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Scenario Analysis of Electricity Demand in the Residential Sector Based on the Diffusion of Energy-Efficient and Energy-Generating Products

Author

Listed:
  • Yusuke Kishita

    (School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan)

  • Yohei Yamaguchi

    (Graduate School of Engineering, Osaka University, Osaka 565-0871, Japan)

  • Yuji Mizuno

    (The Institute of Applied Energy, Tokyo 105-0003, Japan)

  • Shinichi Fukushige

    (School of Creative Science and Engineering, Waseda University, Tokyo 169-8555, Japan)

  • Yasushi Umeda

    (School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan)

  • Yoshiyuki Shimoda

    (Graduate School of Engineering, Osaka University, Osaka 565-0871, Japan)

Abstract

A variety of energy-efficient and energy-generating products, such as photovoltaics (PV) and electric vehicles, have diffused into the market to reduce greenhouse gas emissions in the residential sector. Understanding future changes in electricity demand and supply is complicated by uncertainties such as lifestyle shifts and national energy policies, and how such changes interact with the diffusion of products. To address this issue, this study adopts a scenario approach to analyze the impact of product diffusion on residential electricity demand under different social circumstances. Two simulation models are employed for the analysis: (i) a model for estimating the diffusion of products based on consumer preferences and (ii) a model to estimate electricity demand in residential sectors considering product diffusion. To demonstrate the proposed method, a scenario analysis case study was conducted, estimating the electricity demand in the residential sector of Toyonaka City, Osaka, Japan, for 2030. The results show that compared to 2012, the net electricity demand in the city in 2030 is projected to decrease by 20–39% depending on the scenarios considered, with changes in demographics and PV diffusion identified as among the most critical factors.

Suggested Citation

  • Yusuke Kishita & Yohei Yamaguchi & Yuji Mizuno & Shinichi Fukushige & Yasushi Umeda & Yoshiyuki Shimoda, 2024. "Scenario Analysis of Electricity Demand in the Residential Sector Based on the Diffusion of Energy-Efficient and Energy-Generating Products," Sustainability, MDPI, vol. 16(15), pages 1-15, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6435-:d:1444276
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    References listed on IDEAS

    as
    1. Bartusch, Cajsa & Alvehag, Karin, 2014. "Further exploring the potential of residential demand response programs in electricity distribution," Applied Energy, Elsevier, vol. 125(C), pages 39-59.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    3. Yamaguchi, Yohei & Shoda, Yuto & Yoshizawa, Shinya & Imai, Tatsuya & Perwez, Usama & Shimoda, Yoshiyuki & Hayashi, Yasuhiro, 2023. "Feasibility assessment of net zero-energy transformation of building stock using integrated synthetic population, building stock, and power distribution network framework," Applied Energy, Elsevier, vol. 333(C).
    4. Sun, Chuyu & Zhao, Xiaoli & Qi, Binbin & Xiao, Weihao & Zhang, Hongjun, 2022. "Economic and environmental analysis of coupled PV-energy storage-charging station considering location and scale," Applied Energy, Elsevier, vol. 328(C).
    5. Yu, Zhenyu & Lu, Fei & Zou, Yu & Yang, Xudong, 2022. "Quantifying the real-time energy flexibility of commuter plug-in electric vehicles in an office building considering photovoltaic and load uncertainty," Applied Energy, Elsevier, vol. 321(C).
    6. Yusuke Kishita & Takuma Masuda & Hidenori Nakamura & Kazumasu Aoki, 2023. "Computer‐aided scenario design using participatory backcasting: A case study of sustainable vision creation in a Japanese city," Futures & Foresight Science, John Wiley & Sons, vol. 5(1), March.
    7. Vilaça, Mariana & Santos, Gonçalo & Oliveira, Mónica S.A. & Coelho, Margarida C. & Correia, Gonçalo H.A., 2022. "Life cycle assessment of shared and private use of automated and electric vehicles on interurban mobility," Applied Energy, Elsevier, vol. 310(C).
    8. Kobashi, Takuro & Choi, Younghun & Hirano, Yujiro & Yamagata, Yoshiki & Say, Kelvin, 2022. "Rapid rise of decarbonization potentials of photovoltaics plus electric vehicles in residential houses over commercial districts," Applied Energy, Elsevier, vol. 306(PB).
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