A server that manages energy of a power grid by using a plurality of energy storage resources includes a loss obtaining unit and a selector. The loss obtaining unit obtains for each of the plurality of energy storage resources, energy loss including retention loss and input and output loss, the energy loss being caused in storing energy in each energy storage resource. When surplus electric power occurs in the power grid, the selector selects at least one energy storage resource for storing surplus electric power from among the plurality of energy storage resources based on the energy loss caused in storing surplus electric power.

An embodiment apparatus for an electric vehicle includes an indoor power outlet configured to receive power through one of a plurality of lines except for a single-phase alternating current (AC) charging line among three-phase AC input lines, a sensor configured to measure a required current of an electronic device connected to the indoor power outlet, and a controller configured to control a bidirectional on board charger of the electric vehicle based on the required current.

A battery module includes battery stack (2) including a plurality of stacked battery cells (1), a pair of end plates (3) disposed at both end parts in a stacking direction of battery stack (2), bind bar (4) in which the pair of end plates (3) are coupled, and electronic circuit block (6) mounted with voltage detection circuit (22) that detects a voltage of battery cells (1). Electronic circuit block (6) is disposed on an outer surface of both end plates (3) disposed at both end parts of battery stack (2), and electronic circuit block (6) is connected to battery cells (1) via voltage detection line (19).

A system and method for providing real-time distributed micro-grid optimization using price signals to the electrical grid system by allowing bi-directional electricity usage from a distributed network of energy storage stations to form a large, distributed resource for the grid. A machine learning optimization module ingests various forms of data-from grid telemetry to traffic data to trip-to-trip data and more-in order to make informed spatiotemporal decisions about optimal pricing signals as well as strategically placing and balancing energy stores across various regions to support optimum energy usage, risk mitigation, grid fortification, and revenue generation. Energy stores are then sent updated price signals and updated parameters as to the amount of energy to hold or release.

Single, internally adjustable modular battery systems are provided, for handling power delivery from and to various power systems such as electric vehicles, photovoltaic systems, solar systems, grid-scale battery energy storage systems, home energy storage systems and power walls. Batteries comprise a main fast-charging lithium ion battery (FC), configured to deliver power to the electric vehicle, a supercapacitor-emulating fast-charging lithium ion battery (SCeFC), configured to receive power and deliver power to the FC and/or to the EV and to operate at high rates within a limited operation range of state of charge (SoC), respective module management systems, and a control unit. Both the FC and the SCeFC have anodes based on the same anode active material and the control unit is configured to manage the FC and the SCeFC and manage power delivery to and from the power system(s), to optimize the operation of the FC.

A server includes a processing device. The server manages a plurality of vehicles. The processing device sets priority levels for the vehicles. The processing device sets the priority level of a vehicle in which its switching device is in a closed state to be higher than the priority level of a vehicle in which its switching device is in an open state. The processing device selects, based on the priority levels, a participating vehicle to be used for demand-increasing demand response from among the vehicles.

The application discloses an automatic transfer switch and a power supply system. The automatic transfer switch includes: a first switch unit having a first end connected to a first device through a converter port, and a second end electrically connected to a power grid through a power grid port; a second switch unit having a first end connected to a second device through an electric vehicle port and a charging/discharging circuit unit, and a second end electrically connected to the second end of the first switch unit; a third switch unit, having a first end electrically connected to the power grid through the power grid port, and a second end electrically connected to a load through a load port; a sampling unit; and a control unit connected to the sampling unit.

A charging apparatus for a vehicle where a terminal (1, FIG. 2) is connected to at least one kerbside power/data unit (9) to provide a power (4) and a data connection (5) to the power/data unit (9), the power/data unit (9) being connected to a nearby vehicle (17) to provide power to charge the vehicle (17) and receive data from the vehicle (17). The fact that the kerbside power/data unit (9) can charge a vehicle (17) using power supplied from a terminal (1, FIG. 2) and can transmit data from the vehicle (17) to the terminal (1, FIG. 2) provides the power and data requirements for connected autonomous vehicles at a kerbside location.

A method for controlling an exchange of power between a charging infrastructure and an electricity supply grid is provided. A number of power units are formed as electric vehicle. Each power unit has a variable state of charge. From the individual states of charge of the power units, an overall state of charge can be determined. For the overall state of charge, a flexibility range in dependence on time can be predefined for a control time period. The flexibility range is spanned by a progression over time of an upper limit of the overall state of charge and a progression over time of a lower limit of the overall state of charge for the control time period. The flexibility range has range points which can be defined by a value of the overall state of charge and a point in time in the control time period.

The present solution can execute a handshake process to establish a bidirectional session utilizing communications that can be implemented on EVs and chargers from various manufacturers. The present solution relates to a charger that can execute a handshake process communication between the charger and an electric vehicle to establish a session for bidirectional power delivery between the charger and the electric vehicle via a power cable. The charger can transmit, in the handshake process to the electric vehicle, a data structure comprising a field for a minimum current with a value for the field that is less than zero. The charger can configure, subsequent to transmission of the data structure comprising the value for the minimum current, the session for bidirectional power delivery between the charger and the electric vehicle via the power cable.