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Transformer Monitoring



Dielectric Voltage Testing – Standard Methods

There are two standard methods from ASTM International: D877, Standard Test Method for Dielectric Breakdown Voltage of Insulating Liquids Using Disk Electrodes, and D1816, Standard Test Method for Dielectric Breakdown Voltage of Insulating Oils of Petroleum Origin Using VDE Electrodes. VDE stands...

FERC Complaint Targets Duke, PJM Transmission Planning

A coalition of large energy consumers and ratepayer advocates has filed a complaint with the Federal Energy Regulatory Commission (FERC), urging the agency to prohibit transmission owners from independently planning "local" transmission projects exceeding 100 kilovolts (kV). The coalition argues...

Transformer Monitoring

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Case Study: Rapid Changes in Bushing Health

Introduction
Continuous online monitoring of bushings provides real-time information which can result in the early detection of a possible failure.

Challenge: A Major Alarm
A prominent U.S. utility was looking for a way to improve system reliability for their 138kV assets. They researched and reviewed options available on the market that included affordable bushing monitoring. After review, the utility chose to pilot the Dynamic Ratings’ C50 Transformer Monitor to see if it was worth the...

Related Articles


FERC Complaint Targets Duke, PJM Transmission Planning

A coalition of large energy consumers and ratepayer advocates has filed a complaint with the Federal Energy Regulatory Commission (FERC), urging the agency to prohibit transmission owners from independently planning "local" transmission projects exceeding 100 kilovolts (kV). The coalition argues...

Zensol new instrument for OLTC testing

According to CIGRE A2.34, the dynamic resistance measurement or DRM (OFFLINE) is a test that offers diagnostics for several diverter or selector switch malfunctions such as: contact problems, broken springs, broken transition resistors, poor contact pressure, inadequate transition time, momentary...


The Role of AI and Machine Learning in Predicting Transformer Faults

AI and Machine Learning can predict transformer faults by analyzing dissolved gas data, thermal patterns, and vibration trends to identify insulation degradation, detect anomalies, and prevent costly power transformer failures before they occur. Why AI Integration into Transformer Diagnostics...

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