for each of the plurality of pixels. Methods and machine-readable media are also described.

Detection of faint perturbations of interest using statistical models of image texture

A method of automatic defect recognition includes receiving a initial set of inspection image data of a scanned object from a scanning machine; applying a first image analysis algorithm to this set of inspection image data; then removing from the set of inspection image data any defect-free image regions, so as to retain a set of analyzed inspection image data; applying an additional image analysis algorithm(s) to the set of analyzed inspection image data, wherein the additional algorithm(s) has a higher computational cost than the first image analysis algorithm; and based on the applying of the additional image analysis algorithm(s), removing from the first set of inspection image data a second set of defect-free image regions, thereby retaining a set of twice-analyzed inspection image data.

Sequential approach for automatic defect recognition

A method for identifying defects in radiographic image data corresponding to a scanned object is provided. The method includes acquiring radiographic image data corresponding to a scanned object. In one embodiment, the radiographic image data includes an inspection test image and a reference image corresponding to the scanned object. The method includes identifying one or more regions of interest in the reference image and aligning the inspection test image with the regions of interest identified in the reference image, to obtain a residual image. The method further includes identifying one or more defects in the inspection test image based upon the residual image and one or more defect probability values computed for one or more pixels in the residual image.

Method and system for identifying defects in radiographic image data corresponding to a scanned object

A method for determining 3D distances on a 2D pixelized image of a part or object includes acquiring a real 2D pixelized image of the object, creating a simulated image of the object using the 3D CAD model and the 2D pixelized image, determining a specified cost function comparing the simulated image with the real 2D pixilated image and repositioning the simulated image in accordance with iterated adjustments of a relative position between the CAD model and the 2D pixilated image to change the simulated image until the specified cost function is below a specified value. Then, the workstation is used to generate a 3D distance scale matrix using the repositioned simulated image, and to measure and display distances between selected pixels on a surface of the real image using 2D distances on the 2D pixelized image of the object and the 3D distance scale matrix.

Methods and apparatus for measuring 3D dimensions on 2D images

A method for automatically identifying defects in turbine engine blades is provided. The method comprises acquiring one or more radiographic images corresponding to one or more turbine engine blades and identifying one or more regions of interest from the one or more radiographic images. The method then comprises extracting one or more geometric features based on the one or more regions of interest and analyzing the one or more geometric features to identify one or more defects in the turbine engine blades.

Method for automatic identification of defects in turbine engine blades

Growing community of inventors

Niskayuna, NY, United States of America

Robert August Kaucic