International Business Machines Corporation

Olle L Sundstroem

Harold D Dykeman

Olivier Gallay

Jacint Szabo

Fabian Mueller

Carl Binding

Exemplary embodiments relate to a matching engine for the coordination of electric energy production and consumption, in particular in the presence of uncertainty. The engine provides matching based on uncertainty and flexibility in the electric supply and demand chains. The system can use quantified characterizations of uncertainty and flexibility provided by performance measurements of the elements in the chain.

Uncertainty-flexibility matching engine for inter-temporal electric energy products

The present invention relates to an energy allocation system for operating at least an energy storage device to substantially balance the energy consumed by the energy storage device with the energy supplied thereto, comprising the steps of: determining a power flexibility of the energy storage device by generating an upper time-varying power function; predicting energy consumption data per discrete time-slots over a given time-window for the device; predicting a demand for energy by the device in a given planning time-period; generating a time-varying upper energy function for the demand prediction that defines an uppermost limit for the supply of energy to the device; generating a time-varying lower energy function for the demand prediction that defines a lowermost limit for the supply of energy to the device, and supplying energy to the device in a range defined by the limits specified by the upper energy function and the lower energy function.

Energy allocation system for balancing energy consumption

A method for allocating energy to a plurality of devices, wherein each device is configured to consume, store and/or supply energy, the method includes the steps of: assigning each device to a group of devices; assigning an aggregation node device to each group of devices; for a selection of devices transmitting local power cost functions of the devices and/or power usage profiles of the devices with respect to a predetermined time slot to the assigned aggregation node device; at the aggregation node device, generating aggregated data as a function of the received local power cost functions and/or power usage profiles; transmitting the aggregated data to a central processing device; at the central processing device, optimizing a global cost function for allocating power to the devices as a function of the aggregated data.

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Rueschlikon, Switzerland

Olle L Sundstroem