As the density of Electric Vehicle deployments in residential neighborhoods increase, demand on local power grids may exceed the local utility power supply causing local brown outs or transformer failure. The invention describes a method and process which enables the acquisition and efficient RF transmission of data that enables utility customers, utilities and/or other controlling entities to collaboratively regulate the timing and rate of Electric Vehicle battery charging in a manner that avoids peak-load related transformer failures.

A system and method of operating a system for controlling charging of a battery of a user's electric vehicle from a power source is based upon intervening in a controlled manner between the power source and the electric vehicle and dynamically controlling a level for charging of the vehicle's electric energy storage system. The level potentially being different from a maximum available charging power from the power source. The controlled intervention occurs in accordance with a charging schedule determined by the server and transmitted by the server to the charging cable. The charging cable then operates according to the charging schedule resulting in a corresponding controlled charging of the vehicle's electric energy storage system.

The present disclosure is directed to energy storage and supply management system. The system may include one or more of a control unit, which is in communication with the power grid, and an energy storage unit that stores power for use at a later time. The system may be used with traditional utility provided power as well as locally generated solar, wind, and any other types of power generation technology. In some embodiments, the energy storage unit and the control unit are housed in the same chassis. In other embodiments, the energy storage unit and the control unit are separate. In another embodiment, the energy storage unit is integrated into the chassis of an appliance itself.

The present disclosure is directed to energy storage and supply management system. The system may include one or more of a control unit, which is in communication with the power grid, and an energy storage unit that stores power for use at a later time. The system may be used with traditional utility provided power as well as locally generated solar, wind, and any other types of power generation technology. In some embodiments, the energy storage unit and the control unit are housed in the same chassis. In other embodiments, the energy storage unit and the control unit are separate. In another embodiment, the energy storage unit is integrated into the chassis of an appliance itself.

A system and process/method of modeling demand-response (DR) and distributed-energy resource (DER) assets is provided, facilitating the aggregation of said assets in virtual power plants (VPPs), and using VPPs to provide energy balancing services needed to minimize the impact of Variable Energy Resources (VER) on power system. The method accurately accounts for assets by qualifying assets based on various parameters and by forecasting the capabilities of the resulting VPPs for provision of balancing services. Asset performance factors that may affect the aggregated VPP's capabilities are monitored and recalculated when necessary. Near-term forecasted VPP capability is compared to near-term forecasted imbalances in the electric-power-supply system, and the VPP is dispatched to minimize the system imbalances. The dispatch signal is disaggregated to control commands to individual assets. This process provides a reliable and cost effective approach to support higher penetrations of renewable generation in the electric power system.

The present disclosure is directed to energy storage and supply management system. The system may include one or more of a control unit, which is in communication with the power grid, and an energy storage unit that stores power for use at a later time. The system may be used with traditional utility provided power as well as locally generated solar, wind, and any other types of power generation technology. In some embodiments, the energy storage unit and the control unit are housed in the same chassis. In other embodiments, the energy storage unit and the control unit are separate. In another embodiment, the energy storage unit is integrated into the chassis of an appliance itself.

The present disclosure is directed to energy storage and supply management system. The system may include one or more of a control unit, which is in communication with the power grid, and an energy storage unit that stores power for use at a later time. The system may be used with traditional utility provided power as well as locally generated solar, wind, and any other types of power generation technology. In some embodiments, the energy storage unit and the control unit are housed in the same chassis. In other embodiments, the energy storage unit and the control unit are separate. In another embodiment, the energy storage unit is integrated into the chassis of an appliance itself.

Provided are energy device control systems for distributed grid subsystem that control a first power demand of a plurality of appliances. The control system comprises a graphical user interface configured to accept a user input indicative of a first demand and dynamic allocation flexibility associated with the a respective energy device; a communication interface configured to aggregate dynamic allocation values from a plurality of system nodes including at least the user input indicative of a first demand and the dynamic allocation flexibility; and at least one processor programmed to: generate a learning model for evaluating dynamic future allocation with future energy execution prediction, wherein the dynamic future allocation includes at least energy operational information based on a categorization of energy usage at a plurality of respective energy devices; and trigger energy generation on the energy grid at respective generator nodes according to the learning model and dynamic projections.

A method for generating scheduling recommendations for energy consumption tasks includes determining an estimated time-variant quantity of carbon emissions released from an energy supply plant over a future time interval; predicting a probability of user compliance with a recommendation to initiate an energy consumption task at one or more times within the future time interval; selecting a recommended start time for the energy consumption task based on both the predicted time-variant quantity of carbon emissions and the predicted probability of user compliance with the recommendation at the recommended start time; and outputting the recommended start time.

A power supply switching device (20) according to the present disclosure is used in supplying power to chargers (30) installed in the parking lot of a housing complex. The power supply switching device (20) includes switches (21) and a controller (22). The switches (21) switch the power supply on and off to each group among groups into which the chargers (30) are divided. The controller (22) controls the switches (21). The controller (22) controls the switching on and off of the switches (21) so that only one switch (21) among the switches (21) is on, or all of the switches (21) are off.