Examples relate to adjusting load power consumption based on a power option agreement. A computing system may receive power option data that is based on a power option agreement and specify minimum power thresholds associated with time intervals. The computing system may determine a performance strategy for a load (e.g., set of computing systems) based on a combination of the power option data and one or more monitored conditions. The performance strategy may specify a power consumption target for the load for each time interval such that each power consumption target is equal to or greater than the minimum power threshold associated with each time interval. The computing system may provide instructions the set of computing systems to perform one or more computational operations based on the performance strategy.

Examples relate to adjusting load power consumption based on a power option agreement. A computing system may receive power option data that is based on a power option agreement and specify minimum power thresholds associated with time intervals. The computing system may determine a performance strategy for a load (e.g., set of computing systems) based on a combination of the power option data and one or more monitored conditions. The performance strategy may specify a power consumption target for the load for each time interval such that each power consumption target is equal to or greater than the minimum power threshold associated with each time interval. The computing system may provide instructions the set of computing systems to perform one or more computational operations based on the performance strategy.

Provided are a method and apparatus for dynamically controlling electrical loads, a storage medium and an electronic apparatus. The method includes that: a current capacity balance of a user sub-region is acquired from an intelligent electricity monitoring and metering terminal through a mobile terminal; when the current capacity balance is smaller than a load power of an electric consumption device to be started in the user sub-region, a regional coordination control apparatus or a server is requested through the mobile terminal to adjust and increase a capacity allocated for the user sub-region, such that a capacity balance will be greater than or equal to the load power; and whether to allow to start the electric consumption device is determined according to a decision replied by the regional coordination control apparatus or the server.

A frequency stabilization arrangement for a power transmission grid has a modular multi-level converter with a first terminal for electrical connection to a power transmission grid, and an electrical resistor unit with a second terminal for electrical connection to the power transmission grid.

A frequency stabilization arrangement for a power transmission grid has a modular multi-level converter with a first terminal for electrical connection to a power transmission grid, and an electrical resistor unit with a second terminal for electrical connection to the power transmission grid.

Transaction-enabled systems and methods for royalty apportionment and stacking are disclosed. An example system may include a plurality of royalty generating elements (a royalty stack) each related to a corresponding one or more of a plurality of intellectual property (IP) assets (an aggregate stack of IP). The system may further include a royalty apportionment wrapper to interpret IP licensing terms and apportion royalties to a plurality of owning entities corresponding to the aggregate stack of IP in response to the IP licensing terms and a smart contract wrapper. The smart contract wrapper is configured to access a distributed ledger, interpret an IP description value and IP addition request, to add an IP asset to the aggregate stack of IP, and to adjust the royalty stack.

Transaction-enabled systems and methods for royalty apportionment and stacking are disclosed. An example system may include a plurality of royalty generating elements (a royalty stack) each related to a corresponding one or more of a plurality of intellectual property (IP) assets (an aggregate stack of IP). The system may further include a royalty apportionment wrapper to interpret IP licensing terms and apportion royalties to a plurality of owning entities corresponding to the aggregate stack of IP in response to the IP licensing terms and a smart contract wrapper. The smart contract wrapper is configured to access a distributed ledger, interpret an IP description value and IP addition request, to add an IP asset to the aggregate stack of IP, and to adjust the royalty stack.

A system and method for managing vehicle charging stations such that when at least two of a plurality of electric vehicle charging stations (also known as electric vehicle service equipment, or EVSE) occupied with vehicles awaiting a charge, the present system manages the charging of individual vehicles in cases where the aggregated demand for charging exceeds the capacity of the circuits supplying the plurality of EVSE. By cycling so that only a few of the vehicles are charging at a time, the demand on the circuits is kept below a predetermined limit. In cases where a load shedding event is in progress, the limit can be further reduced. In cases where the cost of electricity is varying dynamically, the system considers a driver's explicit charging requirements (if any) and preferences for opportunistic charging when the price of electricity is not too high.

In one embodiment, the method includes obtaining, by a first processing device, energy demand data representative of the energy consumption of respective tasks of a processing pipeline, obtaining, by the first processing device, battery availability data representative of the available energy of the batteries of other respective processing devices, for respective tasks of the processing pipeline, selecting, by the first processing device, one of the processing devices for executing the task, as a function of the energy demand data and the battery availability data, and controlling, by the first processing device, the execution of the respective tasks on the selected processing devices.

In one embodiment, the method includes obtaining, by a first processing device, energy demand data representative of the energy consumption of respective tasks of a processing pipeline, obtaining, by the first processing device, battery availability data representative of the available energy of the batteries of other respective processing devices, for respective tasks of the processing pipeline, selecting, by the first processing device, one of the processing devices for executing the task, as a function of the energy demand data and the battery availability data, and controlling, by the first processing device, the execution of the respective tasks on the selected processing devices.