Noise Effects on Detection and Localization of Faults for Unified Power Flow Controller-Compensated Transmission Lines Using Traveling Waves

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Authors,

This paper presents a novel algorithm for detecting and localizing faults in transmission lines compensated with a UPFC, using traveling wave-based methods.

In my opinion, the manuscript is interesting and presents promising results. However, it has several shortcomings that require the authors’ response and clarification:

1. The manuscript contains only simulation results. Therefore, the obtained findings should be discussed in the context of current IEEE standards. I kindly ask the authors to address this issue and include appropriate commentary in the manuscript.
2. In my opinion, the noise structure used in the study requires a more detailed description. It is not clear what criteria the authors used when selecting the number of harmonics and the SNR level. Was this choice based on IEEE standards? I would like to ensure that the selected parameters reflect real-world power system conditions. Therefore, I ask the authors to explain (also in the manuscript) in which practical scenarios the number of harmonics and the SNR level used in the manuscript are significant.
3. Please elaborate on the research gap that necessitated the development of the proposed algorithm, and include this discussion in the manuscript.
4. To enhance the credibility of the results presented in Tables 2 and 3, please provide at least one detailed example showing how the error results (6) were obtained for a selected case.
5. Please include the pseudo-code of the algorithm shown in Figure 4 in the manuscript. I also recommend specifying the function names used for implementing DWT and CT in the programming language employed.

In my opinion, the manuscript has been prepared carefully, but the authors did not avoid some minor errors:

Lines 157-158: A period should be inserted at the end of formula (4).

Line 177: "Where" should be replaced with "where." I also suggest removing the indentation from the sentence.

Lines 189-190: A period should be inserted at the end of formula (4).

Line 190: The variable "d1" requires correction.

Line 243: I suggest removing the indentation from the sentence.

Lines 325-326: A period should be inserted at the end of formula (6).

Yours sincerely,

Reviewer

Author Response

Dear Reviewer,

We sincerely thank you for your valuable time and thorough review of our manuscript.
We truly appreciate your insightful comments and suggestions, all of which have been carefully considered. The changes made in response to your observations have been highlighted in green in the revised manuscript for your convenience. Below, we provide detailed responses to each of your comments.

Comment 1:
The manuscript contains only simulation results. Therefore, the obtained findings should be discussed in the context of current IEEE standards. I kindly ask the authors to address this issue and include appropriate commentary in the manuscript.

Response 1:
Thank you for your comment. We have addressed this observation by adding a specific discussion in the conclusions section.
We clarified that the proposed method aligns with IEEE Standard C37.114-2004 for fault localization in transmission lines and took into account IEEE Standard 1138-2009 regarding FACTS devices, specifically the UPFC.
We also justified the use of a high sampling rate (80 kHz) and its contribution to obtaining reliable results within the technical margins defined by these standards.
This addition can be found in the Conclusions section of the revised manuscript.

Comment 2:
The noise structure used in the study requires a more detailed description. It is not clear what criteria the authors used when selecting the number of harmonics and the SNR level. Was this choice based on IEEE standards? Please explain in the manuscript.

Response 2:
Thank you for this important observation. We expanded the description of the noise model in Section 4 (Network Description).
We now specify that the 3rd, 5th, and 7th harmonics were considered based on IEEE Std 519-2014, as these are the most common in industrial and commercial networks.
Furthermore, we clarified that the SNR values of 20, 30, and 40 dB were selected to represent various real-world noise conditions and are consistent with the recommendations of IEEE Std 1057-2017.
This additional information ensures the realism and relevance of the simulation scenarios.

Comment 3:
Please elaborate on the research gap that necessitated the development of the proposed algorithm, and include this discussion in the manuscript.

Response 3:
We appreciate your suggestion. We addressed it by expanding the Introduction section.
We now emphasize that disturbances generated by devices such as UPFCs affect the propagation of traveling waves used for fault localization, and that this phenomenon has received limited attention in the literature.
This context highlights the research gap that motivated the development of our proposed algorithm, aiming to improve reliability and accuracy under realistic conditions.

Comment 4:
To enhance the credibility of the results presented in Tables 2 and 3, please provide at least one detailed example showing how the error results (6) were obtained for a selected case.

Response 4:
Thank you for this suggestion. A detailed example has been added in Section 6 (Results).
In the example, we illustrate the calculation of the fault location using the arrival times of traveling waves and show how the location error is determined using formula (7).
This explicit example strengthens the credibility and reproducibility of the reported results.

Comment 5:
Please include the pseudo-code of the algorithm shown in Figure 4 in the manuscript. I also recommend specifying the function names used for implementing DWT and CT in the programming language employed.

Response 5:
Thank you for your suggestion. We included the pseudocode of the proposed algorithm as Figure 5, located in Section 5 (Development of Noise Analysis).
Additionally, we clarified that the DWT was implemented using the function pywt.dwt() and the CT was implemented by generating the coefficient matrix with the NumPy library.
This information improves the clarity and reproducibility of our method.

Comment 6:
Minor corrections:

• Lines 157-158: A period should be inserted at the end of formula (4).
• Line 177: "Where" should be replaced with "where." Also, remove indentation.
• Lines 189-190: A period should be inserted at the end of formula (4).
• Line 190: The variable "d1" requires correction.
• Line 243: Remove indentation.
• Lines 325-326: A period should be inserted at the end of formula (6).

Response 6:
Thank you for carefully identifying these minor issues. We have corrected all the typographical and formatting errors as suggested.
These adjustments are reflected throughout the revised manuscript and have been highlighted in green.

Reviewer 2 Report

Comments and Suggestions for Authors

This work is interesting.

fault detection and localization in UPFC-compensated transmission lines using traveling waves in a noise-free environment has been reported in [17], while this paper reports the analysis under noisy conditions, with noise levels of 20 dB, 30dB and 40 dB and transient frequencies of 1 kHz, 5kHz and 10 kHz. Simulink simulations show the robustness of the traveling wave method in noisy environments with an average fault localization error smaller than 1%, and fault detection rates greater than 90%。

I have some suggestions to improve this paper.

 

Major issue:

For table 2 & 3, let us focus on the first row in table 2, 0.501% error under 20db, 0.545% error under 30db, and 0.324% error under 40db. This is contrary to the observation that greater SNR, smaller location error. Why?

 

Does load changes have any influence on the fault detection? Such as the 200MW load deceases to 150MW.

 

Method base on travelling waves to localize the exact moment of the fault may be given briefly.

 

What happens in Fig.5 may be given? A 25 ohm load is loaded, or others?

 

What happens in Fig.6 may be given? The normal CD1 is what? The fault threshold 5% may be given. the fault CD1 is what.

 

Why chose a fault inception angle of 36degree?

 

Why chose a 20db noise?

 

Author Response

Dear Reviewer,
We sincerely appreciate your careful review and valuable comments. Below, we provide detailed responses to each of your observations. Please note that the changes made to the manuscript in response to your suggestions have been highlighted using light blue text markers for easy identification.
 
1.    For table 2 & 3, let us focus on the first row in table 2, 0.501% error under 20db, 0.545% error under 30db, and 0.324% error under 40db. This is contrary to the observation that greater SNR, smaller location error. Why?
We appreciate your valuable observation. In general, it is expected that the localization error decreases as the signal-to-noise ratio (SNR) increases. However, since the noise introduced in the tests is harmonic in nature (3rd, 5th, and 7th orders), its influence is not completely uniform across all frequencies and time instances of the signal. This causes slight fluctuations in detection accuracy, even as the SNR increases. Moreover, since the localization method relies on the precise detection of traveling waves, slight distortions in high-frequency components can nonlinearly affect the results.In summary, although the general trend of the results shows lower error with higher SNR, the observed variations are attributable to the non-stationary and frequency-dependent nature of the harmonic noise, as well as to the sensitivity of the analysis method used.
We have added this clarification to the results section for better understanding.
2.    Does load changes have any influence on the fault detection? Such as the 200MW load deceases to 150MW.
Fault detection based on traveling waves primarily relies on the abrupt high-frequency transients caused by faults, rather than steady-state load conditions. Although variations in load can slightly alter the signal's base magnitude, the proposed algorithm applies an adaptive threshold (5% of the peak value) that normalizes detection criteria, thus mitigating any load-dependent effects. Tests conducted with a reduced load of 150 MW confirmed that the detection and localization performance remains stable under these conditions.
3.    Method base on travelling waves to localize the exact moment of the fault may be given briefly.
The explanation was added in Section 3 of the manuscript. A briefly concise description of the traveling wave principle was included, describing how a fault generates incident and reflected wavefronts that propagate along the transmission line. 
4.    What happens in Fig.5 may be given? A 25 ohm load is loaded, or others?
We clarify that the connection of a 25-ohm load alters the steady-state impedance of the system but has minimal impact on fault detection using traveling waves. This is because the detection focuses on identifying abrupt, high-frequency disturbances shortly after the fault occurs (within less than 1 ms), a process that remains unaffected by slower changes in system impedance or load conditions.
5.    What happens in Fig.6 may be given? The normal CD1 is what? The fault threshold 5% may be given. the fault CD1 is what.
Figure 6 (now 7) clearly shows a fault event, where the detail coefficients cD1 (from the db4 wavelet transform) peak at 0.12 pu. This value, significantly higher than normal levels, indicates an abrupt system disturbance such as a short circuit or traveling wave. Under normal 60 Hz sinusoidal operation, cD1 coefficients remain below 0.01 pu. Minor noise or harmonic distortions may temporarily increase them to 0.02 pu, but never exceed the critical threshold.
The detection threshold is set at 0.05 pu (5% of the nominal value). This filter ensures that only relevant disturbances are captured while ignoring regular system fluctuations. During the fault event in Figure 6, cD1 values reached 0.12 pu substantially exceeding the 0.05 pu threshold. This not only confirms a fault condition but also demonstrates its severity, being six times higher than normal operating levels and double the established threshold value. The 0.12 pu peak provides clear, actionable data for protection systems to trigger appropriate responses to the fault.
6.    Why chose a fault inception angle of 36degree?
The fault initiation angle of 36° was selected to ensure that the initial energy of the disturbance generated by the fault event would be sufficiently significant. Faults initiated near the zero-crossing angles (0° or 180°) tend to generate traveling waves with very low initial magnitude, complicating both their detection and precise location. The angle of 36°, which corresponds to an instant when the magnitude of the sinusoidal signal reaches approximately 58.8% of its peak value (for a 60 Hz sinusoidal waveform), ensures sufficient traveling wave energy for correct capture and processing via DWT, thereby reducing the possibility of errors during detection and location stages.
7.    Why chose a 20db noise?
SNR levels of 20, 30, and 40 dB were selected to evaluate the method’s performance under different noise conditions, ranging from severe to moderately noisy scenarios. The 20 dB case simulates an extreme condition, aligned with the types of disturbances described in IEEE Std 1159-2019, such as low-order harmonics, impulsive transients, and electromagnetic noise. Although the standard does not specify concrete SNR levels, it does recommend considering such conditions to validate the robustness of monitoring and protection algorithms in electrical systems.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

All my concerns are resolved, no further comments.