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.

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.

Various embodiments include a method for certifying at least one installation-specific amount of energy, wherein the installation-specific amount of energy has been generated or consumed by an energy installation of an energy system. The method may include: capturing a temporal measured signal accumulated in relation to the energy system of a measured variable associated with the amount of energy; transmitting the captured signal to a test unit external to the energy system; disaggregating the transmitted signal using the test unit, and ascertaining the installation-specific amount of energy by way of the disaggregation; issuing a certificate regarding the ascertained installation-specific amount of energy; and receiving the issued certificate at the energy system.

The present disclosure describes transaction-enabling systems and methods. A system can include a facility including a core task including a customer relevant output and a controller. The controller may include a facility description circuit to interpret a plurality of historical facility parameter values and corresponding facility outcome values and a facility prediction circuit to operate an adaptive learning system, wherein the adaptive learning system is configured to train a facility production predictor in response to the historical facility parameter values and the corresponding outcome values. The facility description circuit also interprets a plurality of present state facility parameter values, wherein the trained facility production predictor determines a customer contact indicator in response to the plurality of present state facility parameter values and a customer notification circuit provides a notification to a customer in response.

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.

A method of controlling at multiple customer sites with separate metering electrical devices to control consumption of electricity in an electricity supply web made up of multiple electricity using customers that is over laid on a physical network, comprising the steps of: acquiring a budget for electrical energy for use in a predetermined time period; monitoring real-time use of electrical energy by electrical devices in the overlay web; comparing real-time use of electrical energy with the budget; and sending a control signal to at least one electrical device in the overlay web, based on the comparison, in order to increase or decrease electrical load so that total energy use in the predetermined time period is balanced with the budget. Also disclosed is an apparatus for controlling at least one electrical device in an electricity supply web made up of multiple electricity using customers.

A system for collaborative load balancing within a community of a plurality of energy nodes includes a central allocation server and a plurality of local agent servers. Each of the local agent servers is connected to a respective one of the energy nodes and has a processor configured to: receive input variables or parameters; predict, using the received input variables or parameters, a non-zero energy generation amount that power generation equipment can generate over a planning horizon and an energy consumption amount that will be consumed over the planning horizon; solve, using the energy generation amount and the energy consumption amount, an optimization problem over the planning horizon; and communicate a solution to the optimization problem to the central allocation server. Each of the energy nodes includes power generation equipment, power transmission equipment, and power storage equipment.

The present disclosure describes transaction-enabling systems and methods. A system can include a controller and a fleet of machines, each having at least one of a compute task requirement, a networking task requirement, and an energy consumption task requirement. The controller may include a resource requirement circuit to determine an amount of a resource for each of the machines to service the task requirement for each machine, a forward resource market circuit to access a forward resource market, and a resource distribution circuit to execute an aggregated transaction of the resource on the forward resource market.

A power management apparatus configured to control charge and discharge of the battery, power discharged from the battery being supplied to a power consumption apparatus, the power management apparatus includes a memory, and a processor coupled to the memory and configured to receive, from the power consumption apparatus, first information indicating a first power amount which is predicted to be used in the power consumption apparatus, determine, based on the first power amount, a first value that is a value regarding a residual amount of the battery and is used for determining which of the charge and the discharge of the battery is to be preferentially executed, and control, based on the determined first value and the residual amount of the battery, the charge and the discharge of the battery.

Methods for implementing power delivery transactions between a buyer and a seller of electrical energy supplied to an electrical grid by an integrated renewable energy source (RES) and energy storage system (ESS) of a RES-ESS facility are provided. Estimated total potential output of the RES is compared to a point of grid interconnect (POGI) limit to identify potential RES overgeneration, and the buyer is charged if potential RES overgeneration is less than potential overgeneration during one or more retrospective time windows. The method provides a basis for the RES-ESS facility owner to be paid for an estimated amount of energy that did not get stored as a result of a grid operator not fully discharging an ESS prior to the start of a new day.