Sukhil-Patel commited on
Commit
f8ed73e
1 Parent(s): ea8003c

Upload folder using huggingface_hub

Browse files
Files changed (4) hide show
  1. README.md +57 -3
  2. config.json +80 -0
  3. data_config.yaml +86 -0
  4. model.safetensors +3 -0
README.md CHANGED
@@ -1,3 +1,57 @@
1
- ---
2
- license: mit
3
- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ language: en
3
+ license: mit
4
+ library_name: pytorch
5
+ ---
6
+
7
+
8
+
9
+
10
+
11
+
12
+ # PVNet2
13
+
14
+ ## Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is/does. -->
17
+ 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).
18
+
19
+ - **Developed by:** openclimatefix
20
+ - **Model type:** Fusion model
21
+ - **Language(s) (NLP):** en
22
+ - **License:** mit
23
+
24
+
25
+ # Training Details
26
+
27
+ ## Data
28
+
29
+ <!-- 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. -->
30
+
31
+ 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.
32
+
33
+
34
+ ### Preprocessing
35
+
36
+ Data is prepared with the `ocf_datapipes.training.pvnet` datapipe [2].
37
+
38
+
39
+ ## Results
40
+
41
+ The training logs for the current model can be found here:
42
+ - [https://wandb.ai/openclimatefix/pvnet2.1/runs/[]](https://wandb.ai/openclimatefix/pvnet2.1/runs/[])
43
+
44
+
45
+ The training logs for all model runs of PVNet2 can be found [here](https://wandb.ai/openclimatefix/pvnet2.1).
46
+
47
+ Some experimental notes can be found at in [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing)
48
+
49
+
50
+ ### Hardware
51
+
52
+ Trained on a single NVIDIA Tesla T4
53
+
54
+ ### Software
55
+
56
+ - [1] https://github.com/openclimatefix/PVNet
57
+ - [2] https://github.com/openclimatefix/ocf_datapipes
config.json ADDED
@@ -0,0 +1,80 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "_target_": "pvnet.models.multimodal.multimodal.Model",
3
+ "output_quantiles": [
4
+ 0.02,
5
+ 0.1,
6
+ 0.25,
7
+ 0.5,
8
+ 0.75,
9
+ 0.9,
10
+ 0.98
11
+ ],
12
+ "nwp_encoders_dict": {
13
+ "ukv": {
14
+ "_target_": "pvnet.models.multimodal.encoders.encoders3d.DefaultPVNet",
15
+ "_partial_": true,
16
+ "in_channels": 12,
17
+ "out_features": 256,
18
+ "number_of_conv3d_layers": 6,
19
+ "conv3d_channels": 32,
20
+ "image_size_pixels": 24
21
+ },
22
+ "ecmwf": {
23
+ "_target_": "pvnet.models.multimodal.encoders.encoders3d.DefaultPVNet",
24
+ "_partial_": true,
25
+ "in_channels": 12,
26
+ "out_features": 256,
27
+ "number_of_conv3d_layers": 4,
28
+ "conv3d_channels": 32,
29
+ "image_size_pixels": 12
30
+ }
31
+ },
32
+ "sat_encoder": {
33
+ "_target_": "pvnet.models.multimodal.encoders.encoders3d.ResConv3DNet2",
34
+ "_partial_": true,
35
+ "in_channels": 11,
36
+ "out_features": 256,
37
+ "image_size_pixels": 24,
38
+ "hidden_channels": 32,
39
+ "n_res_blocks": 3,
40
+ "res_block_layers": 3,
41
+ "batch_norm": true,
42
+ "dropout_frac": 0.0
43
+ },
44
+ "pv_encoder": null,
45
+ "output_network": {
46
+ "_target_": "pvnet.models.multimodal.linear_networks.networks.ResFCNet2",
47
+ "_partial_": true,
48
+ "fc_hidden_features": 128,
49
+ "n_res_blocks": 6,
50
+ "res_block_layers": 2,
51
+ "dropout_frac": 0.0
52
+ },
53
+ "embedding_dim": 16,
54
+ "include_sun": true,
55
+ "include_gsp_yield_history": false,
56
+ "forecast_minutes": 2160,
57
+ "history_minutes": 120,
58
+ "min_sat_delay_minutes": 60,
59
+ "sat_history_minutes": 90,
60
+ "pv_history_minutes": 120,
61
+ "pv_interval_minutes": 30,
62
+ "nwp_history_minutes": {
63
+ "ukv": 120,
64
+ "ecmwf": 120
65
+ },
66
+ "nwp_forecast_minutes": {
67
+ "ukv": 1800,
68
+ "ecmwf": 2220
69
+ },
70
+ "optimizer": {
71
+ "_target_": "pvnet.optimizers.EmbAdamWReduceLROnPlateau",
72
+ "lr": 0.0001,
73
+ "weight_decay": 0.25,
74
+ "amsgrad": true,
75
+ "patience": 5,
76
+ "factor": 0.1,
77
+ "threshold": 0.002
78
+ },
79
+ "adapt_batches": true
80
+ }
data_config.yaml ADDED
@@ -0,0 +1,86 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ general:
2
+ description: Config for training the saved PVNet model
3
+ name: PVNet current
4
+ input_data:
5
+ default_forecast_minutes: 2160
6
+ default_history_minutes: 120
7
+ gsp:
8
+ dropout_fraction: 0
9
+ dropout_timedeltas_minutes: null
10
+ forecast_minutes: 2160
11
+ gsp_zarr_path: PLACEHOLDER.zarr
12
+ history_minutes: 120
13
+ time_resolution_minutes: 30
14
+ nwp:
15
+ ecmwf:
16
+ dropout_fraction: 1.0
17
+ dropout_timedeltas_minutes:
18
+ - -180
19
+ forecast_minutes: 2220
20
+ history_minutes: 120
21
+ max_staleness_minutes: null
22
+ nwp_channels:
23
+ - t2m
24
+ - dswrf
25
+ - dlwrf
26
+ - hcc
27
+ - mcc
28
+ - lcc
29
+ - tcc
30
+ - sde
31
+ - sr
32
+ - duvrs
33
+ - u10
34
+ - v10
35
+ nwp_image_size_pixels_height: 12
36
+ nwp_image_size_pixels_width: 12
37
+ nwp_provider: ecmwf
38
+ nwp_zarr_path: PLACEHOLDER.zarr
39
+ time_resolution_minutes: 60
40
+ ukv:
41
+ dropout_fraction: 1.0
42
+ dropout_timedeltas_minutes:
43
+ - -180
44
+ forecast_minutes: 1800
45
+ history_minutes: 120
46
+ max_staleness_minutes: null
47
+ nwp_channels:
48
+ - t
49
+ - dswrf
50
+ - dlwrf
51
+ - hcc
52
+ - mcc
53
+ - lcc
54
+ - sde
55
+ - r
56
+ - vis
57
+ - si10
58
+ - wdir10
59
+ - prate
60
+ nwp_image_size_pixels_height: 24
61
+ nwp_image_size_pixels_width: 24
62
+ nwp_provider: ukv
63
+ nwp_zarr_path: PLACEHOLDER.zarr
64
+ time_resolution_minutes: 60
65
+ satellite:
66
+ dropout_fraction: 0
67
+ dropout_timedeltas_minutes: null
68
+ forecast_minutes: 0
69
+ history_minutes: 90
70
+ live_delay_minutes: 60
71
+ satellite_channels:
72
+ - IR_016
73
+ - IR_039
74
+ - IR_087
75
+ - IR_097
76
+ - IR_108
77
+ - IR_120
78
+ - IR_134
79
+ - VIS006
80
+ - VIS008
81
+ - WV_062
82
+ - WV_073
83
+ satellite_image_size_pixels_height: 24
84
+ satellite_image_size_pixels_width: 24
85
+ satellite_zarr_path: PLACEHOLDER.zarr
86
+ time_resolution_minutes: 5
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f5d050106f48db360d51a5e0545d6530a25b20bf4fea4625d553947f2f0b5987
3
+ size 94218712