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EnergyBench

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  # EnergyBench Dataset
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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 **2,900** buildings, and **Residential**, which includes **75,100** 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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@@ -586,17 +588,101 @@ For datasets involving a large number of buildings, we partitioned the data into
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  Metadata of each datasets are provided in [metadata](https://huggingface.co/datasets/ai-iot/EnergyBench/tree/main/Dataset_V0.0/metadata).
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  Table 1: Summary of EnergBench dataset (Real Buildings)
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- | Category | # Datasets | # Buildings | # Days | # Hourly Obs |
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  |-------------|-------------|--------------|---------|--------|
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  | Commercial | 20 | 2,916 | 16,706 | 62M |
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  | Residential | 47 | 75,121 | 43,852 | 1.2B |
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-
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-
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  Table 2: Summary of EnergBench dataset (Synthetic and Simulated Buildings)
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- | Category | # Datasets | # Buildings | # Days | # Hourly Obs |
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  |-------------|-------------|--------------|---------|--------|
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  | Commercial | 1 | 207,559 | 365 | ~1.7B |
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  | Residential | 4 | 31M | 966 | ~718.7B |
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  # EnergyBench Dataset
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+ ## Overview
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+
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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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  Metadata of each datasets are provided in [metadata](https://huggingface.co/datasets/ai-iot/EnergyBench/tree/main/Dataset_V0.0/metadata).
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  Table 1: Summary of EnergBench dataset (Real Buildings)
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+ | **Category** | **# Datasets** | **# Buildings** | **# Days** | **# Hourly Obs** |
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  |-------------|-------------|--------------|---------|--------|
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  | Commercial | 20 | 2,916 | 16,706 | 62M |
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  | Residential | 47 | 75,121 | 43,852 | 1.2B |
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  Table 2: Summary of EnergBench dataset (Synthetic and Simulated Buildings)
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+ | **Category** | **# Datasets** | **# Buildings** | **# Days** | **# Hourly Obs** |
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  |-------------|-------------|--------------|---------|--------|
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  | Commercial | 1 | 207,559 | 365 | ~1.7B |
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  | Residential | 4 | 31M | 966 | ~718.7B |
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+ ## Dataset Details
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+
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+ Below tables shows the summary of the real buildings
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+
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+ Table 3: Details of real commercial buildings
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+ | **Dataset** | **Location** | **# Buildings**| **Year** | **# Days** | **# Hourly Obs** | **Unit** | **Resolution** | **Type** |
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+ |----------------------------------------------------------|----------------|--------------|---------|---------|---------------|------|------------|----------|
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+ | IBlend | India | 9 | 2013-17 | 1,604 | 296,357 | kW | 15min, 1H | Mains |
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+ | CLEMD | Malaysia | 1 | 2023-23 | 34 | 706 | kW | 15min, 1H | Mains |
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+ | CU-BEMS | Thailand | 1 | 2018-19 | 548 | 1,504,058 | kW | 15min, 1H | Circuits |
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+ | IPC-Commercial | China | 3 | 2016-21 | 2,191 | 132,519 | kW | 1H | Mains |
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+ | EWELD | Southern China | 386 | 2016-22 | 2,260 | 13,730,258 | kWh | 15min,1H | Mains |
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+ | SKC | South Korea | 10 | 2019 | 213 | 50,708 | kW | 15min, 1H | Mains |
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+ | IOT | Sharjah | 1 | 2024 | 171 | 2,163 | kWh | 1H | Circuits |
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+ | SEWA | UAE | 1 | 2020-21 | 730 | 17,489 | kW | 1H | Mains |
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+ | PSS | South Africa | 53 | 2022-23 | 364 | 454,774 | kWh | 30min, 1H | Mains |
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+ | Enernoc | USA | 100 | 2012-13 | 366 | 877,728 | kWh | 15min, 1H | Mains |
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+ | DGS | USA | 322 | 2016-18 | 1,064 | 5,333,851 | NA | 15min, 1H | Mains |
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+ | Berkely | USA | 1 | 2018-21 | 1,096 | 126,159 | kW | 15min, 1H | Circuits |
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+ | HB | Phoenix, USA | 1 | 2023 | 364 | 87,600 | kWh | 1H | Circuits |
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+ | BDG-2 | USA | 1,578 | 2016-17 | 730 | 25,212,579 | kWh | 1H | Mains |
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+ | ULE | Cambridge | 1 | 2023-24 | 365 | 8,783 | kWh | 1H | Mains |
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+ | ECRG-Commercial | Poland | 10 | 2,017 | 7 | 1,690 | kW | 15min, 1H | Mains |
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+ | RKP | Portugal | 3 | 2019 | 98 | 1,319 | kW | 15min, 1H | Mains |
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+ | UCIE | Portugal | 370 | 2011-15 | 1,461 | 12,974,050 | kWh | 15min, 1H | Mains |
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+ | NEST-Commercial | Switzerland | 1 | 2019-23 | 1,460 | 34,798 | kW | 15min, 1H | Mains |
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+ | UNICON | Australia | 64 | 2018-22 | 1,580 | 2,066,301 | kW | 15min, 1H | Mains |
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+ | **Total** | | 2,916 | | 16,706 | 62M | | | |
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+
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+ Table 4: Details of real residential buildings
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+ | **Dataset** | **Location** | **# Buildings** | **Year** | **# Days** | **# Hourly Obs** | **Unit** | **Resolution** | **Type** |
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+ |------------------------------------------------------------------------------|------------------|--------------|---------|---------|---------------|------|------------|----------|
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+ | Prayas | India | 116 | 2018-20 | 911 | 1,536,409 | kWh | 15min, 1H | Mains |
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+ | CEEW | India | 84 | 2019-21 | 914 | 923,897 | kWh | 15min, 1H | Mains |
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+ | RSL | Sri Lanka | 2,903 | 2023-24 | 449 | 11,372,970 | kW | 15min, 1H | Mains |
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+ | IPC-Residential | China | 1 | 2016-21 | 2,191 | 45,471 | kW | 1H | Mains |
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+ | SFAC | China | 1 | 2021-22 | 366 | 115,857 | kWh | 15min, 1H | Circuits |
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+ | ENERTALK | South Korea | 22 | 2016-17 | 242 | 39,923 | kW | 15min, 1H | Mains |
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+ | DCB | Japan | 1 | 2002-22 | 7,457 | 187,008 | kW | 1H | Mains |
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+ | SRSA | South Africa | 1 | 2016-18 | 662 | 13,966 | kWh | 1H | Mains |
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+ | MIHEC | South Africa | 1 | 2019-21 | 1,013 | 19,358 | kWh | 1H | Mains |
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+ | AMPD | Canada | 1 | 2012-14 | 730 | 17,520 | kW | 15min, 1H | Mains |
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+ | RHC | Canada | 1 | 2012-14 | 730 | 17,520 | kWh | 15min, 1H | Mains |
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+ | HUE | British Columbia | 28 | 2012-20 | 2,910 | 610,949 | kWh | 1H | Mains |
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+ | flEECe | USA | 6 | 2017-18 | 259 | 74,492 | kWh | 1H | Mains |
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+ | MFRED | USA | 26 | 2019-20 | 365 | 227,622 | kW | 15min, 1H | Mains |
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+ | SMART-Star | USA | 114 | 2014-16 | 867 | 958,998 | kW | 15min, 1H | Mains |
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+ | Honda SMART Home | USA | 1 | 2020 | 365 | 8,760 | kW | 15min, 1H | Mains |
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+ | PES | USA, Europe | 10 | 2011-14 | 971 | 13,508 | kWh | 15min, 1H | Mains |
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+ | ECWM | Mexico | 1 | 2022-24 | 426 | 10,184 | kW | 1H | Mains |
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+ | WED | Mexico | 5 | 2022-23 | 378 | 45,096 | kWh | 15min, 1H | Mains |
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+ | REEDD | Costa Rica | 46 | 2018-19 | 384 | 12,058 | kW | 15min, 1H | Circuits |
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+ | REFIT | UK | 20 | 2013-15 | 661 | 231,970 | kW | 15min, 1H | Circuits |
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+ | METER | UK | 311 | 2016-19 | 1,065 | 8,928 | kW | 30min, 1H | Mains |
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+ | SAVE | UK | 4,691 | 2016-18 | 904 | 59,918,911 | kWh | 15min, 1H | Mains |
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+ | HES | UK | 16 | 2010-11 | 455 | 115,824 | kWh | 1H | Mains |
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+ | NDB | UK | 1 | 2022 | 229 | 3,282 | kW | 15min, 1H | Circuits |
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+ | LCL | UK | 5,561 | 2011-14 | 828 | 83,925,571 | kWh | 30min, 1H | Mains |
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+ | UKST | Great Britain | 14,319 | 2008-10 | 996 | 207,579,283 | kWh | 30min, 1H | Mains |
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+ | IRH | Ireland | 20 | 2020-21 | 366 | 174,398 | kW | 15min, 1H | Mains |
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+ | DESM | France | 3 | 2020-21 | 365 | 24,018 | kW | 15min, 1H | Mains |
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+ | IHEPC | Sceaux | 1 | 2006-10 | 1,441 | 34,168 | kW | 15min, 1H | Mains |
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+ | NEEA | Portland | 410 | 2018-20 | 855 | 2,922,289 | kW | 15min, 1H | Mains |
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+ | GoiEner | Spain | 25,559 | 2014-22 | 2,775 | 632,313,933 | kWh | 1H | Mains |
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+ | Plegma | Greece | 13 | 2022-23 | 446 | 83,452 | kW | 15min, 1H | Mains |
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+ | DEDDIAG | Germany | 15 | 2016-20 | 1582 | 732,597 | kW | 15min, 1H | Circuits |
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+ | HSG | Germany | 11 | 2014-19 | 1602 | 220,775 | kWh | 15min, 1H | Mains |
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+ | SFHG | Germany | 38 | 2019-20 | 730 | 769,247 | kW | 1H | Mains |
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+ | GREEND | Italy, Austria | 7 | 2013-15 | 570 | 489,644 | kWh | 15min, 1H | Circuits |
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+ | iFlex | Norway | 4,429 | 2020-21 | 445 | 13,515,600 | kWh | 1H | Mains |
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+ | Norwegian | Norway | 1,136 | 2020-22 | 546 | 14,913,408 | kWh | 1H | Mains |
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+ | LEC | Portugal | 172 | 2022-23 | 485 | 1,507,699 | kWh | 15min, 1H | Mains |
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+ | ECCC | Portugal | 51 | 2019-20 | 365 | 447,984 | kW | 15min, 1H | Mains |
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+ | ECRG-Residential | Poland | 15 | 2017 | 7 | 2,535 | kW | 15min, 1H | Mains |
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+ | NESEMP | Scotland | 215 | 2010-12 | 720 | 1,575,682 | kW | 15min, 1H | Mains |
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+ | NEST-Residential | Switzerland | 2 | 2019-23 | 1,460 | 34715 | kW | 15min, 1H | Mains |
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+ | DTH | Slovak Republic | 1,000 | 2016-17 | 395 | 9,453,051 | kWh | 15min, 1H | Mains |
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+ | SGSC | Australia | 13,735 | 2011-14 | 880 | 172,277,213 | kWh | 30min, 1H | Mains |
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+ | BTS | Australia | 1 | 2021 | 89 | 443,208 | kW | 15min, 1H | Circuits |
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+ | **Total** | | 75,121 | | 43,852 | 1.2B | | | |
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+
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+ ## License
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+ EnergyBench dataset is available for download with permissive CC-4.0 license.
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+