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SHEERM: Sustainable Household Energy and Environment Resources Management with Time-Series

Smart Home & Buildings Smart Home
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Catalog metadata: This page is a discovery record, not publisher documentation. Verify the description, schema, provenance, version, licence, and citation at the linked source before use.

Catalog Summary

"A real-world household dataset from 13 residential properties in Portugal over nearly three years, with 15-minute resolution measurements of electrical load, solar PV generation, weather parameters, and electricity market prices, published in Nature Scientific Data."

Catalog Notes

Overview

SHEERM (Sustainable Household Energy and Environment Resources Management) is a real-world dataset presented in Nature Scientific Data that captures household-scale energy dynamics alongside environmental and market factors. It integrates household electrical consumption, on-premises solar energy production, weather conditions, and electricity pricing over a multi-year period.

Data Collection

  • Thirteen Portuguese households equipped with certified smart electric meters recording consumption every 15 minutes.
  • Collection period spans nearly three years of continuous measurements.
  • Data sources include smart meters (household loads), PV systems (solar generation), nearby weather stations (temperature and irradiance), and electricity market data (hourly prices).

Measured Variables

  • Household electrical load (kW), in raw and processed forms.
  • Solar PV generation (kW) derived using photovoltaic modeling and validated against independent measurements.
  • Weather parameters such as solar irradiance, ambient temperature, humidity, and wind.
  • Electricity market price (e.g., EUR/kWh) for day-ahead and real-time markets.

Data Organization

  • Four main partitions: load, price, weather, and PV generation.
  • Load data provided as raw and processed time-series; processed data has missing values handled and outliers removed.
  • All data streams are synchronized using timestamps, enabling multi-dimensional analysis.

Use Cases

  • Short-term and long-term forecasting of household load and solar generation.
  • Demand response and grid optimization studies.
  • Cost minimization strategies based on dynamic electricity pricing.
  • Analysis of renewable integration at the household level.

Access and License

The dataset is published in Nature Scientific Data with an associated public repository (e.g., Zenodo) that hosts the data files and documentation. It is available for research and non-commercial reuse with appropriate citation.

View Data Structure

To explore column names, data types, and sample rows, visit the official dataset page on Kaggle.

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Cite This Dataset

The dataset creators ask users of this dataset to cite the accompanying paper. Use one of the verified formats below.

Cecílio, J., Rodrigues, T., Barros, M., & others (2025). Leveraging Sustainable Household Energy and Environment Resources Management with Time-Series. Scientific Data, 12(1), 479. https://doi.org/10.1038/s41597-025-04750-1

Source metadata: Nature Publishing Group (2025) · DOI: 10.1038/s41597-025-04750-1

Indexed by IoTDataset.com on Feb 03, 2026

Review the Source Record

Confirm the licence, version, access conditions, file format, and provenance at the source before use.

Open Source Page

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