Abstract: An example operation includes one or more of forecasting renewable energy availability and grid demand during peak times for a geographic area of an electric vehicle (EV), executing an artificial intelligence (AI) model to generate an optimized charging schedule for the EV based on the forecasted renewable energy availability and grid demand during peak times for the geographic area, identifying at least one demand-response (DR) event for the geographic area that adjust energy usage of the EV, and modifying the optimized charging schedule based on participation in the at least one DR event by the EV.

Abstract: An example operation includes determining a vehicle is receiving a charge at a charging station, receiving location data of a device of an occupant of the vehicle when the device and the occupant exit the vehicle, determining a time of departure of the vehicle based on an optimal charge level of a battery of the vehicle, and notifying the device to return to the vehicle based on the time of departure.

Abstract: An example operation includes receiving, by a plurality of electric vehicles (EVs) in a vehicle network, a first notification to navigate to a first location in need of a first amount of energy and a second notification to navigate to a second location in need of a second amount of energy; nominating, by the plurality of EVs, one of the plurality of EVs to navigate to the first location and discharge the first amount of energy and navigate to the second location and discharge the second amount of energy; routing, by the one of the plurality of EVs, to the first location and discharging the first amount of energy; and further nominating, by the plurality of EVs, the one of the plurality of EVs to navigate to the second location and discharge the second amount of energy.

Abstract: An example operation includes one or more of receiving a request to discharge energy to an electrical grid, selecting an EV based on a state of charge (SOC) of a battery of the EV and an availability of the EV to discharge the energy, discharging electrical energy from the battery of the EV to an energy storage system at a geographic location, reserving the discharged electrical energy for the electrical grid within the energy storage system for a period of time, and transferring the discharged electrical energy to the electrical grid within the period of time.

Abstract: An example operation includes one or more of halting, by a vehicle, charge to a location when a battery capacity of the vehicle is below a threshold; determining, by the vehicle, another vehicle that is available to provide charge to the location; maneuvering, by the vehicle, to a charging station; maneuvering, by the another vehicle, to the location; and providing, by the another vehicle, charging to the location.

Abstract: An example operation includes one or more of determining, by a vehicle, an amount of energy to provide to a location, the energy located in one or more energy sources including the vehicle, an energy storage device, and an electric grid, the determining based on an ambient temperature of the vehicle, an ambient temperature of the energy storage device, a capacity of a battery in the vehicle, a capacity of the energy storage device, a demand of the electric grid, and an internal temperature of the location; and directing, by the vehicle, at least one of the energy sources to provide the amount of energy, based on determining.

Abstract: An example operation includes one or more of receiving temperature data of a surface of a solar panel from a sensor, receiving energy output data of the solar panel, executing an artificial intelligence (AI) model on the temperature data and the energy output data to generate an output from the AI model which includes a predicted point in time at which the solar panel is to be cooled, and activating a cooling mechanism at the predicted point in time, wherein the cooling mechanism is configured to cool the solar panel.

Abstract: An example operation includes receiving data comprising at least one of weather data, renewable energy production data, or renewable energy consumption data, executing an artificial intelligence model to predict renewable energy production at a location and to predict renewable energy consumption at the location, during a period of time, based on the received data, storing, at the location, a renewable energy production in at least one of an energy storage device or a battery of a vehicle during the period of time, based on the predicted renewable energy production and the predicted renewable energy consumption, and directing, by a control device associated with the location, a renewable energy consumption of an energy-consuming device at the location from the at least one of the energy storage device or the battery of the vehicle during the period of time based on the predicted renewable energy production and the predicted renewable energy consumption.

Abstract: An example operation includes one or more of receiving, by at least one processor on a vehicle, data related to the vehicle as the vehicle is traveling on a route and context related to the data, determining, by the at least one processor, an urgency of the data based on the context related to the data, selecting, by the at least one processor, a display device associated with the vehicle to present the data based on the urgency, executing, by the at least one processor, an artificial intelligence (AI) model on the data and the context related to the data to predict a placement location of the data on the selected display device, and displaying the data at the placement location on the display device.

Abstract: An example operation includes at least one of determining an energy need from each of a plurality of locations in an area, based on a criticality of the energy need, determining a location of an electric vehicle (EV) that can provide energy to each of the plurality of locations, estimating a future availability of at least one additional EV and a future location of the at least one additional EV that can provide the energy to each of the plurality of locations, and autonomously navigating, by the EV, to a first location of the plurality of locations when the criticality of the energy need of the first location is greater than the criticality of the energy need of a second location of the plurality of locations, wherein the location of the EV is closer to the second location than the first location.

Abstract: An example operation includes one or more of collecting artificial intelligence (AI) activity data from a plurality of devices that are associated with a location, determining a number of AI prompts that are going to be executed by the plurality of devices based on the AI activity data, predicting an amount of electricity required for the number of AI prompts based on execution of an AI model on the number of AI prompts, and adjusting, by an electric panel installed at the location, at least one setting of a device from among the plurality of devices associated with the location to optimize energy consumption based on the predicted amount of electricity.

Abstract: An example operation includes at least one of receiving data comprising at least one of weather data, grid load data, or energy usage data related to an area, executing an Artificial Intelligence (AI) model to predict energy production in the area and energy consumption in the area, based on the received data, determining an optimized energy-related output in a timeframe, based on the predicted energy production and the predicted energy consumption, and setting, by a device associated with a location in the area, at least one control at the location based on a parameter associated with the optimized energy-related output, to produce the optimized energy-related output within the timeframe.

Abstract: An example operation includes one or more of: determining, by a charging station, that a vehicle requests approval to receive a charge; accessing, by the charging station, personal information related to the vehicle and related to an occupant of the vehicle; analyzing, by the charging station, the personal information related to the vehicle and related to the occupant of the vehicle; determining, by the charging station, to grant the approval, based on the analyzing; and, responsive to the approval being granted, deleting, by the charging station, the accessed personal information related to the vehicle and related to the occupant of the vehicle, after the vehicle has received the charge.

Abstract: An example operation includes one or more of determining a location in an area that may lose electricity during an event related to a grid, conserving energy through a muting of energy consumption at the location, storing the conserved energy in an energy storage device at the location, and using the conserved energy at the location when the event occurs.

Abstract: An example operation includes one or more of determining a type of energy-consuming action being performed at a location by an energy-consuming system that is receiving energy from a remote energy service provider, receiving energy utilization data associated with the energy-consuming action from the remote energy service provider, determining a pattern of use of the type of energy-consuming action at the location, directing an amount of energy to be stored by an energy storage unit (ESU) at the location based on the energy utilization data and the pattern of use, and adjusting energy utilization of the ESU to locally supply the amount of energy to the system when the system is performing the energy-consuming action at a future point in time.

Abstract: An example operation includes one or more of obtaining a destination of a vehicle, determining an amount of traffic in an area proximate a route to the destination within a time frame, determining a best time to leave in the time frame and a worst time to leave in the time frame, where the best time to leave provides a minimum traffic in the area and the worst time to leave provides a maximum traffic in the area, and determining one or more of a degradation of a battery of the vehicle and an energy usage of the vehicle for one or more of the best time to leave and the worst time to leave.

Abstract: An example operation includes one or more of predicting a time when demand for energy at a location is greater than a first threshold, wherein the energy is received from an energy provider, determining that an amount of energy stored in a battery of an electric vehicle at the location is above a second threshold, wherein the second threshold indicates a minimum state-of-charge of the battery of the electric vehicle, modifying, based on the predicted time and the amount of energy stored in the battery of the electric vehicle, energy consumption by at least one device at the location to reduce energy consumption at the location, and transferring energy from the battery of the electric vehicle to the location while the at least one device at the location is modified to reduce energy consumption.

Abstract: An example operation includes one or more of determining an issue exists with a resource delivery to an electricity provider, determining an electric impact, based on the issue, determining an area that will be affected by the electric impact, and dispatching vehicles to provide electricity to locations within the area.

Abstract: An example operation includes one or more of: determining a degradation of a battery of each vehicle in a group of electric vehicles, wherein the degradation is at a rate greater than a threshold; determining a return when the degradation is lowered; and providing a portion of the return to each of the vehicles in the group, wherein the portion is commensurate with the lowering.

Abstract: An example operation includes at least one of receiving, from at least one sensor at a location, data related to energy usage at the location, determining an energy-negative state exists at the location at a first period of time based on the data indicating energy usage at the location is greater than a threshold of energy provided from at least one energy storage device at the location, and recharging the at least one energy storage device at a second period of time commensurate with the energy usage at the location.