Abstract
Smart meters are devices that provide detailed information about the energy consumed by specific electricity supply points, such as homes, offices, and businesses. Data from smart meters are useful for modeling energy systems, predicting electricity consumption, and understanding human behavior. We present the first smart meter dataset from Spanish electricity supply points, expanding the geographic diversity of available data on energy consumption at the household level and reducing biases in existing data, which typically come from a limited number of countries. The dataset consists of 25,559 raw hourly time series with an average length of nearly three years, spanning from November 2014 to June 2022. It also includes three subsets obtained by segmenting and cleaning the raw time series data, each focusing on the periods before, during, and after the COVID-19 lockdowns in Spain. This dataset is a valuable resource for studying electricity consumption patterns and behaviors that emerge in response to different natural experiments, such as nationwide and regional lockdowns, nighttime curfews, and changes in electricity pricing.
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