Datasets:
Tasks:
Time Series Forecasting
Sub-tasks:
multivariate-time-series-forecasting
Languages:
English
Size:
1B<n<10B
DOI:
License:
| annotations_creators: | |
| - machine-generated | |
| language: | |
| - en | |
| language_creators: | |
| - machine-generated | |
| license: | |
| - mit | |
| multilinguality: | |
| - monolingual | |
| pretty_name: United Kingdom PV Solar generation | |
| size_categories: | |
| - 1B<n<10B | |
| source_datasets: | |
| - original | |
| tags: | |
| - pv | |
| - photovoltaic | |
| - environment | |
| - climate | |
| - energy | |
| - electricity | |
| task_categories: | |
| - time-series-forecasting | |
| task_ids: | |
| - multivariate-time-series-forecasting | |
| # UK PV dataset | |
| PV solar generation data from the UK. | |
| This dataset contains data from 24,662 solar PV systems from 2018 to 2021. | |
| Time granularity varies from 2 minutes to 30 minutes. | |
| This data is collected from live PV systems in the UK. We have reduced the precision of the location of the PV systems for privacy. | |
| If you are the owner of a PV system in the dataset, and do not want this data to be shared, | |
| please do get in contact with info@openclimatefix.org. | |
| This dataset is made possible by [Sheffield Solar](https://www.solar.sheffield.ac.uk/) | |
| ## Files | |
| - metadata.csv: Data about the PV systems, e.g location | |
| - 2min.parquet: Power output for PV systems every 2 minutes. | |
| - 5min.parquet: Power output for PV systems every 5 minutes. | |
| - 30min.parquet: Power output for PV systems every 30 minutes. | |
| - pv.netcdf: (legacy) Time series of PV solar generation every 5 minutes | |
| ### metadata.csv | |
| Metadata of the different PV systems. | |
| Note that there are extra PV systems in this metadata that do not appear in the PV time-series data. | |
| The csv columns are: | |
| - ss_id: The Sheffield Solar id of the system | |
| - latitude_rounded: Latitude of the PV system, but rounded to approximately the nearest km | |
| - longitude_rounded: Longitude of the PV system, but rounded to approximately the nearest km | |
| - llsoacd: The Lower Layer Super Output Area (LLSOA). This is a way to divide up the United Kingdom into small regions. The LLSOA boundaries are published on the data.gov.uk website. | |
| - orientation: The orientation of the PV system, in degrees. | |
| - tilt: The tilt of the PV system with respect to the ground, in degrees. 0 degrees would be horizontal (parallel to the ground). 90 degrees would be standing perpendicular to the ground. | |
| - kwp: The power generation capacity of the PV system (kilowatts peak). | |
| - operational_at: the date the PV system started working (YYYY-MM-DD). | |
| ### {2,5,30}min.parquet | |
| Time series of solar generation for a number of sytems. | |
| Each file includes the systems for which there is enough granularity. | |
| In particular the systems in 2min.parquet and 5min.parquet are also in 30min.parquet. | |
| The files contain 3 columns: | |
| - ss_id: the id of the system | |
| - timestamp: the timestamp of the recording. | |
| - generation_wh: the energy generated in the period (in watt hours) at the given timestamp for the given system | |
| ### pv.netcdf (legacy) | |
| Time series data of PV solar generation data is in an [xarray](https://docs.xarray.dev/en/stable/) format. | |
| The data variables are the same as 'ss_id' in the metadata. | |
| Each data variable contains the solar generation (in kW) for that PV system. | |
| The ss_id's here are a subset of all the ss_id's in the metadata | |
| The coordinates of the date are tagged as 'datetime' which is the datetime of the solar generation reading. | |
| This is a subset of the more recent `5min.parquet` file. | |
| ## example | |
| using Hugging Face Datasets | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("openclimatefix/uk_pv") | |
| ``` | |
| ## useful links | |
| https://huggingface.co/docs/datasets/share - this repo was made by following this tutorial |