A server includes a communication device and a processor. The communication device obtains a power rate unit price dependent on a region where external charging is performed and a time slot when external charging is performed. The processor calculates a first power rate indicating a power rate when the external charging is performed with a first power feeding facility provided at a departure place before departure of a vehicle, calculates a second power rate indicating a power rate when the external charging is performed with a second power feeding facility provided in the vicinity of a traveling route after departure of the vehicle, and when the second power rate is lower than the first power rate, reduces an amount of power feeding during the external charging with the first power feeding facility, as compared with when the second power rate is equal to or higher than the first power rate.

A server includes a communication device and a processor. The communication device obtains a power rate unit price dependent on a region where external charging is performed and a time slot when external charging is performed. The processor calculates a first power rate indicating a power rate when the external charging is performed with a first power feeding facility provided at a departure place before departure of a vehicle, calculates a second power rate indicating a power rate when the external charging is performed with a second power feeding facility provided in the vicinity of a traveling route after departure of the vehicle, and when the second power rate is lower than the first power rate, reduces an amount of power feeding during the external charging with the first power feeding facility, as compared with when the second power rate is equal to or higher than the first power rate.

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.

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 modular system is described which can provide high frequency monitoring of power use and responsive control as well as enabling network connectivity for centralised monitoring and operation. One modular system consists of a communications bus, end caps, and a combination of the modules providing communications, power metering, relay control and battery backup. Each modular system can be configured with a combination of modular units as needed for the application. A combination of bus communication monitoring and tilt detection provides security against external tampering after installation.

A modular system is described which can provide high frequency monitoring of power use and responsive control as well as enabling network connectivity for centralised monitoring and operation. One modular system consists of a communications bus, end caps, and a combination of the modules providing communications, power metering, relay control and battery backup. Each modular system can be configured with a combination of modular units as needed for the application. A combination of bus communication monitoring and tilt detection provides security against external tampering after installation.

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 techniques for proactively operating gas-oil separation plant (GOSP) type process facilities that include determining historical operational characteristics of a GOSP for a past time interval using historical operational data for the GOSP, determining expected operating characteristics of the GOSP for a subsequent time interval using the historical operational characteristics, determining an operating plan for the GOSP using the expected operating characteristics, and operating the GOSP in accordance with the operating plan.

A method for controlling production of one or more refined resources by an energy provider includes predicting a demand for the refined resources by one or more consumers of the refined resources as a function of an incentive offered by the energy provider. The method further includes performing an optimization of an objective function subject to a constraint based on the predicted demand for the refined resources to determine an amount of the refined resources for the energy provider to produce and a value of the incentive at multiple times within a time period. The method also includes providing setpoints for equipment of the energy provider that cause the equipment to produce the amount of the refined resources determined by performing the optimization.