Energy demand science for a decarbonized society in the context of the residential sector. (October 2020)

• Record Type: Journal Article
• Authors: Shimoda, Yoshiyuki; Yamaguchi, Yohei; Iwafune, Yumiko; Hidaka, Kazuyoshi; Meier, Alan; Yagita, Yoshie; Kawamoto, Hisaki; Nishikiori, Soichi
• Is Part Of: Renewable & sustainable energy reviews. Volume 132(2020)
• Publication Date: 2020-10
• Subjects: Energy demand science -- Residential sector -- Decarbonized society -- Measurement and analysis -- Energy demand model -- Influencing factors; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2020.110051
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: To develop a decarbonized society, two contradictory requirements must be met: (1) reducing energy demand and (2) creating flexibility in energy demand in order to respond to fluctuations in renewable electricity generation. To help meet these requirements, conventional energy efficiency studies should be extended to incorporate "energy demand science." This paper presents a definition of "energy demand science" and then reviews the related history and research questions of energy demand science in the context of the residential sector. It then examines three key areas that must be integrated into the next-generation energy demand science: (1) energy demand measurement with detailed granularity and analysis using cutting-edge technology, (2) energy demand modeling that helps clarify the formation mechanism of energy demand, and (3) identification of the factors that influence people's decision making, which represents typical human-dimension research. Energy demand science consists of technical, human, natural environment, demographic, and land-use dimensions, and their integration is key for the establishment of a decarbonized society. Highlights: Energy demand must be reduced and have the flexibility to establish decarbonization. Knowledge integration is needed for planning, design, and operation of energy systems. As energy demand data becomes more granular, data analysis methods must do the same. High spatiotemporal modeling and consideration of occupant behavior is necessary. Identification of factors influencing behavior is important to a human-dimension study.