A printer is described comprising a movable functional element, a chargeable energy-storing device and a charger to charge the chargeable energy-storing device using energy discharged from the movable functional element.

The present invention relates to a server, a communicating device and a system having a function of managing a power demand, which can request saving power usage to a subscriber and compensate the resulting power consumption reduction and a method of managing power usage thereof.

The system of managing power usage includes: a server selecting a subscriber that intends to request power usage reduction by using subscriber information with receiving a request signal for the power usage reduction and transmitting guidance information for the power usage reduction to a communicating device of the selected subscriber; and a communicating device executing a power related application when receiving the guidance information from the server and outputting the guidance information as the execution result. Further, the server grants, when power consumption by the load apparatus of the selected subscriber decreases according to the guidance information, a predetermined compensation to the corresponding subscriber.

Cooling device 1, in particular a freezer 2, having a closable cooling space 3, an electrically operated cooling circuit, and preferably a cold storage pack 4, wherein the at least one closable cooling space 3 and the cold storage pack 4 can be cooled by the electrically operated cooling circuit. The cooling device has a power distributor 5 for distributing electrical power of at least one regenerative power source 6 to an electrically operated cooling circuit of the cooling device 1 and to at least one further electricity consuming device 7. In addition, the power distributor 5 has a control system with a computing unit 23, a memory 24 and priority logic. The priority logic is used to preferentially supply the electrically operated cooling circuit of the cooling device 1 with electricity if there is a lack of electrical power of the at least one regenerative power source 6.

Various embodiments of the teachings herein include a method for operating a network management system for a local energy network. The method may include determining a first operating strategy for an energy store of an electrical device of the local energy network based on a decision criterion using an electronic computing device of the network management system. The first operating strategy comprises a flexible storage strategy for storing energy in the energy store, the flexible storage strategy including a predefined flexibility criterion of the electrical device.

A power adapter configured to apply power to a device is disclosed. The power adapter comprises a switching module having a recess comprising a first set of contacts for receiving control signals, wherein the switching module comprises a switch for selectively applying power to a device based upon the control signals; and a control module removably coupled to the switching module and having a second set of contacts coupled to the first set of contacts of the switching module when the control module is attached to the switching module; wherein the switching module comprises a user interface element.

A control device is connected to power loads installed in a consumer facility so as to be able to communicate with the power loads. The control device includes: a control unit; and a display unit. The control unit determines the power loads and predicted power consumption when the power loads are used, determines at least one usable power load out of the power loads based on a remaining amount of available electric power in the consumer facility and the predicted power consumption, displays the usable power load on the display unit such that the usable power load is selectable, and controls use of the selected power load.

Accordingly the embodiments herein provides a method for load balancing in an energy measurement information system. The method includes collecting, by a power information collecting unit, power information at a snapshot extraction frequency. The snapshot extraction frequency is within a range. Further, the method includes detecting, by an operating status extracting unit, an operating status of at least one load apparatus at the snapshot extraction frequency. The operating status is one of a steady state and a transient state. Furthermore, the method includes generating, by a data set generating unit, a data set including only one or a representative snapshot of the power information, when the normal status is detected; and a data set including a plurality of snapshots of the power information, when the transient state is detected.

Various embodiments include a method for controlling an energy exchange among a plurality of energy systems using a control center, wherein a component of one of the plurality of energy systems is coupled to the control center via an interface module for data exchange. The method includes: transmitting a first data set to the interface module with a prediction profile regarding an energy exchange of the component; transmitting a second data set to the control center using the interface module including the first data set and component-specific data of the component; determining control data using the control center using the prediction profile and the component-specific data and data communicated to the control center by further energy systems to determine the control data; transmitting the determined control data to the interface module; and operating the component based on the control data.

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 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.