Case Study: On-line Monitoring and Diagnostics - Transforming Power Transformer Maintenance through Real-Time Insights

Introduction

Power transformers are one of the most critical and valuable assets of a power system. Their efficient operation is necessary to supply uninterrupted and quality power to all the consumers reliably. In the era of interconnected technology, power transformers, the backbone of electricity distribution networks are undergoing a revolutionary change in how they are monitored and maintained. The advent of on-line monitoring systems has reshaped the landscape of transformer maintenance, allowing operators to access real-time data that significantly influences decision-making processes. In this article, we examine into the implementation of on-line monitoring systems for power transformers, highlighting their impact on maintenance strategies and the reliability of electrical grids.

Figure 1 describes the structure and chain of equipment and technical aspects of transformer monitoring so that the processing of results and diagnosis is ongoing and online to see and analyze the symptoms of potential faults. Such smart structure devices help to recognize the operation of transformer equipment and, among other things, affect the safety and diagnosis of its operating parameters. It should be noted that the assessment of the state of electrical, thermal, and mechanical parameters is one of the main elements for defining possible defects in transformers.

Please observe that the components of the remote transformer monitoring system fall outside the scope of this case study and will not be discussed.

The Need for Remote Monitoring

Power transformers play a pivotal role in ensuring efficient and uninterrupted electricity supply. However, they are subjected to various stresses such as thermal cycling, electrical overloads, and environmental conditions, which can lead to deterioration over time. Early detection of these issues is crucial to prevent outages, disruptions and failures ultimately minimizing downtime. This is where remote monitoring comes into play.

Traditional maintenance practices involve periodic manual inspections and routine tests, which may not capture transient anomalies or provide a comprehensive picture of the transformer's health. Remote monitoring systems, on the other hand, enable continuous data collection and analysis, offering insights into the transformer's condition, performance, and potential risks.

Implementation of Remote Monitoring System

1. Sensor Deployment:

Remote monitoring systems are built on a network of sensors strategically placed on various components of the power transformer. These sensors measure parameters such as temperature, oil levels, winding currents, vibrations, and dissolved gas concentrations. The data collected from these sensors is transmitted in real-time to a central monitoring platform.

2. Data Analytics:

The real value of remote monitoring lies in its ability to analyze the incoming data. Advanced analytics algorithms process the data, identifying trends, anomalies, and potential issues. Machine learning techniques can help predict future conditions based on historical data and patterns.

3. Visualization and Alerts:

The insights gained from the data analysis are presented through intuitive dashboards and visualizations. These interfaces allow operators and maintenance personnel to quickly assess the transformer's health. Additionally, the system can generate alerts and notifications when abnormal conditions are detected, enabling timely responses.

One of the many transformer monitoring systems is Koncar monitoring system which is shown in Figure 2 above.

Real-Time Data Influence on Maintenance Decisions

The implementation of remote monitoring systems has far-reaching implications for power transformer maintenance strategies:

1.??? Condition-Based Maintenance:

On-line monitoring enables a shift from time-based maintenance to condition-based maintenance. Traditional maintenance schedules may result in unnecessary interventions or missed critical issues. Real-time data allows maintenance actions to be targeted precisely when a potential problem is detected, optimizing resource allocation. Proper condition monitoring of the transformers will reduce the chance of sudden breakdown or failure and thus the effective service life of the transformer could be extended.?

As an example, Eaton’s Transformer Monitoring System for distribution transformer encompasses predictive maintenance and failure mitigation.

2. Early Detection of Anomalies:

On-line monitoring systems excel in capturing transient anomalies that might go unnoticed during periodic inspections. This early detection capability empowers operators to address minor issues before they escalate into major problems, reducing the likelihood of unplanned outages.

3. Predictive Insights:

By leveraging historical and real-time data, predictive analytics can forecast future conditions and trends. This foresight enables operators to plan maintenance activities proactively, ensuring that the transformer's health is upheld without unnecessary disruptions to service.

4. Data-Driven Decision Making:

On-line monitoring provides a data-rich environment for making informed decisions. From optimizing loading patterns to determining the ideal time for maintenance, these decisions are guided by insights derived from a comprehensive dataset.

5. Reduced Downtime and Cost:

Timely interventions based on accurate data translate to minimized downtime and reduced maintenance costs. Planned maintenance activities are streamlined, and emergency repairs are less likely due to the ability to address issues preemptively.

Monitoring Functions

Various sensors are used in this system to monitor the internal ongoing operation in the system.?The following functions shown in Figure 3 may be included in the transformer monitoring system:

Bushings

• Operating voltages
• Overvoltages
• Change of bushing capacitance
• Tan delta /power factor
• Loading current (single or three phase)

?Active part

• Power (apparent, active, reactive)
• Losses
• Oil temperature (top, bottom)
• Ambient temperature
• Hot-spot temperature (calculation or fiber optic measurement)
• Gas in oil (single or multi gas sensors)
• Moisture in oil and paper
• Paper insulation ageing and lifetime

Partial Discharges

• Electrical, acoustic and UHF methods are available

On-Load Tap Changer

• Tap position
• Number of switching operations
• Switching time
• Power consumption of the OLTC motor drive
• OLTC oil temperature and differential
• Sum of switched current
• Contact wear

?Cooling system

• Oil temperatures at the cooler inlets and outlets
• Cooling efficiency
• Running hours of pumps and fans
• Content of gas in the Buchholz relay
• Oil level in the conservator
• Intelligent cooling control
• Auxiliary equipment statuses and alarms (pressure relief device, OTI, WTI, Buchholz relay, etc.)

?Tools

• Trend analysis
• Alarms and events logging
• Loading forecast
• Data export to text and Microsoft Excel
• Automatic report generation

CONCLUSIONS

Transformers are one of the key and most valuable components in a power system. Equipping them with an on-line monitoring system is essential for information gathering, condition assessment, better management and decision making. Real-time insights acquired through continuous data collection and analysis, empower operators and maintenance teams to optimize maintenance strategies, prevent failures, ensure smooth operations, and even extend the lifespan of transformers.

As technology continues to advance, on-line monitoring is poised to become an indispensable tool. Unlike traditional systems, there is no need for repeated visits to the transformer's location to conduct preventive maintenance tests and monitoring. The introduction of on-line monitoring and diagnostic techniques has revolutionized maintenance from being time-based to condition-based. These combined factors solidify on-line transformer monitoring systems as a critical requirement for future power system needs.

REFERENCES

?[1] Anjan Mitra, Mousam Dutta and Arpan Pramanick “Digitalisation of Power Transformer Monitoring System”, 2022 IEEE India Council International Subsection Conference (INDISCON), https://www.ieee.org/.

[2] Mohammad Hassan Hashemi, Selim Dikmen,“Real-Time Condition Monitoring of Power Transformers Using the Internet of Things (IoT) and Dissolved Gas Analysis”, 2023 XIX International Scientific Technical Conference Alternating Current Electric Drives (ACED), https://www.ieee.org/.

[3] Sanket Pathak, “Remote Monitoring of Transformer”, https://kemsys.com/.

[4] Transformer monitoring system catalog CA024009EN, 2021, www.eaton.com/cooperpowerseries.

[5] Farzin?Asadi,?Satree?Phumpho and Sawai?Pongswatd, “Remote monitoring and alert system of HV transformer based on FMEA”, 2020 7th International Conference on Power and Energy Systems Engineering (CPESE 2020), Fukuoka, Japan.

[6] Vezir Rexhepi and Vezir Rexhep, “Monitoring parameters of power transformers in the electrical power system through smart devices”, Journal of Energy Systems, 2020, 4(2), 48-57, DOI: 10.30521/jes.724207.

[7] KON?AR-Institute-KON?AR TMS-Transformer Monitoring System-10-1902, Zagreb, Croatia.

[8] https://www.trackster.in/transformer-monitoring.html

[9] https://www.reinhausen.com/servicedetail/transformer-digitalization/online-monitoring