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.

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.

An electric vehicle charging station charging electric vehicles dynamically responds to power limit messages. The charging station includes a charging port that is configured to electrically connect to an electric vehicle to provide power to charge that electric vehicle. The charging station also includes a power control unit coupled with the charging port, the power control unit configured to control an amount of power provided through the charging port. The charging station also includes a set of one or more charging station control modules that are configured to, in response to receipt of a message that indicates a request to limit an amount of power to an identified percentage and based on a history of power provided through the charging port over a period of time, cause the power control unit to limit the power provided through the charging port to the identified percentage.

An energy management system of the present invention can measure and integrate a power consumption amount of each device, can integrate and monitor regional total power consumption amounts, and allows energy to be effectively used by collecting, analyzing, storing and transmitting a use pattern and data through the Internet of Things (IoT) between devices and completely and automatically cutting off and controlling the power to be wasted in a device when the device is not used. The energy management system remotely controls devices and allows energy to be effectively managed through the minimization of power consumption by automatically and completely cutting off the power to be supplied to the devices when the devices are not used, and by cutting off the power to be supplied to the system when the power of all the devices connected to the system is cut off and when the system is in standby.

A method for controlling electrical power consumption for a first group of functional which can be used for operational management during operation of the bioreactor components during operation comprises, inter alia, adjusting a present power control signal for one or more of the functional components from the first group in order to optimise power consumption, when a comparison shows for the first group of functional components that the currently required total electrical power consumption is greater than a predefined total electrical power consumption, such that, for the first group of functional components, an adjusted total electrical power consumption is not greater than the predefined total electrical power consumption. A biotechnological apparatus comprises a bioreactor, a reactor vessel formed in the bioreactor and having a cultivation chamber, and a temperature control device provided with a heat pump and configured to control the temperature of the cultivation chamber.

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.

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.

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.