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  ## Overview
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  A open-source large-scale energy meter dataset designed to support a variety of energy analytics applications, including load profile analysis, and load forecasting.
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- It compiles over 60 detailed electricity consumption datasets encompassing approximately **78,000** real buildings representing the global building stock, offering insights into the temporal and spatial variations in energy consumption.
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  The buildings are classified into two categories: **Commercial**, which includes **2,916** buildings, and **Residential**, which includes **75,121** buildings, with a total of 65,000 building-days of time-series data.
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  These buildings span diverse geographies, climatic zones, and operational profiles, providing a broad spectrum of usage patterns. Additional to the real buildings, it also
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  includes synthetic and simulated buildings electricity consumption data.
 
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  ## Overview
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  A open-source large-scale energy meter dataset designed to support a variety of energy analytics applications, including load profile analysis, and load forecasting.
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+ It compiles over 60 detailed electricity consumption datasets encompassing approximately **78,037** real buildings representing the global building stock, offering insights into the temporal and spatial variations in energy consumption.
581
  The buildings are classified into two categories: **Commercial**, which includes **2,916** buildings, and **Residential**, which includes **75,121** buildings, with a total of 65,000 building-days of time-series data.
582
  These buildings span diverse geographies, climatic zones, and operational profiles, providing a broad spectrum of usage patterns. Additional to the real buildings, it also
583
  includes synthetic and simulated buildings electricity consumption data.