IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v87y2010i3p925-933.html
   My bibliography  Save this article

A data-driven approach for steam load prediction in buildings

Author

Listed:
  • Kusiak, Andrew
  • Li, Mingyang
  • Zhang, Zijun

Abstract

Predicting building energy load is important in energy management. This load is often the result of steam heating and cooling of buildings. In this paper, a data-driven approach for the development of a daily steam load model is presented. Data-mining algorithms are used to select significant parameters used to develop models. A neural network (NN) ensemble with five MLPs (multi-layer perceptrons) performed best among all data-mining algorithms tested and therefore was selected to develop a predictive model. To meet the constraints of the existing energy management applications, Monte Carlo simulation is used to investigate uncertainty propagation of the model built by using weather forecast data. Based on the formulated model and weather forecasting data, future steam consumption is estimated. The latter allows optimal decisions to be made while managing fuel purchasing, scheduling the steam boiler, and building energy consumption.

Suggested Citation

  • Kusiak, Andrew & Li, Mingyang & Zhang, Zijun, 2010. "A data-driven approach for steam load prediction in buildings," Applied Energy, Elsevier, vol. 87(3), pages 925-933, March.
  • Handle: RePEc:eee:appene:v:87:y:2010:i:3:p:925-933
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306-2619(09)00380-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Zhai, H. & Dai, Y.J. & Wu, J.Y. & Wang, R.Z., 2009. "Energy and exergy analyses on a novel hybrid solar heating, cooling and power generation system for remote areas," Applied Energy, Elsevier, vol. 86(9), pages 1395-1404, September.
    2. Bénédicte Vidaillet & V. d'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    3. G. V. Kass, 1980. "An Exploratory Technique for Investigating Large Quantities of Categorical Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 29(2), pages 119-127, June.
    4. Wang, Jiangfeng & Dai, Yiping & Gao, Lin & Ma, Shaolin, 2009. "A new combined cooling, heating and power system driven by solar energy," Renewable Energy, Elsevier, vol. 34(12), pages 2780-2788.
    5. Ruan, Yingjun & Liu, Qingrong & Zhou, Weiguo & Firestone, Ryan & Gao, Weijun & Watanabe, Toshiyuki, 2009. "Optimal option of distributed generation technologies for various commercial buildings," Applied Energy, Elsevier, vol. 86(9), pages 1641-1653, September.
    6. Li, Qiong & Meng, Qinglin & Cai, Jiejin & Yoshino, Hiroshi & Mochida, Akashi, 2009. "Applying support vector machine to predict hourly cooling load in the building," Applied Energy, Elsevier, vol. 86(10), pages 2249-2256, October.
    7. Difs, Kristina & Danestig, Maria & Trygg, Louise, 2009. "Increased use of district heating in industrial processes - Impacts on heat load duration," Applied Energy, Elsevier, vol. 86(11), pages 2327-2334, November.
    8. Desideri, Umberto & Proietti, Stefania & Sdringola, Paolo, 2009. "Solar-powered cooling systems: Technical and economic analysis on industrial refrigeration and air-conditioning applications," Applied Energy, Elsevier, vol. 86(9), pages 1376-1386, September.
    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. Ahmad, Tanveer & Chen, Huanxin & Shair, Jan, 2018. "Water source heat pump energy demand prognosticate using disparate data-mining based approaches," Energy, Elsevier, vol. 152(C), pages 788-803.
    2. Balghouthi, M. & Chahbani, M.H. & Guizani, A., 2012. "Investigation of a solar cooling installation in Tunisia," Applied Energy, Elsevier, vol. 98(C), pages 138-148.
    3. Rezaie, Behnaz & Reddy, Bale V. & Rosen, Marc A., 2014. "An enviro-economic function for assessing energy resources for district energy systems," Energy, Elsevier, vol. 70(C), pages 159-164.
    4. Rezaie, Behnaz & Rosen, Marc A., 2012. "District heating and cooling: Review of technology and potential enhancements," Applied Energy, Elsevier, vol. 93(C), pages 2-10.
    5. DeLovato, Nicolas & Sundarnath, Kavin & Cvijovic, Lazar & Kota, Krishna & Kuravi, Sarada, 2019. "A review of heat recovery applications for solar and geothermal power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    6. Dabwan, Yousef N. & Pei, Gang & Gao, Guangtao & Li, Jing & Feng, Junsheng, 2019. "Performance analysis of integrated linear fresnel reflector with a conventional cooling, heat, and power tri-generation plant," Renewable Energy, Elsevier, vol. 138(C), pages 639-650.
    7. Kerme, Esa Dube & Orfi, Jamel & Fung, Alan S. & Salilih, Elias M. & Khan, Salah Ud-Din & Alshehri, Hassan & Ali, Emad & Alrasheed, Mohammed, 2020. "Energetic and exergetic performance analysis of a solar driven power, desalination and cooling poly-generation system," Energy, Elsevier, vol. 196(C).
    8. Jiang-Jiang, Wang & Chun-Fa, Zhang & You-Yin, Jing, 2010. "Multi-criteria analysis of combined cooling, heating and power systems in different climate zones in China," Applied Energy, Elsevier, vol. 87(4), pages 1247-1259, April.
    9. Shou, Chunhui & Luo, Zhongyang & Wang, Tao & Shen, Weidong & Rosengarten, Gary & Wei, Wei & Wang, Cheng & Ni, Mingjiang & Cen, Kefa, 2012. "Investigation of a broadband TiO2/SiO2 optical thin-film filter for hybrid solar power systems," Applied Energy, Elsevier, vol. 92(C), pages 298-306.
    10. Li, Jing & Li, Pengcheng & Pei, Gang & Alvi, Jahan Zeb & Ji, Jie, 2016. "Analysis of a novel solar electricity generation system using cascade Rankine cycle and steam screw expander," Applied Energy, Elsevier, vol. 165(C), pages 627-638.
    11. Rezaie, Behnaz & Reddy, Bale V. & Rosen, Marc A., 2015. "Exergy analysis of thermal energy storage in a district energy application," Renewable Energy, Elsevier, vol. 74(C), pages 848-854.
    12. Talluri, L. & Fiaschi, D. & Neri, G. & Ciappi, L., 2018. "Design and optimization of a Tesla turbine for ORC applications," Applied Energy, Elsevier, vol. 226(C), pages 300-319.
    13. Fiaschi, Daniele & Manfrida, Giampaolo & Maraschiello, Francesco, 2012. "Thermo-fluid dynamics preliminary design of turbo-expanders for ORC cycles," Applied Energy, Elsevier, vol. 97(C), pages 601-608.
    14. Tempesti, Duccio & Fiaschi, Daniele, 2013. "Thermo-economic assessment of a micro CHP system fuelled by geothermal and solar energy," Energy, Elsevier, vol. 58(C), pages 45-51.
    15. Xiao, Tingyu & Liu, Chao & Wang, Xurong & Wang, Shukun & Xu, Xiaoxiao & Li, Qibin & Li, Xiaoxiao, 2022. "Life cycle assessment of the solar thermal power plant integrated with air-cooled supercritical CO2 Brayton cycle," Renewable Energy, Elsevier, vol. 182(C), pages 119-133.
    16. Wang, Qiliang & Yang, Honglun & Zhong, Shuai & Huang, Yihang & Hu, Mingke & Cao, Jingyu & Pei, Gang & Yang, Hongxing, 2020. "Comprehensive experimental testing and analysis on parabolic trough solar receiver integrated with radiation shield," Applied Energy, Elsevier, vol. 268(C).
    17. Michel Feidt & Monica Costea, 2012. "Energy and Exergy Analysis and Optimization of Combined Heat and Power Systems. Comparison of Various Systems," Energies, MDPI, vol. 5(9), pages 1-22, September.
    18. Ab Kadir, Mohd Zainal Abidin & Rafeeu, Yaaseen & Adam, Nor Mariah, 2010. "Prospective scenarios for the full solar energy development in Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3023-3031, December.
    19. da Fonseca, Maryegli Borges & Poganietz, Witold-Roger & Gehrmann, Hans-Joachim, 2014. "Environmental and economic analysis of SolComBio concept for sustainable energy supply in remote regions," Applied Energy, Elsevier, vol. 135(C), pages 666-674.
    20. Wang, Jiangfeng & Zhao, Pan & Niu, Xiaoqiang & Dai, Yiping, 2012. "Parametric analysis of a new combined cooling, heating and power system with transcritical CO2 driven by solar energy," Applied Energy, Elsevier, vol. 94(C), pages 58-64.

    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:87:y:2010:i:3:p:925-933. 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.