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Transformer Software & Technologies


Optimal Transformer Efficiency Using Weighted Average

In order to improve the efficiency of electrical distribution in commercial buildings, the US Department of Energy (DOE) introduced regulations with more stringent minimums on transformer efficiencies in January 2016. This was covered under the Code of Federal Regulations 10 CFR Part 431.192 and...

EFACEC case study

The EFACEC Group is leading the supply of integrated solutions and equipment in the market of power generation, transmission and distribution. The Group forms a complete value chain, from building turnkey projects to equipment manufacture, where integrated solutions are developed and designed in...

Transformer Software & Technologies

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 Matters

Applies machine learning to transformer data for predictive fault detection.
Analyzes DGA, temperature, and vibration trends for early anomaly alerts.
Enhances reliability through automated, data-driven maintenance decisions.

The Shift Toward Predictive Intelligence

Artificial intelligence (AI)...

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Smart Transformers

Maximizing continuous and reliable power output, extending the life of a power transformer, and reducing maintenance costs are just a few of the benefits motivating electric utilities to move toward buying a “smart transformer”, electrical equipment integrated with Smart Grid-enabling software...

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...


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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