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README.md

@@ -9,12 +9,12 @@ license: mit
 
 
 
-# PVNet_summation
+# PVNet2
 
 ## Model Description
 
 <!-- Provide a longer summary of what this model is/does. -->
-This model class sums the output of the PVNet model's GSP level predictions to make a national forecast of UK PV output. More information can be found in the model repo [1], the PVNet model repo [2], and experimental notes in [this google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing).
+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](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing).
 
 - **Developed by:** openclimatefix
 - **Model type:** Fusion model
@@ -28,21 +28,21 @@ This model class sums the output of the PVNet model's GSP level predictions to m
 
 <!-- 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 the output predictions of our PVNet model which gives GSP (i.e. UK regional) level predictions
-of solar power across Great Britain. This model is trained to take those predictions and use them to estimate
-the national total with uncertainty estimates.
+The model is trained on data from 2019-2022 and validated on data from 2022-2023. See experimental notes in the [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing) for more details.
 
 
 ### Preprocessing
 
-The input data is prepared with the `ocf_data_sampler` [3].
+Data is prepared with the `ocf_data_sampler/torch_datasets/datasets/pvnet_uk` Dataset [2].
 
 
 ## Results
 
-The training logs for the current model can be found [here on wandb](https://wandb.ai/openclimatefix/pvnet_summation/runs/).
+The training logs for the current model can be found here:
+ - [https://wandb.ai/None/runs/kknmvrpq](https://wandb.ai/None/runs/kknmvrpq)
 
-The training logs for all model runs of PVNet_summation can be found [here](https://wandb.ai/openclimatefix/pvnet_summation).
+
+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)
 
@@ -53,6 +53,5 @@ Trained on a single NVIDIA Tesla T4
 
 ### Software
 
-- [1] https://github.com/openclimatefix/PVNet_summation
-- [2] https://github.com/openclimatefix/PVNet
-- [3] https://github.com/openclimatefix/ocf-data-sampler
+- [1] https://github.com/openclimatefix/PVNet
+- [2] https://github.com/openclimatefix/ocf-data-sampler

config.json

@@ -1,16 +1,8 @@
 {
     "_target_": "pvnet_summation.models.flat_model.FlatModel",
-    "output_quantiles": [
-        0.02,
-        0.1,
-        0.25,
-        0.5,
-        0.75,
-        0.9,
-        0.98
-    ],
+    "output_quantiles": null,
     "model_name": "openclimatefix/pvnet_uk_region",
-    "model_version": "4009df82e63e30546e2000728bff34b9c0520617",
+    "model_version": "f3135c47eb0f21320dbd8c590bdd03dfafc39bca",
     "output_network": {
         "_target_": "pvnet.models.multimodal.linear_networks.networks.ResFCNet2",
         "_partial_": true,
@@ -19,8 +11,7 @@
         "res_block_layers": 2,
         "dropout_frac": 0.0
     },
-    "relative_scale_pvnet_outputs": false,
-    "predict_difference_from_sum": true,    
+    "predict_difference_from_sum": true,
     "optimizer": {
         "_target_": "pvnet.optimizers.AdamWReduceLROnPlateau",
         "lr": 0.0001,

pytorch_model.bin

@@ -1,3 +1,3 @@
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-size 46237238
+oid sha256:c27012b38e81a8711e5362f2f2f1813907e171251957353753c388f8a8e4affb
+size 81298030