Inventus Holdings, LLC

In some embodiments, apparatuses and methods are provided herein useful for use in forecasting electrical load needed for a region including a computer and a trained machine learning model. The computer including a control circuit. In some embodiments, the trained machine learning model is configured to: receive forecast environmental data corresponding to the region; determine a day-ahead forecast electrical load needed for the irrigation (such as agricultural irrigation) in the region; transmit a communication configured to cause the day-ahead forecast electrical load needed to be displayed to a user; determine a difference between the day-ahead forecast electrical load needed and an actual electrical load used for the irrigation in the region on a forecast day; obtain actual environmental data corresponding to the region for the forecast day; and apply the difference and the actual environmental data to the random forest algorithm to adjust the trained machine learning model.

A method and system for new property acquisition process for utilities. The process uses preprogrammed virtual reality headsets to provide property owners with a virtual reality (VR) social platform, such as a metaverse-enabled presentation, showing projects, answering questions, and delivering individualized property rights acquisition proposals. The invention enhances the property owner's presentation and enables significant scaling without significant headcount growth.

A tower has an above ground portion and an embedded portion joined to the above ground portion. The above ground portion and the embedded portion have a respective plurality of modular sections where each respective modular section in each of the respective plurality of modular sections has a respective vertical height and a quadrilateral plan view cross section with equal plan view outer dimensions over the respective vertical height of the modular section. At least one lower modular section in the above ground portion comprises a stronger structure than a modular section that is above the at least one lower modular section. Each modular section in each of the respective plurality of modular sections has corner struts that are parallel to one another and modular sections in each of the respective plurality of modular sections are arranged in a linear sequence.

A yaw-bearing grease tray for a wind turbine. The yaw-bearing grease tray includes an arcuate flat band portion with an inner arcuate sidewall, an outer arcuate sidewall, a first end wall and a second end wall which are perpendicular and disposed on the arcuate flat band portion. The yaw-bearing grease tray includes a ledge formed on the first end wall to be substantially parallel to the arcuate flat band portion and a step formed at the second end wall to be substantially parallel to the arcuate flat band portion. A plurality of magnets are disposed on the arcuate flat band portion to magnetically couple with yaw-bearing bolts and yaw-bearing nuts. In one example, the yaw-bearing grease tray is translucent. In another example, a field replaceable absorbent material is sized to fit within the arcuate flat band portion.

A machine-readable medium stores instructions that, when executed by a processor, cause the processor to execute operations. The operations include receiving information identifying a database table and preprocessing the table. The preprocessing includes extracting primary and foreign key relationships and generating sample data by combining frequency-based sampling of common values with random sampling. The operations also include generating, using an LLM, a unified metadata schema. The generating includes processing the table and the sample data using domain-specific prompts and outputting the unified metadata schema. The operations include embedding and indexing the unified metadata schema and converting a natural language question output from an end-user device into a SQL query. The converting includes identifying relevant metadata in the unified metadata schema matching query intent and generating the SQL query using the filtered metadata. The operations also include executing the SQL query and providing query results to the end-user device.

Systems and methods for controlling a multiple generating resource site. A controller receives from a check meter measured characteristics of power flowing through a power interconnect point. The controller receives measured power characteristics for each generating resource exchanging power through the power interconnect point. Based on the characteristics of power flowing through the power interconnect point and measured power characteristics for each generating resource, the controller determines: loss values for each transmission link system connecting each power generating resource to the check meter, and an apportionment of losses among those transmission link systems. Based on control data defining characteristics of power to be exchanged through the power interconnect point, power adjustments for the generating resources are determined based on the apportionment of losses. One or more of the generating resources are commanded to produce power based on the power adjustments.

A method for re-indexing a wind turbine bearing coupled to a blade and having damaged teeth driven by a motor includes installing temporary support structures between the turbine bearing and the blade to decouple a portion of the turbine bearing having the damaged teeth from the blade. The turbine bearing is re-indexed and the temporary support structures removed. The re-indexed turbine bearing is recoupled to the blade.

Employing artificial intelligence to generate regulatory reports is discussed. One example is a machine-readable medium having machine executable instructions for a regulatory reporting system that causes a processor core to execute operations. The operations include assigning a set of labels to an event log of a set of event logs based on applying a pattern matching algorithm to the event log. The event log characterizes a portion of an event associated with a nuclear power plant. The operations also include employing a natural language processor (NLP)-based classifier of a set of NLP-based classifiers to determine whether the event is reportable. The NLP-based classifier determines whether the event is reportable based on analyzing the set of labels. Additionally, the operations include generating a regulatory report based on the set of event logs. In response to a determination that the event log is reportable, the regulatory report indicates the event.

In several aspects, an image of a roof, an elevational image of the roof, and a mask image of the roof are accessed. Next, the mask image is applied to the elevational image of the roof to create a set of coordinate points that denote the portion of the roof. Using a machine learning model, a set of roof segment contours is created for each roof segment in the set of coordinate points that denote the portion of the roof. An iterative loop is performed, in which each roof segment contour in the set of roof segment contours on the roof ridges and the non-roof edges identified. A polygon shape is matched and associated with each roof segment, based on the roof ridges and the non-roof edges identified. Using a GUI, each polygon shape is automatically overlaid on the respective associated roof segment in the image of the roof.

One example relates to an image classification system that includes a memory for storing machine-readable instructions and a processor core for accessing the machine-readable instructions and executing the machine-readable instructions as operations. The operations include accessing a set of images. An image of the set of images includes image timing information. The operations also include accessing a set of user-selected labels. A label of the set of user-selected labels includes label timing information. The operations additionally include determining a time relationship between the set of images and the set of user-selected labels. The operations further include associating the label with the image based on the image timing information, the label timing information, and the time relationship. Additionally, the operations include outputting an indication of the association of the label with the image.