In our earlier blog on the transformer, we shared our views on how to detect possible core & winding damage using the Transformer Turns Ratio Meter. The oil which acts as the insulating medium is one of the reasons for internal transformer failure. The oil decomposes mainly due to Thermal, electrical & chemical stress due to continuous operation. The transformer which is in service for a longer duration is more likely to have dissolved gases, even under regular operation.
In this blog post, we are sharing our knowledge & views on real-time internal health monitoring of the transformer with the help of the Dissolve Gas Analysis method. This method helps the Asset management team to take the decision on the operation & maintenance of the transformer in real-time. There are several ways to check or monitor the transformers:
- Bushing monitoring
- Partial discharge
- Dissolved Gas Analyses (DGA) – ’Blood test’ for transformers
DGA is the most efficient way to monitor Power transformers. Power transformers are the most important assets of substations. The reliability in the operation of power transmission and distribution is due to the proper operation and maintenance of power transformers. The parameters that are most used to assess the health of power transformers are dissolved gas analysis (DGA).
Dissolve Gas Analysis: Ref IEC 60599, IEEE C57.104
Dissolved gas analysis (DGA) is the study of gases dissolved in transformer oil. Whenever a transformer undergoes unusual thermal and electrical stresses, certain gases are produced in it due to the decomposition of the transformer oil. When these stresses are not significantly high, the gasses due to the decomposition of transformer insulating oil will get sufficient time to dissolve in the oil. Using Dissolve Gas Analysis of transformer oil, we can able to predict the actual condition of the internal health of a transformer.
In a DGA test, the gases in oil are extracted and analysed to find the number of gases in a specific amount of oil. By analysing the volume, proportions, types and rate of production of dissolved gases, diagnostic information can be collected. Since these gases can tell the faults of a transformer, they are known as “Fault Gases”. DGA techniques have evolved and become so sensitive and accurate at measuring these gases. These gases are produced by insulation decomposition, oil breakdown, oxidation, vaporization and electrolytic action.
Generally, the gases found in the oil in service are Hydrogen (H2), Methane (CH4), Ethane (C2H6), Acetylene (C2H3), Ethylene (C2H4), Carbon Monoxide (CO), Carbon Dioxide (CO2) Oxygen (O2) & Nitrogen (N2).
There are 2 major Causes of Gas Formation:
- Cellulose Decomposition
- Thermal decomposition of oil-impregnated paper insulation
- Oil Decomposition
- Decomposition of hydrocarbon chains occurs due to thermal and electrical faults
Concept of Dissolve Gas Analysis:
1) Transformers when subjected to excessive thermal or electrical stress leads to the formation of gases and dissolve in transformer oil.
2) The detection of these gases generated in a transformer in service is the first indication of a malfunction that may turn into a failure not addressed well in time.
3) DGA is the “BLOOD TEST” of transformers.
DGA can be either :
1. Offline: In this method, periodical manual sampling of oil is taken and analysis can do at the lab. For lab application, Gas Chromatography is the best suitable method.
2. Online: Real-time & fully automatic sampling of transformer oil and analysis with the devices mounted on the Transformer. For online measurement\
Actually, before the invention of online DGA monitoring, the traditional technique was manual sampling and laboratory DGA was in use for the analysis of Gases. As online DGA monitors have derived, new technologies are introduced in the market & because of their real-time monitoring and fault indication in the early phase, ONLINE DGA monitoring becomes more popular.
There are two important online methods which are used to identify the gases in oil,
- Gas Chromatography (GC)
- Non-Dispersive Infra-Red (NDIR)
Advantages of Online DGA:
- Online monitoring detects faults at their early phase & gives a warning on developing faults.
- It enables corrective action before transformer failure occurs
- It will reduce the cost of repair & maintenance
- Majority of Internal faults can be detected with online DGA
- It enables safe use of transformer
- It detects faults which might go unnoticed between regular oil sampling intervals.
- It is one of the most powerful tools in protecting against unexpected asset failures.
SCOPE has collaborated with one of the leading manufacturers “Vaisala” for offering the online DGA solution for critical devices like power transformers. Vaisala is having their patented technology “Transmission NDIR” & with the help of this in real-time, we can identify the deformation of gases in transformer oil. “Vaisala NDIR” Measurement technology (OPT 100) is best for reliable data with no consumables and no need for maintenance. The graphical representation will give more clarity about the Maintenance free performance of OPT 100.
In this blog, we tried to explain what is the need for Dissolve Gas analysis & Importance of Online DGA. This method requires the readings/results have sensitivity and accuracy as compared with the good DGA lab results. Accurate and maintenance-free online DGA monitors using “Transmission NDIR” are used for this purpose. This will help to understand the Fault Gases accurately in real-time & will enable corrective action before another occurrence of any major failure in the transformer. For more information about the subject please write to us at firstname.lastname@example.org
One Reply to “Monitoring the Internal health of Transformer using Dissolve Gas Analyser”
Thanks a lot for sharing excellent details with regard to Condition / Electrical Health monitoring aspects of an oil filled transformers. Hope, the effort would continue to share information towards timely detection of several component degradation simultaneously with advanced tools. Thanks & regards RKJARIAL