IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v363y2024ics0306261924004793.html
   My bibliography  Save this article

An analogue on/off state-switching control method suitable for inverter-based air conditioner load cluster participating in demand response

Author

Listed:
  • Zhou, Te
  • Chen, Honghu
  • Zhang, Ning
  • Han, Yang
  • Zhou, Siyu
  • Li, Zhi
  • Zhou, Meng

Abstract

With the significant trend towards variable frequency in heating ventilating and air-conditioner (HVAC) loads, the inverter-based air conditioner load (IACL) clusters are poised to become the mainstay in participating in demand response (DR). During the process of DR, once the indoor temperature exceeds the comfort constraint, HVAC load must be forced to exit DR, which brings correlation to the behaviour of the preceding and following periods, making cluster optimization modelling and solution difficult. In order to solve the problems, this paper proposes an analogue ON/OFF state-switching (AOSS) control method suitable for IACL cluster participating in DR. Firstly, the critical working point corresponding to the comfort constraint is analysed for eliminating the temporal coupling for IACL. Then, an AOSS control method is proposed based on the critical point analysis. The feasibility of the proposed AOSS control is validated by the experimental results, with the Hisense KFR-75W/T08SBp-A2 inverter-based air conditioning DR experimental platform. Furthermore, by using the proposed AOSS control, a day-ahead scheduling model is constructed, and, the traditional state-queuing (SQ) model is transplanted to the IACL cluster for short-term power control. And the case studies verified the effectiveness and applicability of the day-ahead scheduling model and the transplanted SQ model.

Suggested Citation

  • Zhou, Te & Chen, Honghu & Zhang, Ning & Han, Yang & Zhou, Siyu & Li, Zhi & Zhou, Meng, 2024. "An analogue on/off state-switching control method suitable for inverter-based air conditioner load cluster participating in demand response," Applied Energy, Elsevier, vol. 363(C).
  • Handle: RePEc:eee:appene:v:363:y:2024:i:c:s0306261924004793
    DOI: 10.1016/j.apenergy.2024.123096
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924004793
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2024.123096?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. Gilson Dranka, Géremi & Ferreira, Paula & Vaz, A. Ismael F., 2022. "Co-benefits between energy efficiency and demand-response on renewable-based energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    2. Forero-Quintero, Jose-Fernando & Villafáfila-Robles, Roberto & Barja-Martinez, Sara & Munné-Collado, Ingrid & Olivella-Rosell, Pol & Montesinos-Miracle, Daniel, 2022. "Profitability analysis on demand-side flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    3. 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.
    4. Wei Hu & Jin Yang & Yi Wu & Weiguo Zhang & Xueming Li & Xiaorong Li & Ciwei Gao, 2020. "Generation-Load Coordinative Scheduling considering the Demand-Response Uncertainty of Inverter Air Conditioners," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-11, July.
    5. Dong, Lianxin & Wu, Qing & Hong, Juhua & Wang, Zhihua & Fan, Shuai & He, Guangyu, 2023. "An adaptive decentralized regulation strategy for the cluster with massive inverter air conditionings," Applied Energy, Elsevier, vol. 330(PA).
    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. 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. Deng, Xu & Lv, Tao & Meng, Xiangyun & Li, Cong & Hou, Xiaoran & Xu, Jie & Wang, Yinhao & Liu, Feng, 2024. "Assessing the carbon emission reduction effect of flexibility option for integrating variable renewable energy," Energy Economics, Elsevier, vol. 132(C).
    3. Rusche, Simon & Weissflog., Jan & Wenninger, Simon & Häckel, Björn, 2023. "How flexible are energy flexibilities? Developing a flexibility score for revenue and risk analysis in industrial demand-side management," Applied Energy, Elsevier, vol. 345(C).
    4. Xia, Mingchao & Song, Yuguang & Chen, Qifang, 2019. "Hierarchical control of thermostatically controlled loads oriented smart buildings," Applied Energy, Elsevier, vol. 254(C).
    5. Li, Zening & Su, Su & Jin, Xiaolong & Chen, Houhe, 2021. "Distributed energy management for active distribution network considering aggregated office buildings," Renewable Energy, Elsevier, vol. 180(C), pages 1073-1087.
    6. 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.
    7. Baxter Williams & Daniel Bishop & Patricio Gallardo & J. Geoffrey Chase, 2023. "Demand Side Management in Industrial, Commercial, and Residential Sectors: A Review of Constraints and Considerations," Energies, MDPI, vol. 16(13), pages 1-28, July.
    8. Couraud, Benoit & Andoni, Merlinda & Robu, Valentin & Norbu, Sonam & Chen, Si & Flynn, David, 2023. "Responsive FLEXibility: A smart local energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    9. Hwang, Hyunkyeong & Yoon, Ahyun & Yoon, Yongtae & Moon, Seungil, 2023. "Demand response of HVAC systems for hosting capacity improvement in distribution networks: A comprehensive review and case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    10. 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.
    11. 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.
    12. 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).
    13. Chen, Xiaoling & Miller, Cory & Goutham, Mithun & Hanumalagutti, Prasad Dev & Blaser, Rachel & Stockar, Stephanie, 2024. "Development and evaluation of an online home energy management strategy for load coordination in smart homes with renewable energy sources," Energy, Elsevier, vol. 290(C).
    14. Song, Yuguang & Chen, Fangjian & Xia, Mingchao & Chen, Qifang, 2022. "The interactive dispatch strategy for thermostatically controlled loads based on the source–load collaborative evolution," Applied Energy, Elsevier, vol. 309(C).
    15. Huang, He & Wang, Honglei & Hu, Yu-Jie & Li, Chengjiang & Wang, Xiaolin, 2022. "Optimal plan for energy conservation and CO2 emissions reduction of public buildings considering users' behavior: Case of China," Energy, Elsevier, vol. 261(PA).
    16. Ottavia Valentini & Nikoleta Andreadou & Paolo Bertoldi & Alexandre Lucas & Iolanda Saviuc & Evangelos Kotsakis, 2022. "Demand Response Impact Evaluation: A Review of Methods for Estimating the Customer Baseline Load," Energies, MDPI, vol. 15(14), pages 1-36, July.
    17. Zhang, Jiarui & Mu, Yunfei & Wu, Zhijun & Jia, Hongjie & Jin, Xiaolong & Qi, Yan, 2024. "Two-stage affine assessment method for flexible ramping capacity: An inverter heat pump virtual power plant case," Applied Energy, Elsevier, vol. 365(C).
    18. Maja Božičević Vrhovčak & Bruno Malbašić, 2023. "Unlocking the Value of Aggregated Demand Response: A Survey of European Electricity Markets," Energies, MDPI, vol. 16(17), pages 1-13, September.
    19. Bo wang & Nana Deng & Wenhui Zhao & Zhaohua Wang, 2022. "Residential power demand side management optimization based on fine-grained mixed frequency data," Annals of Operations Research, Springer, vol. 316(1), pages 603-622, September.
    20. Xinghua Tao & Nan Mo & Jianbo Qin & Xiaozhe Yang & Linfei Yin & Likun Hu, 2023. "Parallel Multi-Layer Monte Carlo Optimization Algorithm for Doubly Fed Induction Generator Controller Parameters Optimization," Energies, MDPI, vol. 16(19), pages 1-20, October.

    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:appene:v:363:y:2024:i:c:s0306261924004793. 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/405891/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.