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Utilizing commercial heating, ventilating, and air conditioning systems to provide grid services: A review

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  • Fu, Yangyang
  • O'Neill, Zheng
  • Wen, Jin
  • Pertzborn, Amanda
  • Bushby, Steven T.

Abstract

The modern power grid faces multiple challenges due to an increase in the adoption of renewable generation, such as dynamically balancing supply and demand at different time scales. Demand side management in buildings plays a vital role in achieving this balance because buildings can provide grid services through a variety of building assets. However, the development of grid-interactive, efficient buildings is still in its infancy, and a systematic and holistic understanding of grid service delivery strategies in terms of energy efficiency, load shifting, load shedding and load modulating is still limited. This paper is a comprehensive review of the development and application of building-level control strategies for utilizing heating, ventilating, and air conditioning systems to provide grid services. These strategies have been investigated through numerical and experimental studies. Control algorithms, such as heuristic rule-based control and model-based control, have been used to enable the automatic control delivery of grid services. The advantages and disadvantages of the strategies are summarized and discussed. Research trends are also identified, which include considering predicted mean vote-based and occupant-based thermal comfort, modeling of occupant behavior, integrating power grid operations with building control, and combining different demand flexibility modes in the control design.

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  • Fu, Yangyang & O'Neill, Zheng & Wen, Jin & Pertzborn, Amanda & Bushby, Steven T., 2022. "Utilizing commercial heating, ventilating, and air conditioning systems to provide grid services: A review," Applied Energy, Elsevier, vol. 307(C).
    • Handle: RePEc:eee:appene:v:307:y:2022:i:c:s0306261921014100
    DOI: 10.1016/j.apenergy.2021.118133
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    as
    1. El Geneidy, Rami & Howard, Bianca, 2020. "Contracted energy flexibility characteristics of communities: Analysis of a control strategy for demand response," Applied Energy, Elsevier, vol. 263(C).
    2. Široký, Jan & Oldewurtel, Frauke & Cigler, Jiří & Prívara, Samuel, 2011. "Experimental analysis of model predictive control for an energy efficient building heating system," Applied Energy, Elsevier, vol. 88(9), pages 3079-3087.
    3. Patteeuw, Dieter & Henze, Gregor P. & Helsen, Lieve, 2016. "Comparison of load shifting incentives for low-energy buildings with heat pumps to attain grid flexibility benefits," Applied Energy, Elsevier, vol. 167(C), pages 80-92.
    4. Kim, Youngjin & Norford, Leslie K., 2017. "Optimal use of thermal energy storage resources in commercial buildings through price-based demand response considering distribution network operation," Applied Energy, Elsevier, vol. 193(C), pages 308-324.
    5. Wang, Huilong & Wang, Shengwei & Tang, Rui, 2019. "Development of grid-responsive buildings: Opportunities, challenges, capabilities and applications of HVAC systems in non-residential buildings in providing ancillary services by fast demand responses," Applied Energy, Elsevier, vol. 250(C), pages 697-712.
    6. Wang, Shengwei & Tang, Rui, 2017. "Supply-based feedback control strategy of air-conditioning systems for direct load control of buildings responding to urgent requests of smart grids," Applied Energy, Elsevier, vol. 201(C), pages 419-432.
    7. Nolan, Sheila & Neu, Olivier & O’Malley, Mark, 2017. "Capacity value estimation of a load-shifting resource using a coupled building and power system model," Applied Energy, Elsevier, vol. 192(C), pages 71-82.
    8. 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.
    9. Favoino, Fabio & Jin, Qian & Overend, Mauro, 2017. "Design and control optimisation of adaptive insulation systems for office buildings. Part 1: Adaptive technologies and simulation framework," Energy, Elsevier, vol. 127(C), pages 301-309.
    10. Shcherbakova, Anastasia & Kleit, Andrew & Cho, Joohyun, 2014. "The value of energy storage in South Korea’s electricity market: A Hotelling approach," Applied Energy, Elsevier, vol. 125(C), pages 93-102.
    11. Wang, Huilong & Wang, Shengwei & Shan, Kui, 2020. "Experimental study on the dynamics, quality and impacts of using variable-speed pumps in buildings for frequency regulation of smart power grids," Energy, Elsevier, vol. 199(C).
    12. Wang, D. & Parkinson, S. & Miao, W. & Jia, H. & Crawford, C. & Djilali, N., 2013. "Hierarchical market integration of responsive loads as spinning reserve," Applied Energy, Elsevier, vol. 104(C), pages 229-238.
    13. Liang, Zheming & Bian, Desong & Zhang, Xiaohu & Shi, Di & Diao, Ruisheng & Wang, Zhiwei, 2019. "Optimal energy management for commercial buildings considering comprehensive comfort levels in a retail electricity market," Applied Energy, Elsevier, vol. 236(C), pages 916-926.
    14. DeForest, Nicholas & Shehabi, Arman & Selkowitz, Stephen & Milliron, Delia J., 2017. "A comparative energy analysis of three electrochromic glazing technologies in commercial and residential buildings," Applied Energy, Elsevier, vol. 192(C), pages 95-109.
    15. 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.
    16. Arteconi, A. & Hewitt, N.J. & Polonara, F., 2012. "State of the art of thermal storage for demand-side management," Applied Energy, Elsevier, vol. 93(C), pages 371-389.
    17. Zhang, Liang & Wen, Jin & Li, Yanfei & Chen, Jianli & Ye, Yunyang & Fu, Yangyang & Livingood, William, 2021. "A review of machine learning in building load prediction," Applied Energy, Elsevier, vol. 285(C).
    18. Fu, Yangyang & Han, Xu & Baker, Kyri & Zuo, Wangda, 2020. "Assessments of data centers for provision of frequency regulation," Applied Energy, Elsevier, vol. 277(C).
    19. Barzin, Reza & Chen, John J.J. & Young, Brent R. & Farid, Mohammed M., 2015. "Peak load shifting with energy storage and price-based control system," Energy, Elsevier, vol. 92(P3), pages 505-514.
    20. Chen, Yongbao & Xu, Peng & Chen, Zhe & Wang, Hongxin & Sha, Huajing & Ji, Ying & Zhang, Yongming & Dou, Qiang & Wang, Sheng, 2020. "Experimental investigation of demand response potential of buildings: Combined passive thermal mass and active storage," Applied Energy, Elsevier, vol. 280(C).
    21. Barzin, Reza & Chen, John J.J. & Young, Brent R. & Farid, Mohammed M., 2015. "Application of PCM underfloor heating in combination with PCM wallboards for space heating using price based control system," Applied Energy, Elsevier, vol. 148(C), pages 39-48.
    22. Aste, Niccolò & Manfren, Massimiliano & Marenzi, Giorgia, 2017. "Building Automation and Control Systems and performance optimization: A framework for analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 313-330.
    23. Biegel, Benjamin & Westenholz, Mikkel & Hansen, Lars Henrik & Stoustrup, Jakob & Andersen, Palle & Harbo, Silas, 2014. "Integration of flexible consumers in the ancillary service markets," Energy, Elsevier, vol. 67(C), pages 479-489.
    24. Bianchini, Gianni & Casini, Marco & Vicino, Antonio & Zarrilli, Donato, 2016. "Demand-response in building heating systems: A Model Predictive Control approach," Applied Energy, Elsevier, vol. 168(C), pages 159-170.
    25. Jin, Qian & Favoino, Fabio & Overend, Mauro, 2017. "Design and control optimisation of adaptive insulation systems for office buildings. Part 2: A parametric study for a temperate climate," Energy, Elsevier, vol. 127(C), pages 634-649.
    26. Dong, Bing & Li, Zhaoxuan & Taha, Ahmad & Gatsis, Nikolaos, 2018. "Occupancy-based buildings-to-grid integration framework for smart and connected communities," Applied Energy, Elsevier, vol. 219(C), pages 123-137.
    27. Yin, Rongxin & Kara, Emre C. & Li, Yaping & DeForest, Nicholas & Wang, Ke & Yong, Taiyou & Stadler, Michael, 2016. "Quantifying flexibility of commercial and residential loads for demand response using setpoint changes," Applied Energy, Elsevier, vol. 177(C), pages 149-164.
    28. Tang, Hong & Wang, Shengwei, 2022. "A model-based predictive dispatch strategy for unlocking and optimizing the building energy flexibilities of multiple resources in electricity markets of multiple services," Applied Energy, Elsevier, vol. 305(C).
    29. Wang, D. & Parkinson, S. & Miao, W. & Jia, H. & Crawford, C. & Djilali, N., 2012. "Online voltage security assessment considering comfort-constrained demand response control of distributed heat pump systems," Applied Energy, Elsevier, vol. 96(C), pages 104-114.
    30. Hoon Lee, Jae & Jeong, Jinhwa & Tae Chae, Young, 2020. "Optimal control parameter for electrochromic glazing operation in commercial buildings under different climatic conditions," Applied Energy, Elsevier, vol. 260(C).
    31. 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.
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