A Survey of Diagnostic and Condition Monitoring of Metal Oxide Surge Arrester in the Power Distribution Network
Abstract
:1. Introduction
2. Failures
2.1. Internal Humidity
2.2. Superficial Pollution
2.3. Sealing Loss
2.4. Non-Uniform Voltage Distribution
2.5. Overvoltage due to Switching
2.6. Excessive Lightning Surge Magnitude and Duration
2.7. Varistor Degradation
2.8. Varistor Displacement
3. MOSA Diagnostic and Condition Monitoring Methods
3.1. Thermal Image
3.2. Partial Discharge
3.3. Electromagnetic Field
3.4. Leakage Current
3.5. V-I Characteristics
3.6. Refrence Voltage
3.7. Power Loss
3.8. Impulse Test
3.9. Comparison of Different Diagnostic Methods
3.10. A Look at Upcoming Research
4. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
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References | [22] | [11] | [23] | [20] | [24] | [25] | [26] | [16] | [27] | This Paper |
---|---|---|---|---|---|---|---|---|---|---|
Leakage current | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
Thermal image | - | ✓ | - | - | ✓ | - | - | - | ✓ | ✓ |
Partial discharge | ✓ | ✓ | - | - | - | - | - | ✓ | - | ✓ |
Resistive current | ✓ | - | - | ✓ | - | ✓ | ✓ | - | ✓ | ✓ |
V-I characteristic | - | - | ✓ | ✓ | - | ✓ | - | - | - | ✓ |
Power loss | ✓ | - | - | ✓ | - | ✓ | ✓ | ✓ | - | ✓ |
Reference voltage | - | - | ✓ | ✓ | - | - | ✓ | - | - | ✓ |
Electromagnetic | - | - | - | - | ✓ | - | - | - | - | ✓ |
Reference | Properties | Advantage | Disadvantage |
---|---|---|---|
[37] | Uses thermovision to detect arrester failure and the probability of a fault. Employs a digital image processing technique based on the watershed transform, and uses the neuro-fuzzy network. | A non-destructive procedure; a decision-making instrument for identifying surge arrester faults. In addition to normal and faulty conditions, the surge arrester includes the following intermediate conditions: light and suspicious. | If the parameters of a thermogram alter drastically, the tool may not produce reliable data. The thermogram’s placement should be properly specified. |
[16] | After immersion testing, it observes the partial discharge and leakage current on eight surge arresters. | It assesses the behavioral relationship between internal humidity and partial discharge and MOSA degradation. | The measurement of partial discharge was less accurate than power loss. The electrical partial discharge measurements are particularly susceptible to external noise. |
[24] | Utilizes the electromagnetic emission method to identify partial discharge and lightning arrester surface flaws. | As a diagnostic technique, the WVD analysis can be employed with the use of a signal processing algorithm. It has a wireless connection and a small and inexpensive antenna. | Since there may be other electromagnetic signals present, data collecting with this method is highly challenging and is susceptible to errors. |
[50] | Analyzes leakage currents to assess the condition of the arrester. | It creates a database of medium- and high-voltage arresters with varying functioning conditions. It uses signal processing in MATLAB and the simulation of the leakage current in ATP-EMTP to verify its analysis. | The extraction result of resistive and capacitive components of the leakage current may be unreliable, and online testing is difficult. |
[12] | Classifies arresters using experimental tests and the multi-layer support vector machine method (SVM). | The classifier performs exceptionally well regarding training speed and reliability. It can categorize samples into some categories. | The SVM cannot detect the error of specific information; it can only categorize samples into some categories. The classification performance is heavily dependent on the MOSA parameters chosen; the algorithm cannot choose the MOSA parameters automatically. |
[13] | The MOSA’s condition assessment utilizes a leakage current analysis technique at the operating condition. | The applicability of specific indicators for evaluating the MOSA’s condition was assessed. There has been a suggestion for a solution to reduce the impact of voltage harmonics and fluctuation on the result of the leakage current analysis. | The difficulty of simultaneous current and voltage measurements at the network and higher harmonics may make tests invalid. |
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Ranjbar, B.; Darvishi, A.; Dashti, R.; Shaker, H.R. A Survey of Diagnostic and Condition Monitoring of Metal Oxide Surge Arrester in the Power Distribution Network. Energies 2022, 15, 8091. https://doi.org/10.3390/en15218091
Ranjbar B, Darvishi A, Dashti R, Shaker HR. A Survey of Diagnostic and Condition Monitoring of Metal Oxide Surge Arrester in the Power Distribution Network. Energies. 2022; 15(21):8091. https://doi.org/10.3390/en15218091
Chicago/Turabian StyleRanjbar, Behnam, Ali Darvishi, Rahman Dashti, and Hamid Reza Shaker. 2022. "A Survey of Diagnostic and Condition Monitoring of Metal Oxide Surge Arrester in the Power Distribution Network" Energies 15, no. 21: 8091. https://doi.org/10.3390/en15218091
APA StyleRanjbar, B., Darvishi, A., Dashti, R., & Shaker, H. R. (2022). A Survey of Diagnostic and Condition Monitoring of Metal Oxide Surge Arrester in the Power Distribution Network. Energies, 15(21), 8091. https://doi.org/10.3390/en15218091