61 results about "Utility industry" patented technology

Carbon emission reduction using machine learning is provided. A system receives data for profiles linked with locations of an entity. The system determines, based at least in part on data from a utility service provider system and the data indicative of energy consumption associated with the locations, a first value of a metric indicative of carbon emissions associated with the locations. The system determines, based on a comparison of the first value of the metric with a threshold, to invoke an automated process via the payroll processing system to reduce the metric. The system generates, generate, using one or more models trained with machine learning, an action to execute via the automated process. The system selects a first profile from that is compatible with the action, and commands the payroll processing system to execute the generated action to cause a reduction in the first value of the metric.

A building energy system includes equipment configured to consume, store, or discharge one or more energy resources purchased from a utility supplier. At least one of the energy resources is subject to a demand charge. The system further includes a controller configured to determine an optimal allocation of the energy resources across the equipment over a demand charge period. The controller includes a stochastic optimizer configured to obtain representative loads and rates for the building or campus for each of a plurality of scenarios, generate a first objective function comprising a cost of purchasing the energy resources over a portion of the demand charge period, and perform a first optimization to determine a peak demand target for the optimal allocation of the energy resources. The peak demand target minimizes a risk attribute of the first objective function over the plurality of the scenarios.

Examples described herein provide a system for controlling power flow in an energy distribution network. The system includes a plurality of inverters, each having an inverter controller associated therewith. The system further includes a utility controller associated with a utility and configured to communicate with at least a subset of the plurality of inverters. The system further includes a customer controller associated with a customer of the utility and configured to communicate with at least the utility controller. The system further includes a direct current (DC) breaker associated with a battery of the customer. The system further includes a DC meter of the customer, the DC meter and the DC breaker each configured to communicate with the utility controller and the customer controller. The utility controller is configured to determine a current operational scenario of the energy distribution network and to control power routing within the energy distribution network.

Approaches for managing utility bills and optimizing utility consumption in industrial environments are described. A utility bill resolution system automates extraction, parsing, analysis, and resolution of utility bills from utility providers. The system detects anomalies within bills using machine learning models and verifies bill authenticity using real-time consumption data. A utility consumption optimization system analyzes historical consumption data and utility rate information to generate optimized operation schedules for utility-intensive equipment and processes. The optimization system considers time-of-day pricing structures and implements peak shaving strategies to reduce costs. Both systems leverage advanced technologies including optical character recognition, natural language processing, and Internet of Things (IoT) devices to enhance accuracy and efficiency. The integrated approach enables industrial consumers to ensure billing accuracy, proactively optimize utility consumption patterns, and achieve significant cost savings while improving operational efficiency across multiple utility consumption sites.

According to an embodiment, disclosed is a system comprising an energy management module, electrically coupled to a utility meter, energy consuming devices and energy producing devices, comprising, a communication module configured to receive input energy data from utility meter, and energy information of energy consuming devices and energy producing devices; a processor storing instructions in a non-transitory memory that, when executed, cause the processor to: determine energy consumption data of the devices; identify a first device based on a first set of predefined priority values which requires energy; identify a second device based on a second set of predefined priority values which has excess energy; establish a connection and control energy transfer from the second device to the first device based on the energy consumption data and the input energy data to enable smart scheduling and power optimization among the energy consuming devices and the energy producing devices.

A system for processing utility bills having distinct formats is provided. The system comprises at least one processor. The processor obtains a plurality of utility bills comprising at least two utility bills of distinct formats and generates bill data based on the plurality of utility bills. The bill data includes a plurality of fields and corresponding field values for each bill. The processor classifies the field values into a set of predetermined uniform categories based on a field-category mapping to obtain uniform classified data. The processor computes one or more utility metrics for each utility bill. The processor generates utility reports for the utility bills based on the uniform classified data and the utility metrics, where each is of a predefined standard template and includes the utility metrics and uniform classified data. The processor provides the utility reports in the predefined standard template for display on a user interface.

The disclosure includes methods, systems and apparatus for predictive management of efficient selecting and receiving of retail electric utility service to a facility for a period, by automated selecting of a retail utility service provider corresponding to a selected least cost path of predicted rate plan choices across the period, wherein costs of all possible, viable time-bounded predicted rate plan choices are determined for predicted consumer usage where a predicted market of retail rate formulas for the period are predicted in relation to at least one variable, such as weather.

To provide a method and system for improving the reliability of a utility system asset.SOLUTION: The method includes receiving a time series signal collected from a sensor in a utility system asset, using an inference model to generate an estimated value of the time series signal, performing a pairwise difference operation between the actual value and the estimated value of the time series signal to generate a residual, and performing a sequential probability ratio test (SPRT) on the residuals to generate an SPRT alarm, applying an irrelevance filter that removes SPRT alarm for a signal that does not correlate with previous failures of similar utility system assets to the SPRT alarm to generate a filtered SPRT alarm, using a logistic regression model to calculate an RUL-based risk indicator for the utility system asset on the basis of the filtered SPRT alarm, and generating a notification indicating that the utility system asset needs to be replaced when the risk indicator exceeds a threshold value.SELECTED DRAWING: Figure 2

The present disclosure provides a method for predicting coincident peak events in electricity demand. The method includes receiving historical electrical usage data and forecasted demand data for a given timeframe, training a simulation engine based on the historical data, generating a plurality of load scenarios for a target period of time using the trained simulation engine, and computing a probability that the target period of time will include a new record high peak in electricity demand based on the generated scenarios. The method enables accurate prediction of peak demand events without relying on weather or economic data, allowing utilities and consumers to better manage electricity usage and reduce costs associated with peak demand periods.

A gas line size gauge device is provided. The device is designed to assist first responders, utility workers, and contractors in accurately identifying natural gas pipe sizes during field operations. The device comprises multiple pipe sections corresponding to common industry-standard diameters. A connecting member secures the sections while allowing individual sections to be rotated upwards or downwards for direct size comparison. Each section includes permanent markings, which may be embossed, laser-etched, or phosphorescent for enhanced visibility. Color differentiation between the sections may further aid in quick identification. The device also features attachment points for securing to tool belts or emergency kits. A method of using the device involves extending individual sections to compare with a gas pipe, repeating the process until a match is found, and referencing the corresponding marking for verification.

A method may include receiving production data and facility data associated with an enterprise, such that the production data includes operational tasks performed in a hydrocarbon production system, and the facility data includes one or more utility operations within one or more buildings associated with the enterprise. The method may also include receiving sustainability parameter data associated with one or more operations corresponding to the enterprise based on the production data and the facility data, generating a sustainability report representative of sustainability parameters associated with the operations of the enterprise based on the sustainability parameter data, and sending the sustainability report to one or more engineering workflow systems to determine action plans associated with improving the sustainability parameters. After receiving the action plans, the method includes sending commands to cause devices to adjust their respective operations.

Distributed energy resources may be outside the control of a utility. While these distributed energy resources may be managed by distributed energy resource (DER) management systems, the DER management systems do not have knowledge of the overall power network to which the distributed energy resources are connected and do not have the same objective as the utility. Consequently, operation of the distributed energy resources by the DER management systems may result in network violations. Accordingly, disclosed embodiments integrate knowledge from the management system of the utility into the DER management systems using probabilistic optimal power flow to generate operating ranges that may be used in the DER dispatch of each DER management system. These operating ranges may be used to constrain the DER dispatch, to thereby ensure secure and safe operation of the overall power network, while requiring little to no modifications in the DER management systems.

Systems and methods are provided for allocating and providing power to electric loads based on load classification information. A power system, such as a local electrical utility, may receive load demand requests from customers or loads wanting to consume power, and the system may allocate power to the loads based on load classifications of each of the loads. The system may then communicate the power allocations to the loads, and the loads may then consume power based on the power allocated to each of the loads. These improvements may be used to, for example, reduce the likelihood or frequency of demand response events in which power demand exceeds supply since the system may limit the total amount of power that is allocated at any given time.

A meter collar configured to connect to a utility meter is provided herein and comprises a controller configured to dynamically (automatically) determine how much energy a home can import to or export from a grid based on at least one of data obtained from a transformer of the grid, a temperature of the meter collar, a utility meter limit, or from another utility data network.

An externally-controllable electrical power generating system for providing auxiliary or backup power to a load bus or device. The system may be used indoors, and generally includes a power source comprising a first DC output, an electrical storage unit comprising a DC input coupled to the first DC output of the power source, the electrical storage unit further comprising a second DC output. An inverter coupled to the second DC output receives power, the inverter having a first AC output that can be synchronized with an AC load bus or AC grid. The system includes a contactor connected between the first AC output and an AC load bus, and is controllable with an external controller operated by a utility or a managing entity, such that the external controller can enable the controller to connect or disconnect the contactor.

A cabinet lock for securing a door panel to a cabinet housing comprising a latching component, an electromechanical component, and a communications module. The latching component has a latch housing and latch member reciprocally translatable between locked and unlocked orientations to selectively secure the door panel to the cabinet housing. The electromechanical component includes an actuator operably coupled to a drive member that is coupled to the latch member whereby powering of the actuator translates the latch member to at least one of the unlocked or locked orientations. The communications module is configured for communication with a remote device of a municipal traffic control agency and / or a utilities worker. The communications module is configured to receive a control signal from the remote device for moving the latch member to the at least one of the unlocked orientation or the locked orientation.

Techniques for obtaining and processing utility consumption data (e.g., gas, water, electricity, etc.) of a utility network to determine if a violation has occurred with respect to a restriction schedule associated with a service site. By way of example, a number of utility restriction schedules associated with a number of service sites may be generated that indicate, for example, a type of restricted activity and / or event (e.g., irrigation), seasons and / or which days activity is allowed or not allowed, duration activity is allowed, and / or mitigation to take place if a violation is detected. A device (e.g., a smart utility meter, a router, etc.) may monitor utility consumption and detect a particular usage activity (e.g., irrigation) via data disaggregation. The device may compare the activity to the restriction schedule for that particular service site and perform automatic mitigation if a violation is detected.

The disclosure includes methods, systems and apparatus for predictive management of efficient selecting and receiving of retail electric utility service to a facility for a period, by automated selecting of a retail utility service provider corresponding to a selected least cost path of predicted rate plan choices across the period, wherein costs of all possible, viable time-bounded predicted rate plan choices are determined for predicted consumer usage where a predicted market of retail rate formulas for the period are predicted in relation to at least one variable, such as weather.

A flow meter is configured for use on a distribution line. These configurations incorporate a backup counter that can record data in absence of power. This counter may supplement a primary indexer that generates a value for corrected volume. In one implementation, the flow meter may include components to foreclose the need for the primary indexer. These components may include a processing unit and power source, for example, an energy harvester that can generate power from the localized area around the device. In this way, the flow meter can operate independent of any fixed power source to generate values for corrected volume, which utilities can use to bill customer for consumption of resources.

Backup electric power with a batter(ies) storing electrical energy (kilowatt hours—KWH) and a DC-to-AC inverter converting the stored electrical energy from the battery into electrical AC power (kilowatts—KW) may be provided for emergency power used when power from the electric utility fails. Condominium units and apartments in high rise buildings can benefit from having DC-to-AC inverter battery systems installed in each unit. Spare capacity power from existing emergency backup generators may be utilized to charge the battery of the inverter battery system of each condominium / apartment unit. The DC-to-AC inverter battery system may be used to reduce ampacity requirements of the electric utility power distribution system and electric service entrance equipment coupled to the utility electric meter per occupancy. Cold fusion-low energy nuclear reaction (LENR) power generation, may be used in place of or partial substitution of power from the electric utility.

Methods and systems are provided for assessing the effects of an adopted technology on power demands on an electrical grid. An estimate of a rate of deployment for the adopted technology in a target utility area is determined over a predetermined time period. An estimate of a total stock of the adopted technology in one or more dissemination areas is determined by geospatially disaggregating the estimated rate of deployment of the adopted technology across the one or more dissemination areas. The estimated total stock of the adopted technology is derived from a forecasted energy consumption profile for one or more subareas within the target utility area. The forecasted energy consumption profiles are integrated with current consumption profiles for display in a graphical user interface.

This disclosure relates generally to systems and methods for locating and mapping buried utility objects using Artificial Intelligence (AI). In an exemplary embodiment, electromagnetic data related to underground utilities and communication systems is collected and provided to a Deep Learning model to build a training set. New data is then collected and provided to the learning model to enable AI to make a prediction as to the type and location of any existing utilities. This predicted data may be used to create a map which may be stored and / or displayed. In some embodiments, the AI (Deep Learning model) processing may be performed locally in a Utility Locator and / or cable drum-reel, and / or remotely in a wireless device such as a mobile phone, laptop, vehicle, etc., and / or in the Cloud.

A system for automating matching of energy load with energy generation for energy consumers, utilities, and gird operators, comprising a processor and a memory containing instructions configuring the processor to collect, from a grid network connecting load centers and generation sources, energy datasets including energy attribute records and energy load data, match each load center to the generation sources based on the energy datasets, matching further comprises generating actionable energy models, each one of the actionable energy models representing a configurable allocation of the energy attribute records, based on the energy datasets, and matching the load centers and generation sources as a function of at least one actionable energy model, populate an allocation report for each load center, and transmit the allocation report to an external device in communication with the processor.

A method for obtaining measurement data from a meter includes measuring raw data at one or more measurement locations around a system using the meter, receiving a request for the measurement data, determining whether the measurement data can be derived from the raw data based on a known measurement function of the meter, and determining whether the measurement data can be derived from the raw data based on a known measurement function of the meter. And in response to determining that the requested measurement data can be derived from the raw data, generating the requested measurement data from the raw data. The method may be applicable to utility meters, such as smart utility meters, and in particular, but not exclusively, to electricity meters, gas meters, or water meters.

A building stud (2) comprising a web (4) and first and second flanges (6, 8) formed with and depending from said web (4); a member (18) formed in said web (4) by a continuous cut (10) made in said web (4) and located in an operable position in which the member (18) is not located in a plane (21) of the web (4); an aperture (24) formed in the web (4) resulting from the member (18) being located in said operable position; wherein at least one conduit or cable (38, 40, 42, 44) is adapted to be secured to said member (18) and extends through said aperture (24).

Systems and methods for interval energy disaggregation utilizing machine learning are provided. An example method includes obtaining and cleaning weather data and customer data, and based on the customer data, determining whether a structure utilizes solar energy. If the structure utilizes solar energy, the overall aggregate data is disaggregated by using and training a first machine learning model, to ultimately produce a predicted solar production. The predicted solar production is extracted from an overall aggregate data of the structure. Then, the method continues with disaggregating the non-solar aggregate data by utilizing at least a second ML model, to produce disaggregated data relating to at least one of AC energy consumption and EV (electric vehicle) consumption. The disaggregated data is provided to the customer or utility. The disaggregated data comprises at least one of the predicted solar production, the AC energy consumption, and the EV consumption of the structure.

The present disclosure provides a system and method for implementing a framework for Risk-Based Inspection (RBI) methodologies to address the need for efficient asset risk assessment and management in industries such as oil and gas, petrochemical, chemical, specialty chemical, power generation, utilities, pipeline, hi-tech industries, pharmaceutical, and manufacturing. The system analyses asset parameters, including specifications, historical data, and real-time performance metrics, to determine the probability of failure (PoF) and consequence of failure (CoF). Risk levels are calculated by combining PoF and CoF, allowing for the identification and prioritization of high-risk assets. In addition, real-time data updates refine risk assessments, enabling dynamic adjustments to inspection strategies. This framework generates optimized inspection recommendations and maintenance schedules, improving asset reliability, safety, and operational efficiency.

A computer system (which may include one or more computers) that modifies a plan for a power-system project is described. During operation, the computer system may access stored information that specifies the plan for the power-system project and second information specifying prior power-system projects that were successful. Then, the computer system may submit the plan and may receive feedback about the plan during an approval process associated with a utility commission and / or a municipal government. Moreover, based at least in part on the second information and the feedback, the computer system may automatically modify the plan for the power-system project, where the modified plan increases an estimated probability of success of the power-system project. Next, the computer system may provide third information specifying the modified plan for the power-system project.

The present disclosure provides an energy orchestration router arranged to be installed between a utility energy meter and a main breaker panel of a building. The router includes a communication interface arranged to communicatively couple the router to the utility energy meter, the main breaker panel, and one or more energy assets at the building. The router further includes a power stage arranged to orchestrate bidirectional energy conversion and distribution for the energy assets and at least one processor arranged to perform operations including receiving data from the utility energy meter, the main breaker panel, and the energy assets, generating orchestration policies for allocating energy flows between the energy assets, and executing the orchestration policies in real-time, causing the power stage to control electron flow between the utility energy meter and the energy assets to dynamically optimize operation based on the orchestration policies.

A system, method and apparatus is described for a dynamic mobile application that provides a real time collection, analysis and reporting information management platform for building and construction projects, emergency services and disaster management tasks. The mobile device application includes multiple modules interconnected including a finance module, an operations module, a utilities module and a safety module.