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Describing Long-Term Electricity Demand Scenarios in the Telecommunications Industry: A Case Study of Japan

Author

Listed:
  • Yusuke Kishita

    (Advanced Manufacturing Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), 1-2-1, Namiki, Tsukuba, Ibaraki 3058564, Japan)

  • Yohei Yamaguchi

    (Division of Sustainable Energy and Environmental Engineering, Osaka University, 2-1, Yamada-oka, Suita, Osaka 5650871, Japan)

  • Yasushi Umeda

    (Department of Precision Engineering, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 1138656, Japan)

  • Yoshiyuki Shimoda

    (Division of Sustainable Energy and Environmental Engineering, Osaka University, 2-1, Yamada-oka, Suita, Osaka 5650871, Japan)

  • Minako Hara

    (Nippon Telegraph and Telephone Corporation, 3-9-11, Midori-cho, Musashino, Tokyo 1808585, Japan)

  • Atsushi Sakurai

    (Nippon Telegraph and Telephone Corporation, 3-9-11, Midori-cho, Musashino, Tokyo 1808585, Japan)

  • Hiroki Oka

    (Nippon Telegraph and Telephone Corporation, 3-9-11, Midori-cho, Musashino, Tokyo 1808585, Japan)

  • Yuriko Tanaka

    (Nippon Telegraph and Telephone Corporation, 3-9-11, Midori-cho, Musashino, Tokyo 1808585, Japan)

Abstract

Due to the rapid expansion of information and communication technology (ICT) usage, the telecommunications industry is faced with a challenge to promote green ICT toward achieving a low-carbon society. One critical obstacle in planning long-term strategies for green ICT is the uncertainty of various external factors, such as consumers’ lifestyle and technological advancement. To tackle this issue, this paper employs a scenario planning method to analyze electricity consumption in the telecommunications industry, where both changes in various external factors and energy-saving measures are assumed. We propose a model to estimate future electricity consumption of the telecommunications industry using a statistical approach. In a case study, we describe four scenarios that differ in the diffusion of ICT and the technological advancement of ICT equipment in order to analyze the electricity consumption in Japan’s telecommunications industry to 2030. The results reveal that the electricity consumption in 2030 becomes 0.7–1.6-times larger than the 2012 level (10.7 TWh/year). It is also shown that the most effective measures to reduce the electricity consumption include improving the energy efficiency of IP (Internet Protocol) communication equipment and mobile communication equipment.

Suggested Citation

  • Yusuke Kishita & Yohei Yamaguchi & Yasushi Umeda & Yoshiyuki Shimoda & Minako Hara & Atsushi Sakurai & Hiroki Oka & Yuriko Tanaka, 2016. "Describing Long-Term Electricity Demand Scenarios in the Telecommunications Industry: A Case Study of Japan," Sustainability, MDPI, vol. 8(1), pages 1-16, January.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:1:p:52-:d:61871
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    References listed on IDEAS

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    1. Lubritto, C. & Petraglia, A. & Vetromile, C. & Curcuruto, S. & Logorelli, M. & Marsico, G. & D’Onofrio, A., 2011. "Energy and environmental aspects of mobile communication systems," Energy, Elsevier, vol. 36(2), pages 1109-1114.
    2. World Bank, 2015. "World Development Indicators 2015," World Bank Publications - Books, The World Bank Group, number 21634.
    3. Jens Malmodin & Dag Lundén & Åsa Moberg & Greger Andersson & Mikael Nilsson, 2014. "Life Cycle Assessment of ICT," Journal of Industrial Ecology, Yale University, vol. 18(6), pages 829-845, December.
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    1. Kühn, Katharina Isabella, 2021. "Is Visiting the ESB Website Deteriorating the Air Quality of our Countries? A Statistical Analysis of the Relationship Between Air Pollution Levels and Information & Communication Technologies," Junior Management Science (JUMS), Junior Management Science e. V., vol. 6(4), pages 839-851.
    2. Pruethsan Sutthichaimethee & Kuskana Kubaha, 2018. "The Efficiency of Long-Term Forecasting Model on Final Energy Consumption in Thailand’s Petroleum Industries Sector: Enriching the LT-ARIMAXS Model under a Sustainability Policy," Energies, MDPI, vol. 11(8), pages 1-18, August.
    3. Jens Malmodin & Dag Lundén, 2018. "The Energy and Carbon Footprint of the Global ICT and E&M Sectors 2010–2015," Sustainability, MDPI, vol. 10(9), pages 1-31, August.
    4. Jacek Brożyna & Grzegorz Mentel & Eva Ivanová & Gennadii Sorokin, 2019. "Classification of Renewable Sources of Electricity in the Context of Sustainable Development of the New EU Member States," Energies, MDPI, vol. 12(12), pages 1-22, June.
    5. Yi Liang & Dongxiao Niu & Ye Cao & Wei-Chiang Hong, 2016. "Analysis and Modeling for China’s Electricity Demand Forecasting Using a Hybrid Method Based on Multiple Regression and Extreme Learning Machine: A View from Carbon Emission," Energies, MDPI, vol. 9(11), pages 1-22, November.
    6. Yu Sun & Elisabete A. Silva & Wei Tian & Ruchi Choudhary & Hong Leng, 2018. "An Integrated Spatial Analysis Computer Environment for Urban-Building Energy in Cities," Sustainability, MDPI, vol. 10(11), pages 1-19, November.

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