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Transformer Monitoring


Advancements in Dissolved Gas Analysis: NEI & Gassing Events

One of the most important steps when looking at DGA data is to decide whether the data support the existence of a fault that is actively breaking down the insulation before you try to use a triangle, pentagon, or gas ratio method to identify a fault type. Otherwise, you are diagnosing random...

TRANSFORMER INRUSH

ABSTRACTHere we discuss the phenomenon of transformer inrush; what it is and its significance to transformer protection design. INTRODUCTIONA couple of years ago in this Transformer Special Edition, we wrote an article that covered the most used transformer protection schemes. As was pointed out...

How to Improve Transformer Protection

Using symmetrical components for fault discrimination in differential protection BY IMRAN RIZVI, ABB Inc. Classical differential protection schemes are subject to ghost differential currents due to current transformer (CT) saturation and magnetization currents. Several methods are used to counter...

Transformer Monitoring

Hydrogen Gas in Transformer Oil

Why event-based fault type identification is better than a sample-by-sample approach

Introduction

Fault type identification is an important step in dissolved gas analysis (DGA). When a significant amount fault gas production is detected in a transformer, we want to know what kind of physical condition could be responsible for the gassing. Knowing the type of fault can help to identify the nature and location of the problem in the transformer. That in turn can also suggest what physical inspections or tests may be warranted in order...

Related Articles


How to Improve Transformer Protection

Using symmetrical components for fault discrimination in differential protection BY IMRAN RIZVI, ABB Inc. Classical differential protection schemes are subject to ghost differential currents due to current transformer (CT) saturation and magnetization currents. Several methods are used to counter...

DGA graphs

Advancements in Dissolved Gas Analysis: Accounting for Gas Loss

Dissolved gas analysis (DGA) in transformers is a very successful periodic screening method to identify transformers that may be having problems. It is a symptom-based assessment of health, rather than a condition-based assessment. That is because the gases themselves do not cause failure, but are...

Smart Transformers: Enhancing Grid Efficiency and Reliability

The evolving demands of modern power grids necessitate the adoption of advanced technologies that can provide enhanced efficiency, reliability, and flexibility. Smart transformers are at the forefront of this technological revolution, offering a range of capabilities that significantly improve the...

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FERC Approves Interconnection for Talen Energy, Amazon Data Center

In a significant move that underscores the growing demand for reliable and sustainable energy to power the expanding digital infrastructure, the Federal Energy Regulatory Commission (FERC) has approved an interconnection agreement between Talen Energy, Amazon Web Services (AWS), and Exelon. This...


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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