Abstract
The rapid popularization of advanced metering infrastructure (AMI) smart meters produces customer high-frequency energy consumption data. These data provide diverse options for energy economics and policy research. In this review, we examine studies applying high frequency smart meter data to explore the overall impact of household new technology adoption and COVID-19 on energy consumption patterns. We find that high frequency smart meter data boosts the accuracy of forecasting models with various data-driven algorithms. In addition, there is a lack of precise assessment and inclusive understanding of energy poverty in advanced economics. Smart meter data help expand and deepen the energy poverty research. Research on how vulnerable groups exhibit energy poverty can improve society's understanding of energy poverty and help implement related policy assistance programs.
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