| --- |
| tags: |
| - tabular |
| - energy |
| - forecasting |
| - weather |
| - tsfile |
| - format:tsfile |
| - timeseries |
| pretty_name: REG-Forecasting_v2 |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
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| # REG-Forecasting_v2 (TsFile) |
| |
| Apache TsFile version of |
| [`wachawich/REG-Forecasting_v2`](https://huggingface.co/datasets/wachawich/REG-Forecasting_v2). |
| |
| ## Overview |
| |
| Renewable Energy Generation (REG) forecasting data at **hourly** granularity, spanning |
| **2020-01-01 to 2025-11-19**. For each hour it records the generation (`value`) of two |
| generation types together with the shared meteorological and solar-geometry features. |
| Compared with the v1 dataset, this version adds extra columns such as `solar_count`, |
| `wind_turbine_count`, and cyclic time encodings (`sin_time`, `cos_time`, |
| `day_of_month_sin/cos`, `month_of_year_sin/cos`). |
|
|
| - **Two generation types:** `type_name` = `Solar` / `Wind`. |
| - **Forecast target:** `value` — generation in that hour. |
| - **Features:** radiation, cloud cover, temperature, humidity, pressure, wind |
| speed/direction, precipitation, sunrise/sunset times, and cyclic calendar encodings. |
|
|
| ## Schema (TsFile structure) |
|
|
| - **Time** (INT64, milliseconds) — the hourly timestamp. |
| - **type_name** (TAG) — the device dimension, `Solar` / `Wind`. Query one type with |
| `WHERE type_name='Solar'`. |
| - All remaining columns are FIELDs: `value` plus the meteorological and calendar features. |
| |
| Type mapping: floating-point → DOUBLE, integers → INT64, strings → STRING. A small number |
| of byte-for-byte duplicate rows (from daylight-saving transitions) were removed so that a |
| single device never carries two points at the same timestamp. |
| |
| ## Usage |
| |
| Read `data.tsfile` with the Apache TsFile Java or Python SDK. |
| |
| ## Source & license |
| |
| - Original dataset: https://huggingface.co/datasets/wachawich/REG-Forecasting_v2 |
| - Author: wachawich |
| - License: not declared by the original dataset card; please defer to the original dataset. |
| |
