Analysis of Photovoltaic Systems with Battery Storage, Electric Vehicle Charging, and Smart Energy Management

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper studies the PV system with battery storage, EV charging, and smart energy management.

Some problems are given as follows,

1. The paper is more like a engineering report. The idea is mainly based on historical data statistics.  There is no theoretical contribution. The difference and contribution compared with the existing literature is not found.
2. Many basic data such as efficiency can not show the contribution of the authors. There are related to the actual products.
3. The relation of PV, EV, and BS is not clear. The role and newly contribution of the management system are not found. For actual EMS or DTS, the power balance is dependent on the predicted load instead of the historical data.
4. The conclusions are quite normal.
5. The literature is far from enough to support this research. Many papers are more profound than this paper.

Author Response

Response reviewer 1

1.  The paper is more like an engineering report. The idea is mainly based on historical data statistics.  There is no theoretical contribution. The difference and contribution compared with the existing literature is not found.

Response 1:  

We appreciate the reviewer's feedback regarding the nature of our paper. While it is true that our study is based on historical data and practical implementation, it provides valuable insights into the real-world application of photovoltaic (PV) systems integrated with battery storage and electric vehicle (EV) charging. Unlike purely theoretical studies, our research emphasizes empirical validation of smart energy management strategies. The main contribution of our work lies in:

• Demonstrating a practical implementation of a grid-connected PV system integrated with battery storage and EV charging in Constanta, Romania.
• Providing a detailed energy flow analysis, showing a self-sufficiency rate of 92.2% and a reduction of 6239 kg in CO₂ emissions per year.
• Using PV*SOL and Global Solar Atlas to model and optimize the energy efficiency of the integrated system.
• Offering insights into the economic and environmental benefits of such a setup, contributing to the advancement of smart energy solutions. While the paper does not propose a new theoretical framework, it provides a practical contribution to the field of renewable energy integration and sustainable energy management.

1. Many basic data such as efficiency cannot show the contribution of the authors. There are related to the actual products.

Response 2: 

The reviewer’s concern regarding basic efficiency data is noted. The efficiency values presented in the paper are crucial for evaluating the system’s performance under real-world conditions. Our study does not solely focus on system efficiency; rather, it provides a comprehensive evaluation of the effectiveness of integrating PV systems, battery storage, and EV charging. Specifically, we:

• Show that 92.2% of the total energy consumption is covered by solar power, significantly reducing dependency on the grid.
• Analyze seasonal variations in energy production, demonstrating that peak generation occurs in summer months (May–August), with lower production in winter.
• Assess energy losses in battery charging/discharging, inverter operation, and EV charging inefficiencies.
• Provide an in-depth economic and environmental analysis, emphasizing cost savings and carbon footprint reduction. The efficiency values are not merely technical parameters but integral to evaluating the sustainability and feasibility of smart energy systems

 

1. The relation of PV, EV, and BS is not clear. The role and newly contribution of the management system are not found. For actual EMS or DTS, the power balance is dependent on the predicted load instead of the historical data.

Response 3:  

The relationship between PV, EV, and Battery Storage (BS) is a core focus of our research, and we acknowledge the need for further clarity. The role of the Energy Management System (EMS) in balancing power between these components is crucial. Our study illustrates:

• PV Power Generation: The system generates 13710 kWh annually, with most of the energy being used for self-consumption, battery storage, or EV charging.
• Battery Storage: The battery stores excess solar energy (1016 kWh annually) and releases it during low solar production periods, ensuring continuous power availability.
• EV Charging: The EV primarily utilizes solar power (2335 kWh annually), with the remainder supplemented by battery storage or grid power.
• Energy Management System (EMS): Our smart energy management approach prioritizes solar power usage while ensuring grid stability and optimal power distribution. While traditional Energy Management Systems (EMS) depend on predicted loads, our study integrates historical data to provide a practical validation of energy optimization techniques. Future research could integrate AI-driven forecasting models to further enhance system efficiency.

1. The conclusions are quite normal.

Response 4:  

We acknowledge that our conclusions follow a standard structure. However, they are based on comprehensive real-world data analysis, emphasizing key findings such as:

• The self-sufficiency rate of 92.2%, reducing dependency on grid electricity to only 317 kWh per year.
• A high-performance ratio (88.48%), demonstrating effective energy conversion from solar radiation to usable electricity.
• A significant reduction in carbon emissions (6239 kg per year), promoting environmental sustainability.
• Economic benefits of reducing reliance on fossil fuels and grid electricity. Our study provides a practical blueprint for large-scale implementation of smart energy systems, which is a vital step toward sustainability. The findings serve as a reference for policymakers, researchers, and engineers interested in improving renewable energy adoption.

 

1. The literature is far from enough to support this research. Many papers are more profound than this paper.

Response 5:  

We recognize the importance of a strong literature foundation. The paper references multiple recent studies in the field of PV integration, battery storage, and smart energy management. Some of the key references include:

• Green (2000): Discussing advancements in PV technology and its impact on energy policy.
• Firoozzadeh et al. (2019): Exploring methods to enhance PV efficiency through phase change materials.
• Babatunde et al. (2022): Investigating hybrid PV-wind systems with hydrogen and battery storage.
• Osman et al. (2023): Analyzing renewable energy participation in Sudan and its role in sustainable transportation.
• Dubey et al. (2013): Examining temperature effects on PV performance. While our references provide a solid background, we acknowledge that additional literature could strengthen our argument. We will enhance the literature review section by including:
• More comparative studies with existing EMS and Distributed Energy Systems (DES).
• Advanced forecasting methods for load prediction and energy management.
• Case studies on PV, battery, and EV integration in different geographical regions.

We appreciate the reviewer’s constructive comments and have addressed each concern by:

• Clarifying the novelty and contribution of our work as a practical validation of renewable energy integration.
• Highlighting the efficiency and economic benefits of the system beyond basic data statistics.
• Elaborating on the relationship between PV, EV, and Battery Storage, emphasizing the role of the Energy Management System.
• Strengthening the conclusion section to emphasize key findings.
• Committing to expanding the literature review to include more theoretical advancements and comparative studies.

Thank you for your insightful review. We hope these responses clarify the significance of our research and its contribution to the field of sustainable energy systems.

 

Reviewer 2 Report

Comments and Suggestions for Authors

This paper focuses on the research of photovoltaic systems in Constanta, Romania. The paper focuses on the integration of photovoltaic systems with battery energy storage, electric vehicle charging, and intelligent energy management, which is in line with the trend of sustainable energy development. The theme has important practical significance. Research focuses on comprehensive analysis of actual systems in specific regions, with a greater emphasis on theory or single technology compared to previous studies. There are certain innovations in research objects and methods, providing new practical references for the application of renewable energy in regions. Combining direct measurement and simulation to obtain energy consumption data, and utilizing local meteorological stations and Global Solar Atlas data to ensure data comprehensiveness and accuracy. Using PV * SOL for system simulation can effectively evaluate system performance under different conditions. The method is scientific and reasonable, and can accurately reflect system characteristics. Deeply analyzed the system performance. By displaying data through various charts, the system's operating patterns are visually presented, such as the impact of seasonal changes on the system, and the research content is rich and in-depth. The proposed comprehensive model provides practical examples for energy transformation in similar regions and helps promote sustainable energy development.

Author Response

Response to reviewer 2

This paper focuses on the research of photovoltaic systems in Constanta, Romania. The paper focuses on the integration of photovoltaic systems with battery energy storage, electric vehicle charging, and intelligent energy management, which is in line with the trend of sustainable energy development. The theme has important practical significance. Research focuses on comprehensive analysis of actual systems in specific regions, with a greater emphasis on theory or single technology compared to previous studies. There are certain innovations in research objects and methods, providing new practical references for the application of renewable energy in regions. Combining direct measurement and simulation to obtain energy consumption data and utilizing local meteorological stations and Global Solar Atlas data to ensure data comprehensiveness and accuracy. Using PV * SOL for system simulation can effectively evaluate system performance under different conditions. The method is scientific and reasonable and can accurately reflect system characteristics. Deeply analyzed the system performance. By displaying data through various charts, the system's operating patterns are visually presented, such as the impact of seasonal changes on the system, and the research content is rich and in-depth. The proposed comprehensive model provides practical examples for energy transformation in similar regions and helps promote sustainable energy development.

Response

We sincerely appreciate the reviewer’s detailed and constructive feedback. Your recognition of the study’s practical significance, innovative methodology, and contribution to sustainable energy development is greatly valued. Below, we provide a detailed response to your observations and comments.

1. Research Focus and Practical Significance
   We are pleased that the reviewer acknowledges the importance of integrating photovoltaic (PV) systems with battery energy storage, EV charging, and intelligent energy management in line with global trends in sustainable energy development. Our study aims to bridge the gap between theoretical models and real-world applications by implementing and analyzing an actual system in Constanta, Romania. The findings serve as a practical reference for policymakers and engineers aiming to enhance renewable energy adoption in various regions.
2. Innovations in Research Methods and Contributions
   We appreciate the reviewer’s recognition of the innovative aspects of our research. The study introduces several key contributions, including:

• Combining direct measurement and simulation: This dual approach ensures greater accuracy and reliability in evaluating energy consumption and performance.
• Utilizing local meteorological data and Global Solar Atlas: This integration provides a comprehensive and location-specific analysis of solar energy potential.
• Using PV*SOL for system simulation: This allows us to evaluate system performance under various environmental conditions, ensuring realistic modeling of energy generation and consumption.
• Providing a practical framework for energy transformation: The proposed model demonstrates the feasibility of integrating PV, battery storage, and EV charging in real-world applications, offering guidance for future deployments.

3. Scientific and Rational Methodology
   The reviewer notes that our methodology is scientific and reasonable, which aligns with our objective of delivering a rigorous and well-validated study. Our approach includes:

• Energy flow analysis: Evaluating power distribution across PV systems, battery storage, EV charging, and grid interaction.
• Seasonal variation assessment: Understanding how fluctuations in solar irradiance and temperature impact system efficiency.
• Performance ratio evaluation: Our system achieves an 88.48% performance ratio, confirming its efficiency.
• Carbon footprint reduction analysis: A key outcome of our study is the annual reduction of 6239 kg in CO₂ emissions, reinforcing the sustainability impact of the proposed model.

4. Data Visualization and System Performance Analysis
   We appreciate the reviewer’s recognition of the comprehensive and in-depth system performance analysis presented in our study. By leveraging various charts and visualizations, we effectively illustrate:

• The impact of seasonal changes on energy generation and consumption.
• Energy distribution across PV, battery, EV, and the grid.
• Efficiency losses in charging, discharging, and power conversion.
• The high solar fraction (92.2%), demonstrating significant self-sufficiency in energy consumption.

These visual representations not only make our findings more accessible and interpretable but also serve as valuable references for researchers and practitioners in the field.

5. Practical Implications and Future Applications
   The proposed comprehensive model offers a scalable and replicable approach to renewable energy integration, particularly in regions with similar climatic and energy consumption profiles. Our study contributes to the growing body of literature supporting energy transition strategies, including:

• Decentralized energy management through smart grids.
• Integration of PV and EV infrastructure to promote sustainable mobility.
• Enhancements in battery storage solutions to optimize renewable energy utilization.

We acknowledge that further improvements can be made by incorporating advanced forecasting models for load prediction and real-time energy management using artificial intelligence and machine learning. This will be a focus of our future research efforts.

We sincerely thank the reviewer for their thoughtful and encouraging feedback. Your insights validate the significance of our research and motivate us to further enhance our work. We have aimed to provide a scientifically robust, practically relevant, and methodologically sound study that contributes to the advancement of sustainable energy solutions. We welcome any further suggestions to strengthen the paper’s impact and applicability.

 

Reviewer 3 Report

Comments and Suggestions for Authors

The paper brings the experience of an experimental installation located in Costanta (Romania) and including a PV system coupled with a battery storage and an EV charging system. By analysing the the operation results of the experimental system, the authors can demonstrate that the battery coupling can enhance energy independence (92.2% of hours of consumption covered by solar energy) and emissions reduction (6239 kg of CO2 per year).

The paper is well written and easy to read for a common reader. However, a couple of aspects could be better clarified:

• At the beginning of paragraph 2.2, the text mentions both “household appliances” and “grid interaction”. These two aspects should be clarified: on one side it should be explained which household appliances are supposed to be directly fed by the experimental system. On the other side, it would be great if the wording “interaction with the grid is better clarified: to what extent is the surplus stored in the batteries put available for sale to the grid and what is the portion which is held for future requests of the EV? With which criteria is this management carried out? A layout drawing for the overall apparatus would be maybe helpful to this aim.
• The usage of PV* SOL and of Global Solar Atlas is affirmed throughout the paper, but no better specification is given of what the two tags stand for. Additionally, it would be great to have some bibliographic references on them.
• The graph in Figure 1 is not clear. It should be replaced by one in which the trend of the total consumption is better readable.
• The balance sheet in Figure 2 should be better clarified. What does the generic term “consumption” stand for? The numbers indicated are annual figures (that can be deduced from other parts of the paper but here it is not clear). Again: the +9641/-317 kWh sold/bought to/from the network should be better specified: is this a constant pattern throughout the year or there is a price strategy? When the text says that the battery supplies 750 kWh to the “system” what is meant here as “system”?
• Regarding the electric vehicle (or vehicles?) how is its temporal behavior modelled? How is uncertainty on time and duration of charge accounted for?
• The conclusions affirm that the demonstrated model is a “scalable model for future smart grid solutions”. How is the “scalability” property demonstrated, since the authors have just experimented the illustrated installation? What scale economies (e.g.) could be obtained by doubling the dimension of the PV plant and of the battery and connecting a fleet of EV?

As a suggestion for further research (maybe better if already indicated in the paper), the authors could investigate the business model of opening the illustrated experimental plant to a provision of ancillary services to the electrical system, by put (at least a part) of the battery surplus available for short charge/discharge cycles piloted from external requests. What about a participation of this “virtual power plant” to an ancillary services market?

Author Response

Response to reviewer 3

The paper brings the experience of an experimental installation located in Constanta (Romania) and including a PV system coupled with a battery storage and an EV charging system. By analyzing the operation results of the experimental system, the authors can demonstrate that the battery coupling can enhance energy independence (92.2% of hours of consumption covered by solar energy) and emissions reduction (6239 kg of CO2 per year).

The paper is well written and easy to read for a common reader. However, a couple of aspects could be better clarified:

We appreciate the reviewer’s detailed and insightful feedback. Your comments have helped us clarify key aspects of the study and improve the manuscript. Below, we address each point raised in your review.

• At the beginning of paragraph 2.2, the text mentions both “household appliances” and “grid interaction”. These two aspects should be clarified: on one side it should be explained which household appliances are supposed to be directly fed by the experimental system. On the other side, it would be great if the wording “interaction with the grid is better clarified: to what extent is the surplus stored in the batteries put available for sale to the grid and what is the portion which is held for future requests of the EV? With which criteria is this management carried out? A layout drawing for the overall apparatus would be maybe helpful to this aim.
• Response:

1. Clarification of Household Appliances and Grid Interaction (Section 2.2)
   We acknowledge the need for greater clarity regarding the role of household appliances and grid interaction. The experimental system supplies energy to various household appliances, including lighting, refrigeration, heating and cooling systems, and other essential electrical loads. These appliances are prioritized for direct consumption to maximize self-sufficiency. Regarding grid interaction, the system follows a structured energy management approach:

• Surplus solar energy is first stored in the battery to be used when solar production is insufficient.
• Energy stored in the battery is then allocated based on priority: first for household consumption, then for EV charging, and only excess energy beyond these demands is sold to the grid.
• The sale of surplus energy to the grid follows a dynamic strategy, depending on real-time system constraints and energy demand.

To further clarify these aspects, we have added a layout drawing illustrating the overall apparatus, showing the relationship between PV generation, battery storage, grid interaction, and EV charging.

 

• The usage of PV* SOL and of Global Solar Atlas is affirmed throughout the paper, but no better specification is given of what the two tags stand for. Additionally, it would be great to have some bibliographic references on them.
• Response:

Explanation of PV*SOL and Global Solar Atlas Usage
Thank you for pointing this out. PV*SOL is a simulation tool used to model and evaluate PV system performance under various conditions, accounting for solar irradiance, shading, and load demand. Global Solar Atlas, developed by the World Bank Group, provides solar resource data and climate analytics for site-specific energy yield assessment. We have included bibliographic references to these sources to improve the clarity of their roles in our study.

• The graph in Figure 1 is not clear. It should be replaced by one in which the trend of the total consumption is better readable.

The balance sheet in Figure 2 should be better clarified. What does the generic term “consumption” stand for? The numbers indicated are annual figures (that can be deduced from other parts of the paper but here it is not clear). Again: the +9641/-317 kWh sold/bought to/from the network should be better specified: is this a constant pattern throughout the year or there is a price strategy? When the text says that the battery supplies 750 kWh to the “system” what is meant here as “system”?

 

• Response:
• We acknowledge the reviewer’s concern regarding the clarity of Figure 1. To improve readability, we have enhanced the visualization by adjusting the graphical elements to better illustrate the trend of total consumption over time. However, replacing the figure entirely is not feasible, as it effectively represents the distribution of energy consumption within the system, which is a crucial aspect of the study.
• Similarly, in Figure 2, we have provided a more precise definition of the term "consumption", explicitly distinguishing between household loads, EV charging, and other energy uses. Additional annotations have been included to clearly indicate that the numbers represent annual energy figures, ensuring better interpretation.
• Regarding the grid interaction, we have clarified that +9641 kWh is exported to the grid, while 317 kWh is imported, with variations occurring seasonally. Grid exports peak during high solar production months, while grid imports increase during winter periods when solar generation is lower.
• When referring to “the battery supplying 750 kWh to the system”, we specifically mean that this energy is allocated to cover household consumption and EV charging needs before any reliance on the grid. This clarification ensures a more transparent representation of energy distribution within the study.
• Regarding the electric vehicle (or vehicles?) how is its temporal behavior modelled? How is uncertainty on time and duration of charge accounted for?
• Response:

4. Modeling the Temporal Behavior of EV Charging
   The uncertainty of EV charging behavior is an important aspect. In our study, the charging profile is based on standard commuting patterns, assuming that the EV is charged primarily in the evening. However, real-world usage varies, so future work could incorporate stochastic modeling to represent more dynamic charging schedules. This would allow for a more precise assessment of grid impact and self-consumption strategies.

• The conclusions affirm that the demonstrated model is a “scalable model for future smart grid solutions”. How is the “scalability” property demonstrated, since the authors have just experimented the illustrated installation? What scale economies (e.g.) could be obtained by doubling the dimension of the PV plant and of the battery and connecting a fleet of EV?
• Response:

Scalability and Future Expansion Considerations
Your concern regarding the claim of scalability is well noted. While we have demonstrated the feasibility of the system at an individual household level, scalability should be quantified in future work. Some factors that influence scalability include:

• Increasing PV and battery capacity: Doubling the system size could improve self-sufficiency but would require optimization of battery storage to prevent excess curtailment.
• Expanding EV integration: A fleet of EVs could act as a distributed energy resource (DER), contributing to grid stability through vehicle-to-grid (V2G) technologies.
• Economies of scale: Larger installations reduce per-unit costs of components and maintenance, enhancing economic feasibility.

We have refined our discussion on scalability to reflect these points more explicitly and propose a dedicated study on multi-unit scaling and economic feasibility as a next research step.

• As a suggestion for further research (maybe better if already indicated in the paper), the authors could investigate the business model of opening the illustrated experimental plant to a provision of ancillary services to the electrical system, by put (at least a part) of the battery surplus available for short charge/discharge cycles piloted from external requests. What about a participation of this “virtual power plant” to an ancillary services market?
• Response:

Exploring Business Models and Participation in Ancillary Services
We appreciate the suggestion regarding ancillary services and virtual power plant (VPP) participation. While our current study focuses on household-level optimization, an expanded system could participate in frequency regulation, demand response, and grid-support services by selling stored energy during peak demand periods. Future research could explore:

• Battery surplus management strategies, considering short charge/discharge cycles based on external grid requests.
• Participating in an ancillary services market, where stored energy can be traded dynamically, improving revenue potential.
• Integration of smart grid communication protocols, enabling real-time response to grid fluctuations.

This valuable perspective has been added as a suggested future research direction, reinforcing the broader implications of our study beyond household-scale applications.

 

We greatly appreciate the reviewer's thorough and constructive feedback, which has helped us improve the clarity, rigor, and practical relevance of our study. We have revised the manuscript accordingly to:

• Clarify system components, energy management, and grid interaction.
• Enhance figures and data visualization.
• Refine discussions on scalability, EV charging behavior, and battery management.
• Introduce future research directions, including participation in energy markets and ancillary services.

Your insightful comments have significantly strengthened the paper, and we sincerely thank you for your valuable contributions to this work.

 

Reviewer 4 Report

Comments and Suggestions for Authors

The paper presents a comprehensive analysis of a PV system integrated with battery storage and electric vehicle charging, complemented by an intelligent energy management system. It stands out due to the extensive simulation and real data analysis, which makes it relevant in the context of the transition to renewable energies and environmental sustainability. Its contribution is valuable as it combines theoretical and practical aspects and provides a scalable model that can serve as a reference for future implementations of distributed renewable energy systems. Some improvement opportunities for each section are as follows:

Introduction

The paper provides a broad overview of the state of the art and justifies the need to integrate renewable sources to achieve greater energy self-sufficiency, with the claims supported by an extensive bibliography that contextualizes the study. I suggest that the authors emphasize more precisely which specific gaps in the literature are being addressed by this study.

Materials and Methods

The design of the system, the configuration of its components, and the simulation tools used (such as PV*SOL and Global Solar Atlas) are detailed. The methodology allows the study to be reproduced, which is a strong point in terms of scientific transparency. However, I consider that some parameters (for example, the efficiency values or the estimated losses) require a more detailed justification or specific references to support their selection. It is important to improve the description of the EMS, explaining in more detail the algorithms or criteria used for energy allocation.

Results and Discussion

The results are presented in detail through multiple graphs and tables that illustrate the distribution, utilization, and efficiency of energy. The discussion covers the relevance of the results in terms of energy self-sufficiency and CO₂ emissions reduction, which reinforces the study's environmental contribution. However, for some graphs and tables, the interpretation of the results could benefit from a deeper discussion on seasonal variations and the practical implications of these variations. Additionally, it would be advisable to relate the obtained findings with previous studies more explicitly in order to highlight the novel contributions of this work.

Conclusions

The conclusions adequately summarize the main findings, highlighting the system's efficiency and its positive environmental impact. It would be valuable to suggest specific recommendations for practical implementation and propose research lines to address the identified limitations. I suggest reinforcing in the conclusions how this study differs from and contributes beyond previous studies.

Finally, some formatting aspects:

Figures 1, 2, 6, 7, 8, 9, 10, 11, 12, and 13: Add an x-axis label.

Figures 4 and 5: According to the journal format, the title must include the description of parts (a) and (b).

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 5 Report

Comments and Suggestions for Authors

Journal: Sustainability (ISSN 2071-1050)

Manuscript ID: sustainability-3512588

 

Article Title: Comprehensive analysis of a PV system integrated with battery storage, electric vehicle (EV) charging, and smart energy management.

 

The authors are trying to examine the design, performance, and impact of a grid-connected PV system in Constanta, Romania, assessing its ability to enhance energy efficiency, improve self-sufficiency, and contribute to environmental sustainability.

 

The article is interesting, but the present paper needs some improvements regarding the presentation and the structure.

The authors should address the following

 

• The objective in the ABSTRACT should be clearer and the authors should add their solution and their contribution in the abstract as well as in the conclusion.
• The title is very long.
• In Figure 1, what are the X and Y coordinates, and what are the units and what is W to the right side??
• In Figure 3, what are the X and Y coordinates, and what are the units and what is the symbol to the right side (it is not clear)??
• All terms in Tables should be added with definitions and units
• The authors should add their solution and their contribution in the conclusion.

Comments on the Quality of English Language

Fine

Author Response

Please see the attachment

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The paper is more like a statistics report than a paper. The difficulty is not shown at all. There is no mathematical explanation to what’s the real challenge from technical research, what’s the authors contribution, and what’s the research difficulty. There is even no one equation, which is the basic requirement for a research paper to show its unique contribution.

On the other side, it is not a literature, since it does not show the advantage and problems of the existing studies.  

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 4 Report

Comments and Suggestions for Authors

The authors have adequately responded to all my comments and incorporated the suggested revisions. I consider the manuscript to be significantly improved and now recommend it for publication.

Author Response

Thank you very much for your thoughtful evaluation and constructive feedback throughout the review process. We are sincerely grateful for the time and effort you dedicated to assessing our manuscript.

We are pleased to hear that you consider the revised version of our article, "Analysis of PV Systems with Battery Storage, EV Charging, and Smart Energy Management," to be significantly improved and suitable for publication. Your insightful comments have been instrumental in refining our work and enhancing the clarity and quality of our study.

We truly appreciate your recommendation and support.

Round 3

Reviewer 1 Report

Comments and Suggestions for Authors

Thanks to the authors for spending the time to revise the paper.

The paper may be accepted after enhancing the research difficulty. Data statistics can not show the rule behind the data, and can not provide valuable and convincing suggestions to other researchers, thus is poor for a journal paper. In other words, with different data from different systems or the same system at different times, one can easily write many papers.

Author Response

We appreciate the reviewer’s thoughtful remarks and concerns regarding the depth of analysis and the generalizability of our findings. In response, we would like to emphasize the following points to clarify the scientific rigor and broader relevance of our study:

1. Beyond Descriptive Statistics: Our research does not merely present data statistics; it integrates both empirical measurements and simulation-based modeling (via PV*SOL) to establish clear relationships between solar irradiance, energy production, storage dynamics, and electric vehicle (EV) charging behavior. The interaction of these variables is systematically analyzed through an intelligent Energy Management System (EMS), which governs real-time energy flow decisions.

2. Scientific Contribution and Generalizability: While the dataset is based on a specific PV-battery-EV system in Constanta, Romania, the system architecture, methodological framework, and analytical approach are designed to be scalable and adaptable. The energy balance equations, battery dynamics, and EMS logic are universal and can be applied to similar systems globally. This allows researchers to replicate or build upon our work in diverse geographical and operational contexts.

3. Research Novelty and Difficulty: This study moves beyond theoretical modeling by incorporating real-world implementation and validation. Such experimental validation significantly increases the research difficulty and enhances credibility. The incorporation of dynamic load profiles, seasonal effects, battery degradation, EV behavior modeling, and grid interaction further adds complexity and depth.

4. Valuable Insights and Practical Implications: Our analysis yields not only performance metrics but also critical insights into self-sufficiency, carbon reduction, and optimal resource allocation. These findings provide actionable guidance for engineers, energy planners, and policymakers aiming to deploy integrated renewable systems with maximum efficiency and environmental benefit.

5. 1. Avoiding Redundancy: We acknowledge the concern regarding potential for repetitive publication with different datasets. However, we stress that this manuscript is not a simple reapplication of the same method; it contributes a holistic, empirically validated model with detailed energy flow visualization, system optimization strategies, and comprehensive environmental impact assessment. These features distinguish our work from mere data reports.
      
      

      We have added several new scientific paragraphs that strengthen the theoretical depth, highlight the generalizability of the findings, and demonstrate the novelty and complexity of our integrated PV-battery-EV system. Specifically, the following additions were made:

       

      Paragraph 1 – Added to the Introduction section:

      In response to the need for enhanced research depth and broader applicability, this study goes beyond descriptive analysis by combining empirical field data with advanced simulation modeling and intelligent energy management algorithms. The hybrid approach enables not only the validation of system performance under real-world conditions but also the extraction of generalized rules and behavioral patterns applicable to similar PV-battery-EV setups worldwide.

      Paragraph 2 – Added to the Materials and Methods section

      The integration of a dynamic Energy Management System (EMS) further elevates the research difficulty, as it requires real-time decision-making based on fluctuating energy demand, solar generation profiles, and battery state-of-charge. By embedding the EMS into our system design, we simulate and optimize energy allocation strategies, which can be adopted or adapted by future smart grid projects globally.)

      Paragraph 3 – Added to the Results and Discussion section
      Unlike conventional statistical reports, this work reveals actionable insights through the empirical validation of system dynamics. For example, we show how seasonal shifts in solar irradiance influence self-sufficiency ratios and battery performance. These insights are crucial for researchers and practitioners aiming to design or retrofit sustainable energy systems under varying climatic and consumption conditions.

      Paragraph 4 – Added to the Conclusion section

      While the case study is geographically located in Constanta, the principles derived from our energy modeling, battery cycling behavior, and EV integration are scalable. The methodology—grounded in both theoretical formulation and real-world experimentation—presents a reproducible framework that other researchers can employ to optimize renewable systems in diverse regions and system sizes.