PVNet2

Model Description

This model class uses satellite data, numerical weather predictions, and recent Grid Service Point( GSP) PV power output to forecast the near-term (~8 hours) PV power output at all GSPs. More information can be found in the model repo [1] and experimental notes in this google doc.

  • Developed by: openclimatefix
  • Model type: Fusion model
  • Language(s) (NLP): en
  • License: mit

Training Details

Data

The model is trained on data from 2019-2022 and validated on data from 2022-2023. See experimental notes in the the google doc for more details.

Preprocessing

Data is prepared with the ocf_datapipes.training.pvnet datapipe [2].

Results

The training logs for the current model can be found here:

The training logs for all model runs of PVNet2 can be found here.

Some experimental notes can be found at in the google doc

Hardware

Trained on a single NVIDIA Tesla T4

Software

Downloads last month
29,935
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API: The model has no pipeline_tag.