A phase sequence adjustment system includes a power conversion circuit and a control circuit. The power conversion circuit is connected to a main power supply with a phase sequence. The control circuit respectively provides a first and a second excitation signals to the power conversion circuit, so as to short the power conversion circuit with the main power supply twice. The control circuit includes a current detection circuit and a control unit. The current detection circuit obtains two current signals respectively during two short-circuit operations. The control unit calculates two current phase angles respectively according to these two current signals and determines whether the phase sequence is positive or negative accordingly. The control unit selects one from the two current phase angles, calculates a voltage phase angle of the main power and a phase angle difference there-between to adjust a feedback phase sequence accordingly.

Techniques for phase identification using feature-based clustering approaches are disclosed. Embodiments employ linear and nonlinear dimensionality reduction techniques to extract feature vectors from raw time series. In an embodiment, a constrained clustering algorithm separates smart meters into phase connectivity groups. Another embodiment clusters smart meter data, where voltage measurements are collected from smart meters and a SCADA system. Then, customer voltage time series are normalized and linear or nonlinear dimensionality reduction is applied to the normalized time series to extract key features. Next, constraints in the clustering process are defined by inspecting network connectivity data. Then, a constrained clustering method is applied to partition customers into clusters. Lastly, each clusters phase is identified by solving a minimization problem. In another embodiment, a machine learning algorithm generalizes a subset of phase connectivity measurements to a distribution network, the algorithm being an extension of a Mapper algorithm in topological data analysis.

Techniques for phase identification using feature-based clustering approaches are disclosed. Embodiments employ linear and nonlinear dimensionality reduction techniques to extract feature vectors from raw time series. In an embodiment, a constrained clustering algorithm separates smart meters into phase connectivity groups. Another embodiment clusters smart meter data, where voltage measurements are collected from smart meters and a SCADA system. Then, customer voltage time series are normalized and linear or nonlinear dimensionality reduction is applied to the normalized time series to extract key features. Next, constraints in the clustering process are defined by inspecting network connectivity data. Then, a constrained clustering method is applied to partition customers into clusters. Lastly, each clusters phase is identified by solving a minimization problem. In another embodiment, a machine learning algorithm generalizes a subset of phase connectivity measurements to a distribution network, the algorithm being an extension of a Mapper algorithm in topological data analysis.

Boundary test circuit, memory and boundary test method are provided. The boundary test circuit may include a plurality of serially-connected wrapper boundary registers (WBRs) and a plurality of toggle circuits (TCs). Each WBR may include a first I/O for receiving an initial test signal and a second I/O for transmitting the initial test signal to the WBR at a succeeding stage. Each TC may include an input for receiving the initial test signal stored in a corresponding WBR, a control I/O for receiving a toggle signal, and an output for transmitting a real-time test signal to the integrated circuit. The toggle signal may be configured to control phase switching of the real-time test signal, and, depending on the toggle signal, the real-time test signal may have a phase identical or inverse to a phase of the initial test signal. This method improves the efficiency and flexibility of the boundary test.

A method includes performing by a processor: receiving a plurality of synchrophasor measurements of a power system signal associated with a time interval from a plurality of phasor measurement units (PMUs), respectively, each of the plurality of synchrophasor measurements including a phase angle, frequency value, and a timestamp associated with the synchrophasor measurement; determining, for each of the plurality of PMUs, a dominant mode frequency of a forced oscillation signal component of the power system signal based on the frequency value and the phase angle; determining, for each of the plurality of PMUs, a mode angle of the forced oscillation signal component at the dominant mode frequency; and determining a geographic forced oscillation source location for a source of the forced oscillation signal component based on the plurality of mode angles associated with each of the plurality of PMUs, respectively, and geographic locations of the plurality of PMUs.

A method includes performing by a processor: receiving a plurality of synchrophasor measurements of a power system signal associated with a time interval from a plurality of phasor measurement units (PMUs), respectively, each of the plurality of synchrophasor measurements including a phase angle, frequency value, and a timestamp associated with the synchrophasor measurement; determining, for each of the plurality of PMUs, a dominant mode frequency of a forced oscillation signal component of the power system signal based on the frequency value and the phase angle; determining, for each of the plurality of PMUs, a mode angle of the forced oscillation signal component at the dominant mode frequency; and determining a geographic forced oscillation source location for a source of the forced oscillation signal component based on the plurality of mode angles associated with each of the plurality of PMUs, respectively, and geographic locations of the plurality of PMUs.

A method includes performing by a processor: determining a phase angle alignment parameter based on a ratio of a phase angle difference and a frequency difference, the phase angle difference comprising a difference between a first phase angle corresponding to a reference synchronized measurement device (SMD) and a second phase angle corresponding to a follower SMD, the frequency difference comprising a difference between a frequency at which the first and second phase angles are measured and a nominal frequency; receiving a first plurality of synchrophasor measurements of a power system signal from the reference SMD; receiving a second plurality of synchrophasor measurements of the power system signal from the follower SMD, the first plurality of synchrophasor measurements and the second plurality of synchrophasor measurements being offset in time relative to each other by a sampling time shift; and aligning phase angles of the second plurality of synchrophasor measurements with phase angles of the first plurality of synchrophasor measurements using the phase angle alignment parameter.

A method includes performing by a processor: determining a phase angle alignment parameter based on a ratio of a phase angle difference and a frequency difference, the phase angle difference comprising a difference between a first phase angle corresponding to a reference synchronized measurement device (SMD) and a second phase angle corresponding to a follower SMD, the frequency difference comprising a difference between a frequency at which the first and second phase angles are measured and a nominal frequency; receiving a first plurality of synchrophasor measurements of a power system signal from the reference SMD; receiving a second plurality of synchrophasor measurements of the power system signal from the follower SMD, the first plurality of synchrophasor measurements and the second plurality of synchrophasor measurements being offset in time relative to each other by a sampling time shift; and aligning phase angles of the second plurality of synchrophasor measurements with phase angles of the first plurality of synchrophasor measurements using the phase angle alignment parameter.

Exemplary methods and systems for building an electrical grid topology and detecting faults in an electrical grid are disclosed herein. In an exemplary embodiment, a method for building an electrical grid topology of an electrical grid comprising a plurality of grid elements, the method comprises sending, from a first signaling module of a plurality of signaling modules of the electrical grid, a mapping signal; receiving, at a second signaling module of the plurality of signaling modules, the mapping signal; and deriving, from the mapping signal, grid characteristics of the electrical grid; wherein the grid characteristics are derived from the mapping signal based on the influence that one or more of the plurality of grid elements has on the mapping signal.

The present disclosure pertains to detection of abnormal, risky, or abberant conditions in a power distribution network and to corresponding trip signals being used to trip open devices such as reclosers upstream of where the abnormal condition is detected. Detection of a missing broadband over power-line signal or of an open circuit between phases of a power distribution circuit may prevent severed conductors from causing a ground fault, therefore avoiding the possibility of fire and dangerous conditions.