A method includes steps: 1) obtaining monitoring information of different monitoring points in normal state of power equipment; 2) setting faults and obtaining monitoring information of different fault types, positions, monitoring points of the equipment; 3) taking the monitoring information obtained in steps 1) to 2) as training dataset, taking the fault types and positions as labels, inputting the training dataset and the labels to deep CNN for training; 4) collecting monitoring data, performing verification and classification using step 3), obtaining probability values corresponding to each of the labels; 5) taking classification results of different labels as basic probability assignment values, with respect to a monitoring system composed of multiple sensors, taking different sensors as different evidences for decision fusion, performing fusion processing using the DS evidence theory to obtain fault diagnosis result. The invention can intelligently realize fault detection, fault type determination, and fault positioning of the power equipment.

A fault isolating device for use in a microgrid disconnected from a main power grid includes a voltage meter for detecting a voltage anomaly indicative of an electrical fault, a timer for establishing a time window that begins and ends a predetermined time after a voltage anomaly is detected, a switch that is opened at the start of the time window, and a microcontroller that determines whether to leave the switch open to isolate a faulted portion of the microgrid or to close the switch. A plurality of fault isolating devices can be distributed throughout a microgrid to isolate a faulted branch or faulted branches of an islanded microgrid without interfering with normal fuse operation when the microgrid is connected to the main power grid.

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.

A method for automatically categorizing disturbances in an electrical system includes capturing at least one energy-related waveform using at least one intelligent electronic device in the electrical system, and processing electrical measurement data from, or derived from, the at least one energy-related waveform to identify disturbances in the electrical system. In response to identifying a disturbance in the electrical system, each sample of the at least one energy-related waveform associated with the identified disturbance is analyzed and categorized into one of a plurality of disturbance categories. The disturbance categories may include, for example, (a) voltage sags due to upline electrical system disturbances, (b) voltage sags due to downline electrical system faults, (c) voltage sags due to downline transformer and/or motor magnetization, and (d) voltage sags due to other downline disturbances.

Provided is a method for analyzing the stability of a PMSG-WT connected to a weak power grid considering the influence of power control. New energy power generation mostly uses a perturbation and observation (P&O) method for maximum power point tracking, and nonlinear discontinuous links therein make stability analysis difficult. The present application analyzes the stability of the PMSG-WT connected to the weak grid system based on a describing function method, and fully considers the nonlinear discontinuous links in the power loop, thus making the analysis result more accurate. At the same time, the describing function method is a method that can quantitatively calculate the frequency and amplitude of oscillation. The analysis method of the present application can provide a powerful and good reference for oscillation suppression and controller design.

A method for detection of a sub-synchronous oscillation in a power system includes measuring a three-phase measurement signal of an electric system value, analyzing the measurement signal to detect an oscillation component of the measurement signal having an oscillation frequency lower than a system frequency of the power system, deciding whether the detected oscillation component at the oscillation frequency qualifies as a sub-synchronous oscillation, and disconnecting a generator from the power system that might be affected by the sub-synchronous oscillation. To detect sub-synchronous oscillations with low computational effort and good accuracy, an amplitude of each phase of the oscillation component is calculated and compared against a threshold, a sub-synchronous oscillation is detected upon exceeding the threshold during a given time delay, and a fault signal is generated upon detecting a sub-synchronous oscillation. A device having a processing unit is also provided.

A method for controlling an energy network includes transmitting a respective offer message by using a plurality of agent devices, each agent device being assigned to a subnetwork of the energy network, and each offer message indicating a subnetwork-specific measure for controlling the respective subnetwork and a period for which the subnetwork-specific measure is offered. A network control arrangement is used for receiving the offer messages, and identifying an undesirable network state of the energy network. A subnetwork-specific measure is selected from the plurality of subnetwork-specific measures, and an acceptance message is transmitted to that agent device which sent the offer message containing the selected subnetwork-specific measure by using the central network control arrangement. A corresponding agent device, a corresponding network control arrangement and a system including an agent device and a network control arrangement are also provided.

A method for controlling a power grid includes using a communication device to receive first data messages with first phasor measurement data from a first phasor measurement unit. A reference device is used to determine a deviation between the first phasor measurement data and reference data. The first phasor measurement data are recognized as plausible when the deviation lies below a previously defined upper threshold value and/or above a previously defined lower threshold value. A corresponding grid control arrangement is also provided.

A system that detects temperature and current events in a power grid is provided. The system includes at least one sensor associated with an electric meter; a plurality of bus bars connected to the electric meter; at least one temperature sensor uniquely associated with each of the plurality of bus bars; and at least one current sensor uniquely associated with each of the plurality of bus bars. The system detects a plurality of temperatures and/or currents and compares the detected plurality of temperatures and/or currents to expected thresholds or threshold ranges for temperatures and/or currents in the system to provide a comparison result and determines if a notification related to temperature and/or current events in the system should be sent based on the comparison result.

A method for recovering missing phase measurement unit (PMU) measurements from a plurality of PMUs is provided. The method comprises: receiving a plurality of obtained PMU measurements from the plurality of PMUs; populating a PMU dataset based on the plurality of obtained PMU measurements; determining a plurality of missing entries within the PMU dataset, wherein each of the plurality of missing entries indicates a missing PMU measurement within the PMU dataset at a particular time; determining a plurality of substitute entries for the plurality of missing entries based on an optimization algorithm that determines differences associated with a missing entry, of the plurality of missing entries, and a first set of PMU measurements, of the plurality of obtained PMU measurements, that are taken immediately prior to the missing entry; and inserting the plurality of substitute entries into the PMU dataset to generate a new PMU dataset.