IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i12p2133-d122964.html
   My bibliography  Save this article

A Two-Level Optimal Scheduling Strategy for Central Air-Conditioners Based on Metal Model with Comprehensive State-Queueing Control Models

Author

Listed:
  • Yebai Qi

    (Electric Power Planning & Engineering Institute, Beijing 100120, China
    Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Dan Wang

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Yu Lan

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Hongjie Jia

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Chengshan Wang

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Kaixin Liu

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Qing’e Hu

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Menghua Fan

    (State Grid Energy Research Institute, Changping District, Beijing 102249, China)

Abstract

Unlike some thermostatically controlled appliances (TCAs) with small capacities, Central Air-conditioner (CAC) has huge potential for demand response because of its large capacity. This paper presents a new CAC control strategy under multiple constraints. The CAC is modeled by three main modules: CAC central unit, water pumps, and temperature simulation of terminal users. The CAC’s power consumption is mainly determined by users’ load ratio. As the information and communication system have become the central nervous system of the smart grid, big data analysis is of great significance. Assuming that reliable two-way communication systems are preset, an integrated parameter priority list (IPPL) control strategy is used to control and monitor CAC. A new intelligent algorithm, Space Exploration and Unimodal Region Elimination (SEUMRE) algorithm, is introduced for solving the optimization problem of demand response targets generation under multiple constraints with the help of big data analysis. In this paper, influences and constrain factors, such as price and users’ comfortable levels are taken into account to satisfy the need of actual situation. Simulation results show that the proposed approach, when comparing with other typical optimization algorithms, yields better performances and efficiency.

Suggested Citation

  • Yebai Qi & Dan Wang & Yu Lan & Hongjie Jia & Chengshan Wang & Kaixin Liu & Qing’e Hu & Menghua Fan, 2017. "A Two-Level Optimal Scheduling Strategy for Central Air-Conditioners Based on Metal Model with Comprehensive State-Queueing Control Models," Energies, MDPI, vol. 10(12), pages 1-21, December.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:12:p:2133-:d:122964
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/12/2133/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/10/12/2133/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Behrangrad, Mahdi & Sugihara, Hideharu & Funaki, Tsuyoshi, 2011. "Effect of optimal spinning reserve requirement on system pollution emission considering reserve supplying demand response in the electricity market," Applied Energy, Elsevier, vol. 88(7), pages 2548-2558, July.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wojciech M. Kempa & Dariusz Kurzyk, 2022. "Analysis of Non-Steady Queue-Length Distribution in a Finite-Buffer Model with Group Arrivals and Power Saving Mechanism with Setups," Energies, MDPI, vol. 15(22), pages 1-15, November.

    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. 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.
    2. Wang, Dan & Zhou, Yue & Jia, Hongjie & Wang, Chengshan & Lu, Ning & Sui, Pang-Chieh & Fan, Menghua, 2016. "An energy-constrained state priority list model using deferrable electrolyzers as a load management mechanism," Applied Energy, Elsevier, vol. 167(C), pages 201-210.
    3. Motalleb, Mahdi & Thornton, Matsu & Reihani, Ehsan & Ghorbani, Reza, 2016. "A nascent market for contingency reserve services using demand response," Applied Energy, Elsevier, vol. 179(C), pages 985-995.
    4. Elif Ustundag Soykan & Mustafa Bagriyanik, 2020. "The Effect of SMiShing Attack on Security of Demand Response Programs," Energies, MDPI, vol. 13(17), pages 1-17, September.
    5. Liu, Zhe & Wang, Dan & Jia, Hongjie & Djilali, Ned, 2014. "Power system operation risk analysis considering charging load self-management of plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 136(C), pages 662-670.
    6. Vardakas, John S. & Zorba, Nizar & Verikoukis, Christos V., 2015. "Performance evaluation of power demand scheduling scenarios in a smart grid environment," Applied Energy, Elsevier, vol. 142(C), pages 164-178.
    7. Zhaojing Yin & Yanbo Che & Dezhi Li & Huanan Liu & Dongmin Yu, 2017. "Optimal Scheduling Strategy for Domestic Electric Water Heaters Based on the Temperature State Priority List," Energies, MDPI, vol. 10(9), pages 1-15, September.
    8. Arteconi, Alessia & Patteeuw, Dieter & Bruninx, Kenneth & Delarue, Erik & D’haeseleer, William & Helsen, Lieve, 2016. "Active demand response with electric heating systems: Impact of market penetration," Applied Energy, Elsevier, vol. 177(C), pages 636-648.
    9. Huang, Renfang & Zhang, Zhen & Zhang, Wei & Mou, Jiegang & Zhou, Peijian & Wang, Yiwei, 2020. "Energy performance prediction of the centrifugal pumps by using a hybrid neural network," Energy, Elsevier, vol. 213(C).
    10. De Coninck, Roel & Helsen, Lieve, 2016. "Quantification of flexibility in buildings by cost curves – Methodology and application," Applied Energy, Elsevier, vol. 162(C), pages 653-665.
    11. Georges, Emeline & Cornélusse, Bertrand & Ernst, Damien & Lemort, Vincent & Mathieu, Sébastien, 2017. "Residential heat pump as flexible load for direct control service with parametrized duration and rebound effect," Applied Energy, Elsevier, vol. 187(C), pages 140-153.
    12. 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).
    13. Ho-Sung Ryu & Mun-Kyeom Kim, 2020. "Combined Economic Emission Dispatch with Environment-Based Demand Response Using WU-ABC Algorithm," Energies, MDPI, vol. 13(23), pages 1-20, December.
    14. Wei, Zhinong & Chen, Sheng & Sun, Guoqiang & Wang, Dan & Sun, Yonghui & Zang, Haixiang, 2016. "Probabilistic available transfer capability calculation considering static security constraints and uncertainties of electricity–gas integrated energy systems," Applied Energy, Elsevier, vol. 167(C), pages 305-316.
    15. Hong, Ying-Yi & Apolinario, Gerard Francesco DG. & Chung, Chen-Nien & Lu, Tai-Ken & Chu, Chia-Chi, 2020. "Effect of Taiwan's energy policy on unit commitment in 2025," Applied Energy, Elsevier, vol. 277(C).
    16. Zhuang, Chaoqun & Choudhary, Ruchi & Mavrogianni, Anna, 2023. "Uncertainty-based optimal energy retrofit methodology for building heat electrification with enhanced energy flexibility and climate adaptability," Applied Energy, Elsevier, vol. 341(C).
    17. Heydarian-Forushani, E. & Golshan, M.E.H. & Shafie-khah, M., 2015. "Flexible security-constrained scheduling of wind power enabling time of use pricing scheme," Energy, Elsevier, vol. 90(P2), pages 1887-1900.
    18. 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.
    19. Yebai Qi & Dan Wang & Xuyang Wang & Hongjie Jia & Tianjiao Pu & Naishi Chen & Kaixin Liu, 2017. "Frequency Control Ancillary Service Provided by Efficient Power Plants Integrated in Queuing-Controlled Domestic Water Heaters," Energies, MDPI, vol. 10(4), pages 1-21, April.
    20. Navarro-Espinosa, Alejandro & Mancarella, Pierluigi, 2014. "Probabilistic modeling and assessment of the impact of electric heat pumps on low voltage distribution networks," Applied Energy, Elsevier, vol. 127(C), pages 249-266.

    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:gam:jeners:v:10:y:2017:i:12:p:2133-:d:122964. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.