An operation decision-making method for centralized cloud energy storage capable of participating in power grid auxiliary services. The method includes: establishing a model predictive control model; obtaining operating parameters of the current period t from a grid control center at a beginning of a current decision-making cycle; predicting operating parameters within the predetermined time range based on historical data; obtaining decision variables according to the model predictive control model, the operating parameters of the current period and the operating parameters within the predetermined time range; setting a charging power of the centralized energy storage facility in the current period t and a discharging power according to the decision variables; obtaining an actual power of the centralized energy storage facility at an end of the current period t through sensors installed on the centralized energy storage facility as a parameter for a next decision period.

A method of controlling a wind power plant including an energy storage device, the wind power plant being connected to a power grid and comprising one or more wind turbine generators that produce electrical power for delivery to the power grid, the method comprising: processing grid data related to the power grid to determine a probability forecast for a future state of the grid; and controlling charging and discharging of the energy storage device in accordance with the probability forecast.

The present invention relates to a method for directional transmission of power in the form of energy packets via a transmission network. The power to be transmitted is adjustable at at least one location x of each edge by a data and computer network. A data packet is biuniquely assigned to each energy packet, which data packet is formed in a control instance of the data and computer network by means of predictions. This data packet describes an optimized transport path via which optimized transport path a source transmits the physical power in a fixed transmission period T to a load for partial demand coverage. Furthermore, the data packet describes the power class of the energy packet, wherein this power class is defined by the temporal course of a nominal power P.sub.nom(t) determined by predictions and by a remainder R(t) in the transmission period determined by a function of an uncertainty of the predictions. For the transmission of the energy packet, the transmitted power equal to P.sub.nom(t) plus a fraction of R(t) is set for each point in time t within T at at least one location x of each edge of the transport path.

A method for adjusting electrical energy flow schedules of a utility handling a plurality of distributed energy resources. The method comprising the steps of providing information regarding energy flow of the energy resources and storing said information on a distributed ledger; transferring energy schedules from the utility to the distributed ledger; transferring said information regarding the energy flow and the energy schedules from the distributed ledger to a computing means and computing proposed corrections for the energy schedules; transferring said proposed correction to the distributed ledger; transferring said proposed correction to the utility which decides to use or not to use the proposed correction. By deciding to use the proposed correction, the schedules are corrected and information is transferred from the utility to the computing means.

A method estimates a grid state of an electrical power distribution grid having a multiplicity of network sections, in which a central computer arrangement is used to receive measured values from measuring devices. A state estimation device is used to make a prediction of a future grid state, wherein a voltage and a phase angle are respectively ascertained for each network section, and in that a naive Bayes method is used for the prediction.

A method for operating a data center in an electrical network, the method including the steps of: processing a plurality of calculation tasks by the data center; and assigning each one of the plurality of calculation tasks at least one of a prioritization value and a calculation complexity, the plurality of calculation tasks being processed taking into account at least one of the prioritization value and the calculation complexity and taking into account a power provision parameter of the electrical network.

A management device is connected to an AC power line provided with a plurality of connection ports, each of which can be connected to an electric device including a power storage unit. The management device includes a measurement unit configured to measure an electric signal on the AC power line, a determination unit configured to determine a type of the electric device connected to the AC power line via a connection port in the plurality of connection ports based on a measurement result of the measurement unit, and a first prediction unit configured to predict an amount of power supply on the AC power line due to discharge of the power storage unit based on a determination result of the determination unit.

The present invention provides a processing apparatus (10) including: an acquiring unit (11) which acquires an adjustment request specifying a control time period and a control amount for controlling power demand; a determining unit (12) which, on the basis of the adjustment request, determines a first consumer whose power demand is to be controlled, and a control amount of the first consumer and a time period during which power demand of the first consumer is controlled; and an inference unit (13) which infers whether, if power demand of the first consumer were controlled in accordance with a determination result made by the determining unit (12), power demand of the first consumer before and/or after control would change from power demand of the first consumer if the power demand were not controlled.

In a method and system, voltage and/or current signals on an electrical/power system is monitored. A power event is identified from the monitored voltage and/or current signals. In response to event identification, waveforms of the monitored voltage and/or current signals are captured. Energy-related signals are calculated and extracted from pre-event measurements, event measurements and post-event measurements using the captured waveforms. Additional information associated with the event is identified and calculated by comparing (a) the calculated and used energy-related signals from pre-event measurements, with (b) the calculated and used energy-related signals from post-event measurements.

A method for controlling a process that draws power from an electrical power source operates by obtaining time-related electrical demand data from the electrical power source and adaptively adjusting at least one control parameter in a control algorithm for the process to reduce the cost of the electrical energy consumed. The time-related electrical demand data indicates at least diurnal variation, and optionally seasonal variation, in electrical power demand. The time-related electrical power demand data may also include real-time electrical power demand data from the electrical power source.