TRANSFORMER MAINTENANCE

For the maintainance of the transformer we generally go for these inspections

1.we take the reading of the main oil gauge(MOG) on the conservator tank.

2.we check the color of the silica gel in the breather.

3.we check the cooling system of the transformer if any pumps or fans are there.

4.function of the protection system is checked and on yearly basis the mechanical function of the Bucholz relay is checked.

5. Working of the PRV(Pressure releasing valve) is checked.

And there are many other tests are carried out,depending upon the transformer ratings.

Transformer is an important device in power system. So its maintenance is very much important. Following are the maintenance done in a transformer.

DAILY MAINTENANCE

1. Ambient temperature
2. Winding Temperature
3. Load and voltage

WEEKLY MAINTENANCE

1. Oil level- If oil level is low, top up should be done.

MONTHLY MAINTENANCE

1. Relief Diaphragm - Replace if broken or cracked.
2. Dehydrating breather- If found pink change it.
3. Buchholz Relay- Rectify or replace defective contacts.
4. Insulation Resistance Test of winding

QUARTERLY

1. Bushings- Examine for crack or dirt.
2. O.L.T.C Overhauling- Check O.L.T.C for proper functioning. All the moving contacts should be cleaned.

HALF-YEARLY

1. Cooler fans, bearings, motor and control mechanism- Replace burnt or worn out parts. Lubricate bearing. Examine contacts, controls and interlocks.
2. Oil cooler- Test for pressure.

YEARLY

1. Transformer oil- Check for sludge.
2. Check oil filled bushings, gasket, cable box
3. Examine relays, alarms and circuits.
4. Check earth resistance

We need to do condition based maintenance of a transformer. The reliable operation of the power transformers can be ensured by evaluating the condition of the main components in the power transformers.

The main components are the core, insulation paper, windings, main tank, bushings, cooling system, oil, and on load tap changer. Failure pattern of large transformers are useful to prioritize maintenance scheduling though considering the transformers that do not have serious problems are also important. Considering the economic value of power transformers, their role in transmission and distribution network ,they are utilized to the maximum capacity level with the use of online monitoring systems that abruptly prevents unexpected failures.

The time based maintenance and replacement procedures which involves unpredictable failures consumes more man power, time and money is not beneficial in the current economic situation. 

The condition based maintenance deploying online monitors, precisely assess the condition of the transformer and moreover it clearly indicates the maintenance actions to be taken at that instant. New advanced monitors and sensors are now available in the electrical industry for monitoring the transformer parameters throughout it’s life time.

The data required for condition maintenance can be obtained from direct field assessment by the monitors. Mostly the parameters measured are used to perform Degree of polymerization, DGA (dissolved gas analysis), and Furan analysis. Each fault can be identified by their distinctive pattern they exhibit. Minimum of two consecutive samples should be examined for the confirmation of the fault. Thus data obtained from these diagnostic methods are used as input information for the expert system. After reviewing the results and comparing it with the preset values the expert system has to move with decision making process to decide what maintenance measures to be taken

Expert systems are programmed in such way that when the diagnosed values are found to be abnormal they are all set to give an alarm signal to the system operators. Some systems have been scheduled for the strike of PD (partial discharge) signals in transformer successfully, and they can also locate the origin of the discharge. Modern computing technologies have enhanced transformer preventive maintenance.The recent advancement in artificial intelligence (AI) modelling techniques has empowered power engineers to develop a adaptable and functional AI software to diagnose the faults that occurs in the transformer. The deploying of expert systems offers the choice of reducing the manpower and financial constraints required by utilities to analyze transformer condition.

Thus the condition based transformer preventive maintenance is found to be cost effective by avoiding capital intensive procedures in avoiding unplanned outages due to failure of the transformer. It also enhances the equipments working life and energy saving. It is effective by reducing the risks of failures and hence ensures reliability.