





# PVNet2

## Model Description

<!-- Provide a longer summary of what this model is/does. -->
This model class uses satellite data, numericl 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](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing).

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


# Training Details

## Data

<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->

The model is trained on data from 2017-2020 and validated on data from 2021. See experimental notes in the [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing) 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 on wandb](https://wandb.ai/openclimatefix/pvnet2.1/runs/kn81g3qz).

The training logs for all model runs of PVNet2 can be found [here](https://wandb.ai/openclimatefix/pvnet2.1).

Some experimental notes can be found at in [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing)


### Hardware

Trained on a single NVIDIA Tesla T4

### Software

- [1] https://github.com/openclimatefix/PVNet
- [2] https://github.com/openclimatefix/ocf_datapipes
{"language": "en", "license": "mit", "library_name": "pytorch"}
pytorch en license:mit region:us
TAGS
#pytorch #en #license-mit #region-us 







# PVNet2

## Model Description


This model class uses satellite data, numericl 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 2017-2020 and validated on data from 2021. See experimental notes in the the google doc for more details.


### Preprocessing

Data is prepared with the 'ocf_datapipes.URL' datapipe [2].


## Results

The training logs for the current model can be found here on wandb.

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

- [1] URL
- [2] URL
# PVNet2 ## Model Description


This model class uses satellite data, numericl 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 2017-2020 and validated on data from 2021. See experimental notes in the the google doc for more details. ### Preprocessing

Data is prepared with the 'ocf_datapipes.URL' datapipe [2]. ## Results

The training logs for the current model can be found here on wandb.

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

- [1] URL
- [2] URL
TAGS
#pytorch #en #license-mit #region-us 
 # PVNet2 ## Model Description


This model class uses satellite data, numericl 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 2017-2020 and validated on data from 2021. See experimental notes in the the google doc for more details. ### Preprocessing

Data is prepared with the 'ocf_datapipes.URL' datapipe [2]. ## Results

The training logs for the current model can be found here on wandb.

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

- [1] URL
- [2] URL