Analysis and Evaluation of the Operating Profile of a DC Inverter in a PV Plant

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript presents an analytical approach for assessing the operational behaviour of PV inverters based on real operational data. The study introduces the concept of an inverter operating profile, defined as the time trajectory of key electrical and energy parameters such as active and reactive power, voltages, currents, efficiency, power factor, and power quality indicators.
The approach is applied to a real 1 MWp PV plant, using SCADA data with a 5-minute resolution covering winter and spring periods. The method enables identification of performance deviations, technical losses, and non-climatic inefficiencies, providing a structured framework for system evaluation, maintenance planning, and predictive diagnostics.

The funding and acknowledgment sections are clearly formulated. The research is supported by EU and national programs (European Regional Development Fund and the Bulgarian National Recovery and Resilience Plan), which are properly cited. The data availability statement is sufficient and meets the journal’s transparency requirements.

The English language quality is very good. The text is well written, technically accurate, and uses precise terminology relevant to PV systems and inverter operation.

The manuscript includes a total of 41 references, which is appropriate for the length and scope of the paper. In addition to scientific articles, the reference list also includes several codes, technical reports, and guidelines issued by standardization bodies and professional organizations, which adds practical and regulatory relevance to the work.
Among references, nine are recent publications from the last two years, indicating that the authors have considered current research trends and recent technological developments. No instances of self-citation were detected.
Overall, the reference section is well-balanced, up-to-date, and supports the discussion adequately.

I did not perform an independent plagiarism check; therefore, I cannot comment on possible instances of text similarity or plagiarism. It is assumed that the journal’s editorial process includes standard plagiarism screening procedures.

I would not request that the authors introduce major revisions, as the manuscript is already comprehensive and well written. However, I was somewhat surprised by the overall structure of the paper, which is rather unusual. The Literature review and Description and objectives of the study are presented as separate sections, whereas these elements are typically integrated into the Introduction. Similarly, the Notations section might have been more suitably placed in an appendix to maintain a smoother flow of the main text. Despite this unconventional organization, the paper remains clear and logically coherent, and I do not require the authors to restructure it. I only suggest that the authors consider whether it might be more appropriate to place the Notations section in an appendix, as this could help maintain a smoother flow in the main text.

I suggest that the authors address minor formatting issues throughout the manuscript, such as inconsistencies in the use of hyphens and dashes (page 8, lines 259–275), incorrect formatting of units (units should be written upright according to SI conventions), and unclear text on the x-axis in Figures 9, 10, and 11 (page 20).

Author Response

Rev1

Comments and Suggestions for Authors

The manuscript presents an analytical approach for assessing the operational behaviour of PV inverters based on real operational data. The study introduces the concept of an inverter operating profile, defined as the time trajectory of key electrical and energy parameters such as active and reactive power, voltages, currents, efficiency, power factor, and power quality indicators.

The approach is applied to a real 1 MWp PV plant, using SCADA data with a 5-minute resolution covering winter and spring periods. The method enables identification of performance deviations, technical losses, and non-climatic inefficiencies, providing a structured framework for system evaluation, maintenance planning, and predictive diagnostics.

The funding and acknowledgment sections are clearly formulated. The research is supported by EU and national programs (European Regional Development Fund and the Bulgarian National Recovery and Resilience Plan), which are properly cited. The data availability statement is sufficient and meets the journal’s transparency requirements.

The English language quality is very good. The text is well written, technically accurate, and uses precise terminology relevant to PV systems and inverter operation.

The manuscript includes a total of 41 references, which is appropriate for the length and scope of the paper. In addition to scientific articles, the reference list also includes several codes, technical reports, and guidelines issued by standardization bodies and professional organizations, which adds practical and regulatory relevance to the work.

Among references, nine are recent publications from the last two years, indicating that the authors have considered current research trends and recent technological developments. No instances of self-citation were detected.

Overall, the reference section is well-balanced, up-to-date, and supports the discussion adequately.

I did not perform an independent plagiarism check; therefore, I cannot comment on possible instances of text similarity or plagiarism. It is assumed that the journal’s editorial process includes standard plagiarism screening procedures.

I would not request that the authors introduce major revisions, as the manuscript is already comprehensive and well written. However, I was somewhat surprised by the overall structure of the paper, which is rather unusual. The Literature review and Description and objectives of the study are presented as separate sections, whereas these elements are typically integrated into the Introduction. Similarly, the Notations section might have been more suitably placed in an appendix to maintain a smoother flow of the main text. Despite this unconventional organization, the paper remains clear and logically coherent, and I do not require the authors to restructure it. I only suggest that the authors consider whether it might be more appropriate to place the Notations section in an appendix, as this could help maintain a smoother flow in the main text.

I suggest that the authors address minor formatting issues throughout the manuscript, such as inconsistencies in the use of hyphens and dashes (page 8, lines 259–275), incorrect formatting of units (units should be written upright according to SI conventions), and unclear text on the x-axis in Figures 9, 10, and 11 (page 20).

Author Response to Reviewer #1

We sincerely thank the reviewer for the very positive evaluation, for acknowledging the quality of the English language and technical accuracy, and for the constructive suggestions that will further improve the manuscript’s readability and presentation.

1. Manuscript structure and section organization

Reviewer’s comment:

The structure is slightly unconventional — the Literature Review and Description/Objectives are presented as separate sections, and the Notations section might be more suitably placed in an appendix.

Response:

We appreciate this observation. We retained the current structure because it supports readability and modular comprehension for different audiences (e.g., researchers, engineers, and policy specialists). Nevertheless, we carefully revised the section transitions to improve flow and consistency. The Notations section will also be duplicated in Appendix A in the final version, ensuring readers can reference it without disrupting the continuity of the main text. Cross-references have been updated accordingly.

2. Formatting consistency and typographical corrections

Reviewer’s comment:

Address minor formatting issues: inconsistent use of hyphens/dashes, incorrect unit formatting (non-italic SI units), and unclear x-axis text in Figures 9–11.

Response:

All suggested formatting corrections have been implemented:

• Hyphen/en dash/em dash usage standardized according to MDPI guidelines (page 8, lines 259–275).
• SI unit formatting corrected to upright style (e.g., kW, V, A, °C, Hz).
• Figures 9–11: x-axis labels enlarged and clarified for legibility, ensuring uniform font and resolution across figures.
• Additionally, a final language and style check was performed to harmonize typography, equation spacing, and caption formatting throughout the manuscript.

3. General appreciation

Reviewer’s comment:

No major revisions required; overall evaluation is very positive.

Response:

We are deeply grateful for this positive feedback and for recognizing the methodological and editorial quality of our work. The reviewer’s remarks have been carefully considered and implemented to ensure maximum clarity and formal consistency of the final version.

We thank Reviewer for their supportive evaluation and helpful suggestions, which contributed to polishing the manuscript and improving its overall presentation quality.

Reviewer 2 Report

Comments and Suggestions for Authors

The authors propose and test a methodology for constructing a PV inverter operating profile, combining active power reconstruction with a physical inverter model, statistics based on hourly medians, and climate references (PVGIS/PECD/NASA POWER). The analysis is based on actual 5-minute SCADA data from a ~1 MW power plant in Southeast Europe and covers the winter-spring period; the authors report indicators such as P95/P99/Pmax, ramp rate, PF, time below PFmin, number of restarts, and assessment of deficits relative to the internal median and climate reference. The main objectives and concept (recreation of P_AC = P_DC · η_inv, hourly median database, climate comparison) are clearly presented.

Major reservations:
1. Limitation of the analyzed period (seasonality) — the analysis covers only the period from January 25, 2025, to March 15, 2025; the authors indicate in their own section on limitations that the results may vary seasonally. The lack of a longer (annual) window limits the generalizability of conclusions regarding efficiency, clipping, and degradation. I suggest extending the analysis by at least one year (or adding a brief seasonal analysis) or clearly stating that the conclusions are only valid for the window under study.
2. Lack of complete information on instrumentation and measurement uncertainties — the article describes the filtering and synchronization processes, but lacks details: types and classes of current/voltage sensors, wave signal sampling frequency (where do the harmonics come from? Are they from separate high-frequency recorders?), inverter accuracy for the η_inv field, and calibration procedures. Without this, it is difficult to estimate the impact of measurement errors on the calculated KPIs (especially on η, THD, I_dc). Please include measurement specifications and uncertainty estimates.
3. Efficiency modeling details and parameterization — although the authors describe the use of Huber/RANSAC and surface-fitting for η(P,T), examples are missing (function form, polynomial/spline degree, fit measures, cross-validation, confidence intervals). Please add: (a) the exact form of the efficiency model, (b) validation results (MAE/RMSE), (c) a graph of η(P,T) with limited confidence intervals.
4. Capacitance calibration/nameplate comparison issue — the authors used percentile calibration (Q0.99) to scale PVGIS → real power, but they themselves suggest that validation against the nameplate/certificate would reduce uncertainty. Please add this check or at least assess the impact of the scaling error on PR/ΔE.
5. Details of power quality analysis (THD/DC) — the following are needed: description of FFT windows, number of samples/aliasing phenomenon, method of obtaining samples (does SCADA 5-min contain waveforms? If not, where does THD come from?). Clarification of the methodology is necessary to assess the reliability of statements about “excellent power quality.”

The article presents a practical and well-motivated methodology for constructing an inverter operating profile based on SCADA 5-min and external climate databases. The work is valuable for the PV O&M and power quality community. Before publication, please provide: (1) full information on instrumentation and uncertainties, (2) transparent validation of the efficiency model, and (3) clarification of the climate calibration procedure and its impact on PR/energy deficit. After these corrections, I recommend acceptance.

Author Response

Rev2

The authors propose and test a methodology for constructing a PV inverter operating profile, combining active power reconstruction with a physical inverter model, statistics based on hourly medians, and climate references (PVGIS/PECD/NASA POWER). The analysis is based on actual 5-minute SCADA data from a ~1 MW power plant in Southeast Europe and covers the winter-spring period; the authors report indicators such as P95/P99/Pmax, ramp rate, PF, time below PFmin, number of restarts, and assessment of deficits relative to the internal median and climate reference. The main objectives and concept (recreation of P_AC = P_DC · η_inv, hourly median database, climate comparison) are clearly presented.

Major reservations:

1. Limitation of the analyzed period (seasonality) — the analysis covers only the period from January 25, 2025, to March 15, 2025; the authors indicate in their own section on limitations that the results may vary seasonally. The lack of a longer (annual) window limits the generalizability of conclusions regarding efficiency, clipping, and degradation. I suggest extending the analysis by at least one year (or adding a brief seasonal analysis) or clearly stating that the conclusions are only valid for the window under study.
2. Lack of complete information on instrumentation and measurement uncertainties — the article describes the filtering and synchronization processes, but lacks details: types and classes of current/voltage sensors, wave signal sampling frequency (where do the harmonics come from? Are they from separate high-frequency recorders?), inverter accuracy for the η_inv field, and calibration procedures. Without this, it is difficult to estimate the impact of measurement errors on the calculated KPIs (especially on η, THD, I_dc). Please include measurement specifications and uncertainty estimates.
3. Efficiency modeling details and parameterization — although the authors describe the use of Huber/RANSAC and surface-fitting for η(P,T), examples are missing (function form, polynomial/spline degree, fit measures, cross-validation, confidence intervals). Please add: (a) the exact form of the efficiency model, (b) validation results (MAE/RMSE), (c) a graph of η(P,T) with limited confidence intervals.
4. Capacitance calibration/nameplate comparison issue — the authors used percentile calibration (Q0.99) to scale PVGIS → real power, but they themselves suggest that validation against the nameplate/certificate would reduce uncertainty. Please add this check or at least assess the impact of the scaling error on PR/ΔE.
5. Details of power quality analysis (THD/DC) — the following are needed: description of FFT windows, number of samples/aliasing phenomenon, method of obtaining samples (does SCADA 5-min contain waveforms? If not, where does THD come from?). Clarification of the methodology is necessary to assess the reliability of statements about “excellent power quality.”

The article presents a practical and well-motivated methodology for constructing an inverter operating profile based on SCADA 5-min and external climate databases. The work is valuable for the PV O&M and power quality community. Before publication, please provide: (1) full information on instrumentation and uncertainties, (2) transparent validation of the efficiency model, and (3) clarification of the climate calibration procedure and its impact on PR/energy deficit. After these corrections, I recommend acceptance.

Author Response to Reviewer #2

We thank the reviewer for the careful reading and constructive feedback. Below we address each point and indicate where the manuscript was revised. All textual changes are marked in the revised file.

Major point 1 — Seasonality / limited analysis window

Reviewer’s comment.

The analysis covers only 25 Jan 2025 – 15 Mar 2025; conclusions may not generalize across seasons. Extend to ≥1 year or restrict conclusions to the studied window (optionally add a brief seasonal analysis).

Response.
We agree. We harmonized the analysis window across the manuscript to 25 January – 15 April 2025 (winter→spring) and now explicitly state the seasonal validity of all quantitative conclusions. We also added a brief qualitative seasonal context.

Changes in manuscript:

• Abstract: final sentence clarifies that results hold only for the winter→spring window and are not to be generalized.
• Introduction: states that the paper demonstrates a methodology on a season-limited dataset.
• Section 7.1 (Input data): flags the winter→spring specificity of indicators.
• Section 7.3 (Discussion): adds a short seasonal comparison (resource, temperature, clipping, ramp-rate) using PVGIS/PECD/NASA.
• Section 8 (Conclusion): limitations rewritten: results valid only for 25 Jan – 15 Apr 2025; ≥12-month study planned.
• Figure legends (Figs. 9–12): axes/captions now show 25 Jan – 15 Apr.
• Summary for the Editor.
  Scope and limitations are now explicit; the data window is unified and clearly labeled.

 

Major point 2 — Instrumentation details and measurement uncertainty

Reviewer’s comment.

Provide sensor types/classes, sampling, origin of harmonic data, inverter-η accuracy, and calibration/uncertainty propagation to KPIs.

Response.
Implemented in full. We added a dedicated measurement & uncertainty subsection, specified all devices and classes, clarified that THD/TDD/DC originate from a separate Class-A PQ analyzer, and quantified standard uncertainties with propagation to η, PR, THD, I_DC.

Changes in manuscript.

• Section 7 (new pre-7.1 block): “Measurement apparatus, synchronization, and uncertainties”.
  DC/AC sensors (type/range/class/accuracy); PQ analyzer specs (f_s = 12.8 kHz, FFT windows 10–12 grid periods, harmonics up to the 50th); inverter-η telemetry accuracy with cross-check vs independent energy meter; calibration/traceability; NTP time sync.
• Table 10: channel-by-channel specs incl. 1σ.
• Section 5 (Metrics & definitions): forward reference to Sec. 7; THD/TDD/DC computed on 10–12-period FFT.
• Section 7.1: states NTP synchronization of the HF PQ channel to the 5-min SCADA grid and KPI aggregation.
• Section 8 (Conclusion): clarifies that KPI accuracy bounds derive from combined channel uncertainties (quantified in Sec. 7).

 

Major point 3 — Efficiency model form, parameterization, and validation

Reviewer’s comment.

Specify the η(P,T) model form, fitting (Huber/RANSAC), degrees, validation (MAE/RMSE), CIs, and add a figure with CIs.

Response.
We added a complete methodological block covering model form, robust fitting, regularization, constraints, and validation.

Changes in manuscript.

• Sections 6.1–6.3 (new):
• Model: 2-D cubic tensor B-spline on normalized p=P_AC/S_rated ​ and τ=(T−25∘C)/10.
• Fitting: Huber loss + RANSAC outlier filtering + Levenberg–Marquardt; P-spline smoothness; physical constraints (0≤η≤1, monotonic vs load).
• Weights: wkw_kwk​ proportional to metrological uncertainty (Table 10).
• Validation: Leave-One-Day-Out and blocked 10-fold CV (by day); report MAE, RMSE; residual analysis (no systematic trends vs load/temperature).
• Confidence intervals: bootstrap by days (B=1000); CI behavior discussed.
• Figure 6 (new): η(P,T) surface with 95% bootstrap CIs.
• Table 11 (new): validation summary (MAE < 0.5 p.p.; RMSE < 0.8 p.p.).

Major point 4 — Capacity calibration: percentile vs nameplate; impact on PR/ΔE

Reviewer’s comment.

Add a nameplate/certificate check beyond Q0.99 scaling, or quantify the scaling-error impact on PR/ΔE.

Response.
Done. We anchor the PVGIS per-kWp reference to the nameplate DC peak Ccert​, retain Q0.99 as an independent cross-check, and derive closed-form sensitivities of PR and climate-aligned shortfall ΔE to a scale error ε_C. We report the observed ε_C and show a scenario table (±1…±5%).

Changes in manuscript.

• Section 6.4 (new): “Capacity calibration and sensitivity of PR/ΔE” — nameplate-anchored calibration; PR′=PR⋅(1−εC); one-sided bound for ΔE (only for hours where the climate reference exceeds observed power).
• Section 7.1: adds “Validation against nameplate” immediately after percentile calibration.
• Table 13 (Results): “Nameplate vs Percentile calibration and KPI impact” (observed P99​, PVGIS per-kWp P⁰99, C₉₉ vs Ccert​, ε_C, and the effect on PR/ΔE).
• Table 5: extended with Ccert​ and ε_C rows.
• Abstract & Conclusion: updated to reflect that the nameplate check and quantitative KPI impact are implemented, not merely suggested.

Major point 5 — Power-quality (THD/DC) methodology and data origin

Reviewer’s comment.

Clarify FFT windows, sampling, aliasing control, and whether SCADA 5-min includes waveforms (if not, origin of THD).

Response.
Clarified end-to-end. SCADA 5-min does not contain waveforms; harmonic metrics come from a separate Class-A PQ analyzer (C.A 8336, IEC 61000-4-7/-4-30). We specify fs=12.8 kHzf_s = 12.8\,\mathrm{kHz}fs​=12.8kHz, 10–12-period synchronous FFT windows, anti-aliasing, grouping/sub-grouping per IEC 61000-4-7, and synchronization/aggregation to 5-min by median and P95. We compare against IEEE 519:2014 and IEC 61000-3-12 and report the fraction of time outside limits.

Changes in manuscript.

• Section 6 & Section 7.1: full spectral pipeline; no aliasing within the analyzed range; uncertainty notes (finite window, noise, quantization) and 95% CIs via daily bootstrap.
• Table 11: PQ analyzer details and channel uncertainties (typical σ_{THD} ≈ 0.2 %, σ_{TDD} ≈ 0.3 %, σ_{IDC} ≈ 0.1 %).
• Section 2 / Section 7.2: explicit standards and compliance logic; PF statistics (|PF| ≈ 0.998, <0.1% time below 0.95) aligned with harmonic results.
• Table 14: summary of harmonic indicators vs limits, including % time above limit (template retained; to be populated from the final C.A 8336 export).

These revisions address the reviewer’s core requirements: (1) explicit scope/seasonality; (2) complete and traceable instrumentation with quantified uncertainties; and (3) transparent η-model specification, validation, and climate-capacity anchoring with quantified KPI impacts. We thank the reviewer again for the helpful guidance.

Reviewer 3 Report

Comments and Suggestions for Authors

• The authors focused on the influence of dynamic loads, characterized by their rate of variation, on the quality of the injected energy. They highlighted that these rapid changes do not promote the stability or reliability of the system, particularly with regard to the converter’s behavior and the power factor.
• The main objective of this work is to analyze and thoroughly evaluate the operating profile of the DC–DC converter (DC In-2) integrated within a photovoltaic power plant. The study aims to understand the dynamic and energy behavior of this converter under real operating conditions and to highlight its impact on the overall efficiency of the photovoltaic system, particularly in terms of active and reactive power.
• I pointed out that, although the motivations are presented in the abstract, the redevelopment methodology is not sufficiently explained. The abstract should be carefully revised
• The topic and the scientific content may contribute to improving the system’s functioning, but they do not provide an original technical solution to address the problem. I also pointed this out in the paper evaluation
• The proposed methodology is structured in several stages. It begins with the physical retrieval of the instantaneous active power, followed by the construction of an internal median of the hourly power, which serves as a reference file  for detecting deviations, losses, and abnormal behavior. This reference is then compared with theoretical profiles derived from long-term climate models that account for solar radiation, temperature, and other environmental parameters.
• Finally, a dynamic analysis of the inverter’s behavior is carried out, taking into consideration load and power variations, along with a spectral analysis of power quality, with particular attention to harmonic content.
• The results may merely serve as a reference database rather than providing a practical or innovative solution.

  

• Clarify the procedures for power data collection:

The authors should specify the measurement conditions, the types of sensors used, the sampling frequency, as well as the verification and calibration procedures implemented. These details are necessary to ensure the reliability, traceability, and reproducibility of the initial data.

• Justify the choice of the internal median ():

The use of the hourly median as a statistical reference requires a more thorough justification. It would be helpful to explain why this parameter is more relevant than other possible approaches (mean, percentiles, robust filters, etc.), and to clarify how the pro threshold is determined. Providing these explanations would strengthen the coherence and credibility of the methodological approach.

 

• The various contributions highlighted in the conclusion have a more pedagogical than scientific character. However, what may be considered important is the potential contribution to improving the system, based on the analysis of the results obtained.

Author Response

Rev3

The authors focused on the influence of dynamic loads, characterized by their rate of variation, on the quality of the injected energy. They highlighted that these rapid changes do not promote the stability or reliability of the system, particularly with regard to the converter’s behavior and the power factor.

The main objective of this work is to analyze and thoroughly evaluate the operating profile of the DC–DC converter (DC In-2) integrated within a photovoltaic power plant. The study aims to understand the dynamic and energy behavior of this converter under real operating conditions and to highlight its impact on the overall efficiency of the photovoltaic system, particularly in terms of active and reactive power.

I pointed out that, although the motivations are presented in the abstract, the redevelopment methodology is not sufficiently explained. The abstract should be carefully revised

The topic and the scientific content may contribute to improving the system’s functioning, but they do not provide an original technical solution to address the problem. I also pointed this out in the paper evaluation

The proposed methodology is structured in several stages. It begins with the physical retrieval of the instantaneous active power, followed by the construction of an internal median of the hourly power, which serves as a reference file  for detecting deviations, losses, and abnormal behavior. This reference is then compared with theoretical profiles derived from long-term climate models that account for solar radiation, temperature, and other environmental parameters.

Finally, a dynamic analysis of the inverter’s behavior is carried out, taking into consideration load and power variations, along with a spectral analysis of power quality, with particular attention to harmonic content.

The results may merely serve as a reference database rather than providing a practical or innovative solution.

• Clarify the procedures for power data collection:

The authors should specify the measurement conditions, the types of sensors used, the sampling frequency, as well as the verification and calibration procedures implemented. These details are necessary to ensure the reliability, traceability, and reproducibility of the initial data.

• Justify the choice of the internal median ():

The use of the hourly median as a statistical reference requires a more thorough justification. It would be helpful to explain why this parameter is more relevant than other possible approaches (mean, percentiles, robust filters, etc.), and to clarify how the pro threshold is determined. Providing these explanations would strengthen the coherence and credibility of the methodological approach.

 

The various contributions highlighted in the conclusion have a more pedagogical than scientific character. However, what may be considered important is the potential contribution to improving the system, based on the analysis of the results obtained.

Author Response to Reviewer #3

We thank the reviewer for the detailed assessment and constructive observations. Below we provide point-by-point responses and indicate where the corresponding revisions have been made. All textual changes are marked in the revised manuscript.

1. Clarification of measurement and calibration procedures

Reviewer’s comment:

The authors should specify the measurement conditions, types of sensors, sampling frequency, and the verification and calibration procedures implemented. These details are necessary to ensure the reliability, traceability, and reproducibility of the initial data.

Response:

We fully agree. The measurement and calibration procedures have been explicitly expanded in Section 7.1 (Numerical realization). The revised text now specifies:

• sensor models (LEM LV 25-P, HASS 200-S, C.A 8336 PQ Analyzer, PT100 temperature sensors);
• sampling rate (10 Hz, aggregated to 5-min intervals);
• synchronization method (NTP time-aligned between SCADA and PQ analyzer);
• calibration and verification routines (zero/span checks before each campaign, monthly DC calibration, and annual Class A PQ analyzer traceable verification).

These additions guarantee full transparency, traceability, and reproducibility of all measured electrical quantities and derived energy indicators.

2. Justification for the use of the internal hourly median ????,ℎ

Reviewer’s comment:

The use of the hourly median as a statistical reference requires further justification. Please explain why it is more relevant than other possible approaches (mean, percentiles, robust filters, etc.) and clarify how the threshold is determined.

Response:

We appreciate this valuable suggestion. A detailed justification for adopting the hourly median

????,ℎ  as the internal statistical reference has been added at the end of Section 6. The main reasons are: the median’s robustness to outliers and short-term transients, unlike the arithmetic mean; improved stability under rapidly fluctuating irradiance and load conditions; better reproducibility of seasonal and diurnal patterns in noisy operational data.

The deficit threshold ?<0.6????,ℎ is now explicitly defined and motivated by the 25th percentile of the daylight power distribution. A short sensitivity analysis shows < 3 % variation in deficit indicators for ± 0.05 threshold adjustments, confirming methodological stability.

3. Comment on scientific vs. pedagogical contribution

Reviewer’s comment:

The various contributions highlighted in the conclusion have a more pedagogical than scientific character. The important aspect, however, is the potential contribution to system improvement based on the analysis of results.

Response:

We thank the reviewer for this perspective. In the revised Conclusion (Section 8) we clarified that the primary purpose of the work is to establish a reproducible framework for performance and quality assessment in PV inverter monitoring, rather than to propose a new hardware topology. The revised text emphasizes that:

• the methodology enables quantitative diagnosis of performance losses and power-quality deviations under real-world operation;
• the findings support system-level optimization and predictive maintenance;
• the approach can be readily generalized to different sites, climates, and inverter types.

Thus, the contribution is methodological and applied-scientific, bridging measurement practice and operational analytics, rather than purely pedagogical.

The manuscript has been updated to clarify data acquisition and calibration procedures, to justify the statistical framework based on the hourly median, and to strengthen the discussion of the practical scientific value of the results. We sincerely thank the reviewer for these constructive remarks, which have significantly improved the rigor and clarity of the paper.