IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v141y2021ics1364032121001416.html
   My bibliography  Save this article

Thermal comfort maintenance in demand response programs: A critical review

Author

Listed:
  • da Fonseca, André L.A.
  • Chvatal, Karin M.S.
  • Fernandes, Ricardo A.S.

Abstract

In the context of demand side management, the scientific community has directed some effort into research related to modifying the load curve of consumers, where this becomes an alternative toward making sustainable the consumption of electricity. Therefore, with this possibility, there inevitably emerges the need for maintaining indoor thermal conditions suitable for users, which constitutes the aspect of comfort of highest cost in terms of energy. In this sense, as main contribution, this article presents a review that places demand response and thermal comfort as the central elements, while observing, in a critical manner, how their relationship occurs. In addition, the economic and environmental aspects always present in this type of study are analyzed, as well as the social aspect to maintain indoor climatic conditions. Furthermore, a characterization of the studies is proposed given the presence of a variety of elements related to sustainability in a quantitative and qualitative form. Thus, the studies that most use sustainable resources are highlighted and may help with the challenges to implement demand response programs in practice. Finally, the critical review contributes by identifying how the researches addresses this issue and what gaps can be filled in the future.

Suggested Citation

  • da Fonseca, André L.A. & Chvatal, Karin M.S. & Fernandes, Ricardo A.S., 2021. "Thermal comfort maintenance in demand response programs: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    • Handle: RePEc:eee:rensus:v:141:y:2021:i:c:s1364032121001416
    DOI: 10.1016/j.rser.2021.110847
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032121001416
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2021.110847?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
    2. Hu, Maomao & Xiao, Fu, 2018. "Price-responsive model-based optimal demand response control of inverter air conditioners using genetic algorithm," Applied Energy, Elsevier, vol. 219(C), pages 151-164.
    3. Zhou, Bin & Li, Wentao & Chan, Ka Wing & Cao, Yijia & Kuang, Yonghong & Liu, Xi & Wang, Xiong, 2016. "Smart home energy management systems: Concept, configurations, and scheduling strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 30-40.
    4. Tang, Rui & Wang, Shengwei, 2019. "Model predictive control for thermal energy storage and thermal comfort optimization of building demand response in smart grids," Applied Energy, Elsevier, vol. 242(C), pages 873-882.
    5. Zhang, Xiangyu & Pipattanasomporn, Manisa & Rahman, Saifur, 2017. "A self-learning algorithm for coordinated control of rooftop units in small- and medium-sized commercial buildings," Applied Energy, Elsevier, vol. 205(C), pages 1034-1049.
    6. Yuchun Li & Yinghua Han & Jinkuan Wang & Qiang Zhao, 2018. "A MBCRF Algorithm Based on Ensemble Learning for Building Demand Response Considering the Thermal Comfort," Energies, MDPI, vol. 11(12), pages 1-20, December.
    7. Beaudin, Marc & Zareipour, Hamidreza, 2015. "Home energy management systems: A review of modelling and complexity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 318-335.
    8. Nikolaos Kampelis & Nikolaos Sifakis & Dionysia Kolokotsa & Konstantinos Gobakis & Konstantinos Kalaitzakis & Daniela Isidori & Cristina Cristalli, 2019. "HVAC Optimization Genetic Algorithm for Industrial Near-Zero-Energy Building Demand Response," Energies, MDPI, vol. 12(11), pages 1-23, June.
    9. Shaikh, Pervez Hameed & Nor, Nursyarizal Bin Mohd & Nallagownden, Perumal & Elamvazuthi, Irraivan & Ibrahim, Taib, 2014. "A review on optimized control systems for building energy and comfort management of smart sustainable buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 409-429.
    10. Romero Rodríguez, Laura & Brennenstuhl, Marcus & Yadack, Malcolm & Boch, Pirmin & Eicker, Ursula, 2019. "Heuristic optimization of clusters of heat pumps: A simulation and case study of residential frequency reserve," Applied Energy, Elsevier, vol. 233, pages 943-958.
    11. Romero Rodríguez, Laura & Sánchez Ramos, José & Álvarez Domínguez, Servando & Eicker, Ursula, 2018. "Contributions of heat pumps to demand response: A case study of a plus-energy dwelling," Applied Energy, Elsevier, vol. 214(C), pages 191-204.
    12. Thorsnes, Paul & Williams, John & Lawson, Rob, 2012. "Consumer responses to time varying prices for electricity," Energy Policy, Elsevier, vol. 49(C), pages 552-561.
    13. Siano, Pierluigi, 2014. "Demand response and smart grids—A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 461-478.
    14. Andrew Izawa & Matthias Fripp, 2018. "Multi-Objective Control of Air Conditioning Improves Cost, Comfort and System Energy Balance," Energies, MDPI, vol. 11(9), pages 1-18, September.
    15. Meinrenken, Christoph J. & Mehmani, Ali, 2019. "Concurrent optimization of thermal and electric storage in commercial buildings to reduce operating cost and demand peaks under time-of-use tariffs," Applied Energy, Elsevier, vol. 254(C).
    16. Yan, Xing & Ozturk, Yusuf & Hu, Zechun & Song, Yonghua, 2018. "A review on price-driven residential demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 411-419.
    17. O׳Connell, Niamh & Pinson, Pierre & Madsen, Henrik & O׳Malley, Mark, 2014. "Benefits and challenges of electrical demand response: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 686-699.
    18. Li, Xiwang & Wen, Jin & Malkawi, Ali, 2016. "An operation optimization and decision framework for a building cluster with distributed energy systems," Applied Energy, Elsevier, vol. 178(C), pages 98-109.
    19. Soyoung Yoo & Jiyong Eom & Ingoo Han, 2020. "Factors Driving Consumer Involvement in Energy Consumption and Energy-Efficient Purchasing Behavior: Evidence from Korean Residential Buildings," Sustainability, MDPI, vol. 12(14), pages 1-23, July.
    20. Wissner, Matthias, 2011. "The Smart Grid - A saucerful of secrets?," Applied Energy, Elsevier, vol. 88(7), pages 2509-2518, July.
    21. Xue, Xue & Wang, Shengwei & Yan, Chengchu & Cui, Borui, 2015. "A fast chiller power demand response control strategy for buildings connected to smart grid," Applied Energy, Elsevier, vol. 137(C), pages 77-87.
    22. Manzano-Agugliaro, Francisco & Montoya, Francisco G. & Sabio-Ortega, Andrés & García-Cruz, Amós, 2015. "Review of bioclimatic architecture strategies for achieving thermal comfort," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 736-755.
    23. Taimur Al Shidhani & Anastasia Ioannou & Gioia Falcone, 2020. "Multi-Objective Optimisation for Power System Planning Integrating Sustainability Indicators," Energies, MDPI, vol. 13(9), pages 1-32, May.
    24. Jin, Xin & Baker, Kyri & Christensen, Dane & Isley, Steven, 2017. "Foresee: A user-centric home energy management system for energy efficiency and demand response," Applied Energy, Elsevier, vol. 205(C), pages 1583-1595.
    25. Bianchini, Gianni & Casini, Marco & Pepe, Daniele & Vicino, Antonio & Zanvettor, Giovanni Gino, 2019. "An integrated model predictive control approach for optimal HVAC and energy storage operation in large-scale buildings," Applied Energy, Elsevier, vol. 240(C), pages 327-340.
    26. Nolan, Sheila & O’Malley, Mark, 2015. "Challenges and barriers to demand response deployment and evaluation," Applied Energy, Elsevier, vol. 152(C), pages 1-10.
    27. Hu, Maomao & Xiao, Fu & Wang, Lingshi, 2017. "Investigation of demand response potentials of residential air conditioners in smart grids using grey-box room thermal model," Applied Energy, Elsevier, vol. 207(C), pages 324-335.
    28. Herter, Karen, 2007. "Residential implementation of critical-peak pricing of electricity," Energy Policy, Elsevier, vol. 35(4), pages 2121-2130, April.
    29. Herie Park, 2020. "Human Comfort-Based-Home Energy Management for Demand Response Participation," Energies, MDPI, vol. 13(10), pages 1-15, May.
    30. Yoon, Ah-Yun & Kim, Young-Jin & Zakula, Tea & Moon, Seung-Ill, 2020. "Retail electricity pricing via online-learning of data-driven demand response of HVAC systems," Applied Energy, Elsevier, vol. 265(C).
    31. Matteo Dongellini & Paolo Valdiserri & Claudia Naldi & Gian Luca Morini, 2020. "The Role of Emitters, Heat Pump Size, and Building Massive Envelope Elements on the Seasonal Energy Performance of Heat Pump-Based Heating Systems," Energies, MDPI, vol. 13(19), pages 1-14, September.
    32. Xin-Rui Liu & Si-Luo Sun & Qiu-Ye Sun & Wei-Yang Zhong, 2020. "Time-Scale Economic Dispatch of Electricity-Heat Integrated System Based on Users’ Thermal Comfort," Energies, MDPI, vol. 13(20), pages 1-27, October.
    33. Peter C. Reiss & Matthew W. White, 2005. "Household Electricity Demand, Revisited," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 853-883.
    34. Hu, Maomao & Xiao, Fu & Jørgensen, John Bagterp & Wang, Shengwei, 2019. "Frequency control of air conditioners in response to real-time dynamic electricity prices in smart grids," Applied Energy, Elsevier, vol. 242(C), pages 92-106.
    35. Cui, Borui & Gao, Dian-ce & Wang, Shengwei & Xue, Xue, 2015. "Effectiveness and life-cycle cost-benefit analysis of active cold storages for building demand management for smart grid applications," Applied Energy, Elsevier, vol. 147(C), pages 523-535.
    36. Enescu, Diana, 2017. "A review of thermal comfort models and indicators for indoor environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1353-1379.
    37. Salo, Sonja & Jokisalo, Juha & Syri, Sanna & Kosonen, Risto, 2019. "Individual temperature control on demand response in a district heated office building in Finland," Energy, Elsevier, vol. 180(C), pages 946-954.
    38. Sean Williams & Michael Short & Tracey Crosbie & Maryam Shadman-Pajouh, 2020. "A Decentralized Informatics, Optimization, and Control Framework for Evolving Demand Response Services," Energies, MDPI, vol. 13(16), pages 1-30, August.
    39. Paterakis, Nikolaos G. & Erdinç, Ozan & Catalão, João P.S., 2017. "An overview of Demand Response: Key-elements and international experience," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 871-891.
    40. Li, Xiwang & Malkawi, Ali, 2016. "Multi-objective optimization for thermal mass model predictive control in small and medium size commercial buildings under summer weather conditions," Energy, Elsevier, vol. 112(C), pages 1194-1206.
    41. Gonçalves, Juliana E. & van Hooff, Twan & Saelens, Dirk, 2021. "Simulating building integrated photovoltaic facades: Comparison to experimental data and evaluation of modelling complexity," Applied Energy, Elsevier, vol. 281(C).
    42. Dongsheng Yang & Xinyi Zhang & Bowen Zhou, 2017. "Modeling and Control of Air Conditioning Loads for Consuming Distributed Energy Sources," Energies, MDPI, vol. 10(10), pages 1-17, October.
    43. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Demand response in smart electricity grids equipped with renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 64-72.
    44. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2016. "Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage," Applied Energy, Elsevier, vol. 163(C), pages 93-104.
    45. Haider, Haider Tarish & See, Ong Hang & Elmenreich, Wilfried, 2016. "A review of residential demand response of smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 166-178.
    46. Wang, Chuyao & Ji, Jie & Uddin, Md Muin & Yu, Bendong & Song, Zhiying, 2021. "The study of a double-skin ventilated window integrated with CdTe cells in a rural building," Energy, Elsevier, vol. 215(PA).
    47. Cohn, Steve M., 1980. "Fuel choice and aggregate energy demand in the residential and commercial sectors," Energy, Elsevier, vol. 5(12), pages 1203-1212.
    48. Jie Yang & Tongyu Liu & Huaibao Wang & Zhenhua Tian & Shihao Liu, 2019. "Optimizing the Regulation of Aggregated Thermostatically Controlled Loads by Jointly Considering Consumer Comfort and Tracking Error," Energies, MDPI, vol. 12(9), pages 1-17, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dranka, Géremi Gilson & Ferreira, Paula, 2019. "Review and assessment of the different categories of demand response potentials," Energy, Elsevier, vol. 179(C), pages 280-294.
    2. Meyabadi, A. Fattahi & Deihimi, M.H., 2017. "A review of demand-side management: Reconsidering theoretical framework," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 367-379.
    3. Cruz, Marco R.M. & Fitiwi, Desta Z. & Santos, Sérgio F. & Catalão, João P.S., 2018. "A comprehensive survey of flexibility options for supporting the low-carbon energy future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 338-353.
    4. Tang, Hong & Wang, Shengwei & Li, Hangxin, 2021. "Flexibility categorization, sources, capabilities and technologies for energy-flexible and grid-responsive buildings: State-of-the-art and future perspective," Energy, Elsevier, vol. 219(C).
    5. Hu, Maomao & Xiao, Fu & Wang, Shengwei, 2021. "Neighborhood-level coordination and negotiation techniques for managing demand-side flexibility in residential microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    6. Leinauer, Christina & Schott, Paul & Fridgen, Gilbert & Keller, Robert & Ollig, Philipp & Weibelzahl, Martin, 2022. "Obstacles to demand response: Why industrial companies do not adapt their power consumption to volatile power generation," Energy Policy, Elsevier, vol. 165(C).
    7. McPherson, Madeleine & Stoll, Brady, 2020. "Demand response for variable renewable energy integration: A proposed approach and its impacts," Energy, Elsevier, vol. 197(C).
    8. Amit Shewale & Anil Mokhade & Nitesh Funde & Neeraj Dhanraj Bokde, 2022. "A Survey of Efficient Demand-Side Management Techniques for the Residential Appliance Scheduling Problem in Smart Homes," Energies, MDPI, vol. 15(8), pages 1-34, April.
    9. Nizami, Sohrab & Tushar, Wayes & Hossain, M.J. & Yuen, Chau & Saha, Tapan & Poor, H. Vincent, 2022. "Transactive energy for low voltage residential networks: A review," Applied Energy, Elsevier, vol. 323(C).
    10. Good, Nicholas & Ellis, Keith A. & Mancarella, Pierluigi, 2017. "Review and classification of barriers and enablers of demand response in the smart grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 57-72.
    11. Buttitta, Giuseppina & Jones, Colin N. & Finn, Donal P., 2021. "Evaluation of advanced control strategies of electric thermal storage systems in residential building stock," Utilities Policy, Elsevier, vol. 69(C).
    12. Malik, Anam & Haghdadi, Navid & MacGill, Iain & Ravishankar, Jayashri, 2019. "Appliance level data analysis of summer demand reduction potential from residential air conditioner control," Applied Energy, Elsevier, vol. 235(C), pages 776-785.
    13. Zhan, Sicheng & Chong, Adrian, 2021. "Data requirements and performance evaluation of model predictive control in buildings: A modeling perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    14. Xu, Bing & Nayak, Amar & Gray, David & Ouenniche, Jamal, 2016. "Assessing energy business cases implemented in the North Sea Region and strategy recommendations," Applied Energy, Elsevier, vol. 172(C), pages 360-371.
    15. Kathirgamanathan, Anjukan & De Rosa, Mattia & Mangina, Eleni & Finn, Donal P., 2021. "Data-driven predictive control for unlocking building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    16. Fischer, David & Madani, Hatef, 2017. "On heat pumps in smart grids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 342-357.
    17. Alasseri, Rajeev & Tripathi, Ashish & Joji Rao, T. & Sreekanth, K.J., 2017. "A review on implementation strategies for demand side management (DSM) in Kuwait through incentive-based demand response programs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 617-635.
    18. Bhagya Nathali Silva & Murad Khan & Kijun Han, 2020. "Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities," Sustainability, MDPI, vol. 12(14), pages 1-23, July.
    19. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Hosseinzadeh, Mehdi & Yousefi, Hossein & Khorasani, Sasan Torabzadeh, 2018. "Optimal management of energy hubs and smart energy hubs – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 33-50.
    20. Wu, Xiaomin & Cao, Weihua & Wang, Dianhong & Ding, Min & Yu, Liangjun & Nakanishi, Yosuke, 2021. "Demand response model based on improved Pareto optimum considering seasonal electricity prices for Dongfushan Island," Renewable Energy, Elsevier, vol. 164(C), pages 926-936.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:141:y:2021:i:c:s1364032121001416. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.