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The Development of Cloud Energy Management

Author

Listed:
  • Chin-Chi Cheng

    (Department of Energy and Refrigerating Air-Conditioning Engineering, National Taipei University of Technology, Taipei 10608, Taiwan)

  • Dasheng Lee

    (Department of Energy and Refrigerating Air-Conditioning Engineering, National Taipei University of Technology, Taipei 10608, Taiwan)

  • Ching Hung Wang

    (Chunghwa Telecom, Data Communications Business Group, Taipei 10048, Taiwan)

  • Shu Fen Lin

    (Chunghwa Telecom, Data Communications Business Group, Taipei 10048, Taiwan)

  • Hung-Peng Chang

    (Foundation of Taiwan Industry Service, Taipei 10608, Taiwan)

  • Shang-Te Fang

    (Foundation of Taiwan Industry Service, Taipei 10608, Taiwan)

Abstract

The energy management service (EMS) has been utilized for saving energy since 1982 by managing the energy usage of site or facilities through the microprocessor, computer, Ethernet, internet, and wireless sensor network. The development and represented function groups of EMS are illustrated in the supplementary file of this paper. Along with this tendency, a cloud EMS, named the intelligent energy management network (iEN), was launched by Chunghwa Telecom in 2011 and tested during a pilot run from 2012 to 2013. The cloud EMS integrated three service modes together, including infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). This cloud EMS could reduce the facility cost and enable a continuously improved service for energy conservation. From the literature review, 32 selected EMS cases of whole site and single facility were chosen for calculating the energy savings and payback rate. According to the literature, the average energy savings by applying EMS are 11.6% and 21.4% for the whole site and single facility, respectively. The iEN was applied on 55 demo sites with the similar scale, the same kind of machines and approaching conditions. The testing sites include a factory, a complex building, and a residual building, 12 lighting systems and 8 air conditioning systems. According to the testing results, the average energy savings by applying iEN are 10% and 23.5% for the whole site and single facility, respectively. Comparing with the reported EMS cases, it was found that the energy savings by adopting the cloud EMS were only 70%–80% compared with those using the traditional EMS. Although the cloud EMS presented less energy savings, it revolutionized the traditional EMS by its innovative business model. Compared with the averaged 1.7 years payback period of the traditional EMS, more than 70% of the cloud EMS cases could pay back immediately for the service fees and without the equipment investment.

Suggested Citation

  • Chin-Chi Cheng & Dasheng Lee & Ching Hung Wang & Shu Fen Lin & Hung-Peng Chang & Shang-Te Fang, 2015. "The Development of Cloud Energy Management," Energies, MDPI, vol. 8(5), pages 1-21, May.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:5:p:4357-4377:d:49591
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    References listed on IDEAS

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    1. Machairas, Vasileios & Tsangrassoulis, Aris & Axarli, Kleo, 2014. "Algorithms for optimization of building design: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 101-112.
    2. Swords, B. & Coyle, E. & Norton, B., 2008. "An enterprise energy-information system," Applied Energy, Elsevier, vol. 85(1), pages 61-69, January.
    3. Tian, Jinping & Shi, Han & Li, Xing & Chen, Lujun, 2012. "Measures and potentials of energy-saving in a Chinese fine chemical industrial park," Energy, Elsevier, vol. 46(1), pages 459-470.
    4. van Dam, S.S. & Bakker, C.A. & Buiter, J.C., 2013. "Do home energy management systems make sense? Assessing their overall lifecycle impact," Energy Policy, Elsevier, vol. 63(C), pages 398-407.
    5. Akbari, Hashem & Warren, Mashuri & de Almeida, Anibal & Connell, Deborah & Harris, Jeffrey, 1988. "Use of energy management systems for performance monitoring of industrial load-shaping measures," Energy, Elsevier, vol. 13(3), pages 253-263.
    6. 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.
    7. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
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