IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v93y2015ip2p1385-1393.html
   My bibliography  Save this article

Research on the data transmission optimization for building energy consumption monitoring system based on fuzzy self-adaptation method

Author

Listed:
  • Zhao, Liang
  • Zhang, Jili

Abstract

BECMP (building energy consumption monitoring platform) offers powerful help to realize building energy conservation by collecting energy consumption data. A great quantity BECMPs have been established all over the world in recent years. However, packet loss problem begins to appear when the scale of BECMP is large enough and the network congestion happen. This paper presents a fuzzy control transmission methodology in order to solve the problem based on network delay. The proposed method could adjust the data transmission strategy according to the network congestion level by changing packet interval and packet size to adapt the changes of network load, and improve the quality and efficiency of data transmission. Three novel transmission controllers are proposed, VPI-FSaTC (varying packet interval fuzzy self-adaptive transmission controller), VPS-FSaTC (varying packet size fuzzy self-adaptive transmission controller), and VPIS-FSaTC (varying packet interval & size fuzzy self-adaptive transmission controller). The simulation results indicates that, the packet loss ratio decreases 23%, 71% and 79% by VPI-FSaTC, VPS-FSaTC and VPIS-FSaTC, respectively, compared to the default transmission method.

Suggested Citation

  • Zhao, Liang & Zhang, Jili, 2015. "Research on the data transmission optimization for building energy consumption monitoring system based on fuzzy self-adaptation method," Energy, Elsevier, vol. 93(P2), pages 1385-1393.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:1385-1393
    DOI: 10.1016/j.energy.2015.10.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544215013602
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2015.10.005?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. Faruqui, Ahmad & Sergici, Sanem & Sharif, Ahmed, 2010. "The impact of informational feedback on energy consumption—A survey of the experimental evidence," Energy, Elsevier, vol. 35(4), pages 1598-1608.
    2. Ueno, Tsuyoshi & Sano, Fuminori & Saeki, Osamu & Tsuji, Kiichiro, 2006. "Effectiveness of an energy-consumption information system on energy savings in residential houses based on monitored data," Applied Energy, Elsevier, vol. 83(2), pages 166-183, February.
    3. Filippín, C. & Larsen, S. Flores & Mercado, V., 2011. "Winter energy behaviour in multi-family block buildings in a temperate-cold climate in Argentina," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 203-219, January.
    4. Liang Zhao & Jili Zhang & Ruobing Liang, 2013. "Data Acquisition and Transmission System for Building Energy Consumption Monitoring," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-8, September.
    5. Filippín, C. & Flores Larsen, S., 2009. "Analysis of energy consumption patterns in multi-family housing in a moderate cold climate," Energy Policy, Elsevier, vol. 37(9), pages 3489-3501, September.
    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. Zhang, Chengyu & Luo, Zhiwen & Rezgui, Yacine & Zhao, Tianyi, 2024. "Enhancing building energy consumption prediction introducing novel occupant behavior models with sparrow search optimization and attention mechanisms: A case study for forty-five buildings in a univer," Energy, Elsevier, vol. 294(C).
    2. Barbeito, Inés & Zaragoza, Sonia & Tarrío-Saavedra, Javier & Naya, Salvador, 2017. "Assessing thermal comfort and energy efficiency in buildings by statistical quality control for autocorrelated data," Applied Energy, Elsevier, vol. 190(C), pages 1-17.

    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. Penelope Buckley, 2020. "Prices, information and nudges for residential electricity conservation : A meta-analysis," Post-Print hal-02500507, HAL.
    2. Antonio Paone & Jean-Philippe Bacher, 2018. "The Impact of Building Occupant Behavior on Energy Efficiency and Methods to Influence It: A Review of the State of the Art," Energies, MDPI, vol. 11(4), pages 1-19, April.
    3. Qadeer Ali & Muhammad Jamaluddin Thaheem & Fahim Ullah & Samad M. E. Sepasgozar, 2020. "The Performance Gap in Energy-Efficient Office Buildings: How the Occupants Can Help?," Energies, MDPI, vol. 13(6), pages 1-27, March.
    4. Olmos, Luis & Ruester, Sophia & Liong, Siok-Jen & Glachant, Jean-Michel, 2011. "Energy efficiency actions related to the rollout of smart meters for small consumers, application to the Austrian system," Energy, Elsevier, vol. 36(7), pages 4396-4409.
    5. Filippín, C. & Flores Larsen, S., 2012. "Summer thermal behaviour of compact single family housing in a temperate climate in Argentina," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3439-3455.
    6. Murtagh, Niamh & Nati, Michele & Headley, William R. & Gatersleben, Birgitta & Gluhak, Alexander & Imran, Muhammad Ali & Uzzell, David, 2013. "Individual energy use and feedback in an office setting: A field trial," Energy Policy, Elsevier, vol. 62(C), pages 717-728.
    7. Musiliu 0. Oseni & Michael G. Poilitt & David M. Retner & Laura-Lucia Richter & Kong Chyong, 2013. "2013 EPRG Public Opinion Survey: Smart Energy Survey — Attitudes and Behaviours," Cambridge Working Papers in Economics 1352, Faculty of Economics, University of Cambridge.
    8. Yu, Yihua & Guo, Jin, 2016. "Identifying electricity-saving potential in rural China: Empirical evidence from a household survey," Energy Policy, Elsevier, vol. 94(C), pages 1-9.
    9. Krishnamurti, Tamar & Davis, Alexander L. & Wong-Parodi, Gabrielle & Wang, Jack & Canfield, Casey, 2013. "Creating an in-home display: Experimental evidence and guidelines for design," Applied Energy, Elsevier, vol. 108(C), pages 448-458.
    10. Delmas, Magali A. & Fischlein, Miriam & Asensio, Omar I., 2013. "Information strategies and energy conservation behavior: A meta-analysis of experimental studies from 1975 to 2012," Energy Policy, Elsevier, vol. 61(C), pages 729-739.
    11. Buckley, Penelope, 2020. "Prices, information and nudges for residential electricity conservation: A meta-analysis," Ecological Economics, Elsevier, vol. 172(C).
    12. Fujimi, Toshio & Kajitani, Yoshio & Chang, Stephanie E., 2016. "Effective and persistent changes in household energy-saving behaviors: Evidence from post-tsunami Japan," Applied Energy, Elsevier, vol. 167(C), pages 93-106.
    13. Du, Limin & Guo, Jin & Wei, Chu, 2017. "Impact of information feedback on residential electricity demand in China," Resources, Conservation & Recycling, Elsevier, vol. 125(C), pages 324-334.
    14. Ian H. Rowlands & Tobi Reid & Paul Parker, 2015. "Research with disaggregated electricity end‐use data in households: review and recommendations," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 4(5), pages 383-396, September.
    15. Akito Ozawa & Ryota Furusato & Yoshikuni Yoshida, 2017. "Tailor-Made Feedback to Reduce Residential Electricity Consumption: The Effect of Information on Household Lifestyle in Japan," Sustainability, MDPI, vol. 9(4), pages 1-23, March.
    16. Lopes, M.A.R. & Antunes, C.H. & Martins, N., 2012. "Energy behaviours as promoters of energy efficiency: A 21st century review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4095-4104.
    17. Chou, Jui-Sheng & Gusti Ayu Novi Yutami, I, 2014. "Smart meter adoption and deployment strategy for residential buildings in Indonesia," Applied Energy, Elsevier, vol. 128(C), pages 336-349.
    18. Zhaoyang Kong & Xiucheng Dong & Zhongbing Zhou, 2015. "Seasonal Imbalances in Natural Gas Imports in Major Northeast Asian Countries: Variations, Reasons, Outlooks and Countermeasures," Sustainability, MDPI, vol. 7(2), pages 1-22, February.
    19. Brown, Christopher J. & Markusson, Nils, 2019. "The responses of older adults to smart energy monitors," Energy Policy, Elsevier, vol. 130(C), pages 218-226.
    20. Xu, Xiaojing & Chen, Chien-fei, 2019. "Energy efficiency and energy justice for U.S. low-income households: An analysis of multifaceted challenges and potential," Energy Policy, Elsevier, vol. 128(C), pages 763-774.

    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:energy:v:93:y:2015:i:p2:p:1385-1393. 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.journals.elsevier.com/energy .

    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.