An electrical circuit for connecting an electrical measurement device (16), which is used to measure partial discharges in a power grid having an operating voltage in the range of 1-69 kV, and which has an A/D converter (17) for converting a measured voltage pulse into a digital signal and has a microprocessor unit (18) for evaluating the digital signal, with a measurement output of a capacitive voltage testing system (3) of switchgear for the power grid having the operating voltage in the range of 1-69 kV. The electrical circuit (8) has a frequency response matching resistor (9) which is connected between an input line (10) for connection to the live pole of the measurement output and to ground, and has a high-pass filter (11) connected down-circuit of the frequency response matching resistor (9).

An alert presentation apparatus (EMS (200)) acquires the amounts of power consumed by loads connected to a system, and on the basis of the acquired power amounts, presents a load list including the power consumption of each load. This alert presentation apparatus (EMS (200)) presents the load list so as to reduce the frequency at which the loads that are on the load list change.

Embodiments are generally directed apparatuses, methods, techniques and so forth to select two or more processing units of the plurality of processing units to process a workload, and configure a circuit switch to link the two or more processing units to process the workload, the two or more processing units each linked to each other via paths of communication and the circuit switch.

A changeover method of a high voltage direct current (HVDC) transmission system is provided. A first system is set to an active state. A ready signal is transmitted from the first system to a first COL. A ready detection signal and an active signal are transmitted to the first system, in response to the ready signal. A confirm signal is transmitted to the first system in response to the active signal when the ready detection signal matches the ready signal.

Methods and arrangements for localizing an outage in a power grid. An outage is detected in a power grid, the power grid including interconnected nodes. At least one candidate network topology (in the power grid) with respect to the outage is determined, and power consumption information and measured voltages relative to the nodes in the power grid are received. Voltage at a plurality of the nodes in the power grid is estimated based on the received power consumption information and on the at least one candidate network topology, and a location of the outage is estimated, based on the estimated node voltages and measured voltages. Other variants and embodiments are broadly contemplated herein.

Systems and methods for identifying a fault condition in an Ungrounded Electrical Distribution (UED) system, the system receives measurements with instantaneous values and effective values associated when a fault event is identified, measured transient waveforms and a fault type. A processor applies an empirical mode decomposition to the measured transient waveforms to extract a dominant vibration mode and an associated derived waveform corresponding to the dominant vibration mode. A Hilbert transform is applied to the associated derived waveform to obtain a set of feature attributes. Subsets are computed from the set, at a pre-fault time, at a fault inception time, and at a post-fault time, and inputted into the fault type trained neural network model. An output of the model are locational parameters used to determine a fault section, a fault line segment and a fault location point with a topology connectivity analysis of the UED system.

A fault identification may be triggered by a component of a power generation system (PGS), such as a hardware component, a controller of a hardware component, a device of the PGS, a computer connected to the PGS, a computer configured to monitor the PGS, and/or the like. The fault identification may be the result of a failure of a component of the PGS, a future failure of a component of the PGS, a routine maintenance of the PGS, and/or the like. The fault is converted to a notification on a user interface using a mapping of faults, root-causes, notification rules, and/or the like. The conversion may use one or more lookup tables and/or formulas for determining the impact of the fault on the PGS, and/or the like.

A method analyzes a fault of an ungrounded power distribution system. The method determines a type of a fault in a line segment of the ungrounded power distribution system, and modifies a nodal admittance matrix of the line segment determined before the fault using a transformation matrix corresponding to the type of the fault to produce a faulty nodal admittance matrix of the line segment after the fault. The ungrounded power distribution system is analyzed using the faulty nodal admittance matrix and nodal admittance matrices of functional branches or line segments of the power distribution system.

Systems and methods performed by a fault detection apparatus for fault detection and localization in distribution feeders having branches and nodes. The method including receive feeder raw data in a feeder of a power system. Process the feeder raw data with given operational electrical characteristics of the feeder to generate a branch attribute dataset for each branch separated by a pair of nodes for all branches. Generate a node attribute dataset for each node for all the nodes in the feeder. Input the branch and node attribute datasets into a trained neural network to determine whether a branch has a fault and a fault location within the branch, to output a classification of the fault and the fault location. Generate an alert signal based upon determining the classified fault and fault location in response to the alert signal to an outage response system.

The present invention discloses an edge-cloud collaborative fault detection method for a low-voltage distribution network based on a random matrix theory. An edge-cloud collaborative way is adopted, including fast fault detection running in an edge IoT agent and fault timing and locating analysis running in a distribution network control center. At an edge IoT terminal, the fault is quickly detected based on time-delay correlation analysis, a long-time series model is constructed, a time series is fitted with an autoregressive moving average model, and the fault is quickly judged based on a typical value of a limit spectral density function of the time series; after the edge IoT terminal detects the fault, fault-related data are uploaded to the distribution network control center through data screening, historical data and real-time data are integrated, and a spectral deviation index is configured to perform fault timing and locating analysis.