A Simulation-Assisted Field Investigation on Control System Upgrades for a Sustainable Heat Pump Heating

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

 

Below I attatch my comments:

1. Information about the heating system used is not sufficient. There is no data on the heating and cooling capacity, compressor power, refrigerant type and other parameters of used heat pump. This should be supplemented.

 2. The results of the simulation model response to a single step and temperature response curves are presented. No other model tests have been performed especially with real input parameter changes. This should be supplemented.

 3. The results obtained from the simulation model and the actual heating installation are not compared, particularly in the long-term perspective. The error between model results and real values must be estimated.

Comments on the Quality of English Language

Some sentences should be corrected.

Author Response

Comment

1. Information about the heating system used is not sufficient. There is no data on the heating and cooling capacity, compressor power, refrigerant type, and other parameters of the used heat pump. This should be supplemented.

Response

The information and relevant parameters of the employed heat pump units are essential, and the authors have supplemented such details in the Methods (Section 2.1 Live laboratory description, Table 1).

Comment

2. The results of the simulation model response to a single step and temperature response curves are presented. No other model tests have been performed, especially with fundamental input parameter changes. This should be supplemented.

Response

In this report, the authors introduced the method of simulation tests (Section 2.4 Tuning algorithm tests) and presented the test results (Section 3.1 Simulation test results). The simulation tests included a unit-step response, tracking signal, and anti-interference tests. In the Section 3.1 Simulation test results, the authors provided the simulation test results and discussed them carefully. The test results exhibited the control system’s performance with input parameter changes. The results remained reliable while such tests were conducted in a simulation environment. After that, the control system’s performance in a field investigation was depicted and argued over clearly. Specifically, Fig. 12 (Page 15) exhibited the response performance of the control system (including water temperatures, indoor air temperature, water pump frequency, and valve opening) in a short-term regulation, demonstrating the control quality when the input parameter changes.

Comment

3. The results obtained from the simulation model and the actual heating installation are not compared, particularly in the long-term perspective. The error between model results and actual values must be estimated.

Response

As the reviewer commented, the error analysis cannot be ignored in a study about numerical modeling. Meanwhile, this research argues how to fit the control system for a heat pump heating project. The performance of a control system is usually estimated by the response time, overshoot, settling time, steady-state error, and so on. Specifically, in the Section 3.1 Simulation test results, the value of the steady-state error E_SS in the tuning process was 5.87 E-05, and the value of ITUE was 1051. As the authors commented in the Methods (Section 2.3 Advanced adaptive tuning algorithm, Equation (1)), the comprehensive evaluation index ITUE, rather than other error indexes, depicted the control quality faithfully.

Reviewer 2 Report

Comments and Suggestions for Authors -Specific challenges and issues from the previous heating period does the Smith-predictor-based PIλDμ cascade control system aim to address in heat pump-based renewable energy systems? -How does the advanced fireworks algorithm differ from the other intelligent optimization algorithms used in the study, and what are the key features that contribute to its effectiveness in tuning the structural parameters of the controllers? -What metrics were used to measure the improvements in average exergetic efficiency and complaint rate, and how were these metrics quantified during the simulation and live measurements? -In what ways does the configuration of the Smith-predictor-based control system contribute to reducing overshoot and shortening the settling time, particularly in the context of heating demand and supply? -What implications does the independence of the forecast and regulation of the return water temperature have on the overall efficiency and control strategy of the heating system, and how might an integral predictive control structure address this limitation in future research? Comments on the Quality of English Language

English is fine.

Author Response

Comment

1. What are the specific challenges and issues from the previous heating period that the Smith-predictor-based fractional-order PID cascade control system aims to address in heat pump-based renewable energy systems?

Response

This research is based on an actual Clean Heating Renovation Project in Shanxi Province, China. The specific issues that arose in the previous heating period of the project are common in heat-pump heating systems. Thus, in the Introduction and Methods, the authors analyzed the probable reasons for such challenges above and configured a fit control system to address that. As argued in the Introduction, the main question addressed by the research finally became using an advanced fireworks algorithm to tune the structural parameters of fractional-order PID controllers.

Comment

2. How does the advanced fireworks algorithm differ from the other intelligent optimization algorithms used in the study, and what are the key features that contribute to its effectiveness in tuning the structural parameters of the controllers?

Response

In this report, the authors commented on three intelligent enhancement algorithms for tuning the controller’s structural parameters, including the Particle Swarm Algorithm, the Artificial Fish Swarm Algorithm, and the Fireworks Algorithm. In the Introduction, the authors introduced the origin and development of the Fireworks Algorithm. We commented that the Fireworks Algorithm combined the strengths of swarm intelligence algorithms with narrow-sense evolutionary algorithms, using a unique framework for cooperative and competitive mechanisms and an innovative search strategy called ‘explosion’. Moreover, in the Section 2.3 Advanced adaptive tuning algorithm, the authors detailed the specific improvements in the Standard Fireworks Algorithm and the efforts to enhance the tuning performance of the advanced fireworks algorithm. To highlight the effectiveness of the tuning process of the advanced fireworks algorithm, the authors have supplemented relevant comments in the Abstract and Conclusion, respectively.

Comment

3. What metrics were used to measure the improvements in average energetic efficiency and complaint rate, and how were these metrics quantified during the simulation and live measurements?

Response

The authors have supplemented the relevant information and comments in the Results and discussion (Section 3.2 Live measure, Equations (7-10)). Such metrics were employed in the long-term observation rather than simulation tests.

Comment

4. How does the configuration of the Smith-predictor-based control system contribute to reducing overshoot and shortening the settling time, particularly in heating demand and supply?

Response

According to existing investigations into Smith-predictor-based control systems, the employment of the Smith predictor contributed to eliminating pure delay within a controlled object, which was the motive for Introduction into this research (Section 2.2 Advanced control Strategy and controller design, Figure 5). The authors remained uncertain about how the configuration of the Smith-predictor-based control system contributed to reducing overshoot and shortening the settling time, particularly in the context of heating demand and supply.

Comment

5. What implications does the independence of the forecast and regulation of the return water temperature have on the heating system's overall efficiency and control strategy, and how might an integral predictive control structure address this limitation in future research?

Response

This question is full of profound and challenging insights. The authors appreciate the reviewer’s comments, and we plan to discuss such issues in future studies.

Reviewer 3 Report

Comments and Suggestions for Authors

The study presents a novel approach to upgrading the control system for heat pump heating projects by introducing a Smith-predictor-based PID cascade control system tuned by an advanced fireworks algorithm. Here are some review comments:

1. More researches about the application of PID in heat pump application projected should be citted and discussed.

2. This robustness of this new control method needs to be analyzed.

3. The identification method of response characteristics of  key equipments should be detailed

Author Response

The study presents a novel approach to upgrading the control system for heat pump heating projects by introducing a Smith-predictor-based PID cascade control system tuned by an advanced fireworks algorithm. Here are some review comments:

Comment

1. More research about the application of PID in heat pump application projects should be cited and discussed.

Response

Even though PID control remains the most widely used control law in the HVAC (heating, ventilation, and air conditioning) field for its simplicity and intelligibility, the traditional integer-order PID control cannot fulfill the regulation function for sophisticated systems. In modern heating systems where waste heat and renewable energy sources are utilized extensively, the controlled object is impacted by corresponding processes. Thus, any disturbance will alter the response characteristics of each controlled process in the heating system. Owing to a finite number of controller structural parameters and unsuitable tuning methods that cannot modify these structural parameters in time, the conventional integer-order PID controller can almost not adapt to the alterations in response characteristics. Consequently, increasing the degree of freedom of controllers’ structural parameters and optimizing the tuning methodology have become the dominant measures to improve control performance. Hence, the authors cited and commented on relevant references for exhibiting such efforts in the Introduction. Nonetheless, the research on the fractional-order PID control applied in heat-pump heating projects remains limited.

Comment

2. The robustness of this new control method needs to be analyzed.

Response

The robustness is significant for a control system. In this study, the authors tested the tracking and anti-interference performance of the fitted control system, which presented ‘local robustness’. The results are in the Results and Discussion (Section 3.1 Simulation test results, Figure 11). Meanwhile, the ‘global robustness’ of the fitted control system remains to be observed in the long term (more than one heating period), which has not been included yet in the current report.

Comment

3. The identification method of response characteristics of critical equipment should be detailed.

Response

The identification of controlled object characteristics is necessary for control. Meanwhile, in a system where the controlled object is impacted by corresponding processes (a heat-pump heating system, e.g.), the controlled object’s characteristic tends to change caused by disturbance within/outside the system. Therefore, in such a system, the identification task is the model’s structure rather than the model’s parameter of the controlled object. An adaptive fractional-order PID control system can fit the controller’s structural parameters to the controlled object’s characteristics in time, which is the subject of this study. The identification method utilized in this research is identical to that employed in the report’s references [20-25]. More details about identification methods can be found in specific academic treatises. Considering the topic’s relevance to this report, the authors did not discuss the identification method in detail.

Reviewer 4 Report

Comments and Suggestions for Authors

Review of the paper

A simulation-assisted field investigation on control system upgrade for a heat-pump heating project

 

1. What is the main question addressed by the research?

The article raises an important issue of using an advanced fireworks algorithm to tune the structural parameters of controllers. Simulation and live measures demonstrate that the upgraded control scheme counters the adverse effects of time lag, reduces overshoot, and shortens the settling time. The advanced fireworks algorithm mitigates the adverse effect of capacity lag and simultaneously accelerates the optimizing and converging processes, exhibiting its comprehensive competitiveness among this study’s three intelligent optimization algorithms.

2. Do you consider the topic original or relevant in the field? Does it address a specific gap in the field?

The topic is original because the paper is based on an actual clean heating renovation project and completes the upgrade of the control system within the framework of heat pump heating.

3. What does it add to the subject area compared with other published material?

There were presented comparison and analyzing the effect of control system upgrade on heating efficiency and energy consumption of heating systems.

4. What specific improvements should the authors consider regarding the methodology? What further controls should be considered?

This study configures a Smith-predictor-based PI^lD^m cascade control system with an advanced fireworks algorithm that adaptively tunes the structural parameters of controllers to solve the problems that arose in the last heating period.

However, in Figure 13 A, at temperatures of 0 and -5°C, there is no comparison with the old version control system. It would be appropriate to add it or explain why it should not be there (if so).

5. Are the conclusions consistent with the evidence and arguments presented and do they address the main question posed?

The conclusions are presented clearly, meaningfully and fully reveal the essence of the article.

6. Are the references appropriate?

The references is relevant and corresponds to the topic of the study.

7. Please include any additional comments on the tables and figures.

In Figure 13 A, at temperatures of 0 and -5°C, there is no comparison with the old version control system. It would be appropriate to add it or explain why it should not be there (if so).

Author Response

Comment

1. What does the research address the central question?

Response

This study aims to configure a fit control system for a heat-pump heating project. As discussed in the Introduction, the main question addressed by the research finally became using an advanced fireworks algorithm to tune the structural parameters of fractional-order PID controllers. Fortunately, simulation and live measures demonstrated that the fitted control system countered the adverse effects of time lag, reduced overshoot, and shortened the settling time. Moreover, the advanced fireworks algorithm mitigated the adverse impact of capacity lag. It simultaneously accelerated the optimizing and converging processes, exhibiting its comprehensive competitiveness among this study’s three intelligent optimization algorithms.

Comment

2. Do you consider the topic original or relevant in the field? Does it address a specific gap in the field?

Response

The topic is original because this report is based on an actual Clean Heating Renovation Project and completes the upgrade of the control system within the framework of heat pump heating. Further, it addressed a specific gap in the heat-pump heating field, which is using an advanced fireworks algorithm to tune the structural parameters of fractional-order PID controllers.

Comment

3. What does it add to the subject area compared with other published material?

Response

The value of this study is fitting a Smith-predictor-based fractional-order PID cascade control system into an actual clean heating renovation project and using an advanced fireworks algorithm to tune the structural parameters of controllers adaptively. The simulation and field investigation supported our argument, and the results exhibited the positive effect of control system upgrades on the heating performance and energy efficiency of a heat-pump heating system.

Comment

4. What specific improvements should the authors consider regarding the methodology? What further controls should be considered? In Figure 13 A, at temperatures of 0 °C and -5 °C, there is no comparison with the old version control system. It would be appropriate to add or explain why it should not be there (if so).

Response

In the Methods, the authors analyzed the probable reasons for the unsatisfactory performance of a heat-pump heating project in detail, thereby presenting a novel control strategy, designing fit controllers, and fitting a tuning scheme for controllers’ structural parameters. To improve the control performance further, we modified the fireworks algorithm to simultaneously accelerate the optimizing and converging processes. In Figure 13 A, at temperatures of 0 °C and -5 °C, there is a comparison with the old-version control system. However, the heat pump units have been scarcely performing with light loads (load ratio ≤ 40%) under the management of the old-version control system. The authors have supplemented relevant comments in the Section 3.2 Live measure.

Comment

5. The conclusions are presented meaningfully and fully reveal the article's essence.

Response

The authors appreciate the reviewer’s commendation.

Comment

6. The references are relevant and correspond to the topic of the study.

Response

The authors appreciate the reviewer’s affirmative comment.

Comment

7. In Figure 13 A, at temperatures of 0 °C and -5 °C, there is no comparison with the old version control system. It would be appropriate to add or explain why it should not be there (if so). Please include any additional comments on the tables and figures.

Response

In Figure 13 A, at temperatures of 0 °C and -5 °C, there is a comparison with the old-version control system. However, the heat pump units have been scarcely performing with light loads (load ratio ≤ 40%) under the management of the old-version control system. The authors have reviewed all the tables and figures in this report and supplemented relevant comments in the text.

Reviewer 5 Report

Comments and Suggestions for Authors

The paper uses the Fireworks Algorithm for parameter optimization and compares the optimization of the heat pump system before and after. I believe the article can be considered for publication after the following minor modifications:

 

 

1. Nomenclature: Include a nomenclature section for reader understanding of technical terms.

2. Clear Innovation Points: Clearly state the innovation in the abstract and conclusion, for example:

“The aim of this paper is...”

“The innovation of this paper is...”

3. Algorithm Details: In the abstract or conclusion, explain which variant of the Fireworks Algorithm you used, why you chose this one, and what its advantages are.

4. Image Update: Please re-capture Figures 4, 6, and 7, ensuring that the lower box is fully visible.

Author Response

The paper uses the Fireworks Algorithm for parameter optimization and compares the optimization of the heat pump system before and after. I believe the article can be considered for publication after the following minor modifications:

Comment

1. Nomenclature: Include a nomenclature section for the reader's understanding of technical terms.

Response

The authors have supplemented the Nomenclature before the Introduction.

Comment

2. Clear Innovation Points: Clearly state the innovation in the abstract and conclusion, for example: “The aim of this paper is...” “The innovation of this paper is...”

Response

The authors have clearly stated the innovation of this study in the abstract and conclusion.

Comment

3. Algorithm Details: In the abstract or conclusion, explain which variant of the Fireworks Algorithm you used, why you chose this one and its advantages.

Response

The authors have supplemented relevant comments in the Abstract and Conclusion, respectively. The advanced fireworks algorithm is detailed in the Section 2.3 Advanced adaptive tuning algorithm.

Comment

4. Image Update: Please re-capture Figures 4, 6, and 7, ensuring the lower box is evident.

Response

The authors have reviewed and updated all the figures in this report, and we are sure that each detail is fully visible. Moreover, the authors suggest that the reviewers read the revised report using a PDF Reader.