A decentralized charging network of mobile power transmitters comprises a server, power receivers, and a fleet of deployable mobile power transmitters comprising a control system, a power source system having a charge measuring device for monitoring the charge transfer, a charging system configured to transfer charge from the power source system to the power receiver, and a communication system for communication between a power receiver, a server, and the control system. A charging request is received and processed by a server from a power receiver or an operator preparing to charge a power receiver. A qualified mobile power transmitter is identified and instructed to arrive at a location and to charge a power receiver according to charging instructions prepared by the server. The charging is monitored and, upon completion, the mobile power transmitter deactivates the charging session and informs the server.

A method for estimating load by energy meter including a load estimation model based on a neural network includes steps of: (a) the energy meter generating sampled supply electric power information by sampling information on electric power based on a predetermined sampling rate; (b) the energy meter instructing the load estimation model to output load information; and (c) the energy meter (i) transmitting the load information and information on an amount of the electric energy to a data management server and (ii) instructing the data management server to monitor the information on the amount of the electric energy, information on each sub-electric power for each of the loads, and information on each sub-amount of the electric energy for each of the loads.

A method and device for estimating spatial distribution of power system inertia based on multi-innovation identification. The method includes: (S1) acquiring time-series data including each node frequency of a power system and a transmission power of a transmission line; decomposing a frequency signal in a series of different spaces to identify a disturbance occurring moment; (S2) analyzing a relationship among node inertia, node frequency and node injection power; constructing an OEMA model to describe an active power-frequency dynamic process of the node after the disturbance occurs; analyzing a coupling relationship between an unknown parameter of the model and the node inertia; (S3) solving the OEMA model based on multi-innovation identification to identity the unknown parameter; and (S4) according to the relationship between a vector of the parameter and the node inertia, calculating each node inertia to estimate the spatial distribution of the power system inertia.

A method for monitoring energy-related data in an electrical system includes processing energy-related data from or derived from energy-related signals captured by at least one intelligent electronic device in the electrical system to identify at least one variation/change in the energy-related signals. The method also includes determining if the at least one identified variation/change meets a prescribed threshold or thresholds, and in response to the at least one identified variation/change meeting the prescribed threshold or thresholds, characterizing and/or quantifying the at least one identified variation/change. Information related to the characterized and/or quantified at least one identified variation/change is appended to time-series information associated with the energy-related data, and characteristics and/or quantities associated with the time-series information are evaluated to identify at least one potential load type associated with the characterized and/or quantified at least one identified variation/change.

According to embodiments of the present invention, techniques are provided for producing energy from one or more energy production sources. Energy consumption and energy production sources for an entity in a geographic location are analyzed. Sensor data based on the analysis of the entity is collected, wherein the sensor data includes crowdsourced sensor data. A model is generated based on the collected sensor data and the analysis of the entity, wherein the model includes optimization criteria for energy production. The model is utilized to determine an energy production source and energy production for the entity. Occurrence of a triggering event is detected, and the energy production source is adjusted based on the detected triggering event. The model is updated based on newly collected sensor data.

A device and method are provided for monitoring quality and performance parameters of an electricity distribution component in an electricity distribution network and detecting any deviation of operating parameters from the specified regulatory set and enforced limits. The critical and increasing problem is mitigated for the myriad of private domestic and commercial DEG devices being installed and connected to the distribution networks which were not initially designed for, or even not anticipated with, the recent DEG evolution, and the increasing complex electrical components with changing loads and power factors across the distribution network.

A power plug for coupling an electrical appliance to an electrical power supply, comprising: a current sensor, configured to measure current supplied through the plug to the electrical appliance; a voltage sensor, configured to measure voltage supplied through the plug to the electrical appliance; a processor configured to determine power consumption data from data relating to the current and voltage measurements made by the current and voltage sensors and monitor the performance of the electrical appliance using the power consumption data; and a transmitter, configured to transmit information relating to the performance of the electrical appliance.

The invention relates to a system to identify an electrical device connected to an electrical outlet. The electrical outlet has a sensor configured to measure an electrical signal of an electricity supply to the electrical device connected to the electrical outlet. A processor is configured to receive the measured electrical signal and determine an electrical signature of the electrical device based on one or more features of a frequency domain spectrum of the electrical signal. A processor is configured to compare the electrical signature against a signature database to identify the electrical device.

A smart plug designed to electrically connect a household appliance to power lines. The smart plug has an electronic controller configured to measure current and voltage of the electric power supplied to household appliance via a smart plug, determine electric quantities indicative at least of prefixed current harmonics and/or prefixed voltage harmonics, based on said measured current and voltage, determine load information which are indicative of electric loads of the household appliance being activated during an operating cycle performed by household appliance, based on determined electric quantities; determine the operating cycle performed by the household appliance based on the load information, communicate determined operating cycle to a network system.

A system and method for combining a remote audio source with an animatronically controlled puppet includes the steps of entering an audio file on a user client by a person where the audio file is a statement spoken by the person. The audio file is sent to a secondary client that is remote to the user client. The secondary client has a puppet controlled by animatronics. The audio file is received by an audio circuit board that converts the audio file into movement parameters. The movement parameters are sent to at least one servomechanism mounted in the puppet to actuate the animatronics in synchronicity with the audio file. Movement of the puppet is video recorded to define a video file. The audio and video files are combined to define a final video production viewable by the person.