Determinants and approaches of household energy consumption: A review

• Published in: Energy reports Vol. 10; pp. 1833 - 1850
• Main Authors: Tran, Le Na, Cai, Gangwei, Gao, Weijun
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-11-2023; Elsevier
• Subjects: Energy use prediction; Household energy consumption; Influencing factors; Occupant behavior; Text mining; Text mining; Occupant behavior; Household energy consumption; Influencing factors; Energy use prediction
• ISSN: 2352-4847; 2352-4847
• DOI: 10.1016/j.egyr.2023.08.026

Considering the trend of home energy use in the context of global energy scarcity, this study examines the effects of variables such as physical and social factors on household energy. Article summarization and text mining approaches were utilized to create a broad picture of home energy demand with successful predictive models to identify the most significant drivers and potential simulation techniques. Results show that the data-driven method was largely adopted, and hybrid modeling is the cutting-edge option to consider for energy forecasting. The findings demonstrated the importance of occupant-related parameters, which primarily focus on occupant behaviors. The shift in energy demand necessitates increased research efforts in residential areas in Asia-Pacific regions, which call for an energy conservation strategy in these emerging nations. The findings give academics and decision-makers a complete vision of analyzing home energy demand in the early phases and drive the development of effective energy-saving strategies and policies. Our review provides comparative perspectives of energy use drivers and a holistic understanding of various approaches, which can help to close the existing gaps and provide researchers in the same field with a straightforward direction.