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Electrochemical sensor for predicting transformer overload by phenol measurement
Timothy Bosworth1, Steven Setford, Richard Heywood
1Cranfield Centre for Analytical Science, Cranfield University, Silsoe, Beds, UK.
Talanta
|October 31, 2008
Summary
New polyphenol oxidase (PPO) sensors can detect phenol in transformer oil, predicting transformer overload. The oxygen electrode sensor offers superior accuracy for monitoring transformer health and preventing failures.
Area of Science:
- Electrochemistry
- Biotechnology
- Power Systems Engineering
Background:
- Transformer overload poses significant safety and economic risks to the power transmission industry.
- Phenol levels in transformer oil indicate overload risk due to the degradation of phenol-formaldehyde resins.
- Accurate and timely phenol measurement is crucial for preventing transformer failures.
Purpose of the Study:
- To develop and evaluate novel polyphenol oxidase (PPO) based sensors for measuring phenol in transformer oil.
- To assess the performance of two sensor types: oxygen electrode and screen-printed electrode (SPE).
- To provide a tool for at-site monitoring of transformer oil to prevent failures.
Main Methods:
- Development of two PPO sensors utilizing enzymatic oxygen consumption (oxygen electrode) or o-quinone reduction (SPE).
- Preparation of ex-service transformer oils via aqueous extraction or direct dilution in propan-2-ol.
- Comparison of sensor performance against the International Electrotechnical Commission (IEC) standard method.
Main Results:
- Both sensors demonstrated sensitivity and reliability in measuring phenol.
- The oxygen electrode sensor showed higher accuracy, especially at low phenol concentrations, compared to the SPE.
- The SPE offers greater simplicity for potential field-based applications.
Conclusions:
- PPO-based sensors provide a viable method for detecting phenol in transformer oils.
- The oxygen electrode sensor is more accurate, while the SPE is more suitable for on-site use.
- These sensors can serve as rapid screening tools for at-site monitoring, enhancing transformer reliability and reducing failures.
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