The present disclosure describes systems and techniques that enhance effectiveness and efficiency of a contingency analysis tool that is used for studying the magnitude and likelihood of extreme contingencies and potential cascading events across a power system. The described systems and techniques include deploying the contingency analysis tool in a high-performance computing (HPC) environment and incorporating visual situational awareness approaches to allow power system engineers to quickly and efficiently evaluate multiple power system simulation models. Furthermore, the described systems and techniques include the power system contingency-analysis tool calculating and coordinating protection element settings, as well as assessing controls of the power system using small-signal nomograms, allowing power system engineers to more effectively comprehend, evaluate, and analyze causes and effects of cascading events against a topology of a power system.

A system for monitoring and analyzing electrical operating parameters of a load (10) in a electric network (20), said system comprising a smart socket (110) arranged to be placed in series between the load (10) and the electric network (20), said smart socket (110) comprising a voltage detection module arranged to measure a voltage value in the electric network (20), as an electric potential difference between the ends of the load (10), a current detection module in the electric network (20) arranged to measure a current value adsorbed by the load (10), when the load (10) is connected to the electric network (20), a control unit connected to the voltage detection module and to the current detection module. In particular, the control unit is arranged to carry out a periodic acquisition of the voltage value in said electric network (20), obtaining a voltage trend over time and a periodic acquisition of the current value adsorbed by the load (10), obtaining a current trend over time. In particular, the control unit comprises a neural network arranged to carry out a training comprising the steps of definition of a number n of events E.sub.i′ association, to each event E.sub.i′ of a number m.sub.i of patterns p.sub.ij of predetermined current and/or voltage trends, extrapolation of characteristic parameters c.sub.ik distinguishing the pattern p.sub.ij associated with the classified event E.sub.i′. The neural network is then arranged to carry out an analysis of the acquired voltage and/or current trend by the definition and the classification of possible anomalous patterns with respect to predetermined voltage and/or current trends.

A system to enable identification of arcing hazards comprises a data storage to store a set of measurements acquired by measurement units of a power distribution system. The system further comprises at least one processor configured to identify candidate arcing events represented by the measurements by using an unsupervised machine learning process, and to train a supervised machine learning classifier for automatic real-time identification of arcing events, by using labeled training data based on the identified candidate arcing events.

A power quality analysis system is configured to carry out a power quality analysis in an electrical environment. The system comprises one or more power consuming units each electrically connected to a main power supply by a multiconductor (multicore) cable and one or more power quality sensors configured to provide one or more power quality analysis measurements. The one or more power quality sensors are clamp-on power quality sensors configured to provide one or more power quality analysis measurements when the clamp-on power quality sensors are clamped onto the outside of or arranged in the proximity of the multiconductor cable. The clamp-on power quality sensors are configured to provide the one or more power quality analysis measurements without being electrically connected to any of the conductors of the multiconductor cable.

Provided are a method and device for identifying an individual appliance through analysis of a harmonic component of a power signal. An operating appliance identification method includes collecting a mixed load signal from a home power distribution network, generating a first candidate appliance list by selecting first candidate appliances among individual appliances registered in an individual appliance harmonic analysis information table based on a ratio of a harmonic component value included in the mixed load signal, generating a second candidate appliance list including second candidate appliances by filtering the first candidate appliances based on a magnitude of the harmonic component value included in the mixed load signal, and identifying an operating appliance among a plurality of appliances connected to the home power distribution network by using the second candidate appliance list.

A power distribution network monitoring system includes a plurality of measuring instruments that are installed at predetermined positions on power lines constituting a power distribution network and configured to perform electrical measurement of the power lines; a data collection relay configured to receive data related to measurement results from the plurality of measuring instruments; an imaging unit that is disposed near the data collection relay and configured to capture an image including the data collection relay; an abnormality detector configured to use the image captured by the imaging unit to detect an abnormality in the data collection relay; and a storage unit configured to store image data taken by the imaging unit. The image data consists of a single image previously captured by the imaging unit. The abnormality detector compares the latest image captured by the imaging unit and the image data stored by the storage unit and determines whether or not an appearance of the data collection relay changes. If it is determined that there is no change in the appearance of the data collection relay, the image data in the storage unit is updated with the latest image captured by the imaging unit.

A method for operating at least two pulse-width-modulated inverters connected to a direct-current supply network. The pulse-width-modulated inverters are each actuated via an actuation signal and operated in an operating point. A phase difference is generated between the actuation signals of the at least two pulse-width-modulated inverters by adapting the actuation signal of at least one of the pulse-width-modulated inverters as a function of operating point information describing the operating points of the pulse-width-modulated inverters.

In order to classify a current waveform of current estimated to be supplied to the same electric instrument, even when an operation mode of an operating electric instrument is unknown, a classification computer includes: a first classification unit to perform first classification of each piece of set information by information being included in each piece of the set information being a combination of waveform information and on/off information, and representing a similarity degree of the waveform information; a second classification unit to perform second classification of each piece of the set information by information being included in each piece of the set information and representing a similarity degree of the on/off information; and a third classification unit to classify the set information by a classification result related to the first classification and the second classification.

Transmission-line voltage measurements in a digital-electricity power system are validated by acquiring a series of transmission-line voltage measurements during a sample period when a transmitter-disconnect device is in a non-conducting state. A numerical analysis is performed to determine a point in time at which AC components in the transmission line have diminished and at which the primary change in the transmission-line voltage measurement values is due to DC decay. A receiver acquires a series of receiver-voltage measurements during the same sample period; and a numerical analysis is performed on the receiver-voltage measurements to determine the point in time at which the AC components have diminished and where the primary change in the transmission-line voltage measurement values is due to DC decay. The transmitter-disconnect device is then placed in a non-conducting state based on an evaluation of those measurements.

Systems and methods to disconnect a faulted region of a power grid are described. For example, a control system may obtain a set of regions of a power grid. The control system may obtain a current magnitude and a voltage magnitude of the power grid. The control system may detect a fault in the power grid based at least in part on the current magnitude. The control system may, from the set of regions, determine a faulted region that the fault is located within based on a voltage magnitude of one or more buses in the power grid, a net change in power with respect to time of one or more regions in the set of regions, or both. The control system may send one or more signals to electrically disconnect the faulted region from the power grid.