Construction of active protection system for power transformers: from passive response to active blocking

As the core hub equipment of the power system, the safe and stable operation of power transformers is directly related to the reliability of the power grid and the security of energy supply. However, the complex operating environment and many internal and external factors pose severe challenges to the safe operation of transformers. The transformation from "post-event tripping" to "pre-event early warning and mid-event blocking" and building an active protection system based on panoramic sensing and intelligent decision-making has become an inevitable trend in the development of current transformer safe operation technology. As an emerging protection method, active protection technology can detect potential risks in time before a fault occurs, providing a strong guarantee for the safe operation of the transformer.

I. The importance of power transformers

As the core equipment for voltage conversion and power transmission and distribution in the power grid, power transformers are directly related to the power supply reliability and security of the power grid. In modern power systems, transformers are not only responsible for converting high-voltage electric energy generated by power plants into ultra-high-voltage electric energy suitable for long-distance transmission, but are also responsible for step-by-step step-down of high-voltage electric energy to low-voltage electric energy usable by users, thereby ensuring efficient utilization and reasonable distribution of electric power resources. In addition, as the demand for electricity in metal smelting, industrial production and other fields continues to grow, the role of power transformers in ensuring power supply to key industries has become increasingly prominent. Once a transformer fails, it will not only cause power outages in local areas, but may also trigger a chain reaction, posing a threat to the safe and stable operation of the entire power system. Therefore, ensuring the safe and stable operation of power transformers is of great significance to improving the reliability of the power grid.

II. Limitations of traditional protection models and the necessity of active protection

Traditional transformer protection (such as differential protection, gas protection, overcurrent protection) is mainly based on the threshold action of an electrical quantity or a single non-electrical quantity, and belongs to the "passive response" mode. However, practice has shown that even if the differential protection can operate the outlet extremely quickly within 10 to 20 milliseconds, it is limited by the full breaking time of the circuit breaker itself, which is tens of milliseconds. Before the arc fault is completely removed, the fault energy has often accumulated enough to cause the fuel tank to rupture and the oil to explode. In addition, for the evolution process from minor insulation defects (such as partial discharge) to penetrating arc faults, traditional protection lacks the ability to intervene in the intermediate stage, and is easily affected by transient processes such as excitation inrush current, and there is a risk of insufficient sensitivity or malfunction.

Active protection is different from traditional post-fault action protection. Its core lies in "prevention first, early intervention". It realizes early identification and warning of potential faults by real-time monitoring of the transformer's electrical quantities (voltage, current, power), non-electric quantities (oil temperature, oil level, vibration, gas content) and environmental parameters, combined with big data analysis and artificial intelligence algorithms. For example, through online monitoring of dissolved gases (DGA) in transformer oil, hidden dangers such as insulation aging and partial discharge can be discovered in advance, so that maintenance measures can be taken before faults occur.

III. Main risks and fault evolution of transformer safe operation

Transformer internal faults usually evolve from latent to explosive. Common risks include:

• Insulation fault: caused by insulation aging, moisture, overvoltage, etc., which initially manifests as partial discharge (PD), and then develops into turn-to-turn short circuit, phase-to-phase short circuit and even ground breakdown.
• Overheating fault: caused by overload, poor contact, cooling system failure or multi-point grounding of the iron core, which accelerates the aging of the insulating oil and solid insulation, and may eventually lead to insulation breakdown.
• Mechanical failure: winding deformation, loose fasteners, etc., usually accompanied by abnormal vibration and may further damage the insulation structure.

In the fault evolution chain, "partial discharge → severe discharge defect → high-energy arc breakdown" is one of the most dangerous paths. The key to active protection is to capture the physical characteristics of the "severe discharge defect" stage and cut off the circuit within a millisecond time window to prevent catastrophic consequences.

IV. Key Technologies for Active Protection

Online monitoring and sensor technology: Install high-performance sensors to collect transformer operating status data in real time, including winding temperature, oil chromatography, partial discharge, vibration and noise, etc., forming a multi-dimensional monitoring network.

Intelligent diagnosis and early warning system: Use algorithms such as machine learning and deep learning to analyze and model monitoring data, identify abnormal patterns, and achieve early diagnosis and risk classification warning of faults.

Adaptive protection control: Dynamically adjust the protection settings and logic according to the real-time status of the transformer to avoid misoperation or refusal to operate and improve the reliability of the protection system.

Achieving active protection relies on the deep integration of high-precision status monitoring (perception) and new protection principles (decision-making). Currently, the industry is gradually building a "three-level defense line" or "three lines of defense" safe operation system:

1. Level 1: Minor defect detection and early warning (condition monitoring layer)

By deploying multi-dimensional smart sensors, 7x24-hour panoramic perception is achieved. Core technologies include:

* Dissolved gas analysis (DGA) in oil: Monitor characteristic gases such as H₂, C₂H₂, and CO to determine the type and rate of overheating or discharge failure.

* Partial discharge (PD) monitoring: using ultra-high frequency (UHF), ultrasonic (AE) and high-frequency pulse current (HFCT) technology to detect and locate internal insulation defects.

* Optical fiber temperature measurement and vibration monitoring: directly measure the temperature of winding hot spots and monitor the mechanical status of the core and windings.

These data are fused from multiple sources through edge computing to achieve equipment health index (HI) assessment and early warning.

2. Level 2: Active protection in the severe discharge defect stage (active blocking layer)

This is the core link that distinguishes active protection from traditional protection. When the discharge signal (such as UHF amplitude, pulse current steepness, ultrasonic energy) is monitored to reach the preset serious defect threshold, and the fault is comprehensively judged to be in a rapid development stage, the protection system can directly issue a trip command or link the stability control system to transfer the load without relying on traditional differential criteria. For example, based on the principle of phase sequence differential current characteristic differences, the inter-turn fault protection action time can be shortened to about 20 milliseconds; or the sound, light, and electrical multi-physical characteristics about 100 milliseconds before fault breakdown can be used to achieve precise removal of the "fault budding stage".

3. Level 3: Improvement of traditional arc fault protection performance (underlying protective layer)

For arc faults that have occurred, the sensitivity and quickness of traditional protection are improved through new principles. For example, core saturation identification technology based on main flux linkage estimation can effectively identify excitation inrush current and fault current, realizing fast differential protection without inrush current blocking; slight inter-turn fault protection based on magnetic flux leakage characteristics solves the problem of insufficient sensitivity of traditional differential protection for high impedance inter-turn short circuits.

V. Comprehensive measures for safe operation

In order to ensure the safe operation of transformers, a multi-level and comprehensive management strategy needs to be adopted:

• Routine inspection and maintenance: Regularly conduct appearance inspection, oil sample testing, grounding testing, etc. to maintain a good operating environment of the transformer.
• Insulation aging management: monitor the status of insulation materials, evaluate remaining life, and reasonably arrange maintenance or replacement plans.
• Overload and overheating protection: Through load management and cooling system optimization, prevent long-term overload of the transformer or excessive temperature rise.
• Emergency response plan: Develop a quick response process for sudden failures to shorten power outage time and reduce losses.

VI. Future development trends

With the development of artificial intelligence and Internet of Things technology, transformer active protection is evolving towards "Digital Twin + adaptive control":

* Digital twin: Construct a virtual-real mapping of the transformer multi-physics simulation model and real-time data, dynamically deduce the fault evolution path, predict the remaining life (RUL), and provide a quantitative basis for proactive intervention.

* Adaptive protection: The protection device no longer relies on fixed thresholds, but dynamically adjusts the protection setting value or delay based on the real-time operating load rate, ambient temperature, insulation status, etc., to prevent malfunction while maximizing the equipment carrying capacity.

* AI intelligent diagnosis: Using deep learning algorithms such as CNN and LSTM to automatically identify partial discharge patterns (PRPD) and vibration soundprints, reducing manual analysis costs and improving the recognition rate of weak fault signs.

Conclusion

Active protection and safe operation of power transformers are essentially systematic projects that move the safety line of defense forward. It requires us to expand from a single relay protection thinking to a full-chain technology system of "panoramic sensing-intelligent diagnosis-active blocking-self-healing control". By integrating advanced sensing technology, multi-physics simulation, artificial intelligence and new protection principles to achieve transparent management of the internal status of the transformer and precise control of fault evolution, we can fundamentally curb the occurrence of malignant deflagration accidents and build a solid barrier for the safe and stable operation of new power systems.