General Electric Company

Ge Infrastructure Technology, LLC

General Electric Renovables Espana, S.l.

Ge Vernova Renovables Espana, S.l.

General Electric Technology Gmbh

Sumitha Mohan

Kasi Viswanadha Raju Gadiraju

Shanmuga-Priyan Subramanian

Benjamin Palethorpe

Ali Shahid

Allen Michael Ritter

Govardhan Ganireddy

Rajni Kant Burra

Minesh Ashok Shah

Balakrishna Pamulaparthy

Akshay Ambekar

Rajagopal Kommu

Murali Mohan Baggu Data Venkata Satya

Raju Gurrapu

Sergio Dominguez Ruiz

Arvind Kumar Tiwari

Rupam Mukherjee

Santhosh Kumar C

Akshay Krishnamurty Ambekar

Murali Mohan Baggu Data Kenkata Satya

A method for operating a wind farm having a string (S-S) of wind turbines (-) which are electrically connectable with each other and a grid () via power connections (Cab-Cd) is disclosed. Each wind turbine includes a rotor () with rotor blades (), and a power conversion system () mechanically connected with the rotor (). The method includes disconnecting the string (S-S) from the grid (), and identifying a primary wind turbine () of the disconnected string (S-S) which is electrically connectable with at least one secondary wind turbine (-) of the disconnected string (S-S). The power conversion system () of the primary wind turbine () includes a reactive power capability (RPC) that at least matches a reactive power (RP) of a cluster (C, C, C) to be formed by electrically connecting the primary wind turbine () with the at least one secondary wind turbine (-) of the disconnected string (S-S).

Method for operating a wind farm and a wind farm

The present disclosure relates to systems and methods for improved anomaly detection for rotating machines. An example method may include determining a rotational speed of a rotating machine; determining, using a frequency domain transform of a signal, a frequency domain signal; determining, based on the rotational speed, a first frequency band within the frequency domain signal for identifying a fault frequency; determining a fault frequency within the first frequency band; determining, based on the fault frequency, a second frequency band within the first frequency band, wherein the second frequency band includes the fault frequency; determining, based on the second frequency band, a first fault index and a baseline of the first fault index; determining, based on a deviation of a second fault index from the baseline, a fault condition; and providing an alert based on the fault condition.

Anomaly detection for rotating machines

A method for operating a wind farm having a string (S-S) of wind turbines (-) which are electrically connectable with each other and a grid () is disclosed. Each wind turbine includes a rotor () with rotor blades (), a power conversion system () mechanically connected with the rotor (), and at least one auxiliary subsystem (). The method includes operating the wind turbines of the string in an island operating mode in which the wind turbines are not connected with the grid, and the respective at least one auxiliary subsystem is supplied with electric power generated by the power conversion system of the respective wind turbine; detecting that the rotor of one of the wind turbines is exposed to a wind condition at which at least one of the rotor blades is at risk of stalling at the currently generated electric output power; and increasing the electric power generated by the power conversion system of the one of the wind turbines by an electric power amount which is sufficient for suppling the at least one auxiliary subsystem of at least one of the other wind turbines of the string.

Systems and methods are disclosed for improved fault diagnostics of electrical machines under dynamic load oscillations. The systems and methods may rely on one or more different algorithms for performing such fault diagnostics. One example, algorithm may involve determining a ratio of an instantaneous real power and a reactive power of the motor.

Systems and methods for improved fault diagnostics of electrical machines under dynamic load oscillations

Systems, methods, and computer-readable media are disclosed for monitoring and diagnosing power system assets. An example method may include triggering, by a gateway device and at a first time, a capture of a first waveform from a first intelligent electronic device (IED) associated with a first asset in a power system. The method may also include transmitting, by the gateway device, the capture of the waveform to a remote device. The method may also include extracting fault features from the first waveform corresponding to different failure modes associated with the asset of the power system. The method may also include determining, based on the features extracted from first waveform, that a fault of a first fault mode has occurred in the asset. The method may also include providing an alert that the fault has been identified, wherein the alert initiates or otherwise facilitates a control action in the power system.

Systems and methods for monitoring and diagnosing power system assets

A system for commissioning a wind turbine is provided. The system includes a test wind turbine, one or more additional wind turbines coupled to the test wind turbine, and a control system. The control system includes a first control module for controlling the one or more additional wind turbines to act as a power source and provide power to the test wind turbine. The control system also includes a second control module for controlling the one or more additional wind turbines to act as a load for dissipating test power generated by the test wind turbine.

System and method for commissioning wind turbines

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Bengaluru, India

Sumitha Mohan