Abstract: According to some embodiments, a system and method are provided comprising a vegetation module to receive image data from an image source; a memory for storing program instructions; a vegetation processor, coupled to the memory, and in communication with the vegetation module, and operative to execute program instructions to: receive image data; estimate a vegetation segmentation mask; generate at least one of a 3D point cloud and a 2.5D Digital Surface Model based on the received image data; estimate a relief surface using a digital terrain model; generate a vegetation masked digital surface model based on the digital terrain model, the vegetation segmentation mask and at least one of the 3D point cloud and the 2.

Abstract: According to some embodiments, a system and method are provided comprising a vegetation management module to receive image data from an image source; a memory for storing program instructions; a vegetation management processor, coupled to the memory, and in communication with the vegetation module, and operative to execute program instructions to: receive first image data and second image data for an area of interest; overlay the first image data over the second image data to generate an overlaid image; receive feeder attribute data for at least one feeder in the overlaid image; generate a risk score for the at least one feeder based in part on the received feeder attribute data; and generate a visualization based on the at least one feeder and the generated risk score. Numerous other aspects are provided.

Abstract: According to some embodiments, a system and method are provided comprising a vegetation module to receive image data from an image source; a memory for storing program instructions; a vegetation processor, coupled to the memory, and in communication with the vegetation module, and operative to execute program instructions to: receive image data; estimate a vegetation segmentation mask; generate at least one of a 3D point cloud and a 2.5D Digital Surface Model based on the received image data; estimate a relief surface using a digital terrain model; generate a vegetation masked digital surface model based on the digital terrain model, the vegetation segmentation mask and at least one of the 3D point cloud and the 2.

Abstract: According to some embodiments, a system and method are provided comprising a vegetation management module to receive image data from an image source; a memory for storing program instructions; a vegetation management processor, coupled to the memory, and in communication with the vegetation module, and operative to execute program instructions to: receive first image data and second image data for an area of interest; overlay the first image data over the second image data to generate an overlaid image; receive feeder attribute data for at least one feeder in the overlaid image; generate a risk score for the at least one feeder based in part on the received feeder attribute data; and generate a visualization based on the at least one feeder and the generated risk score. Numerous other aspects are provided.

Abstract: A method for estimating and managing life of a gas turbine is provided. The method includes estimating a remaining useful life of a component of a gas turbine, obtaining parameters of the gas turbine, at least one of which comprises the estimate of the remaining useful life of a component of the gas turbine, assigning operating weightages to the gas turbine parameters based a plant objective, generating a set point for operating the gas turbine based on the weighted gas turbine parameters, and adjusting an operating characteristic of the gas turbine to meet the set point.

Abstract: A control method for optimizing or enhancing an operation of a power plant that includes thermal generating units for generating electricity. The power plant may include multiple possible operating modes differentiated by characteristics of operating parameters. The method may include tuning a power plant model so to configure a tuned power plant model. The method may further include simulating proposed operating modes of the power plant with the tuned power plant model. The simulating may include a simulation procedure that includes: defining a second operating period; selecting the proposed operating modes from the possible operating modes; with the tuned power plant model, performing a simulation run for each of the proposed operating modes whereby the operation of the power plant during the second operating period is simulated; and obtaining simulation results from each of the simulation runs.

Abstract: Systems and methods for generating solution recommendations for power plant operation can be provided by certain embodiments of the disclosure. In one embodiment, a system may include a processor configured to collect power plant operational data from power plant components. The power plant operational data may be analyzed to identify cost factors for the power plant components. Based at least in part on the power plant operational data and the cost factors, upgrade opportunities for the power plant components may be determined. Financial values may be calculated for the upgrade opportunities. Based at least in part on the financial values, recommendations may be generated using a product interaction database and provided as an electronic output to a user.

Abstract: The present embodiments related to a machinery failure evaluation system and associated method. The system may receive time-series data associated with a piece of machinery. An anomaly associated with the piece of machinery may automatically be determined by comparing the time-series data with a model associated with the piece of machinery. Furthermore, it may be determined that the anomaly is not a known fault based on performing a lookup of known failure modes. In a case that the anomaly is not a known fault, an alert associated with an unknown failure mode may be transmitted.

Abstract: The present subject matter is directed to a system and method for optimizing wind turbine operation. For example, the present disclosure is configured to generate operating data for at least one operational parameter of the wind turbine for a predetermined time period. The system can then determine a robustness measurement of at least a portion of the operating data. In general, the robustness measurement indicates the tendency of the operating data to be affected by outliers present in the operating data. In addition, the robustness measurement is typically a function of a distribution of the operating data. The present disclosure is then configured to determine at least one optimal set point for the operational parameter as a function of the robustness measurement and a power production of the wind turbine. The wind turbine can then be operated based on the optimal set point.

Abstract: Embodiments of the disclosure relate to systems and methods of forecasting power plant performance. In one embodiment, a system can include a computer that is configured to use a calibrated physics-based simulation model to generate training data. The training data is used by the computer to effectuate a surrogate neural network model. Furthermore, the computer is configured to receive a periodic performance index. The periodic performance index, which is indicative of dynamic changes in one or more operating parameters of the power plant, is processed in combination with the surrogate neural network model by the computer for forecasting one or more performance parameters of the power plant.

Abstract: A method for continuously monitoring the working condition of a heat recovery steam generator (“HRSG”) using infrared thermography, comprising the steps of identifying target locations inside the HRSG, positioning one or more infrared cameras to continuously monitor and record the temperature at each target location, generating continuous thermographic images corresponding to selected components and locations at each target locations, comparing the continuous thermographic images to corresponding, stored base line images and generating a set of comparative data reports in real time for each target location in order to predict the life span or potential failure of HRSG components.

Abstract: A system for detecting an at-fault combustor includes a sensor that is configured to sense combustion dynamics pressure data from the combustor and a computing device that is in electronic communication with the sensor and configured to receive the combustion dynamics pressure data from the sensor. The computing device is programmed to convert the combustion dynamics pressure data into a frequency spectrum, segment the frequency spectrum into a plurality of frequency intervals, extract a feature from the frequency spectrum, generate feature values for the feature within a corresponding frequency interval over a period of time, and to store the feature values to generate a historical database. The computing device is further programmed to execute a machine learning algorithm using the historical database of the feature values to train the computing device to recognize feature behavior that is indicative of an at-fault combustor.

Abstract: Systems and methods for improved control of a turbomachine system with a bottoming cycle system are presented. The systems and methods include a controller that utilizes modeling techniques to derive a plurality of load path curves. The controller utilizes a current load path, a minimum load path, and a constant efficiency load path. The systems and methods include a control process configured to receive a user input representative of a life cycle control modality and to execute a control action based on deriving a load efficiency by applying the current load path, the minimum load path, the constant efficiency load path, or a combination thereof, and the life cycle control modality. The control action is applied to control the turbomachine system and the bottoming cycle system fluidly coupled to the turbomachine system. Further, the life cycle control modalities may be selected by a user based upon known tradeoffs.

Abstract: A method of controlling a water level in a steam drum includes predicting a transient in the steam drum based on plant characteristics including steam flow from the steam drum, drum pressure in the steam drum, and one or both of a gas turbine load and a position of a bypass valve configured to control the steam flow from the steam drum to two or more steam flow conduits. The method further includes generating a sliding setpoint to control the water level based on predicting the transient in the steam drum.

Abstract: Systems and methods for on-line monitoring of hot gas path components of a gas turbine are provided. According to one embodiment of the disclosure, a system may include a camera operable to monitor one or more hot gas path components of the gas turbine and a processor communicatively coupled to the camera. The processor is operable to receive realtime data from the camera monitoring the one or more hot gas path components of the gas turbine and compare the realtime data to reference data. Based on the comparison, the processor can determine that a difference between the realtime data and the reference data exceeds a predetermined threshold. If the difference exceeds the predetermined threshold, the processor can notify operators of an anomaly in the one or more hot gas path components.

Abstract: Systems and methods provided herein. In one embodiment, a system includes an advisory system including a loss computation engine configured to derive a total system loss for an industrial plant based on a first sensor positioned in a first industrial plant component and on a first physical model of the first industrial plant component. The advisory system further includes a cost model configured to use a cost function to derive a cost based on the total system loss, and a control strategy system configured to derive an advisory report, a control correction factor, or a combination thereof, based on the cost, wherein a control system is configured to apply the control correction factor to control a process in the industrial plant.

Abstract: Systems and methods provided herein output an operational advisory based upon a plurality of models derived from a plurality of data, in which the plurality of models comprise at least one of a plant transfer function, a degradation contributor model, or a plant level cost model, and in which the plurality of data is derived from at least one of current plant data, historical plant data, business data, environmental data, component data, degradation contribution data, an optimization goal, or a combination thereof.

Abstract: A control method for optimizing an operation of a power plant having generating units during a selected operating period subdivided so to include regular intervals within which each of the generating units comprises one of an on-condition and an off-condition.

Abstract: A method for estimating and managing life of a gas turbine is provided. The method includes estimating a remaining useful life of a component of a gas turbine, obtaining parameters of the gas turbine, at least one of which comprises the estimate of the remaining useful life of a component of the gas turbine, assigning operating weightages to the gas turbine parameters based a plant objective, generating a set point for operating the gas turbine based on the weighted gas turbine parameters, and adjusting an operating characteristic of the gas turbine to meet the set point.

Abstract: A control method for optimizing an operation of a power plant having generating units during a selected operating period subdivided so to include regular intervals within which each of the generating units comprises one of an on-condition and an off-condition.