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

Yusuke Kishita (), Yohei Yamaguchi, Yuji Mizuno, Shinichi Fukushige, Yasushi Umeda and Yoshiyuki Shimoda
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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

Sustainability, 2024, vol. 16, issue 15, 1-15

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.

Keywords: scenario analysis; electricity demand and supply; photovoltaics; electric vehicles; future uncertainties (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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