18 results about "Utility company" patented technology

The invention discloses a double-layer non-cooperative demand response method based on asynchronous multi-agent reinforcement learning, and the method comprises the steps: S1, constructing a double-layer non-cooperative game framework: constructing a double-layer dynamic game model between a public utility company and a consumer; s2, completing modeling of the partially observable Markov game, and converting the double-layer non-cooperative game into the partially observable Markov game; s3, designing an asynchronous multi-agent reinforcement learning algorithm as a game equilibrium solving engine; and S4, implementing centralized training and priority experience playback to realize asynchronous multi-agent reinforcement learning algorithm efficiency optimization. The method is suitable for a dynamic game scene between a public utility company and a consumer group in an intelligent power grid environment, and can realize efficient consumption and load fluctuation suppression of distributed energy in a power grid.

Techniques for smart electricity meter operation and management of open-switch events are described. In an example, a voltage value of a transformer-side of a service site is measured. Power consumption at the service site is measured. Based at least in part on the voltage value being non-zero and the power consumption being zero, it is determined that an open-switch event occurred. That is, because the utility company is supplying typical voltage to the electricity meter, and because the power consumption is zero, a breaker switch may have tripped. Accordingly, a customer of the service site is notified of the open-switch event.

Techniques are provided for managing discharging and recharging a battery. The techniques include (a) receiving, from a utility server, pricing information for provision of power by a utility over a lookahead period; (b) determining, with reference to the pricing information, a highest cost of the power over a subset of the lookahead period and a lowest cost of the power over the subset, the highest cost occurring during a first time slot of the subset; (c) in response to determining that a discharge condition is satisfied, assigning the first time slot as a discharge time slot, including: (1) determining that a battery of a power supply device has a state of charge (SoC) of at least a fullness threshold and (2) determining that a difference between the highest cost and the lowest cost exceeds a threshold value; and (d) during the discharge time slot, operating the power supply device to provide power to connected devices using power drawn from the battery.

The present invention relates to a machine capable of cleaning, storing and dispensing cups in a fully automatic manner, which enables practical, efficient and safe use of reusable cups. The machine optimizes the internal structure to compactly store dirty and clean cups, has high daily cleaning ability, and can serve a large number of people. The application of the machine aims to eliminate the use of disposable cups which can generate serious related environmental influences. To this end, the machine provides significantly better utility and hygiene compared to manual cleaning, making the machine suitable for use in offices, utility companies and other commercial institutions. An automatic glass cleaning machine (7) comprising: an inlet system (1) configured to receive and convey one or more cups at a time to an inlet reservoir (2); an inlet reservoir (2) configured to store a plurality of dirty cups; a cleaning system (3) configured to clean one or more cups at a time on a cleaning platform (31); a conveyor (4) configured to move one or more cups at a time; an outlet reservoir (5) configured to store a plurality of clean cups and to dispense the plurality of clean cups through one or more outlets (50).

The disclosure describes techniques for distributing large amounts of data to networked devices. A utility company server sends data to proxy device(s) (e.g., a plurality of data collecting / distributing devices), each of which sends the data to a number of proxied devices (e.g., smart utility meters). Accordingly, the utility company server utilizes a plurality of proxy devices to lessen device workload and network bandwidth consumption. The proxy devices each “manage” a plurality of proxied devices. Advantageously, the techniques provide end-to-end security of the data, avoid devotion of significant network bandwidth to repetitive transmissions, and in some installations reduce battery power consumption. The systems, devices, and techniques for distributing large amounts of data to networked devices may be configured to include: software defined on central office server(s); a plurality of proxy devices associated with each server; and a plurality of proxied devices (e.g., smart metering devices) associated with each proxy device.

The present invention provides a control method for an electric water heater considering demand-side response. First, based on the energy balance process, a hierarchical technique is used, and four main phenomena causing temperature changes inside the electric water heater are considered to construct an electric water heater model. Then, a Gaussian kernel smoother is used to preprocess the power profile, and K-means is used to classify the smoothed profiles of multiple clusters determined by the usage profile criterion. After that, a minimum cost objective function of the electric water heater is constructed. Immediately afterwards, an electric water heater demand response model is constructed based on the constructed electric water heater model, the data selected by the Gaussian kernel smoother, and the minimum objective function. Finally, MATLAB is used to solve the electric water heater demand response model. The present invention clusters users according to their power distribution, allowing part of the peak electricity consumption period to be transferred to the off-peak period, which can help users reduce electricity costs and help utility companies manage the electricity demand during peak periods.

A first energy converter that can consume a first physical energy form of a first energy delivery network can be controlled to produce a second physical energy form of a second energy delivery network and inject the second physical energy form into the second energy delivery network. A second energy converter that can consume the second physical energy form of the second energy delivery system can be controlled to produce the first physical energy form of the first energy delivery network and inject the first physical energy form into the first energy deliver network. The controlling of the first energy converter and the controlling of the second energy converter can be coordinated. Related apparatus, systems, techniques and articles are also described.

An artificial intelligence system including a machine learning module for assisting in electrical grid maintenance. The machine learning module receiving data sets from UAVs travelling in the proximity of power lines and communicating sensed observations to a data library for training the module to spot markers of potential hazards and calculating a probability of hazards occurring under various conditions. The system communicating hazards of a type or above a predetermined level of probability to a communication center or utility company to remediate or schedule preventative maintenance.

This application discloses a two-tier non-cooperative demand response method based on asynchronous multi-agent reinforcement learning, comprising: S1. Constructing a two-tier non-cooperative game framework, including: building a two-tier dynamic game model between utility companies and consumers; S2. Modeling a partially observable Markov game, transforming the two-tier non-cooperative game into a partially observable Markov game; S3. Designing an asynchronous multi-agent reinforcement learning algorithm as the engine for solving the game equilibrium; and S4. Implementing centralized training and prioritized experience replay to optimize the efficiency of the asynchronous multi-agent reinforcement learning algorithm. This application is applicable to dynamic game scenarios between utility companies and consumer groups in smart grid environments, enabling efficient consumption of distributed energy resources and load fluctuation suppression in the power grid.

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.

An electrical load management system for controlling first, second, and third electrical loads is provided. A load management computer determines a demand threshold indicating a threshold amount of demanded power from a utility company power grid. The computer determines whether a time interval has an associated non-peak energy charge. And if so, then the computer determines whether a first total load request from the first, second, and third electrical loads will exceed the demand threshold. And if so, then the computer determines whether a second total load request from the first and second electrical loads having high and medium load priorities, respectively, will exceed the demand threshold. And if not, then the computer commands the first and second electrical loads to be energized for the predetermined time interval.

An electricity meter and electricity system or grid that is hardened against attack vectors is described, and provided in part by automated multiple-factor authentication over multiple communication networks. In an example, a utility company may control an advanced metering infrastructure (AMI) network to provide internal communications. Metering devices may utilize customer's Wi-Fi to gain access to the internet, allowing electricity consumption data to be transmitted over the internet. Multiple authentication factors are used to prevent a bad actor from impersonating the metering device or cloud server. In an example, each metering device determines a secret, and sends the secret over the AMI network to a utility company server, and which relays the secret to the cloud server. The cloud server uses the secret to establish trust with metering devices. Additionally, the metering devices and the cloud server have signed certificates, which are used in additional authentication processes.

Techniques for smart electricity meter operation and management of open-switch events are described. In an example, a voltage value of a transformer-side of a service site is measured. Power consumption at the service site is measured. Based at least in part on the voltage value being non-zero and the power consumption being zero, it is determined that an open-switch event occurred. That is, because the utility company is supplying typical voltage to the electricity meter, and because the power consumption is zero, a breaker switch may have tripped. Accordingly, a customer of the service site is notified of the open-switch event.

The disclosure describes techniques for distributing large amounts of data to networked devices. A utility company server sends data to proxy device(s) (e.g., a plurality of data collecting / distributing devices), each of which sends the data to a number of proxied devices (e.g., smart utility meters). Accordingly, the utility company server utilizes a plurality of proxy devices to lessen device workload and network bandwidth consumption. The proxy devices each "manage" a plurality of proxied devices. Advantageously, the techniques provide end-to-end security of the data, avoid devotion of significant network bandwidth to repetitive transmissions, and in some installations reduce battery power consumption. The systems, devices, and techniques for distributing large amounts of data to networked devices may be configured to include: software defined on central office server(s); a plurality of proxy devices associated with each server; and a plurality of proxied devices (e.g., smart metering devices) associated with each proxy device.

A system for automating matching of energy load with energy generation for energy consumers, utilities, and grid 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.

Networked utility services handle data-flow in a system to operate electrical vehicle charging stations. In an example, first and second utility companies may operate in first and second respective areas. A user may have a residence in the first area and may have an electric vehicle at a vehicle charging station in the second area. The user may provide identification at the vehicle charging station in the second area, and the user's vehicle may be charged at that location using electricity from the second utility. Data including the user's identification and the electricity consumed in the charging may be sent to the first utility serving the area including the user's residence. The first utility may bill the user for the electricity used to charge the user's vehicle at the remote vehicle charging station. The charging station, both utilities and / or other parties may share in the receipts.

A method for using a remote server to schedule operating cycles of an appliance includes receiving a request to perform an operating cycle of the appliance at a preferred start time, obtaining an energy consumption capacity schedule from a utility company providing power to the appliance, determining a cycle start time of the operating cycle based at least in part on the energy consumption capacity schedule and the preferred start time, and transmitting a cycle authorization for initiating the operating cycle of the appliance at the cycle start time.