用智能电表数据补全缺失月份，精准预测家庭年用电量
Back-filling Missing Data When Predicting Domestic Electricity Consumption From Smart Meter Data
- 基于用电模式划分五类用户，按昼夜峰谷特征补全数据
- 可补全最多6个月缺失数据，实现全年用电量可靠估算
- 揭示夜间用电多的用户更适合峰谷电价，助其省钱
本研究利用家庭智能电表数据，估算全年电费。针对仅拥有不足一年数据的用户，提出一种回填方法，可补全最多六个月内缺失的用电数据，确保全年用电量估计的可靠性。根据日、夜及高峰用电模式，识别出五种典型家庭用电行为特征，表明对多数用户而言，尤其是夜间用电较多的用户，采用分时电价（ToU）比固定电价更具经济优势。研究成果有助于消费者更有效地管理能源使用，并为选择合适电价方案提供依据。
原文摘要 · Abstract (English)
This study uses data from domestic electricity smart meters to estimate annual electricity bills for a whole year. We develop a method for back-filling data smart meter for up to six missing months for users who have less than one year of smart meter data, ensuring reliable estimates of annual consumption. We identify five distinct electricity consumption user profiles for homes based on day, night, and peak usage patterns, highlighting the economic advantages of Time-of-Use (ToU) tariffs over fixed tariffs for most users, especially those with higher nighttime consumption. Ultimately, the results of this study empowers consumers to manage their energy use effectively and to make informed choices regarding electricity tariff plans.
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