A battery pack includes a housing, a plurality of rechargeable battery cells, a connection interface, a near-field communication (NFC) reader, a battery management system, and a communication gateway. The connection interface is in communication includes a plurality of data pins, a positive terminal, and a negative terminal. The battery management system is in communication with the NFC reader and is configured to receive information from the NFC reader including an NFC tag identification, then retrieve stored parameters corresponding to the NFC tag identification, and configure at least one of the plurality of data pins based upon the stored parameters corresponding to the NFC tag identification.

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.

A method for estimating the state of health of an exchangeable rechargeable battery. The method includes: i. determining a remaining capacity of the battery during a charging operation, in such a manner, that a first charging value is ascertained by measuring an open-circuit voltage, as long as no charging current or only a minimal charging current is flowing; at least one further charging value is ascertained by measuring the charging current in specific time intervals, until the charging operation is completed; and a sum of the ascertained charging values is calculated; ii. determining a remaining performance of the battery during the charging operation in such a manner, that after a predefined battery voltage is reached, the charging current is briefly changed, and the respective battery voltage is measured; and an impedance of the battery is calculated from the quotient of the difference of the measured charging currents and battery voltages.

A power control device is contained within a housing and has an electric current sensor configured to measure current passing through an electric outlet during a time period, a proximity sensor configured to detect a distance of an object relative to the electric outlet during the time period, a relay switch that can open or close to stop or conduct current through a circuit in the electric outlet in response to a command, and a wireless network interface in communication with the electric current sensor and the proximity sensor, the wireless network interface configured to transmit and receive data from the current sensor and the proximity sensor, to transmit commands to the relay switch, transmit the data to a computing device, and receive commands from the computing device.

Aspects of the subject disclosure may include, for example, a transmission system having a coupling device, a bypass circuit, a memory and a processor. The coupling device can facilitate transmission or reception of electromagnetic waves that propagate along a surface of a transmission medium. The memory can store instructions, which when executed by the processor, causes the processor to perform operations including restarting a timer to prevent the bypass circuit from disabling the transmission or reception of electromagnetic waves by the coupling device. Other embodiments are disclosed.

A system for collaborative load balancing within a community of a plurality of energy nodes includes a central allocation server and a plurality of local agent servers. Each of the local agent servers is connected to a respective one of the energy nodes and has a processor configured to: receive input variables or parameters; predict, using the received input variables or parameters, a non-zero energy generation amount that power generation equipment can generate over a planning horizon and an energy consumption amount that will be consumed over the planning horizon; solve, using the energy generation amount and the energy consumption amount, an optimization problem over the planning horizon; and communicate a solution to the optimization problem to the central allocation server. Each of the energy nodes includes power generation equipment, power transmission equipment, and power storage equipment.

Provided is an power and communications network convergence system including wireless base stations, and DC grid groups, each grid group belonging to a cell. Each grid in the grid group has a DC line to which devices including a power generator and a power storage are connected, and performs, based on state information on each device, first control for reducing power fluctuations in the line. A first grid belonging to a cell performs, based on state information on each grid, second control for interchanging power with a second grid belonging to the cell. If a power situation of a first grid group belonging to a first cell and a power situation of a second grid group belonging to a second cell satisfy a preset condition, the first grid group performs third control for interchanging power with the second grid group.

A method is disclosed for controlling the operating of a consumption appliance by way of a selector switch controlled by an energy saving device connected to a management center. The consumption appliance is kept in its default power mode, until receiving, by the energy saving device, an authentic secured control message sent by the management center. This message includes a command onto the mode in which the consumption appliance has to be switched. A counter is initialized with an initialization value before to be triggered. The consumption appliance is switched in the mode indicated by the command, either until the counter has reached a threshold value, or until receiving another authentic control message. If the counter has reached the threshold value, then the consumption appliance is switched in its default power mode. If another authentic secured control message has been received, then returning to the step of initializing the counter.

Systems and methods for determining a location of an event in an electric power delivery system using a machine learning engine are provided. The machine learning engine may be trained based on a topology of the electric power delivery system, where the topology may be a layout of line sections and corresponding sensors of the electric power delivery system. Based on the topology, one or more training matrices that indicate possible event locations may be generated. In turn, the machine learning engine may be trained using the training matrices and logistic regression models to determine locations of events that occur during operation of the electric power delivery system.

A controllable electrical outlet may comprise a resonant loop antenna. The resonant loop antenna may comprise a feed loop electrically coupled to a radio-frequency (RF) communication circuit and a main loop magnetically coupled to the feed loop. The controllable electrical outlet may comprise one or more electrical receptacles configured to receive a plug of a plug-in electrical load and may be configured to control power delivered to the plug-in electrical load in response to an RF signal received via the RF communication circuit. The RF performance of the controllable electrical outlet may be substantially immune to devices plugged into the receptacles (e.g., plugs, power supplies, etc.) due to the operation of the resonant loop antenna. For example, degradation of the RF performance of the controllable electrical outlet may be less when the controllable electrical outlet includes the resonant loop antenna rather than other types of antennas.