The present disclosure provides a new and improved method and apparatus of scheduling for a charging infrastructure serving a plurality of electric vehicles. A computer-implemented method for scheduling a charging infrastructure serving a plurality of electric vehicles is provided, in which a prediction for a usage pattern of the charging infrastructure is made with a context based on historical usage patterns of the charging infrastructure and the contexts of the historical usage patterns, and a schedule scheme for deciding a distribution of charging spots of the charging infrastructure among the electric vehicles is determined based on the predicted usage pattern.

Systems and methods to test an electric power delivery system include a communication subsystem to transmit test signals to one or more merging units, a test subsystem to transmit a test data stream to the one or more merging units via the communication subsystem, and a processor subsystem to receive looped back data from the one or more merging unit in response to the transmitted test data stream and to determine an operating condition based on the looped back data.

A system and method for optimizing power grid operations and enhancing the life of switching components therein is provided. Current meteorological information of a region of operation of the power grid is collected during operation thereof, along with historical meteorological data of the region. A plurality of prediction models are executed using the current meteorological information and/or the historical meteorological data and a meteorological parameter of the region is forecast by selectively combining outputs of at least some of the executed prediction models, the meteorological parameter being a parameter that causes a renewable energy source in the power grid to generate power. The forecasted meteorological parameter is compensated with physical models and the historical meteorological data, and optimal switching operations of switching components in the power grid are computed based on the compensated forecasted meteorological parameter, with the switching components being controlled based on the computed optimal switching operations.

The present disclosure provides systems and methods for flexible renewable energy power generation. The present disclosure also provides systems and methods for firming power generation from multiple renewable energy sources.

Apparatus and methods for recovering energy in a petroleum, petrochemical, or chemical plant as described. The invention relates to a recovered electric power measuring system comprising at least one processor; at least one memory storing computer-executable instructions; and at least one receiver configured to receive data from a sensor on an electrical powerline connected to a generator of a power-recovery turbine, the power-recovery turbine located in a petroleum, petrochemical, or chemical process zone wherein a portion of a first process stream flows through the power-recovery turbine and generates recovered electric power as direct current, the power-recovery turbine electrically connected to a single DC to AC inverter and the output of the DC to AC inverter electrically connected to a first substation.

A system may include a transformer that may convert a first voltage to a second voltage, such that the second voltage is output via a conductor. The system may also include a wireless current sensor that may detect current data associated with current conducting via the conductor and a processor. The processor may receive the current data, determine one or more temperature measurements associated with the transformer based on the current data, and send a signal to a component in response to the one or more temperature measurements exceeding one or more respective threshold values.

A system for monitoring and analyzing electrical operating parameters of a load (10) in a electric network (20), said system comprising a smart socket (110) arranged to be placed in series between the load (10) and the electric network (20), said smart socket (110) comprising a voltage detection module arranged to measure a voltage value in the electric network (20), as an electric potential difference between the ends of the load (10), a current detection module in the electric network (20) arranged to measure a current value adsorbed by the load (10), when the load (10) is connected to the electric network (20), a control unit connected to the voltage detection module and to the current detection module. In particular, the control unit is arranged to carry out a periodic acquisition of the voltage value in said electric network (20), obtaining a voltage trend over time and a periodic acquisition of the current value adsorbed by the load (10), obtaining a current trend over time. In particular, the control unit comprises a neural network arranged to carry out a training comprising the steps of definition of a number n of events E.sub.i′ association, to each event E.sub.i′ of a number m.sub.i of patterns p.sub.ij of predetermined current and/or voltage trends, extrapolation of characteristic parameters c.sub.ik distinguishing the pattern p.sub.ij associated with the classified event E.sub.i′. The neural network is then arranged to carry out an analysis of the acquired voltage and/or current trend by the definition and the classification of possible anomalous patterns with respect to predetermined voltage and/or current trends.

A system includes an electrical apparatus configured to monitor or control one or more aspects of an electrical power distribution network; and a control system including more than one electronic processor, where the electronic processors are configured to cause the control system to interact with the electrical apparatus, an interaction between the control system and the electrical apparatus including one or more of the control system providing information to the electrical apparatus and the control system receiving information from the electrical apparatus, and if some of the electronic processors are unable to cause the control system to interact with the electrical apparatus, at least one of the other electronic processors is able to cause the control system to interact with the apparatus.

A load control device may be used to control and deliver power to an electrical load. The load control device may comprise a control circuit for controlling the power delivered to the electrical load. The load control device may comprise multiple actuators, where each of the actuators is connected between a terminal of the control circuit and a current regulating device. The number of the actuators may be greater than the number of the terminals. The control circuit may measure signals at the terminals and determine a state configuration for the actuators based on the measured signals. The control circuit may compare the state configuration to a predetermined dataset to detect a ghosting condition.

A device, a method and a system for monitoring an electrical connection status of a disconnector device are disclosed. The disconnector device is connectable to pole-mounted equipment in a power distribution or transmission grid, thereby disconnecting the pole-mounted equipment. The connection status monitoring device includes a determining section configured to determine whether the disconnector device has been activated and to generate connection status indicator data, indicative of whether the disconnector device has been activated. The determining section further includes a wireless communication section which is adapted to connect to a wireless communication infrastructure using a wireless communication protocol, and to transmit the connection status indicator data over the wireless communication infrastructure.