A system for energy metering for a building, such as a data center.

A non-transitory computer-readable medium storing a program that causes a computer to execute a process including, calculating, for each of a plurality of groups each of which is a combination of two power distribution lines selected from a plurality of power distribution lines, an index value that indicates a correlation between time-series data of a sum of line currents that flow through the two power distribution lines included in a group and time-series data of consumed power consumed by at least one consuming subject coupled to a transformer coupled to any one of phases that corresponds to combinations of two of the plurality of power distribution lines or current that corresponds to the power; and determining that a phase that corresponds to the group that corresponds to the index value indicating a highest correlation among the plurality of groups is a connection phase to which the transformer is coupled.

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.

Methods, systems, and apparatus, including computer programs stored on a computer-readable storage medium, for obtaining a reference phase signal that is synchronized with an alternating current (AC) phase of a multi-phase electrical power distribution system. The apparatus obtains output signals from sensors, each output signal representative of an electromagnetic emission detected by a respective sensor. The apparatus identifies, based on comparing respective phases of the output signals to the reference phase signal, a particular AC phase of the multi-phase electrical power distribution system associated with a source of the emissions. The apparatus provides an indication of the particular AC phase to a user.

Methods, systems, and apparatus, including computer programs stored on a computer-readable storage medium, for obtaining a reference phase signal that is synchronized with an alternating current (AC) phase of a multi-phase electrical power distribution system. The apparatus obtains output signals from sensors, each output signal representative of an electromagnetic emission detected by a respective sensor. The apparatus identifies, based on comparing respective phases of the output signals to the reference phase signal, a particular AC phase of the multi-phase electrical power distribution system associated with a source of the emissions. The apparatus provides an indication of the particular AC phase to a user.

A system and method for combining a remote audio source with an animatronically controlled puppet includes the steps of entering an audio file on a user client by a person where the audio file is a statement spoken by the person. The audio file is sent to a secondary client that is remote to the user client. The secondary client has a puppet controlled by animatronics. The audio file is received by an audio circuit board that converts the audio file into movement parameters. The movement parameters are sent to at least one servomechanism mounted in the puppet to actuate the animatronics in synchronicity with the audio file. Movement of the puppet is video recorded to define a video file. The audio and video files are combined to define a final video production viewable by the person.

A method of determining a phase misalignment between a first signal generated from a first signal path and a second signal generated from a second signal path may include obtaining multiple samples of the first signal proximate to when the first signal crosses zero wherein the first signal can be approximated as linear; obtaining multiple samples of the second signal proximate to when the second signal crosses zero wherein the first signal can be approximated as linear; based on the multiple samples of the first signal, approximating a first time at which the first signal crosses zero; based on the multiple samples of the second signal, approximating a second time at which the second signal crosses zero; and determining the phase misalignment between the first signal and the second signal based on a difference between the first time and the second time.

A method of determining a phase misalignment between a first signal generated from a first signal path and a second signal generated from a second signal path may include obtaining multiple samples of the first signal proximate to when the first signal crosses zero wherein the first signal can be approximated as linear; obtaining multiple samples of the second signal proximate to when the second signal crosses zero wherein the first signal can be approximated as linear; based on the multiple samples of the first signal, approximating a first time at which the first signal crosses zero; based on the multiple samples of the second signal, approximating a second time at which the second signal crosses zero; and determining the phase misalignment between the first signal and the second signal based on a difference between the first time and the second time.

A method includes performing by a processor: receiving a plurality of power system synchrophasor measurements over a time interval from a plurality of phasor measurement units (PMUs) in a power system, determining a variation in frequency of a power signal generated by the power system based on the plurality of power system synchrophasor measurements, and determining a clock time shift based on the variation in frequency of the power signal.