Internet of Things Dataset for Home Renewable Energy Management

Overview

This Internet of Things dataset for home renewable energy management was published in Data in Brief in 2024 to address the lack of publicly available data for simulating smart home and smart city energy management scenarios. The dataset is synthetic but generated using realistic parameters and partially based on real consumption data from homes in Saudi Arabia.

Dataset Generation

• Five separate datasets representing 20, 50, 100, and 200 homes over 365 days (one year) were generated and analyzed for suitability.
• For 50 homes, energy consumption and production profiles were generated using input derived from an existing dataset of Saudi homes.
• The data mimics realistic energy consumption and solar production patterns in smart homes that both consume and produce energy and can trade it peer-to-peer.

Data Structure

• Each dataset is provided as a CSV file where each row corresponds to a day (365 days) and each column represents the energy profile of a particular home.
• Values represent daily energy consumption or net consumption/production; positive values indicate net draw from the grid or peers, while negative values may indicate surplus production.
• The 20/50/100/200-home files allow experimentation with different city sizes; files can be merged carefully for larger synthetic cities.

Key Characteristics

• Focus on IoT-enabled smart home and smart city energy management and prediction.
• Generation procedure assumes typical appliance operation patterns (e.g., fridge 24/7, lights several hours per day, AC and kitchen appliances with daily usage windows), aggregated into whole-home values.
• Includes synthetic energy production values per home based on weather inputs and solar assumptions.

Limitations

• The dataset is synthetic rather than measured; it is statistically realistic but not directly observed.
• The maximum of 200 homes means it does not represent very large cities; merging files is possible but must be done carefully.
• No appliance-level breakdown is provided; only daily home-level values are available.

Use Cases

• Simulation of smart home energy management and optimization algorithms.
• Research on peer-to-peer energy trading among homes in smart city contexts.
• Development of energy consumption and production forecasting models in residential microgrids.

Access and License

The dataset is described in the Data in Brief article and made available via the associated data repository referenced in the paper. Users should consult the repository page for licensing terms and citation details.