The article presents the first smart meter dataset from Spanish electricity supply points, expanding the geographic diversity of available data on household energy consumption and reducing biases typically found in datasets from limited countries. The dataset, collected by GoiEner, a renewable energy cooperative, consists of 25,559 raw hourly time series with an average length of nearly three years, from November 2014 to June 2022. It includes three subsets focusing on periods before, during, and after the COVID-19 lockdowns in Spain. The dataset is valuable for studying electricity consumption patterns and behaviors in response to various natural experiments, such as nationwide and regional lockdowns, nighttime curfews, and changes in electricity pricing. The data has been validated to confirm the presence of expected seasonal patterns in electricity consumption time series. The dataset is publicly available on Zenodo, with detailed metadata and processing methods described in the article.The article presents the first smart meter dataset from Spanish electricity supply points, expanding the geographic diversity of available data on household energy consumption and reducing biases typically found in datasets from limited countries. The dataset, collected by GoiEner, a renewable energy cooperative, consists of 25,559 raw hourly time series with an average length of nearly three years, from November 2014 to June 2022. It includes three subsets focusing on periods before, during, and after the COVID-19 lockdowns in Spain. The dataset is valuable for studying electricity consumption patterns and behaviors in response to various natural experiments, such as nationwide and regional lockdowns, nighttime curfews, and changes in electricity pricing. The data has been validated to confirm the presence of expected seasonal patterns in electricity consumption time series. The dataset is publicly available on Zenodo, with detailed metadata and processing methods described in the article.