The present invention relates to a method for measuring the AC impedance of a battery in a composite power supply power system, comprising the following steps: determining the AC disturbance signal amplitude, operating the DC/DC voltage converter to generate the AC disturbance signal, collecting the output signals of the fuel cell and the lithium battery, calculating the output power of the fuel cell and the lithium battery; calculating the demand power of the load, and when the demand power is stable, calculating the impedance of the lithium battery and the fuel cell separately, otherwise, only the impedance of the fuel cell is calculated.

A control device is connected to power loads installed in a consumer facility so as to be able to communicate with the power loads. The control device includes: a control unit; and a display unit. The control unit determines the power loads and predicted power consumption when the power loads are used, determines at least one usable power load out of the power loads based on a remaining amount of available electric power in the consumer facility and the predicted power consumption, displays the usable power load on the display unit such that the usable power load is selectable, and controls use of the selected power load.

A system includes an entropy device configured to generate and distribute input entropy data and an intelligent electronic device (IED) of an electric power distribution system. The IED is configured to perform operations that include receiving the input entropy data distributed by the entropy device, generating a set of keys using the input entropy data, and establishing a Media Access Control Security (MACsec) communication link using the set of keys.

Techniques for operational planning in a microgrid by means of optimization are provided. This involves a power exchange with a primary grid being taken into consideration. The operational planning in this case is performed by using an optimization, e.g. a (mixed) integer linear optimization. The various examples describe how a power exchange (balancing) can be provided for a primary grid to which the microgrid is connected. In particular, this is achieved by taking into consideration a distinction for the constraint of the optimization. In this manner, a lead time between a request for the power exchange and the actual activating of the power exchange can be taken into consideration.

An example operation includes one or more of determining that a transport at a location will be idle for an idle time duration prior to a predicted event or outage at an electrical grid servicing the location; providing the transport with an estimated duration of the predicted event or outage, and an estimated electricity usage at the location during the duration of the predicted event or outage; and charging the transport during at least a portion of the idle time duration to at least meet the estimated electricity usage.

A method for determining a sequence of operation of at least one set of generator units of an electrical network includes assigning a rank to each generator unit; from a projected load curve, determining a minimum number of generator units; for each generator unit having a rank less than or equal to the minimum number of generator units, allocating in the sequence of operation the on state to the generator unit for each time interval; for each generator unit having a rank greater than the minimum number of generator units, allocating, by increasing rank, for each time interval of the sequence of operation the on state or the off state to the generator unit, and for each generator unit to which is assigned the on state at a given time interval of the sequence of operation, allocating an operating power, by optimisation of a cost function over a period.

An apparatus in an illustrative embodiment comprises at least one processing device comprising a processor coupled to a memory. The processing device is configured to receive power consumption data relating to at least one monitored device, and to classify the monitored device based at least in part on the power consumption data. The processing device is further configured to select a power policy for the classified device, and to control application of power to the classified device in accordance with the selected power policy. For example, controlling application of power to the classified device in accordance with the selected power policy may comprise determining contextual information for the classified device, generating a control signal based at least in part on the contextual information and the selected power policy, and transmitting the control signal to at least one node of a node network. Other illustrative embodiments include methods and computer program products.

Systems for providing operating reserves to an electric power grid are disclosed. In one embodiment, a system comprises at least one power consuming device, at least one controllable device, and a client device constructed and configured in network communication. The at least one controllable device is operably coupled to the at least one power consuming device. The at least one controllable device is operable to control a power flow from the electric power grid to the at least one power consuming device responsive to power control instructions from the client device. Each of the at least one power consuming device has an actual value of power reduced and/or to be reduced based on revenue grade metrology, and confirmed by measurement and verification. The actual value of power reduced and/or to be reduced is a curtailment value as supply equivalence and provides operating reserve for the electric power grid.

A method performed in which a forecast, a generation information, and a regulation information are obtained. A control information is determined in the event that the regulation information is indicative of over- or underproduction. The control information is indicative of a control of the amount of electrical energy generated by power generating plants. The control information is determined based on the obtained regulation and generation information. Based on the time at which the regulation information is obtained, the remaining time of a predetermined interval is determined. Operating points for the plants are determined such that, for the remaining time, the amount of energy generated by the plants for the predetermined interval saves or generates at least one determined difference between the amount of energy generated according to the forecast and generation information. The operating points are based on the control information. The determined control information is output.

The present disclosure is directed to a machine learning system for use with a power distribution system. The machine learning system includes a data library, a machine learning module, and an action module. The data library stores a plurality of data samples, where at least a portion of the data samples are associated with one or more intelligent electronic devices (IEDs). The machine learning module processes data samples from the data library using at least one machine learning algorithm and outputs at least one recommendation and/or prediction based on the data samples received. The action module receives the at least one recommendation and/or prediction and performs at least one action based on the recommendation and/or prediction. The at least one action includes outputting at least one communication signal and/or at least one control signal to at least one client or at least one of the one or more IEDs.