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Transformer Monitoring


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...

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...

Transformer Monitoring

hydrocarbon gas emission

Advancements in Dissolved Gas Analysis: Data Quality

Introduction
There is more to DGA interpretation than comparing the latest gas concentrations to limits in a table or plotting them in a triangle or pentagon to identify the apparent fault type. We have found that the whole DGA history of a transformer must be considered when interpreting its most recent DGA results.
Trend evaluation and accurate assessment of short-term changes require accuracy and low measurement variability of gas data. Data quality problems must be...

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Distribution Transformer Loss Costs

A car owner must make some important decisions when purchasing a new vehicle—particularly if he or she has not bought one in decades. The features of the hundreds of 2015 models available can seem overwhelming. The budget-conscious owner, considering factors such as fuel efficiency,...

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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...

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...


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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