Abstract: An example method utilizing different pipelines of a prediction system, comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.

Abstract: An example method comprises receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.

Abstract: An exemplary method includes solving on a computing system an optimal power flow formulation for a plurality of generators in a power system. The solving includes computing using multi-threaded parallelism a plurality of constraints for the formulation, computing using multi-threaded parallelism a plurality of Jacobian functions of the constraints, and computing using multi-threaded parallelism a Hessian of Lagrangian functions. The method further includes outputting results of the solving, wherein the results comprise values of generation levels for the plurality of generators. Apparatus and program products are also disclosed.

Abstract: Systems and methods for providing high performance access to NFT metadata including ownership information. An example method requests NFT metadata from a server that has cached NFT metadata extracted from a mirror NFT blockchain. Periodically, new blocks that have been added to an NFT blockchain are added to the mirror blockchain and processed to update a cache with metadata modifications. Additionally, the method includes requests for NFT ownership information. An ownership transaction table is generated and updated from the mirror blockchain. Ownership request can include requests for all the NFTs owned by a crypto-wallet address.

Abstract: Conventional television audience measurements are made with diaries or by imaging the area in front of a television and trying to identify the people in the images watching television. Unfortunately, diaries are only accurate if the audience members record entries in them, and image-based techniques are intrusive. The present techniques address these problems by using a viewer's wearable device to measure a viewer's proximity to a television. The wearable device emits or receives low-power beacon signals; measurements of the signal strength are used to calculate the viewer's distance to the television. If the viewer is close enough to the television and the television is on, the viewer may be engaged with the content on the television. This system is simple, non-intrusive, and can used to measure engagement with each television in a multi-television household.

Abstract: A variable power generation asset may be subject to ramp events, which are large variations in power generated by the variable power generation asset within a short period of time. A variable power generation forecast system may receive or generate benchmark power forecasts and generated power measurements. Ramp predictors are based on the benchmark power forecasts and the generated power measurements. The variable power generation forecast system utilizes a feedback error correction model that predicts forecast errors for the benchmark power forecasts at various look-ahead times. The variable power generation forecast system applies sets of decision trees to the ramp predictors and last known forecast errors of the benchmark power forecasts to obtain the predicted forecast errors. The variable power generation forecast systems uses the predicted forecast errors and the benchmark power forecasts to generate more accurate power forecasts at the various look-ahead times.

Abstract: An example method includes, at a weather forecast time, determining a lag between a target renewable energy site and a first nearby site for which respective power measurements are correlated, selecting a first forecast look-ahead time, determining if the first forecast look-ahead time is less than or equal to the lag, determining a series of lagged power measurements at a time of forecast which constitute a series of correlation-based forecasts for power generation at the target site based on the lag, generating a set of ramp predictors incorporating correlation-based forecasts from the first site and the first forecast look-ahead time, receiving power forecast errors, applying sets of decision trees to the predictors and the power forecast errors to obtain predicted forecast errors, and generating second power forecasts for the set of look-ahead times of the target site based on the first power forecasts and the predicted forecast errors.

Abstract: Aggregation of noisy datasets into a master firmographic database. In an embodiment, firmographic records are received from a plurality of sources, and normalized into a common schema. One or more firmographic records may be cleaned by replacing a value of one or more fields in those firmographic record(s) with a value of those field(s) in another firmographic record. The firmographic records may then be clustered, and each of the clusters may be collapsed into a single conflated firmographic record based on a voting process. A master identifier may be generated for each conflated firmographic record, and the conflated firmographic records may be merged into a master firmographic database that is indexed by master identifiers.

Abstract: Systems and methods for rate limiting API service requests at an API service platform. An example method includes receiving a plurality of client service requests, determining when a safe operating threshold has been exceeded by the received requests to create a system overage or debt. In the case where it is determined that the safe operating threshold has been exceeded, determining the degree to which the safe operating limit has been exceeded, and rate limiting one or more clients transmitting service requests, identified as having the highest service request rates to eliminate the overage or debt.

Abstract: A method for generating electric substation load transfer control parameters includes adjusting elements in a fundamental scale matrix according to a condition change of a power grid, wherein the fundamental scale matrix is constructed based on the topology structure of the power grid, and the elements in the fundamental scale matrix represent switch information and risk values of paths between nodes of the power grid, wherein the switch information represents number of switching times required for connecting two nodes of the power grid; and performing operations on the adjusted fundamental scale matrix to generate switch information and risk values of paths for electric substation load transfer control, as electric substation load transfer control parameters.

Abstract: An example method comprises receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.

Abstract: Systems and methods for efficiently serving blockchain requests using an optimized cache are disclosed herein. An example method normalizing a request for blockchain data into a key, the request including a hash of a canonical head block of the blockchain data, searching a distributed key value store using the key, the distributed key value store comprising key value pairs, each of the key value pairs being associated with responsive blockchain data, determining when one of the key value pairs match the key, placing a pending job space for a job in the distributed key value store when one of the key value pairs is not found, and storing a new key value pair in the distributed key value store when a response for the request is obtained, the response being new responsive blockchain data.

Abstract: Various embodiments manage energy generation in a power generation and distribution system. In one embodiment, a set of residual load data is obtained for a given period of time measured at one or more nodes within a power generation and distribution system. The set of residual load data encodes a set of power flow signals. The set of residual load data is analyzed. An amount of power contributed to the set of residual load data by at least one energy generator class is determined based on the analysis of the set of residual load data.

Abstract: An example method comprises receiving first historical data of a first time period and failure data, identifying at least some sensor data that was or potentially was generated during a first failure, removing the at least some sensor data to create filtered historical data, training a classification model using the filtered historical data, the classification model indicating at least one first classified state at a second period of time prior to the first failure indicated by the failure data, applying the classification model to second sensor data to identify a first potential failure state based on the at least one first classified state, the second sensor data being from a subsequent time period, generating an alert if the first potential failure state is identified based on at least a first subset of sensor signals generated during the subsequent time period, and providing the alert.

Abstract: An example method comprises receiving first historical meso-scale numerical weather predictions (NWP) and power flow information for a geographic distribution area, correcting for overfitting of the historical NWP predictions, reducing parameters in the first historical NWP predictions, training first power flow models using the first reduced, corrected historical NWP predictions and the historical power flow information for all or parts of the first geographic distribution area, receiving current NWP predictions for the first geographic distribution area, applying any number of first power flow models to the current NWP predictions to generate any number of power flow predictions, comparing one or more of the any number of power flow predictions to one or more first thresholds to determine significance of reverse power flows, and generating a first report including at least one prediction of the reverse power flow and identifying the first geographic distribution area.

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: A system and method of managing a network with assets are described. The method includes generating a directed graph with each of the assets represented as a node, determining individual failure probability of each node, computing downstream failure probability of each node according to an arrangement of the nodes in the directed graph, computing upstream failure probability of each node according to the arrangement of the nodes in directed graph, and computing network failure probability for each node based on the corresponding individual failure probability, the downstream failure probability, and the upstream failure probability. Managing the network is based on the network failure probability of the assets.

Abstract: A method may comprise storing a first service provider record associated with a first project located at a first geographic location, receiving a request for project identifiers located within a section of a geographic area, providing a subset of the first set of the one or more project identifiers to be displayed on a second map the first user device, receiving a selected project of the project identifiers, providing a project page indicating categorical identifiers associated with the first project indicating at least some work performed, a link to at least one service professional's profile page, an opinion review and an insight review, receiving a selection of the link to the at least one service professional's profile page, and providing, a profile page of the at least one service professional, the profile page including contact information of the at least one service professional.

Abstract: A method may comprise storing a first service provider record associated with a first project located at a first geographic location, receiving a request for project identifiers located within a section of a geographic area, providing a subset of the first set of the one or more project identifiers to be displayed on a second map the first user device, receiving a selected project of the project identifiers, providing a project page indicating categorical identifiers associated with the first project indicating at least some work performed, a link to at least one service professional's profile page, an opinion review and an insight review, receiving a selection of the link to the at least one service professional's profile page, and providing, a profile page of the at least one service professional, the profile page including contact information of the at least one service professional.

Abstract: An example method comprises receiving first historical data of a first time period and failure data, identifying at least some sensor data that was or potentially was generated during a first failure, removing the at least some sensor data to create filtered historical data, training a classification model using the filtered historical data, the classification model indicating at least one first classified state at a second period of time prior to the first failure indicated by the failure data, applying the classification model to second sensor data to identify a first potential failure state based on the at least one first classified state, the second sensor data being from a subsequent time period, generating an alert if the first potential failure state is identified based on at least a first subset of sensor signals generated during the subsequent time period, and providing the alert.