Data-Driven Model-Based Control Strategies to Improve the Cooling Performance of Commercial and Institutional Buildings

Round 1

Reviewer 1 Report

Thank you for the work you did in this project. 

I have read the article carefully. 

You wrote: "The dataset was cleaned based on statistical means and expert knowledge" did you assess the expert knowledge? 

You wrote: "since there is no energy meter at each chiller evaporator, the total building cooling load was used instead" did you scale the influence of using cooling load in lieu of the energy meter?

Please, conduct the following: 

1- Uncertainties on the variables.

2- Sensitivities on both inputs and outputs.

Please, list all the energy consumers in the cooling system associate with numerical values. 

Please, make a site survey for the system and write down any potential energy consumers such as valves, dumpers actuators and so on.

When you make a comprehensive study, it will be a 3-D one and work as an X-Ray for the system. 

 

Thank you again for your work and I am looking to hearing from you.

Author Response

Thank you for the work you did in this project.

I have read the article carefully.

Response: We would like to thank you for reviewing the manuscript. Your comments were very useful, and we addressed them in the revised version of the manuscript.

You wrote: "The dataset was cleaned based on statistical means and expert knowledge" did you assess the expert knowledge?

Response: Expert knowledge refers to our experience on data processing and common sense used to clean the data. For example, the detection of outliers was performed based on statistical methods, but also based on examination of the data by visualization. This sentence has been reformulated to make it clearer.

You wrote: "since there is no energy meter at each chiller evaporator, the total building cooling load was used instead" did you scale the influence of using cooling load in lieu of the energy meter?

Response: The building cooling load refers to the building cooling thermal power and was measured using a flow meter and two temperature sensors (supply, return), which constitute an energy meter. To develop chiller performance curves, the cooling thermal power at each evaporator should be used; however, it is not usually measured in existing buildings. To address this issue, we used the building cooling load as a proxy, and we developed performance curves for several combinations of chillers in operation. To avoid any transitory effects due to chiller sequencing, we filtered the data in such a way that the corresponding combination of chillers must have been in operation for one hour and must remain in operation for one hour. Therefore, although we have not evaluated the assumption of “building cooling load = evaporator thermal load”, we considered that the combination of chillers in operation provided the building cooling load, which is a reasonable approximation to us. This sentence has been rephrased to better explain it.

Please, conduct the following:

1- Uncertainties on the variables.

2- Sensitivities on both inputs and outputs.

Response: Since we are working on an existing building, available information is relatively scarce to perform an uncertainty analysis. For the case study building, for instance, we do not know which type of temperature sensors and flow meters were installed, nor their main characteristics. However, we have conducted an uncertainty analysis on the building cooling thermal power as part of another study on the same building focusing on virtual energy meters [36]. For this purpose, we used typical sensor bias errors based on literature review and our experience. We have referred to this work in the revised version of the manuscript.

Please, list all the energy consumers in the cooling system associate with numerical values.

Please, make a site survey for the system and write down any potential energy consumers such as valves, dumpers actuators and so on.

When you make a comprehensive study, it will be a 3-D one and work as an X-Ray for the system.

Response: The approach you mentioned is definitely the most appropriate. One way to address the list of all the energy consumers could be to inventory each piece of equipment with name plates and nominal power; however, the list is long with regards to the number of components in the studied system (note that we have over 500 VAV boxes, where the dual-duct boxes have two dampers each) and seems out of the scope of this work. Moreover, this approach is not necessarily applicable with operational data since there are no energy measurements for valves and damper actuators. Nonetheless, the energy use related to valves and damper actuators is expected to be small compared to the electric power of chillers, circulating pumps and fans in cooling towers and air-cooled condensers. In the original version, we applied a top-down approach to quantify the contribution of chillers, pumps and fans in Figure 3. These results could be more granular and could represent the contribution of each component, but it might be in contradiction with the proposed approach, which aims to be simple and to evaluate the chilled water system as a whole. A sentence has been added in the revised version to address the energy use of valves and damper actuators. 

Reviewer 2 Report

This paper proposed to develop and evaluate energy efficiency measures to improve the cooling system performance of a commercial building. The proposed strategies include chiller sequencing strategy, free cooling strategy, and supply air temperature rest strategies. The comments were as follows.

(1) The proposed strategy did not have much innovation. The research gap was not clearly explained.

(2) The paper mainly reported a case study for a commercial building in Canada. It is questionable whether this case study represent all commercial and institutional buildings.

(3) The data analysis of this paper was like writing a case report.

(4) In Section 4.3: The description of Generalizability of proposed data-driven measures were very rough and may not be realistic.

 

Author Response

This paper proposed to develop and evaluate energy efficiency measures to improve the cooling system performance of a commercial building. The proposed strategies include chiller sequencing strategy, free cooling strategy, and supply air temperature rest strategies. The comments were as follows.

Response: Thank you for accepting to review this manuscript. Your comments have helped us improve the quality of the manuscript.

(1) The proposed strategy did not have much innovation. The research gap was not clearly explained.

Response: The research gaps as well as the innovation have been better explained in the revised version of the manuscript and we hope that the innovation is now clarified. In a nutshell, we have developed data-driven model-based control strategies for operating the chilled-water based system, which aim to be generic and applicable to many HVAC configurations while being easily implemented in buildings, compared to more complex methods such as predictive control.

(2) The paper mainly reported a case study for a commercial building in Canada. It is questionable whether this case study represent all commercial and institutional buildings.

Response: The question of building typicality is critical in this work. We aim to provide measures which are applicable to many buildings. The case study building has a chilled-water system composed of multiple chillers with primary/secondary air handling units and variable air volume terminal boxes. This configuration has been found relatively common in commercial and institutional buildings. ASHRAE Guideline 36 [31] concentrated among others on primary/secondary air handling units and variable air volume terminal boxes whereas at least 5 other research papers mentioned in the literature review have focused on chilled-water systems, and more specifically chiller sequencing with case study buildings located in Canada, mainland China, Hong Kong, Singapore and Taiwan [23-25,32-33,40].

(3) The data analysis of this paper was like writing a case report.

Response: Section 2 provides the description of the case study building and includes information gained from operational data in Section 2.3, which could be seen as a data analysis section. The goal of this subsection is to provide more context to the obtained results; especially, the contribution of chillers, pumps and cooling towers to the building electric power and the impact of ventilation on the building cooling load, which mainly depends on the climate. However, we consider a full detailed data analysis out of scope of this work; only the information required to better understand the proposed control strategies is presented. We tentatively explained it in the original version of the manuscript, but we have improved it in the revised version. Moreover, each subsection in Section 3 focusses on the proposed measures and the associated data-driven models; operational data was thus required and is further explained in the context of modelling. Section 4 evaluates the performance of data-driven measures. Results are given in Table 4 for the whole period of time, and figures are shown to better explain how each measure affects the overall performance.

(4) In Section 4.3: The description of Generalizability of proposed data-driven measures were very rough and may not be realistic.

Response: The proposed data-driven measures aim to be implemented by means of simple rule-based controls. Since they only require software modifications, these measures might be more realistic compared to other control retrofits, which typically need hardware upgrades or retrofits. The supply air-temperature reset strategy is inspired from ASHRAE Guideline 36 [31], which aims to ease the practical implementation of high-performance local controls. The free cooling strategy is similar to an air economizer that adjusts fresh air intake based on indoor/outdoor conditions; the proposed approach is based on a similar framework, facilitating the implementation. Compared to previous research, the current approach for the chiller sequencing is also simpler, thus more easily implementable, since it is only based on the current building cooling load. Chilled-water system is lumped, which avoids the complexity of controlling pump speed, water flow rate and temperature as performed in [23], the development of a model predictive control strategy [24], which requires in essence more implementation efforts (e.g. frequent access to weather forecasts, optimization routine, communication with the control system) or the need for advanced optimization routines [40]. These measures have been implemented in the case study building and we are currently replicating the approach to other existing buildings equipped with a chiller-water system but different AHU configurations. Therefore, we consider that Section 4.3 provides a realistic description of the generalizability of the measures and useful insights for their practical implementation in existing buildings. 

Reviewer 3 Report

Dear authors,
Your paper is interesting and the topic presented follows current trends. The article is well written in a clear way. Furthermore, not much editing is required.
The research and its design are clear and no significant errors were detected. The methods used were described in detail.
However, some additional corrections must be done for the article to be published as professional scientific work.
1.    The abstract gives a good sense of the article and allows even a person not familiar with the field to follow.
2.    The conditional statements “could”, “can”, and “should” are not always used in the correct way. Sometimes the use suggests that the authors are not sure in the places where definite statements (supported by other research) are required (e.g. line 50).
3.    The introduction is well-written and gives a good state-of-art overview of the field. One comment to control strategies review- some aspects of new tools/systems used and control based on occupancy should be implemented and referenced (e.g. DOI: 10.1109/IDAACS53288.2021.9661000)
Paper objectives and contributions are well presented.
4.    Chapter 2 is well written presenting the examined object. However, as the authors, at the beginning of the chapter are introducing the building, the figure with the view/picture of this structure would allow for better understanding.
5.    The presented results are very clear. No additional questions to the methodology or performed tests. Some figures seem to be out of focus, probably due to the conversion to pdf. Please check this before the final submission.
6.    Small values presentation problem, - there is a rule to put the space between the value and the unit, which authors are doing correctly. This rule does not apply to 0C and %. Check the whole article and make changes. This problem occurs frequently.
7.    The conclusions are mostly correct but the element of underlining the novelty is not put strong enough. Please improve.

Conclusions:
The topic of the article is interesting and the article has no significant problems with methodology, data presentation and results discussion. Can be considered for publication after minor corrections.
 

Author Response

Dear authors,

Your paper is interesting and the topic presented follows current trends. The article is well written in a clear way. Furthermore, not much editing is required.

The research and its design are clear and no significant errors were detected. The methods used were described in detail.

Response: We would like to thank you for your detailed review of the manuscript and for your positive feedback. Your valuable comments have helped us improve the scientific value of the present work.

However, some additional corrections must be done for the article to be published as professional scientific work.

1. The abstract gives a good sense of the article and allows even a person not familiar with the field to follow.

Response: Thank you for the positive feedback.

2. The conditional statements “could”, “can”, and “should” are not always used in the correct way. Sometimes the use suggests that the authors are not sure in the places where definite statements (supported by other research) are required (e.g. line 50).

Response: We have revised the usage of conditional statements throughout the document and have made modifications when it was relevant.

3. The introduction is well-written and gives a good state-of-art overview of the field. One comment to control strategies review- some aspects of new tools/systems used and control based on occupancy should be implemented and referenced (e.g. DOI: 10.1109/IDAACS53288.2021.9661000)

Response: Thank you for raising this topic. We have already cited two review papers related to occupant centric controls in the original version of the manuscript [15-16]. [15] concentrates on MPC based on occupancy behavior whereas [16] covers field implementation of occupant-centric building controls. The manuscript also mentions an article focusing on the optimization of fresh air intake based on occupancy to reduce energy usage [20]. We went through the proposed article and although interesting, it seems out of the scope of the present work for two main reasons: the case study building is a 40-m2 residential home and not a commercial building, and the emphasis is more on CO2 concentration and ventilation, rather than energy efficiency and cooling system. Since occupant-centric controls is not the focus of this paper while we concentrate on commercial and institutional buildings, we think that we have provided enough relevant information with [15-16, 20] but thank you for the suggestion.

Paper objectives and contributions are well presented.

4. Chapter 2 is well written presenting the examined object. However, as the authors, at the beginning of the chapter are introducing the building, the figure with the view/picture of this structure would allow for better understanding.

Response: We would have liked to show a picture of the case study building; however, this information is confidential and cannot be shared, and the same comment applies to the operational data. We consider that Figs 1-2 provide enough information on the systems under study to understand the proposed approach while limiting the amount of specific details that could allow to identify the case study building.

5. The presented results are very clear. No additional questions to the methodology or performed tests. Some figures seem to be out of focus, probably due to the conversion to pdf. Please check this before the final submission.

Response: We will make sure that the figures are of the best quality and the conversion to pdf might have affected their quality as you mentioned.

6. Small values presentation problem, - there is a rule to put the space between the value and the unit, which authors are doing correctly. This rule does not apply to 0C and %. Check the whole article and make changes. This problem occurs frequently.

Response: We have revised the usage of unit format throughout the document and have made modifications for the °C accordingly. For %, the space between the value and the unit only occurs in tables for readability purposes; in the main text, no space was used.  

7. The conclusions are mostly correct but the element of underlining the novelty is not put strong enough. Please improve.

Response: We have better explained the research gaps and the innovation in the introduction section and we have reformulated the novelty in the conclusions. We hope that the revised version of the manuscript is now clearer.  

Round 2

Reviewer 2 Report

The authors have addressed all the comments.