Optimal Control Strategies for Demand Response in Buildings under Penetration of Renewable Energy

Round 1

Reviewer 1 Report

The paper presents two control strategies for optimized demand response of buildings.

 

All the following indicated aspects should be clarified and better explained in the manuscript.

 

Introduction

1. For the sake of readability, at the end of Section 1 the authors should describe how the paper is structured.

 

Literature review

2. The main contributions of the paper are clearly described. Nevertheless, from the current manuscript it is not grasp understanding the novelty of the work. The authors should better highlight the innovative aspects of their work in the manuscript.

 

System design

3. A formal definition of demand response at the beginning of Section 2 is missing. Do the authors consider electric demand response or even multi-carrier microgrids?
4. The considered flexible loads are rule based and prediction based loads. Several recent scientific studies on energy management of buildings show that for instance loads could be modeled as non-controllable, shiftable and controllable comfort-based loads and controllable energy based loads. Do the authors handle all these devices? The Authors should comment this point.
5. The authors assume that temperature is enough for occupants to evaluate the internal comfort. Conversely, Several recent scientific studies show that Predict Mean Vote (PMV) is commonly used for assessing the building internal comfort (e.g., https://doi.org/10.1109/SMC.2019.8914489, https://doi.org/10.1109/CDC.2014.7040147, documents that could be cited in the text). The Authors should comment this point.
6. The storage dynamics in Table 3 is modelled as a first order buffer based on charging and discharging profiles. Several recent scientific studies on energy storage modelling (e.g., https://doi.org/10.1109/CASE48305.2020.9216875, https://doi.org/10.3390/en12071231, documents that could be cited in the text), show that generally mixed logical dynamical constraints are used to avoid simultaneous charging and discharging commands The Authors should comment this point.

 

Problem formulation

7. The authors should clearly characterize the overall optimal control problem that they intend to solve. What type of decision variables (i.e. integer, real, etc) and how many? How many constraints (bounding, inequality, equality)?

 

Case study

8. Is the case study based on real data? How are the data generated?
9. The author should report the running time of simulations (see the comment on large-scale dimensionality).
10. There is no sensitivity analysis in the paper. Is it reasonable?
11. The outcome of the proposed approach should be assessed and condensed into a suitable indicator(s) that synthetically summarizes the related overall correctness and accuracy.

 

Conclusions

12. Conclusions needs to be extended to present further implications for future research and many managerial insights based on the results of the study, as well as limitations.

 

Minor

13. The authors should check that all the used acronyms are explained the first time they are used.
14. Mainly the English is good and there are only a few typos. However the paper should be carefully rechecked.

Author Response

Responds to the reviewers 1#:

The paper presents two control strategies for optimized demand response of buildings.

All the following indicated aspects should be clarified and better explained in the manuscript.

Introduction

1. For the sake of readability, at the end of Section 1 the authors should describe how the paper is structured.

Reply: Thanks for your comments. The structure of this paper has been described. See lines 122 to 127.

Literature review

2. The main contributions of the paper are clearly described. Nevertheless, from the current manuscript it is not grasp understanding the novelty of the work. The authors should better highlight the innovative aspects of their work in the manuscript.

Reply: We highlighted innovation of this paper again. See lines 100 to 106.

System design

3. A formal definition of demand response at the beginning of Section 2 is missing. Do the authors consider electric demand response or even multi-carrier microgrids?

Reply: The formal definition of DR is added. We consider electric DR in this paper. See lines 58 to 60.

 

4. The considered flexible loads are rule based and prediction based loads. Several recent scientific studies on energy management of buildings show that for instance loads could be modeled as non-controllable, shiftable and controllable comfort-based loads and controllable energy based loads. Do the authors handle all these devices? The Authors should comment this point.

Reply: We only considered controllable comfort-based HVAC loads (also, adjustable loads) in this paper. We specified this in Section 2.5, see lines 206 to 209.

 

5. The authors assume that temperature is enough for occupants to evaluate the internal comfort. Conversely, Several recent scientific studies show that Predict Mean Vote (PMV) is commonly used for assessing the building internal comfort (e.g., https://doi.org/10.1109/SMC.2019.8914489, https://doi.org/10.1109/CDC.2014.7040147, documents that could be cited in the text). The Authors should comment this point.

Reply: Thanks for your recommendation. The thermal comfort index PMV was added and these two papers were cited also (reference No. 35, 36) See lines 218 to lines 220.

 

6. The storage dynamics in Table 3 is modelled as a first order buffer based on charging and discharging profiles. Several recent scientific studies on energy storage modelling (e.g., https://doi.org/10.1109/CASE48305.2020.9216875, https://doi.org/10.3390/en12071231, documents that could be cited in the text), show that generally mixed logical dynamical constraints are used to avoid simultaneous charging and discharging commands The Authors should comment this point.

Reply: The recommended papers have been cited (reference No. 37, 38).

Problem formulation

7. The authors should clearly characterize the overall optimal control problem that they intend to solve. What type of decision variables (i.e. integer, real, etc) and how many? How many constraints (bounding, inequality, equality)?

Reply: This load distance is the decision variable and the temperature setting range is the constraint for the DR optimal control problem. We added the description, see lines 214 to 215.

Case study

8. Is the case study based on real data? How are the data generated?

Reply: The building case is a real office building in Shanghai, while the DR control strategies have been implemented on a dynamic simulation platform Dymola. The electricity flexibility data in Table 4 was calculated by using the energy flexibility quantification framework that we proposed in our previous work (reference No. 27). We explained it, see lines 286 to 293.

 

9. The author should report the running time of simulations (see the comment on large-scale dimensionality).

Reply: The running time of each simulation has been described. See lines 307 to 309.

One typical summer day was simulated and analyzed for these two scenarios. The simulation running time of each scenario is approximately 50 seconds on Dymola (Version 2018) on Windows 10, with a 2.6 GHz processor (Intel Core i7-10700) and 16 GB RAM.

 

10. There is no sensitivity analysis in the paper. Is it reasonable?

Reply: We have validated the Dymola model with real building data; thus, we didn’t do the sensitivity analysis for the simulation model.

 

11. The outcome of the proposed approach should be assessed and condensed into a suitable indicator(s) that synthetically summarizes the related overall correctness and accuracy.

Reply: The load match index is the indicator to show the performance of the DR control strategies we proposed. And we compared this indicator in different DR control strategies. The results show that the prediction-based DR control strategy outperforms the rule-based DR control.

See lines 360 to 369.

As shown in Fig. 9, meanwhile, the peak load of the case building can be shifted by 24%–38% using only the energy flexibility capacity of passive thermal mass, and this rate could reach 51%–55% when an active storage tank is integrated, without sacrificing the occupant’s comfort. In paper [43], 25% of peak load reduction can be achieved by setting 2 °C higher than the normal thermostat setting in the cooling demand season. Similar results of 18.7% to  39.0% have been found in several other papers [44-46].

 

Conclusions

12. Conclusions needs to be extended to present further implications for future research and many managerial insights based on the results of the study, as well as limitations.

Reply: We modified the conclusion section. See lines 403 to 409.

 

Minor

13. The authors should check that all the used acronyms are explained the first time they are used.

Reply: We checked it thoroughly.

 

14. Mainly the English is good and there are only a few typos. However the paper should be carefully rechecked.

Reply: Our paper has been edited by Elsevier Language Editing Services, and we double-checked the grammar and structure again.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments on the manuscript number “Optimal control strategies for demand response in buildings under penetration of renewable energy”. I believe that the manuscript should be extended and provide more information to correctly communicate the work. The manuscript is in general well written, and the topic of the manuscript is suitable for Buildings Journal. The authors should attend the following comments:

1. What do the authors mean with "securing the safety of the power grid"?

2. In page 3, section 1.2, please erase the word "urgently"

3. I believe that the last five lines of the introduction are not necessary

4. In Fig 1, how come you don't not use the historical duck curve for China instead of the duck curve of California.

5. How do the authors know that the trend is going to be similar in the future? How did the authors build Fig 2?

6. More details of the HVAC, storage tank, etc. should be provided by the authors instead of just cite their previous work.

7. What does the load represent in Fig. 3? Does it represent only the load of the electricity demand of the HVAC? or does it represent the whole demand of electricity considering lighting, refrigerator, HVAC, etc.?

8. How did the authors obtain the curves of Fig. 4? It is not explained in the manuscript. Did they obtain it from a previous work of the authors? please explain.

9. How did the authors determine the actual load curves?

10. More details of the control strategy with the water tank should be provided by the authors. How is the water discharged and how it helps to reduce or increase the load demand?

11. I believe that the methodology is not sufficiently well explained that someone else knowledgeable about the field could repeat the study 

12. how does the storage tank work to store energy? is it connected to a TABS system? Is it buried in the ground?  

13. How is the thermal mass used as energy flexibility resource? Authors should give more details of the scenarios studied in the manuscript.

14. In page 11, How is the water tank integrated into the HVAC?

15. In page 11, Why do the load match indices are equal to 0.51 and 0.55?

16. What type of energy storage devices are charged?

17. The results obtained by the study should be compared to the available data noted in the literature review to highlight any new contribution of the work presented in the paper.    

 

Author Response

Responds to the reviewers 2#

Comments and Suggestions for Authors

Comments on the manuscript number “Optimal control strategies for demand response in buildings under penetration of renewable energy”. I believe that the manuscript should be extended and provide more information to correctly communicate the work. The manuscript is in general well written, and the topic of the manuscript is suitable for Buildings Journal. The authors should attend the following comments:

1. What do the authors mean with "securing the safety of the power grid"?

Reply: Thanks for your comments.

We have modified this section to make it clearer. We revised the word “safety” to “reliability” to avoid confusion and added the definition of DR in the Introduction section. See lines 58 to 60.

Demand Response (DR) is defined as “changes in electric use by demand-side resources from their normal consumption patterns in response to changes in the price of electricity or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized”.

Thus, users can reduce load use during peak load time and increase load use during valley load time of the power grid by participating DR programs. In this way, blackout could be avoided when extreme weather situations happen.

2. In page 3, section 1.2, please erase the word "urgently"

Reply: It has been deleted.

3. I believe that the last five lines of the introduction are not necessary

Reply: One of reviewer asked us to add the description of the paper structure. Thus, we kept it and let the editor to make the final decision.

4. In Fig 1, how come you don't not use the historical duck curve for China instead of the duck curve of California.

Reply: The concept of “duck curve” originally proposed in reference [14] by using California case, thus, we presented the duck curve of California first and we also presented the duck curve of North China in Fig. 2.

5. How do the authors know that the trend is going to be similar in the future? How did the authors build Fig 2?

Reply: To avoid misguidance, we deleted the sentence “For different areas in China, the net load demand curve may vary owing to the utilization of solar energy resources, whereas the trend in Fig. 2 is similar now and in the future”. The data in Fig. 2 is from an official report, and we cited it in the paper.

6. More details of the HVAC, storage tank, etc. should be provided by the authors instead of just cite their previous work.

Reply: Table 4 Table 5 and Fig. 5 have been added to show the detailed information of the building case.

7. What does the load represent in Fig. 3? Does it represent only the load of the electricity demand of the HVAC? or does it represent the whole demand of electricity considering lighting, refrigerator, HVAC, etc.?

Reply: It represent the total electricity load of buildings. We modified this part to make it clearer. See lines 177 to 180.

8. How did the authors obtain the curves of Fig. 4? It is not explained in the manuscript. Did they obtain it from a previous work of the authors? please explain.

Reply: Fig. 4 shows the schematic diagram of DR control strategy, so there is no real data in this figure. We modified this part to make it clearer.

9. How did the authors determine the actual load curves?

Reply: In the schematic diagram Fig. 4, all the curves are hypothetic, so we changed it to hypothetic net load curve.

10. More details of the control strategy with the water tank should be provided by the authors. How is the water discharged and how it helps to reduce or increase the load demand?

Reply: We added the context to describe the discharging and charging mode. See lines 240 to 244.

For instance, the water tank can be charged/discharged to increase or reduce the thermal load demand so that the power demand from the chiller could be changed. In this way, the chiller can be shut off to reduce power demand and the storage tank is discharging to provide the cooling load demand during the electricity peak load time. Furthermore, the chiller can also be turned on to increase the power demand for charging the storage tank during the valley load time.

11. I believe that the methodology is not sufficiently well explained that someone else knowledgeable about the field could repeat the study 

Reply: We added more information and modified this section carefully to make it clearer.

12. how does the storage tank work to store energy? is it connected to a TABS system? Is it buried in the ground?  

Reply: The water storage tank is connected with the HVAC systems, so, it stores chilled water. Fig. 5 shows the schematic layout and several operation modes have been descripted. See lines 251 to 259.

13. How is the thermal mass used as energy flexibility resource? Authors should give more details of the scenarios studied in the manuscript.

Reply: The detailed thermal mass of the building case is listed in Table 4. The calculation of flexibility from thermal mass was using the quantification framework that is mentioned in our previous study [27].

14. In page 11, How is the water tank integrated into the HVAC?

Reply: There is a loop that the chiller’s chiller water outlet connects with water tank. So that the chilled water can be stored in the tank and discharged when it is needed. We added Fig. 5 to show the detail.

15. In page 11, Why do the load match indices are equal to 0.51 and 0.55?

Reply: The load match indices are calculated by using the equation proposed in Section 2.4.

                                                 

16. What type of energy storage devices are charged?

Reply: Water storage tank.

17. The results obtained by the study should be compared to the available data noted in the literature review to highlight any new contribution of the work presented in the paper.

Reply: The results from literature review have been compared with our results. See lines 360 to 369.

As shown in Fig. 9, meanwhile, the peak load of the case building can be shifted by 24%–38% using only the energy flexibility capacity of passive thermal mass, and this rate could reach 51%–55% when an active storage tank is integrated, without sacrificing the occupant’s comfort. In paper [43], 25% of peak load reduction can be achieved by setting 2 °C higher than the normal thermostat setting in the cooling demand season. Similar results of 18.7% to 39.0% have been found in several other papers [44-46].

Author Response File: Author Response.pdf

Reviewer 3 Report

This paper presents the problem of the intermittent nature of renewable energy resources on the grid and suggests that building interventions can play a huge role in smoothing the net load demand curve for the grid. The originality of the paper is presenting a load match index to evaluate the effect of different interventions, in this case demand response control strategies. The authors implement a case study to show how the index works. The manuscript is well-written. More discussion is necessary. The zone named "abnormal zone" showing is plausible. For how many days did the authors calculate the scenarios? Why did the authors not expect this? The water tank has to be more detailed in the methods. For example "the load increase/reduction capacity is almost equal to the chiller load" can be given before. Some minor revisions include: The second sentence in the abstract beginning with "However, traditional..." is hard to understand. The first reference for Fig. 1 is on the beginning of page 2, yet the figure is on page 4. Please repeat that the duck curve is "the net load demand curve" in the beginning of Section 2. The paper does not cite the previous study in this sentence "To solve the duck curve problems and ensure the safety of the grid, a previous study proposed three approaches, as follows:" Revise section as sector in "In particular, the building section has massive potential..." Is there an input variable 2 in the water tank control strategy? If there is not, please explain why? In Table 3, please revise "temperatur" to "temperature". Please name the ASHRAE and Chinese standards defined in section 3.1 and Fig.5.

Author Response

Responds to the reviewers 3#

Comments and Suggestions for Authors

This paper presents the problem of the intermittent nature of renewable energy resources on the grid and suggests that building interventions can play a huge role in smoothing the net load demand curve for the grid. The originality of the paper is presenting a load match index to evaluate the effect of different interventions, in this case demand response control strategies. The authors implement a case study to show how the index works. The manuscript is well-written. More discussion is necessary. The zone named "abnormal zone" showing is plausible.

Reply: Thanks for your comments. More discussion about predicted based and ruled-based control were added. See lines 360 to 369.

For the rule-based control case, as shown in Fig. 9, the existence of an “abnormal zone” degrades the ability of load shifting. Thus, this zone could be avoided by designing a better rule-based DR control strategy. The temperature setting in Table 1 could be optimized, for instance, temperature could be set lower to increase the power demand during the abnormal zone time. For the predicted based control case, the “abnormal zone” problem disappears, which means that the predicted based control is better despite the predicted load baseline is additionally required. As shown in Fig. 9, meanwhile, the peak load of the case building can be shifted by 24%–38% using only the energy flexibility capacity of passive thermal mass, and this rate could reach 51%–55% when an active storage tank is integrated, without sacrificing the occupant’s comfort. In paper [43], 25% of peak load reduction can be achieved by setting 2 °C higher than the normal thermostat setting in the cooling demand season. Similar results of 18.7% to 39.0% have been found in several other papers [44-46].

 

For how many days did the authors calculate the scenarios? Why did the authors not expect this?

Reply: One day. The Fig. 8,9,10 show the duration already so we didn’t mention it in our first submission. To make it clearer, we added the simulation time in our revised manuscript. See lines 307 to 309.

 

The water tank has to be more detailed in the methods. For example "the load increase/reduction capacity is almost equal to the chiller load" can be given before.

Reply: Table 4 Table 5 and Fig. 5 have been added to provide more detailed of the model. More description has been added also. See lines 252 to 259.

 

Some minor revisions include: The second sentence in the abstract beginning with "However, traditional..." is hard to understand. The first reference for Fig. 1 is on the beginning of page 2, yet the figure is on page 4. Please repeat that the duck curve is "the net load demand curve" in the beginning of Section 2. The paper does not cite the previous study in this sentence "To solve the duck curve problems and ensure the safety of the grid, a previous study proposed three approaches, as follows:" Revise section as sector in "In particular, the building section has massive potential..." Is there an input variable 2 in the water tank control strategy? If there is not, please explain why? In Table 3, please revise "temperatur" to "temperature". Please name the ASHRAE and Chinese standards defined in section 3.1 and Fig.5.

Reply: We revised all of them carefully.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Previous comments and concerns have been sufficiently addressed. In the revised paper several improvements have been added.

Reviewer 2 Report

The authors have correctly attended all comments raised by the reviewer, I do recommend to accept the manuscript

Reviewer 3 Report

My concerns are sufficiently addressed.