Ge Infrastructure Technology, LLC

Ge Vernova Infrastructure Technology LLC

General Electric Technology Gmbh

Mitalkumar Kanabar

Masoud Abbaszadeh

Subhrajit Roychowdhury

Hengxu Ha

Prabhakar Neti

Balakrishna Pamulaparthy

Ihab Hamour

Balamourougan Vinayagam

Vijayasarathi Muthukrishnan

Sankara Subramanian Srigopalakrishnamurthi

Sudhanshu Mishra

Akilezkrishnamurthy Arthanari

Rajagopal Kommu

Pubudu Eroshan Weerathunga

Austin Byrne

Umar Naseem Khan

Claudia Cosoreanu

A system for dynamic rating of a power grid may include a plurality of terminal units, and a controller. The terminal units may detect a voltage phasor and a current phasor at nodes of the power grid. The controller may, based on the voltage phasors and the current phasors of the plurality of nodes, determine a dynamic thermal stability power rating for each line, a dynamic angular stability power rating for each node, and a dynamic voltage stability power rating for each node. The controller may, based on the dynamic thermal stability power rating, the dynamic angular stability power rating, and the dynamic voltage stability power rating, determine a dynamic system rating for the power grid. The controller may control the power grid in response to the dynamic system rating.

Systems and methods for dynamic rating of power grids

Systems and methods are disclosed for asset health assessment and fleet management. An example method may include classifying a first power system asset into a first sub-system and a second sub-system. The example method may also include measuring, by a processor of a protection relay and from a first power system asset, electrical, thermal, and/or mechanical data associated with the first power system asset. The example method may also include identifying a first fault feature for the first sub-system, wherein the first fault feature is influenced by load oscillations in the first power system asset. The example method may also include comparing the first fault feature to a second fault feature of a third sub-system in a second power system asset, wherein the second fault feature is the same as the first fault feature, and wherein the second fault feature is not associated with load oscillations. The example method may also include adjusting a threshold value based on the comparison of the first fault feature to the second fault feature of the third sub-system. The example method may also include calculating, by the processor and for a first sub-system of the first power system asset, a first value based on the electrical, thermal, and/or mechanical data. The example method may also include calculating, by the processor, based on the first value, and using recent measurement data, a second value associated with the first sub-system. The example method may also include calculating, by the processor and using historical average data, a third value associated with the first sub-system. The example method may also include determining, by the processor and based on the second value and the third value, a fourth value associated with the first power system asset. The example method may also include determining, by the processor, that the fourth value is greater than a threshold value. The example method may also include generating, by the processor, a warning based on the determination that the fourth value is greater than the threshold value.

Systems and methods for integrated condition monitoring for power system asset health scoring

Systems and methods for power system switching element (PSSE) anomaly detection are disclosed. An example PSSE anomaly detection unit may include a power system switching element position estimator (PSSEPE) and a comparison unit. The PSSEPE may be configured to receive a set of measurements and a set of control commands associated with a PSSE, calculate an anomaly confidence score based on the set of measurements and the set of control commands, and estimate a calculated PSSE position based on the set of measurements and the set of control commands. The comparison unit may be configured to receive the calculated PSSE position from the PSSEPE, receive the set of measurements and the set of control commands from the PSSEPE, receive a reported PSSE position associated with the PSSE, and determine a PSSE anomaly decision based on a difference between the reported PSSE position and the calculated PSSE position.

Systems and methods for power system switching element anomaly detection

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Markham, Canada

Mitalkumar Kanabar