高频智能电表数据在能源经济与政策研究中的应用综述

Xiaofeng Ye, Zheyu Zhang, Y. Qiu
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引用次数: 3

摘要

先进计量基础设施(AMI)智能电表的快速普及产生了用户高频能耗数据。这些数据为能源经济学和政策研究提供了多种选择。在这篇综述中,我们研究了应用高频智能电表数据的研究,以探索家庭新技术采用和COVID-19对能源消耗模式的总体影响。我们发现高频智能电表数据提高了各种数据驱动算法预测模型的准确性。此外,发达经济学缺乏对能源贫困的精确评估和包容性理解。智能电表数据有助于扩大和深化能源贫困研究。研究弱势群体如何表现出能源贫困,可以提高社会对能源贫困的认识,有助于实施相关政策援助项目。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Review of application of high frequency smart meter data in energy economics and policy research
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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