Research on household energy demand patterns, data acquisition and influencing factors: A review

Understanding household energy consumption (HEC) demand patterns and their influencing factors at different times can provide insights into household energy demand and consumption behavior. Combining with optimization technology can improve energy efficiency, promote energy conservation, and predict future energy demand. Obtaining comprehensive and accurate data is the basis for revealing and analyzing HEC patterns and related activities. The main purpose of this paper is to review the current methods of obtaining HEC data in different time dimensions, HEC patterns, and influencing factors at different times, and organically combine all three. We first start with HEC data. This paper provides an overview of the current methods and data types used to collect information on HEC and related activities. It includes macro panel data, micro questionnaire survey data, micro case study data, and micro smart meter and advanced sensor data. Following this, presents current studies on HEC patterns, with a focus on cross-country comparisons in the temporal dimension. Direct and indirect (time-occupancy) studies are two ways of studying HEC patterns over time. Finally, discusses the factors that influence HEC demand, such as climate, building type, and socio-demographic factors. The understanding of these factors is crucial for promoting energy conservation and efficiency in households.

Automated summary

This paper reviews the methods of obtaining household energy consumption (HEC) data in different time dimensions, HEC patterns, and influencing factors at different times, and organically combines all three for discussion. The findings show that understanding the demand patterns and influencing factors of household energy consumption is crucial for promoting energy conservation and efficiency.