Abstract: 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 coefficients 34 and 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.

Abstract: 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.

Abstract: 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.

Abstract: 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).

Abstract: 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.

Abstract: 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.

Abstract: 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 coefficients 34 and 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.

Abstract: 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.

Abstract: 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).

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: An anomaly detection method includes acquiring image data corresponding to nondestructive testing (NDT) of a scanned object. The NDT image data comprises at least one inspection test image of the scanned object and multiple reference images for the scanned object. The anomaly detection method further includes generating an anomaly detection model based on a statistical analysis of one or more image features in the reference images for the scanned object and identifying one or more defects in the inspection test image, based on the anomaly detection model.

Abstract: 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.

Abstract: A method for an anomaly detection method is provided. The method includes acquiring at least one two-dimensional or three-dimensional or n-dimensional inspection test image data of a scanned object. The method further includes partitioning the inspection test image data of the scanned object into multiple sub-regions. The method also includes computing one or more texture metrics for each sub-region. Finally, the method includes discriminating between an anomalous and a non-anomalous region in the scanned object according to one or more values of the computed texture metrics and identifying one or more anomalies in the inspection test image data.

Abstract: An inspection system is provided. The inspection system includes at least one source configured to emit a beam of radiation onto an object. The inspection system also includes at least two area detectors having different characteristics configured to receive a reflected beam of radiation from the object and output a plurality of image data streams corresponding to the different characteristics, wherein the at least two area detectors disposed in at least one of a cascaded arrangement or separated by a pre-determined distance along a direction parallel or perpendicular to a scan direction of the object.

Abstract: A method and system for presenting images of an object of interest is provided. The method includes producing one or more cine loops of images from at least one of multiple projection views or multiple reconstructed 3D images including a 3D volume obtained from one or more beamlines. The method also includes generating at least one combined image including a first component and a second component wherein the first component and the second component each include one of a baseline image or the one or more cine loops of images. The combined image is generated via at least one of superimposing the first component and the second component, displaying the first component adjacent to the second component, and toggling between the first component and the second component. The method also includes displaying the at least one combined image.

Abstract: A system and method for ascertaining the identity of an object within an enclosed article. The system includes an acquisition subsystem, a reconstruction subsystem, a computer-aided detection (CAD) subsystem, and an alarm resolution subsystem. The acquisition subsystem communicates view data to the reconstruction subsystem, which reconstructs it into image data and communicates it to the CAD subsystem. The CAD subsystem analyzes the image data to ascertain whether it contains any area of interest. A feedback loop between the reconstruction and CAD subsystems allows for continued, more extensive analysis of the object. Other information, such as risk variables or trace chemical detection information may be communicated to the CAD subsystem to dynamically adjust the computational load of the analysis.