Update README.md

README.md

@@ -541,6 +541,14 @@ config:
   data_files:
   - split: train
     path: Dataset_V0.0/Synthetic-Energy-Load-Profiles/15min/SynD/*.parquet
+- config_name: Synthetic-Buildings-900K-Commercial-15min
+  data_files:
+  - split: train
+    path: Dataset_V0.0/Synthetic-Energy-Load-Profiles/15min/Buildings-900K/comstock_amy2018_release_2/*/*.parquet
+- config_name: Synthetic-Buildings-900K-Residential-15min
+  data_files:
+  - split: train
+    path: Dataset_V0.0/Synthetic-Energy-Load-Profiles/15min/Buildings-900K/resstock_amy2018_release_2/*/*.parquet
 - config_name: Synthetic-SDG-Hourly
   data_files:
   - split: train
@@ -549,6 +557,18 @@ config:
   data_files:
   - split: train
     path: Dataset_V0.0/Synthetic-Energy-Load-Profiles/Hourly/SynD/*.parquet
+- config_name: Synthetic-Buildings-900K-Commercial-Hourly
+  data_files:
+  - split: train
+    path: Dataset_V0.0/Synthetic-Energy-Load-Profiles/Hourly/Buildings-900K/comstock_amy2018_release_2/*/*.parquet
+- config_name: Synthetic-Buildings-900K-Residential-Hourly
+  data_files:
+  - split: train
+    path: Dataset_V0.0/Synthetic-Energy-Load-Profiles/Hourly/Buildings-900K/resstock_amy2018_release_2/*/*.parquet
+- config_name: Synthetic-HRSA-Residential-Hourly
+  data_files:
+  - split: train
+    path: Dataset_V0.0/Synthetic-Energy-Load-Profiles/Hourly/HRSA/*/*.parquet
 ---
 
 
@@ -557,15 +577,26 @@ config:
 A open-source large-scale energy meter dataset designed to support a variety of energy analytics applications, including load profile analysis, and load forecasting.
 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. 
 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. 
-These buildings span diverse geographies, climatic zones, and operational profiles, providing a broad spectrum of usage patterns.
+These buildings span diverse geographies, climatic zones, and operational profiles, providing a broad spectrum of usage patterns. Additional to the real buildings, it also 
+includes synthetic and simulated buildings electricity consumption data. 
 
 All processed datasets contain hourly data, with some offering additional 15-minute and 30-minute resolution. To ensure efficient storage, we saved the datasets in Parquet format rather than CSV. 
 For datasets involving a large number of buildings, we partitioned the data into multiple Parquet files.
 
 Metadata of each datasets are provided in [metadata](https://huggingface.co/datasets/ai-iot/EnergyBench/tree/main/Dataset_V0.0/metadata).
 
-Table 1: Summary of EnergBench dataset
+Table 1: Summary of EnergBench dataset (Real Buildings)
 | Category    | # Datasets | # Buildings | # Days | # Hourly Obs |
 |-------------|-------------|--------------|---------|--------|
 | Commercial  | 20          | 2,916        | 16,706  | 62M    |
 | Residential | 47          | 75,121       | 43,852  | 1.2B   |
+
+
+
+
+Table 2: Summary of EnergBench dataset (Synthetic and Simulated Buildings)
+| Category    | # Datasets | # Buildings | # Days | # Hourly Obs |
+|-------------|-------------|--------------|---------|--------|
+| Commercial  | 1           | 207,559      | 365     | ~1.7B  |
+| Residential | 4           | 31M          | 966     | ~718.7B |
+