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Integrated Proactive Control Model for Energy Efficiency Processes in Facilities Management: Applying Dynamic Exponential Smoothing Optimization

Author

Listed:
  • Shunling Ruan

    (College of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China)

  • Haiyan Xie

    (Department of Technology, Illinois State University, Normal, IL 61790-5100, USA)

  • Song Jiang

    (College of Management, Xi’an University of Architecture and Technology, Xi’an 710055, China)

Abstract

Sustainable facilities management (SFM) opens the door of opportunity for companies to evaluate the quality of resources and environment management at their facilities. It enables the principles of sustainable development. There is still inefficiency in quantitative research of integrating environmental factors, particularly multi-source data, to monitor and control complicated systems in buildings. The objective of this research is to develop an effective method to dynamically optimize energy efficiency in SFM plans and strategies. The research question is: can the integrated proactive method reduce energy consumption with dynamically adjustable controls? This paper proposes a coordinated proactive control method using dynamic time-series prediction (PCM-DTSP) for SFM, which optimizes system controls by integrating the prediction results and monitored environmental-data. The results show that, after optimization, the temperature fluctuations are reduced to 33.3%. The average temperature and maximum temperature are reduced by 8% and 13.1%, respectively. The instantaneous power consumption was reduced by 0.17 KW per hour for each cooling system unit. The PCM-DTSP method can significantly optimize energy efficiency, which paves the way for long-term comprehensive energy management. The contribution of the research lies in its optimized control of energy consumption, temperature stabilization, and improvement of environmental comfort solutions, which can be generalized to various types of buildings.

Suggested Citation

  • Shunling Ruan & Haiyan Xie & Song Jiang, 2017. "Integrated Proactive Control Model for Energy Efficiency Processes in Facilities Management: Applying Dynamic Exponential Smoothing Optimization," Sustainability, MDPI, vol. 9(9), pages 1-22, September.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:9:p:1597-:d:111273
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    1. Durand-Estebe, Baptiste & Le Bot, Cédric & Mancos, Jean Nicolas & Arquis, Eric, 2014. "Simulation of a temperature adaptive control strategy for an IWSE economizer in a data center," Applied Energy, Elsevier, vol. 134(C), pages 45-56.
    2. Giuseppe Ioppolo & Stefano Cucurachi & Roberta Salomone & Giuseppe Saija & Lei Shi, 2016. "Sustainable Local Development and Environmental Governance: A Strategic Planning Experience," Sustainability, MDPI, vol. 8(2), pages 1-16, February.
    3. Gann, David M. & Salter, Ammon J., 2000. "Innovation in project-based, service-enhanced firms: the construction of complex products and systems," Research Policy, Elsevier, vol. 29(7-8), pages 955-972, August.
    4. Shaikh, Pervez Hameed & Nor, Nursyarizal Bin Mohd & Nallagownden, Perumal & Elamvazuthi, Irraivan & Ibrahim, Taib, 2014. "A review on optimized control systems for building energy and comfort management of smart sustainable buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 409-429.
    5. Ni, Jiacheng & Bai, Xuelian, 2017. "A review of air conditioning energy performance in data centers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 625-640.
    6. Fabio Fantozzi & Francesco Leccese & Giacomo Salvadori & Michele Rocca & Marco Garofalo, 2016. "LED Lighting for Indoor Sports Facilities: Can Its Use Be Considered as Sustainable Solution from a Techno-Economic Standpoint?," Sustainability, MDPI, vol. 8(7), pages 1-13, June.
    7. Dounis, A.I. & Caraiscos, C., 2009. "Advanced control systems engineering for energy and comfort management in a building environment--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1246-1261, August.
    8. Ahn, Jonghoon & Cho, Soolyeon & Chung, Dae Hun, 2017. "Analysis of energy and control efficiencies of fuzzy logic and artificial neural network technologies in the heating energy supply system responding to the changes of user demands," Applied Energy, Elsevier, vol. 190(C), pages 222-231.
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    1. Corsini, Filippo & Appio, Francesco Paolo & Frey, Marco, 2019. "Exploring the antecedents and consequences of environmental performance in micro-enterprises: The case of the Italian craft beer industry," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 340-350.
    2. Aladayleh Khaled Jameel & Qudah Shatha Mustafa Abdallah Al & Bargues José Luis Fuentes & Gisbert Pablo Ferrer, 2023. "Global trends of the research on COVID-19 risks effect in sustainable facility management fields: a bibliometric analysis," Engineering Management in Production and Services, Sciendo, vol. 15(1), pages 12-28, March.

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