Provided is an artificial intelligence (AI)-based peer-to-peer (P2P) power trading method and apparatus that encourages a household with relatively great power consumption or a household with relatively small power consumption according to a power load pattern for each time period to participate in power trading by optimizing power consumption through AI-based P2P power trading in a cluster including a nanogrid.

A power control apparatus of an embodiment controls power to be output to a power system from a power station including a power generation unit, and a power storage unit. The power control apparatus includes a power generation control unit, a power storage control unit, and a cooperation control unit. The power generation control unit controls an output of the power generation unit based on a power generation set value. The power storage control unit controls an output of the power storage unit based on a power storage set value. The cooperation control unit outputs the power generation set value to the power generation control unit and outputs the power storage set value to the power storage control unit based on a power demand amount of the power system so as to make the power generation unit and the power storage unit operate in a cooperative manner.

A method, a computer system, and a computer program product for optimizing home energy efficiency and device upgrade scheduling is provided. The present invention may include gathering data about home utilities and energy consumption patterns over time. The present invention may include training a machine learning model based on the gathered data. The present invention may include detecting inefficient devices or utility configurations based on the trained machine learning model. The present invention may include gathering data about current and future advances in home device and energy technology. The present invention may include determining optimal utility configurations and detecting candidate device upgrades. The present invention may include performing cost/benefit analysis based on the determined utility configurations and device upgrades. The present invention may include providing personalized recommendations to the user based on the cost/benefit analysis.

A method for aggregating a group of EVs based on EV flexibility includes: obtaining a prediction result on a fast charging demand of each EV based on a preset model; determining a distribution area of each substation involved in an EV activity range as an aggregation area; establishing an aggregation model based on the EV fast charging demand, in which the aggregation model includes energy balance equations and various constraints; obtaining an EV fast charging load power curve and an EV energy curve of each aggregation area based on the aggregation model; determining upper and lower limits of multiple EV fast charging load power curves as a flexibility range for the EV fast charging load power, and determining upper and lower limits of multiple EV energy curves as a flexibility range for the EV energy; and aggregating a group of EVs based on the above flexibility ranges.

An underwater data center is provided. A data center is positioned in a water environment, powered by one or more sustainable energies and including: an electronic device; a housing member that houses the electronic device and the data center under water; and a heat exchanger that is provided at the housing member and that is configured to discharge, into a water environment, heat discharged from the electronic device. The underwater data center is coupled to a sustainable energy source.

An exemplary control unit may respond to electrical grid needs within a controlled environment agricultural system, which may include one or more power consuming and environment controlling systems. The control unit may identify criticality of and power consumption by the systems and may compare those with the current cost of power (capacity and energy). The control unit may analyze the cost of adjusting power to systems and the cost of powering those systems during a specified period of time. The analysis may account for the value of adjusting the electricity as well as tariffs and market mechanisms specific to the electricity market in a responsive manner. The cost of powering off or reducing power to those systems may be identified by considering the value of the associated crops, and the impact that the system has on the crops.

An underwater data center system includes a data center positioned in a water environment, powered by one or more sustainable energy sources. One or more data center nodes are coupled to the data center or included in the data center. A controller is coupled to the one or more data center nodes. A housing member houses the data center node under water. The underwater data center is coupled to a sustainable energy source that provides energy to the underwater data center. One or more cables are coupled to the one or more data center nodes or the sustainable energy source. One or more cable monitoring devices detect a state of the one or more cables.

Systems and methods for aggregating and integrating distributed grid element inputs are disclosed. A data platform is provided for a distribution power grid. The data platform provides a crowd-sourced gaming system for identifying grid elements and determining dynamic electric power topology. The data platform also provides an interactive interface for displaying a view of a certain area with identified grid elements. The data platform communicatively connects to the identified grid elements, collects data from the identified grid elements, and manages the distribution power grid.

A terminal apparatus includes a communication unit configured to communicate with at least one device that a user uses, an input and output unit, and a control unit. The control unit is configured to identify a device to be controlled, of the at least one device, as a subject device, cause the input and output unit to display at least one first region indicating an amount of electric power used by the at least one subject device by area, and receive input of an operation to expand or contract the first region and control the subject device in accordance with the operation.

The present disclosure provides systems and methods for serving two or more uncorrelated loads connected to a renewable energy powerplant. The uncorrelated loads comprise a power grid and one or more industrial processes. A system may comprise a renewable energy system (RES), an energy storage system (ESS), and a controller programmed to: discretize an upcoming forecast horizon into a plurality of time periods; calculate one or more metrics for sending energy generated by the first RES to: (1) the ESS, (2) the power grid, and (3) the one or more industrial processes; prioritize the: (1) ESS, (2) power grid, and (3) one or more industrial processes.