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.

An example energy storage system and a related method are disclosed. In the energy storage system, a controller obtains information about user equipment, and then controls a converter and a battery group based on the information about the user equipment, to supply electric energy to an electric device or receive electric energy from a power sourcing device. In this way, the energy storage system can provide reasonable power scheduling, thereby improving utilization of the energy storage system.

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 method for designing a distributed communication topology of a micro-grid based on network mirroring and global propagation rates includes the following steps: first, determining the communication connectivity of distributed directed networks in the micro-grid; next, obtaining, for connected directed communication networks, mirror networks thereof based on a mirroring operation, and selecting an optimal distributed directed communication topology corresponding to a maximum performance indicator based on algebraic connectivity and communication costs; solving, for the optimized distributed communication topology, pinned distributed generation sets corresponding to different pinning numbers based on global propagation rates and out-degrees; and finally, establishing a distributed secondary voltage control of the micro-grid based on the optimal distributed communication network and pinned nodes of the micro-grid, to achieve accurate reactive power sharing and average voltage restoration.

A system provides a “virtual room” for remotely sharing content experiences via electronic devices at different locations. The system may enable synchronization of the content at the different locations, access control, be able to provide and/or experience interaction feedback regarding the content, control the interaction feedback that is provided and/or experienced, enhance the ability of people to distinguish the content from the interaction feedback, and so on. As such, people may be able to share content experiences more like they were present in a single location while remote from each other.

An electrical power distribution system configured to automatically regulate one or more Voltage/VAR control devices for optimization of one or more user defined metrics in an alternating current (AC) electrical power distribution system that includes one or more power distribution lines configured to transmit AC electrical power between a substation and a plurality of loads, each power distribution line including one or more Voltage/VAR control devices configured to regulate voltage and reactive power of the AC electrical power on the power distribution line according to an operational setting for each of the one or more Voltage/VAR control devices and one or more sensors configured to sense a sensed quality of the AC electrical power on the one or more power distribution lines with at least one communication network communicating with the one or more Voltage/VAR control devices and the one or more sensors.

A computer-implemented method and system is provided. The system adaptively switches prediction strategies to optimize time-variant energy demand and consumption of built environments associated with renewable energy sources. The system analyzes a first, second, third, fourth and a fifth set of statistical data. The system derives of a set of prediction strategies for controlled and directional execution of analysis and evaluation of a set of predictions for optimum usage and operation of the plurality of energy consuming devices. The system monitors a set of factors corresponding to the set of prediction strategies and switches a prediction strategy from the set of derived prediction strategies. The system predicts a set of predictions for identification of a potential future time-variant energy demand and consumption and predicts a set of predictions. The system manipulates an operational state of the plurality of energy consuming devices and the plurality of energy storage and supply means.

A server performs a process including: when the server receives a second DR execution instruction, the step of obtaining a vehicle list; the step of turning off a determination flag of each candidate vehicle; the step of obtaining a number of times of turning on and off a relay at a time of DR for one of candidate vehicles each showing a determination flag in an OFF state; when the number of times of turning on and off the relay is greater than a threshold value, the step of turning on an exclusion flag; the step of performing a notification process; when a determining process ends, the step of performing a process of allocating a DR amount; and the step of transmitting a DR signal.

A battery-powered node includes a primary cell, a secondary cell, and a battery controller. The battery controller includes a current source that draws power from the primary cell to charge the secondary cell. The battery-powered node draws power from the secondary cell across a wide range of current levels. When the voltage of the secondary cell drops beneath a minimum voltage level, the current source charges the secondary cell at a constant current level and a charging signal is sent to the battery-powered node. When the voltage of the second cell exceeds a maximum voltage level, the current source stops charging the secondary cell and the charging signal is terminated. The battery-powered node records the amount of time the charging signal is active, which can be used to determine a battery depletion level for the primary cell. Battery replacement may then be efficiently scheduled based on the depletion level.