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.

A system for managing electrical loads includes a plurality of branch circuits, a sensor system, and control circuitry. The sensor system is configured to measure one or more electrical parameters corresponding to the plurality of branch circuits, and transmit one or more signals to the control circuitry. The control circuitry is configured to determine respective electrical load information in each branch circuit based on the sensor system, and control the electrical load in each branch circuit using controllable elements based on the respective electrical load information. The control circuitry transmits usage information, generates displays indicative of usage information, accesses stored or referencing information to forecast electrical load, and manages electrical load in response to identified events. The control circuitry can associate each branch circuit with reference load information, and disaggregate loads on each branch circuit based on the reference load information and on the electrical load in the branch circuit.

Disclosed are a hybrid power generation facility and a control method thereof. The hybrid power generation facility includes a gas turbine including a compressor configured to compress air introduced from an outside, a combustor configured to mix the compressed air with fuel and to combust the air and fuel mixture, and a turbine configured to produce power with first combustion gas discharged from the combustor, a GT (gas turbine) generator configured to generate electric power using a driving force generated by the gas turbine, a boiler including a combustion chamber and configured to mix the first combustion gas supplied from the turbine of the gas turbine with air and fuel supplied from the outside, a steam turbine through which steam generated in the combustion chamber passes, a ST (steam turbine) generator configured to generate electric power using a driving force generated by the steam turbine, and an energy storage system configured to be charged based on a decrease rate of power demand of a grid and a maximum decrease rate of power supply from the GT generator and the ST generator.

Systems and methods are directed to controlling components of a utility grid. The system can receive data samples including signals detected at one or more portions of a utility grid. The system can construct a matrix having a first dimension and a second dimension. The system can train a machine learning model based on the matrix to predict values for signals of the utility grid not provided in the matrix. The system can receive bounds for one or more input variables, constraints on one or more output variables, and a performance objective for the utility grid. The system can determine, based on the machine learning model and via an optimization technique, an adjustment to a component of the utility grid that satisfies the performance objective. The system can provide the adjustment to the component of the utility grid to satisfy the performance objective.

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.

An electric power control system for controlling supply and consumption of electric power in a system power supply, a storage battery and an electric power load, said electric power control system including: an estimated value correction unit configured to obtain a difference between a past power control estimated value and a past actual performance value, and to shift a power control estimated value obtained as a result of estimation in a predetermined period to an extent corresponding to said difference, thereby correcting the power control estimated value, wherein said past power control estimated value is a value obtained as a result of estimation performed in a past time relative to said predetermined period, and said past actual performance value is a value obtained as an actual result in the past time; and a power control unit configured to control supply and consumption of electric power in the system power supply, the storage battery, and the electric power load, based on the power control estimated value corrected by the estimated value correction unit.

Techniques for managing an off-grid power system include executing update requests for an off-grid power system that is communicably coupled to an energy management system by determining an amount of stored energy in energy storage devices in response to at least one update request, determining an amount of electrical power generatable by renewable energy power systems in response to another update request, determining a predicted reliability of at least a portion of the energy storage devices and the renewable energy power systems in response to another update request, and determining an amount of electrical power for a remote facility that is electrically coupled to the off-grid power system in response to another update request. The techniques further include determining a control command for the off-grid power system based on the responses to the update requests; and providing the control command to the off-grid power system to adjust an operation of at least one of the energy storage devices or the renewable energy power systems.

A facility providing systems and methods for managing and optimizing energy consumption and/or production is provided. The facility provides techniques for optimizing energy-consuming and energy-producing systems to meet specified demands or goals in accordance with various constraints. The facility relies on models to generate an optimization for an energy system. In order to use generic models to simulate and optimize energy consumption for an energy system, the generic models are calibrated to properly represent or approximate conditions of the energy system during the optimization period. After the appropriate models have been calibrated for a given situation using one or more modeling parameter sets, the facility can simulate inputs and responses for the corresponding system. The facility uses the generated simulations to generate a plan or control schedule to be implemented by the energy system during the optimization period.

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 platform and components for an automated consumer retail utility marketplace are provided, including components for machine learning, components for gamification, and components for supporting a related consumer mobile application that enables improved visibility and control by a consumer over its interaction with energy markets.