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In order to increase the substation’s transformation capacity, Furnas substation in the city of Campinas, received a new bank of 345-138/13,8kV 150MVA single phase, auto-transformers with on load shunt changers, comprised of two phases manufactured by Jeumont/Vatech (France) in 2001 and one phase ASEA, year 1975.

Moving with the general trend of migration from preventive to predictive maintenance, the Jeumont transformers were specified by Furnas, using a contract amendment, for delivery already equipped with sensors and on-line monitoring system. This scope also included the modernization of the ASEA phase by installing sensors fopr monitoring and substitution of electro-mechanical devices by Intelligent Electronic Devices (IEDs).

The outcomes achieved by operating with this online monitoring system on the field will be shown, including the occurrence of a defect in one of the phases of the bank during the period when the system was being installed, with a part of the data capture system already in operation.

We will also show how the readings obtained in the implementation phase helped in investigating the causes for the occurrence.


Furnas Centrais Elétricas S.A. Roberto Albuquerque
Treetech Sistemas Digitais Ltda. Marcos E. G. Alves


With 1720MVA of installed capacity, the Campinas Substation is one of the most important for FURNAS’s transmission system, and is also the venue of one of the company’s four regional operating centers, responsible for the trunks that feed the greater São Paulo.

In order to increase the substation’s transformation capacity, Furnas substation in the city of Campinas, received a new bank of 345-138/13,8kV 150MVA single phase, auto-transformers with on load shunt changers, comprised of two phases manufactured by Jeumont/Vatech (France) in 2001 and one phase ASEA, year 1975.

The current energy market scenario in the world has led companies to operating in an unprecedented competitiveness context, forcing on them a constant search for higher efficiency, better delivery quality and lower costs. Together with this general trend, there has been the migration from preventive to predictive maintenance, which had FURNAS order the Jeumont transformers with delivery specifications including equipped with on-line monitoring sensors and system.

In addressing this specification, the auto-transformer bank was equipped with a Treetech SIGMA on-line monitoring system. This scope also included renovation of the Asea phase by installing the sensors required for on-line monitoring.


The Sigma on-line monitoring system is comprised in three main parts, listed below:

  • Data capture
  • Means of communication
  • Data storage, treatment and availability.

2.1 - Data capture

Capture of readings with transformers in regular operation is done by way of sensors, that can be connected using two differentmain types of architecture:

  • Architecture base dona centralizer element located on the transformer casing, usually a PLC (Programmable Logical Controller), and
  • A decentralized architecture, base don IEDs (Intelligent Electronic Devices) located on the transformer casing.

In choosing the architecture to use with the Sigma system, the inherent features of each of these two types were taken into account as shown in Table 1.

Feature comparison between Centralized and Decentralized Architectures

Centralized Architecture (PLCs)Decentralized Architecture (IEDs)
Centralized system – the PLC concentrates the information coming from every sensor and sends them to the next superior hierarchical level.Decentralized system, where sensors are IEDs (Intelligent Electronic Devices) that send information directly to the next superior hierarchical level.
The centralizer element (PLC) is na additional failure point for the system.There is no centralizer element, thus eliminating a possible failure point.
Sensors must be dedicated for connection to the PLC, thus leading to eventual duplication of sensors and additional costs in monitoring systems.IEDs already part of control and protection systems can be integrated into the data capture and monitoring systems, thus avoiding costs with additional sensors.
Failure in the PLC leads to loss of all system functions. Failure in IED leads only to loss of part of the functions – the remaining ones continue in operation.
The centralizing element (PLC) represents additional costs in installing, programming and system maintenance.There is no centralizing element – additional costs are eliminated.
Centralized system, more difficult to implement expansions and maintenances.Naturally modular system, facilitating expansions and maintenance.
Typical maximum operating temperature 55ºC [3]. Installing close to main equipment (for example, transformers) is not advisable.Operating temperature range -40 to +85ºC, suitable for installing in Substation yard on main equipment.
Installation recommended in control room – large number of cables linking to yard.Typical installation is on main equipment, in yard – only serial communication (twisted pair or opticalfiber) to link with control room.
In general, tested for deployment in industrial environments [3].Tested for adverse conditions of outdoor applications in substation yard environments in accordance with IEC standards: electromagnetic compatibility, temperature, vibration.
Em geral, testado para aplicação em ambiente industrial [3].Testado para as condições adversas de ambiente de subestação de acordo com as normas IEC: compatibilidade eletromagnética, temperatura, vibração.
Serial communication ports do not support surges, impulses and induction existing in substation, forcing the deployment of optical fiber for communication link to control room – high installation cost.Serial communication ports designed for substation environment, allowing the use of twisted pair cables for communication with the control room – low installation cost. Allows optional use of use of optical fiber, with self-powered external converters.
Usually operate with industrial communication protocols [3].Specific communication protocols for use in power systems (time-stamp, clock synchronicity, etc.).

Upon analyzing both, the choice was made for decentralized architecture, given its advantages.

A few IEDs placed on the casing of the transformer, as shown in figure 1, while others are located in a common panel for the bank. In the case of phase A, the ASEA transformer received a retrofit with IEDs being installed to replace the former electro-mechanical devices, such as mechanical thermometers for oil and winding temperatures. IEDs with control functions were also integrated into the monitoring system. The full list of IEDs installed in each point can be seen in Table 2.

In those case where third party sensors could not be integrated into the system by way of serial communication, because of not being intelligent devices, or because the manufacturer does not offer open protocol functionality at serial ports, universal data capture modules were used, capable of receiving multiple digital and/or analog signals, digitize them and make them available on open protocol serial ports.


Figure 1 – IEDs on the casing of the ASEA  transformer

In this way, every sensor, intelligent or conventional was able to be integrated to the monitoring system through a serial communication network, using the means of communication described in item 2.2. Thus, the need to deploy a centralizer element on the casing of the transformer was avoided, simplifying Project and implementation, reducing initial cost and, most important, also reducing the system’s TCO (Total Cost of Ownership) in the same ratio as it increased its reliability and availability.

2.2 - Means of Communication

The SIGMA monitoring system allows communication of data from data capture devices (IEDs) to the stage of storage  and treatment, in the control room, to be performed through different means of communication. On this transformer bank a number of them were used.

As shown in figure 2, the Intelligent Electronic Devices (IEDs) located in the station yard, both directly on the casing of transformers and in the bank’s common panel, were linked together in a standard RS-485 network, using shielded, twisted pair, metallic cables. This deployment, along with several others deploying this communication standard in high voltage substation environment, showed the feasibility of its use in substation environment with totally satisfactory results.

On the bank’s common panel, this RS-485 network is connected to an electric-optical converter, from which a pair of optical fiber cables go to the rack of the monitoring system, in the control room. In this rack, the optical signal is converted back into electric and connected to the system server. IEDs located in the substation control room are linked directly to the server, in the RS-485 standard.

IEDs associated to the monitoring system

LocalIEDs Acquired Data
TransformerTemperature Monitor- Oil temperature
- Winding temperatures
- Load currents
- Alarm and shut down due to excess temperature
Gas in oil Monitor- Hydrogen dissolved in oil
- Alarms for high/very high gas content
Moisture Monitor- Relative saturation (%) of water in oil
- Water in oil content (ppm)
Membrane/Bag Relay- Rupture of conservation tank membrane / bag
Voltage and Current Transducer- Tap changer motor voltages
- Tap changer motor currents
- Power active/reactive/apparent of tap changer motor
Temperature transducer- OLTC oil temperature
- Radiator in/out temperatures
Data capture modules- Contactos de alarma (relé Buchholz, válvula de alivio, niveles de aceite, etc.)
- Estado de los grupos de ventilación forzada
- Alarm contacts (buchholz relay, relief valve, oil levels, etc.)
- State of forced ventilation groups
- OLTC in operation
- OLTC operation time
Common PanelBushing Monitor- Bushing Capacitance
- Bushing Tangent Delta
Voltage and Current Transducer- Phase voltage
- Phase currents
- Power active/reactive/apparent
Temperature transducer- Ambient temperature
Control RoomParallelism Supervisor- Position of tap changer
- State of options local/remote, master/slave/individual and manual/automatic

2.3 - Data Storage, Treatment and Availability

The data supplied by the IEDs located on the transformers, in the common panel for the bank and in the control room are received by a computer (CPU) located in a rack in the substation control room, where it is employed in the monitoring software.

This software’s main functions can be grouped in two classes: Data Digitizing functions, associated to simple data availability and storage, and monitoring functions, with the purpose of taking simple data and transforming these into useful/meaningful information for maintenance purposes, as shown below.

Data Digitizing Functions:

  • On-line display of readings, alarms and states
  • Storage of readings, alarms and states in history databases
  • Inquiry of readings, alarms and states stored in history data bases in the form of charts and tables
  • Local and remote access to system
  • Automatic sending of notices via e-mail in case of abnormality.

Monitoring Functions:

  • Algorithm bsed data treatment
  • Mathematical model based data treatament
  • Obtention of diagnosis of the transformer’s current state
  • Obtention of prognosis for future state of transformer
  • Detection of defect while still in their early stages.

Monitoring Functions are detailed in item 3, below.


Figure 2 – Architecture of the monitoring system


More than just a digitizing system for the data obtained from sensors, a monitoring system must be able to transform this data into meaningful information for maintenance applications, which are the equipment state diagnosis and prognostics.

In order to deliver this function, the monitoring system implemented has an “Engineering Module”, which contains and runs the algorithms and mathematic models for diagnostics and prognostics.

Similar to what happens with the IEDs used in capturing readings, the system’s monitoring functions are also organized modularly, which gives total freedom of choice in terms of the monitoring functions one wishes to install, in addition to facilitating future expansions by simply adding new software modules and their corresponding IEDs. The diagnostic modules used are desbribed below.

3.1 - Insulation Life Cycle

Calculates the estimated lifetime loss for the insulation due to the thermal aging effect of cellulose, according to load conditions, temperatures and water content in insulation, obtained from the corresponding engineering module.

Also calculates the average lifetime loss rate for a given period in the past that is representative of the median operating conditions of the equipment, extrapolating the time remaining to the end of the insulation’s theoretical end of life cycle.

3.2 - Gases in Oil

On-line monitor of the concentration of hydrogen dissolved in oil. Since hydrogen is a gas generated in nearly every type of internal defect that may occur in a transformer, it is considered a key gas in defect detection. Once an abnormality has been detected, the monitoring system recommends performing gas-chromatography testing in laboratory. Results obtained in these tests are then input into the system, that then issues an opinion based on the analysis criteria more generally accept on the market.

3.3 - Moisture in Oil and in Paper

In a first stage, the monitoring system monitors ruptures of the expansion tank’s rubber bag / membrane, issuing an alert in case of oil/air contact. At a second level, there is on-line measurements of water in oil content, in ppm. Through this measurement, correlated to the equipament temperature readings, the percentage water content in solid insulation (paper) is calculated, considering the moisture balance between oil and paper. The percentage of water in paper is used in the functions of “Insulation Lifetime” and “Bubble Formation Temperature”, and warnings are issued for high water in oil and/or paper content.

3.4 - Bubble Formation Temperatures

In addition to potencializing the effects of thermal degradation, the water present in the insulation paper may move to the vapor state in the presence of high temperatures, increasing the risk of insulation failure. The temperature required to cause this phenomenon becomes lower as the water in paper percentage content rises. For this reason, the monitoring system uses the result of the calculation of water in paper content (item 3.4) to also calculate the temperature required to initiate bubble formation. If the temperature of the winding (hottest point) comes close to this value, the system issues an alarm.

3.5 - Efficiency of the Cooling System

Adequate cooling for transformer is vital in their safe operation and without accelerated insulation lifetime loss in the presence of high loads. Therefore, it is essential that the cooling system operates correctly, efficiently dissipating the heat generated.

Efficiency of cooling is monitored by comparing actual oil temperature to expected value, as a function of the ambient temperature, of the load current and of the cooling stage in operation. If the temperature measured is above expected, the system issues a low efficiency warning.

3.6 - Tap Changer Temperature Differential

In normal operating conditions, the tap changer is not a significant source of heat if compared to the active portion of the transformer, so that the temperature of the tap changer oil usually matches the temperature of the transformer oil. However, a few types of failures can cause generation of heat at the tap changer, keeping its temperature higher than the transformer’s. In these cases, monitoring the difference between transformer and tap changer temperatures is used to issue a warning, allowing actions to be taken before the failure becomes severe.

3.7 - Torque of Tap Changer Motor

The on load tap changer is an equipment with moving parts. So, failures with mechanical origins occurring on the tap changer may cause problems of different magnitudes, starting with equipment unavailability and going al the way to severe dielectric failures. In these cases, the torque developed by the tap changer motor will eventually show deviations in relation to its normal behavior, so that monitoring them allows eventual mechanical problems to be spotted and identified.

3.8 - Tap Changer Operating Times

As a complement to the “Torque of Tap Changer Motor” function, this function tracks the time required to perform the tap change in each tap changer operation, issuing an alarm in case this time shows a deviation in relation to the times observed during the equipment’s regular behavior.

3.9 - Maintenance Wizard for OLTC

Based on the number of changes and in the time-in-service of the on load tap changer, the tap changer maintenance wizard delivers meaningful information and alerts useful in helping this maintenance, such as: sum of current switched, number of operations performed, calculation of current contact thickness, equipment in service time, daily average contact wear and tap changes, time forecast to reach minimum contact thickness and time to next maintenance.

3.10 - Forced Cooling Maintenance wizard

By tracking the exact operation times of the fans, the Forced Cooling Maintenance Wizard delivers meaningful information and alerts useful as a maintenance help, such as: fan and pump in-operation times, records of motor operation times, average in-operation times and time forecast to next inspection or maintenance.

3.11 - Specialist Module

This module is an additional tool to be used in treating information. While the other modules point to the existence of a possible/actual problem, the specialist module cross matches information, coming from both sensors and mathematical models, with the com o objective of reaching a diagnosis of the probable cause for the problem, recommending correction actions and giving the prognostic for future complications in case the defect is not corrected.

In order to deliver these functions, a specialist system is used, an Artificial Intelligence technique comprised of a set of rules of decision that discard hypothesis and issue a response containing the most probable causes for a problem. This set of rules is flexible, and can be changed by the user to match their own experience.

This way, the specialist modules offers users an overview of the state of the equipment, without having to browse across the system’s different functionalities. For this reason, the specialist module is always the first screen displayed when the monitoring system is accessed.

3.12 - Simulation Module

In general, the temperature reached by the equipment is the limitingfactor in transformer loading. The simulation module allows users to check, for hypothetical loading conditions, the evolution of the temperatures and the associated loss of lifetime. There are two simulation modes available:

  • Based on actual conditions, with the current load and temperature readings are used as a starting point for the simulation. Users merely inform new load figures, and obtain as output, the oil and winding temperature evolution curves.
  • Based on hypothetical conditions – all simulation conditions are informed by users for a 24-hour period: evolution of ambient temperature and load, cyclical loading or not. The outputs delivered are the oil and winding temperature curves for the 24-hour period, in addition to the daily percentage loss of lifetime and estimated remaining lifetime.

In all simulations, users can modify the cooling command (off, automatic or manual) and the temperatures for actuation and hystheresis of cooling.


Due to the large geography area serviced by Furnas, in addition to the large number of transformers used, one of the main requirements specified for the monitoring system was remote access to information. In order to allow this Access, from any of its facilities, the means of communication chosen was the existing company Intranet.

In order to do this, the monitoring server located in the control room is connected to the Intranet, with access to data, information, diagnosis and prognostics performed exclusively through pages in HTML, without the use of any plug-in, so that they can be opened on any standard internet browser. Tis makes installing any special software in the company computers unnecessary, which avoided a high volume of work for the company IT team, in addition to making the access independent of the operating system used.

In addition, with transformers in regular operating conditions, which is expected to be the vast majority of the time, the monitoring system will remain static, and only issue warnings or diagnosis of defects eventually.

In order to avoid the need for an ongoing monitoring of the system, which would result in a major waste of the maintenance team’s time, the monitoring system has been equipped with a mechanism for automatic sending of e-mails in the event of any abnormality. To this end, the e-mails of staff responsible for maintenance are previously registered on the system.


As early as in the commissioning phase, the monitoring system started to capture data on-line and records of measurements taken in the history data base, allowing local and remote access to information, via FURNAS Intranet.

Still in this stage, a failure occurred in phase B of the AT-4 bank, which was removed from operation by the conventional protections (differential and over-current). In spite of the still incomplete commissioning of the monitoring system, the data captured by the system could be used after the failure event in helping in investigating the causes.

Some of this data is shown in figure 3, where we can see the behaviors of ambient, oil and winding temperatures, in addition to the percentage loaded, in every level considered normal. In this same chart we can also see the differential of the on load tap changer temperature, which indicated the temperature of the tap changer as slightly inferior to the transformer’s, which suggests regular operation for the OLTC diversion switch.


Figure 3 – Measurements of gases and other variables before and after the failure

Only after the failure did the gases in oil content, which to that point had remained stable, showed a high rise, reaching the sensor’s end of scale. Possible reasons mentioned for this were:

  • The failure was sudden, beginning and ending with the failure of the insulation in a very short period of time;
  • The defect was of a type that did not generate hydrogen before the total failure of the insulation;
  • The defect generated hydrogen in small quantities, insufficient to sensitize the sensor used in this specific phase, considering that it is sensitive to CO and the content of this gas in the transformer was much higher than that of hydrogen. With this the sensitivity in measuring H2 is reduced, masking the measurement of small value changes in hydrogen content;
  • The defect occurred in a point without direct contact with the transformer oil, so that the gases generated did not reach the on-line sensor.

Later investigations revealed that the origin was one of the internal over-voltage limiter devices (Zenox), used in parallel with the regulation winding. This proved that the last hypothesis presented above was true, however without discarding the possibility of it being a sudden failure.


On-line power transformer monitoring is a tool that helps in migrating from time-based maintenance (preventive maintenance) to equipment condition based maintenance (predictive maintenance). In this way, maintenance  resources, both financial and human, can be deployed in an optimized way, avoiding unnecessary interventions and detecting possible defects while still in their initial stage. In order to do this, the monitoring system must have data treatment capability, generating diagnosis and prognostics, in addition to featuring some sort of warning mechanism in case an abnormal condition is detected, for example, through sending e-mails or SMS messages.

Application of the monitoring systems also allows analysis of possible occurrences with more information, affording a more in depth knowledge of failure causes and effects, in order to determine even more accurately potential risks of transformer families and allow ongoing enhancement of the monitoring system.

In addition, the use of monitoring systems tends to facilitate dealing with insurance companies, that perceive the a possibility of avoiding failures seen as detectable, which may lead to reduced insurance premiums, since claims will be limited to sudden failures or those still not detectable with existing technology.


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(2) Alves, Marcos, Silva, Gilson, “Experiência de Campo com Monitoração On-Line de um Transformador 343MVA 230kV com 2 Comutadores Sob Carga”, IV Workspot – Workshop on Power Transformers, Recife, Brasil, 2005.

(3) Lavieri Jr., Arthur, Hering, Ricardo, “Novos Conceitos em Sistemas de Energia de Alta Confiabilidade”, Encarte Especial Siemens Energia, http://, Janeiro/2001.

(4) Amom, Jorge, Alves, Marcos, Vita, André, Kastrup Filho, Oscar, Ribeiro, Adolfo, et. al., “Sistema de Diagnósticos para o Monitoramento de Subestações de Alta Tensão e o Gerenciamento das Atividades de Manutenção: Integração e Aplicações”, X ERLAC – Encontro Regional Latinoamericano do CIGRÉ, Puerto Iguazu, Argentina, 2003.

(5) McNutt, W. J., “Insulation Thermal Life Considerations for Transformer Loading Guides”, IEEE Transaction on Power Delivery, vol. 7, No. 1, pp. 392-401, January 1992.

(6) Fabre, J., Pichon, A., “Deteriorating Processes and Products of Paper in Oil. Application to Transformers”, CIGRE Paper 137, 1960.

(7) Shroff, D. H., Stannet, A. W., “A Review of Paper Aging in Power Transformers”, IEE Proceedings, vol. 132, Pt. C, No. 6, pp. 312-319, November 1985.

(8) Lampe, W., Spicar, E., Carrander, K., “Continuous Purification and Supervision of Transformer Insulation System in Service”, IEEE Winter Point Meeting, IEEE Paper A 78 111-7, January/February 1978.

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