Disclosed is state trajectory prediction in an electric power delivery system. Electric power delivery system information is calculated from measurements by intelligent electronic devices (IEDs), and communicated to a state trajectory prediction system. The state trajectory prediction system may be configured to generate a load prediction profile. The load prediction profile may provide a predicted response of a load at a future time. Further, the state trajectory prediction system may be configured to generate a generator prediction profile that provides a predicted response of a generator at a future time. The state trajectory prediction system may generate a state trajectory prediction based, at least in part, on the load prediction profile and the generator prediction profile. The state trajectory prediction may represent a future state of the electric power delivery system.

A power supply unit for an IED for LV or MV electric power applications characterized in that it comprises: a power transformer stage, which is operatively coupled to a feeding conductor to harvest electric power from said feeding conductor; a first storage stage, which is electrically connected to said power transformer stage to store electric energy; a first step-down conversion stage, which is electrically connectable/disconnectable to/from said first storage stage; a switching stage adapted to electrically connect/disconnect said first step-down conversion stage with/from said first storage stage; and a second storage stage, which is electrically connected to said first step-down conversion stage to store electric energy.

A control command apparatus in a power system selecting a measuring apparatus according to a power system state, includes: a measuring apparatus extraction unit (112) extracting a measuring apparatus (2) between a first and second control apparatus (3) downstream the first control apparatus (3), or a measuring apparatus (2) downstream the first control apparatus (3) if no second control apparatus (2) exists, when a predetermined condition is satisfied, based on system configuration information (121), and generating measuring apparatus information (123) associating the extracted measuring apparatus (2) and the first control apparatus (3) with each other; and a control command generation unit (114) acquiring a measurement value from the measuring apparatus (2), identifying a control apparatus (3) associated with the measuring apparatus (2) as a the measurement value source based on the measuring apparatus information (123), and calculating and outputting a control parameter to the identified control apparatus (3).

An electrical panel or an electrical meter may provide improved functionality by interacting with a smart plug. A smart plug may provide a smart-plug power monitoring signal that includes information about power consumption of devices connected to the smart plug. The smart-plug power monitoring signal may be used in conjunction with power monitoring signals from the electrical mains of the building for providing information about the operation of devices in the building. For example, the power monitoring signals may be used to (i) determine the main of the house that provides power to the smart plug, (ii) identify devices receiving power from the smart plug, (iii) improve the accuracy of identifying device state changes, and (iv) train mathematical models for identifying devices and device state changes.

A system for autonomous control in power systems is disclosed. In particular, a secure overlay communication model (“SOCOM”) is disclosed, the system including a combination of hardware and software for detecting power grid states, and determining appropriate actions for addressing detected states. The SOCOM is a logic-based system deployed onto computing devices such as field programmable gate arrays installed at bus controllers, Supervisory Control and Data Acquisition Systems (“SCADAs”), Intelligent Electronic Devices (“IEDs”), or other computing devices in power grid stations and substations. The logic-based nature of the SOCOM allows for seamless integration with preexisting power system equipment. In response to detecting various power grid faults such as line failures and over-current states, the system automatically rearranges power line configurations at the power stations and/or substations. The SOCOM further provides improvements relating to optimal power flow, cost-based power distribution, load management, voltage/volt-amp reactance (“VAR”) optimization, and self-healing.

A method for quantifying power quality events in an electrical system including a plurality of intelligent electronic devices (IEDs) includes processing electrical measurement data from or derived from energy-related signals captured by at least one first IED of the plurality of IEDs to identify a power quality event at a first point of installation of the at least one first IED in the electrical system. An impact of the power quality event at a second point of installation in the electrical system is determined based on an evaluation of electrical measurement data from or derived from energy-related signals captured by at least one second IED of the plurality of IEDs at the second point of installation proximate to a determined time of occurrence of the power quality event at the first point of installation.

A method for characterizing power quality events in an electrical system includes deriving electrical measurement data for at least one first virtual meter in an electrical system from (a) electrical measurement data from or derived from energy-related signals captured by at least one first IED in the electrical system, and (b) electrical measurement data from or derived from energy-related signals captured by at least one second IED in the electrical system. In embodiments, the at least one first IED is installed at a first metering point in the electrical system, the at least one second IED is installed at a second metering point in the electrical system, and the at least one first virtual meter is derived or located at a third metering point in the electrical system. The derived electrical measurement data may be used to generate or update a dynamic tolerance curve associated with the third metering point.

A system for analyzing energy usage measures one or more parameters indicative of energy usage for a plurality of sub-circuits, where the sampling rate for the measuring is substantially continuous, and automatically transmits information related to at least one of the measured parameters at a rate that enables monitoring of current energy usage. The system further detects a significant change in a measured parameter, determines whether the significant change in the measured parameter is caused by a change in energy usage, and automatically transmits information related to the significant change in the measured parameter caused by the change in energy usage after detecting the significant change.

Embodiments of present disclosure relates to a modular interconnection device (MID) and an electrical network system. The MID comprises a modular port assembly, a node, a converter and a local controller. The modular port assembly is configured to transmit alternating current and/or direct current. The node is coupled to an AC source via a first switch and the modular port assembly. The first switch is configured to selectively disconnect the modular interconnection device from the AC source. The converter is coupled to the node via a second switch and coupled to a DC source via a third switch. The converter is configured to convert the AC current into DC current or convert DC current into AC current. The local controller is coupled to the first, second and third switches and configured to control operation of the first, second and third switches.

A method for analyzing power quality events in an electrical system includes processing electrical measurement data from or derived from energy-related signals captured by at least one metering device in the electrical system to generate at least one dynamic tolerance curve. Each dynamic tolerance curve of the at least one dynamic tolerance curve characterizes a response characteristic of the electrical system at a respective metering point in the electrical system. The method also includes analyzing the at least one dynamic tolerance curve to identify special cases which require further evaluation(s)/clarification to be discernable and/or actionable. The at least one dynamic tolerance curve may be regenerated or updated, and/or new or additional dynamic tolerance curves may be generated, to provide the further clarification. One or more actions affecting at least one component in the electrical system may be performed in response to an analysis of the curve(s).