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  1. README.md +24 -31
  2. data_config.yaml +60 -121
  3. model_config.yaml +25 -27
  4. model_weights.safetensors +2 -2
README.md CHANGED
@@ -3,54 +3,54 @@ language: en
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  library_name: pytorch
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  license: mit
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  ---
 
 
 
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-
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-
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-
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-
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- # PVNet2
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-
14
  ## Model Description
15
 
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- <!-- Provide a longer summary of what this model is/does. -->
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- 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).
 
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  - **Developed by:** openclimatefix
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  - **Model type:** Fusion model
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  - **Language(s) (NLP):** en
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  - **License:** mit
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-
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  # Training Details
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27
  ## Data
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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. -->
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-
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- 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.
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  ### Preprocessing
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  Data is prepared with the `ocf_data_sampler/torch_datasets/datasets/pvnet_uk` Dataset [2].
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-
38
 
39
  ## Results
40
 
41
- The training logs for the current model can be found here:
42
- - [https://wandb.ai/openclimatefix/NL-Solar/runs/r4naockv](https://wandb.ai/openclimatefix/NL-Solar/runs/r4naockv)
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-
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-
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- The training logs for all model runs of PVNet2 can be found [here](https://wandb.ai/openclimatefix/pvnet2.1).
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-
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- Some experimental notes can be found at in [the google doc](https://docs.google.com/document/d/1fbkfkBzp16WbnCg7RDuRDvgzInA6XQu3xh4NCjV-WDA/edit?usp=sharing)
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  ### Hardware
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-
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  Trained on a single NVIDIA Tesla T4
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54
  ### Software
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56
  This model was trained using the following Open Climate Fix packages:
@@ -58,14 +58,7 @@ This model was trained using the following Open Climate Fix packages:
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  - [1] https://github.com/openclimatefix/PVNet
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  - [2] https://github.com/openclimatefix/ocf-data-sampler
60
 
 
61
  The versions of these packages can be found below:
62
- - pvnet==4.1.18
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- - ocf-data-sampler==0.2.31
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-
65
-
66
- ---
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- **Migration Note**: This model (HF commit 9ebb76d6497d3f0e53607e99b8ffe33679259464) was migrated on 2025-09-10 to pvnet version 5.0.6.post0+git.e31d0340.dirty
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-
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-
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- ---
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- **Migration Note**: This model was migrated on 2025-12-07 to pvnet version 5.3.0.post0+git.489723d6.dirty
 
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  library_name: pytorch
4
  license: mit
5
  ---
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+ <!--
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+ Do not remove elements like the above surrounded by two curly braces and do not add any more of them. These entries are required by the PVNet library and are automaticall infilled when the model is uploaded to huggingface
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+ -->
9
 
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+ <!-- Title - e.g. PVNet2, WindNet, PVNet India -->
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+ # TEMPLATE
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+ <!-- Provide a longer summary of what this model is/does. -->
 
 
 
 
 
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  ## Model Description
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16
+ <!-- e.g.
17
+ This model class uses satellite data, and numerical weather predictions to forecast the near-term (up to 8 hours ahead) PV power output at all Grid Service Points (GSPs) in Great Britain. More information can be found in the model repo [1]. The model repo also includes links to our workshop paper on this model and some experimental notes.
18
+ -->
19
 
20
  - **Developed by:** openclimatefix
21
  - **Model type:** Fusion model
22
  - **Language(s) (NLP):** en
23
  - **License:** mit
24
 
 
25
  # Training Details
26
 
27
  ## Data
28
 
29
+ <!-- eg.
30
+ The model is trained on data from 2019-2022 and validated on data from 2022-2023. It uses NWP data from ECMWF IFS model, and the UK Met Office UKV model. It uses satellite data from the EUMETSAT MSG SEVIRI instrument.
 
31
 
32
+ See the data_config.yaml file for more information on the channels and window-size used for each input data source.
33
+ -->
34
 
35
+ <!-- The preprocessing section is not strictly nessessary but perhaps nice to have -->
36
  ### Preprocessing
37
 
38
+ <!-- eg.
39
  Data is prepared with the `ocf_data_sampler/torch_datasets/datasets/pvnet_uk` Dataset [2].
40
+ -->
41
 
42
  ## Results
43
 
44
+ <!-- Do not remove the lines below -->
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+ The training logs for this model commit can be found here:
46
+ - [https://wandb.ai/openclimatefix/NL-Solar/runs/rvdfwb7o](https://wandb.ai/openclimatefix/NL-Solar/runs/rvdfwb7o)
 
 
 
 
47
 
48
 
49
+ <!-- The hardware section is also just nice to have -->
50
  ### Hardware
 
51
  Trained on a single NVIDIA Tesla T4
52
 
53
+ <!-- Do not remove the section below -->
54
  ### Software
55
 
56
  This model was trained using the following Open Climate Fix packages:
 
58
  - [1] https://github.com/openclimatefix/PVNet
59
  - [2] https://github.com/openclimatefix/ocf-data-sampler
60
 
61
+ <!-- Especially do not change the two lines below -->
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  The versions of these packages can be found below:
63
+ - pvnet==5.3.0.post6+git.f4136853.dirty
64
+ - ocf-data-sampler==1.0.1.post1+git.b7c40f80.dirty
 
 
 
 
 
 
 
 
data_config.yaml CHANGED
@@ -1,9 +1,24 @@
1
  general:
2
- description: Config for training the saved PVNet model
3
- name: PVNet current
4
  input_data:
 
 
 
 
 
 
 
 
 
 
5
  nwp:
6
  ecmwf:
 
 
 
 
 
7
  accum_channels:
8
  - direct_shortwave_radiation_flux_gl
9
  - downward_longwave_radiation_flux_gl
@@ -21,158 +36,82 @@ input_data:
21
  - snow_depth_gl
22
  - temperature_sl
23
  - total_precipitation_rate_gl
24
- - visibility_sl
25
  - wind_u_component_10m
26
  - wind_v_component_10m
27
- dropout_fraction: 1.0
 
28
  dropout_timedeltas_minutes:
29
- - -180
30
- image_size_pixels_height: 36
31
- image_size_pixels_width: 36
32
- interval_end_minutes: 2880
33
- interval_start_minutes: -120
34
  max_staleness_minutes: null
35
  normalisation_constants:
 
 
 
 
 
 
 
 
 
36
  cloud_cover_high:
37
  mean: 0.3961029052734375
38
  std: 0.42244860529899597
39
- cloud_cover_low:
40
- mean: 0.44901806116104126
41
- std: 0.3791404366493225
42
  cloud_cover_medium:
43
  mean: 0.3288780450820923
44
  std: 0.38039860129356384
 
 
 
45
  cloud_cover_total:
46
  mean: 0.7049227356910706
47
  std: 0.37487083673477173
48
- diff_direct_shortwave_radiation_flux_gl:
49
- mean: 469169.5
50
- std: 818950.6875
51
- diff_downward_longwave_radiation_flux_gl:
52
- mean: 1136464.0
53
- std: 131942.03125
54
- diff_downward_shortwave_radiation_flux_gl:
55
- mean: 420584.6875
56
- std: 715366.3125
57
- diff_downward_ultraviolet_radiation_flux_gl:
58
- mean: 48265.4765625
59
- std: 81605.25
60
  direct_shortwave_radiation_flux_gl:
61
- mean: 11458988.0
62
- std: 13025427.0
63
- downward_longwave_radiation_flux_gl:
64
- mean: 27187026.0
65
- std: 15855867.0
66
- downward_shortwave_radiation_flux_gl:
67
- mean: 11458988.0
68
- std: 13025427.0
69
  downward_ultraviolet_radiation_flux_gl:
70
  mean: 1305651.25
71
  std: 1445635.25
72
- snow_depth_gl:
73
- mean: 8.107526082312688e-05
74
- std: 0.000913831521756947
75
- temperature_sl:
76
- mean: 283.48333740234375
77
- std: 3.692270040512085
78
  total_precipitation_rate_gl:
79
  mean: 3.108070450252853e-05
80
  std: 9.81039775069803e-05
81
- visibility_sl:
82
- mean: 12905302.0
83
- std: 16294988.0
84
- wind_u_component_100m:
85
- mean: 2.393547296524048
86
- std: 7.2320556640625
87
  wind_u_component_10m:
88
  mean: 1.7677178382873535
89
  std: 5.531515598297119
 
 
 
90
  wind_u_component_200m:
91
  mean: 2.7963004112243652
92
  std: 8.049470901489258
93
- wind_v_component_100m:
94
- mean: 1.4244288206100464
95
- std: 6.944501876831055
96
  wind_v_component_10m:
97
  mean: 0.985887885093689
98
  std: 5.411230564117432
 
 
 
99
  wind_v_component_200m:
100
  mean: 1.6010299921035767
101
  std: 7.561611652374268
102
- provider: ecmwf
103
- time_resolution_minutes: 60
104
- zarr_path: PLACEHOLDER.zarr
105
- satellite:
106
- channels:
107
- - IR_016
108
- - IR_039
109
- - IR_087
110
- - IR_097
111
- - IR_108
112
- - IR_120
113
- - IR_134
114
- - VIS006
115
- - VIS008
116
- - WV_062
117
- - WV_073
118
- dropout_fraction: 0.8
119
- dropout_timedeltas_minutes:
120
- - -5
121
- - -10
122
- - -15
123
- - -20
124
- - -25
125
- - -30
126
- image_size_pixels_height: 100
127
- image_size_pixels_width: 100
128
- interval_end_minutes: -60
129
- interval_start_minutes: -90
130
- normalisation_constants:
131
- HRV:
132
- mean: 0.09298719
133
- std: 0.11405209
134
- IR_016:
135
- mean: 0.17594202
136
- std: 0.21462157
137
- IR_039:
138
- mean: 0.86167645
139
- std: 0.04618041
140
- IR_087:
141
- mean: 0.7719318
142
- std: 0.06687243
143
- IR_097:
144
- mean: 0.8014212
145
- std: 0.0468558
146
- IR_108:
147
- mean: 0.71254843
148
- std: 0.17482725
149
- IR_120:
150
- mean: 0.89058584
151
- std: 0.06115861
152
- IR_134:
153
- mean: 0.944365
154
- std: 0.04492306
155
- VIS006:
156
- mean: 0.09633306
157
- std: 0.12184761
158
- VIS008:
159
- mean: 0.11426069
160
- std: 0.13090034
161
- WV_062:
162
- mean: 0.7359355
163
- std: 0.16111417
164
- WV_073:
165
- mean: 0.62479186
166
- std: 0.12924142
167
- time_resolution_minutes: 5
168
- zarr_path: PLACEHOLDER.zarr
169
  solar_position:
170
- interval_end_minutes: 2880
171
- interval_start_minutes: -2880
172
- time_resolution_minutes: 15
173
- generation:
174
- capacity_mode: variable
175
- interval_end_minutes: 2880
176
  interval_start_minutes: -2880
 
177
  time_resolution_minutes: 15
178
- zarr_path: /home/zak/projects/PVNet/nl_solar/pv_data/netherlands_pv_data_v2.nc
 
1
  general:
2
+ description: Initial config for NL model
3
+ name: Netherlands_pvnet_config
4
  input_data:
5
+ site:
6
+ file_path: /home/alex/NL/NL_regional_generation_kw.nc
7
+ metadata_file_path: /home/alex/NL/NL_regional_metadata.csv
8
+ time_resolution_minutes: 15
9
+ interval_start_minutes: -2880
10
+ interval_end_minutes: 2160
11
+ dropout_timedeltas_minutes:
12
+ - -15
13
+ dropout_fraction: 1.0
14
+ dropout_value: -1
15
  nwp:
16
  ecmwf:
17
+ provider: ecmwf
18
+ zarr_path: PLACEHOLDER.zarr
19
+ interval_start_minutes: -120
20
+ interval_end_minutes: 2220
21
+ time_resolution_minutes: 60
22
  accum_channels:
23
  - direct_shortwave_radiation_flux_gl
24
  - downward_longwave_radiation_flux_gl
 
36
  - snow_depth_gl
37
  - temperature_sl
38
  - total_precipitation_rate_gl
 
39
  - wind_u_component_10m
40
  - wind_v_component_10m
41
+ image_size_pixels_height: 10
42
+ image_size_pixels_width: 10
43
  dropout_timedeltas_minutes:
44
+ - -360
45
+ dropout_fraction: 1.0
 
 
 
46
  max_staleness_minutes: null
47
  normalisation_constants:
48
+ temperature_sl:
49
+ mean: 283.48333740234375
50
+ std: 3.692270040512085
51
+ downward_shortwave_radiation_flux_gl:
52
+ mean: 11458988.0
53
+ std: 13025427.0
54
+ downward_longwave_radiation_flux_gl:
55
+ mean: 27187026.0
56
+ std: 15855867.0
57
  cloud_cover_high:
58
  mean: 0.3961029052734375
59
  std: 0.42244860529899597
 
 
 
60
  cloud_cover_medium:
61
  mean: 0.3288780450820923
62
  std: 0.38039860129356384
63
+ cloud_cover_low:
64
+ mean: 0.44901806116104126
65
+ std: 0.3791404366493225
66
  cloud_cover_total:
67
  mean: 0.7049227356910706
68
  std: 0.37487083673477173
69
+ visibility_sl:
70
+ mean: 12905302.0
71
+ std: 16294988.0
72
+ snow_depth_gl:
73
+ mean: 8.107526082312688e-05
74
+ std: 0.000913831521756947
 
 
 
 
 
 
75
  direct_shortwave_radiation_flux_gl:
76
+ mean: 12905302.0
77
+ std: 16294988.0
 
 
 
 
 
 
78
  downward_ultraviolet_radiation_flux_gl:
79
  mean: 1305651.25
80
  std: 1445635.25
 
 
 
 
 
 
81
  total_precipitation_rate_gl:
82
  mean: 3.108070450252853e-05
83
  std: 9.81039775069803e-05
 
 
 
 
 
 
84
  wind_u_component_10m:
85
  mean: 1.7677178382873535
86
  std: 5.531515598297119
87
+ wind_u_component_100m:
88
+ mean: 2.393547296524048
89
+ std: 7.2320556640625
90
  wind_u_component_200m:
91
  mean: 2.7963004112243652
92
  std: 8.049470901489258
 
 
 
93
  wind_v_component_10m:
94
  mean: 0.985887885093689
95
  std: 5.411230564117432
96
+ wind_v_component_100m:
97
+ mean: 1.4244288206100464
98
+ std: 6.944501876831055
99
  wind_v_component_200m:
100
  mean: 1.6010299921035767
101
  std: 7.561611652374268
102
+ diff_downward_longwave_radiation_flux_gl:
103
+ mean: 1136464.0
104
+ std: 131942.03125
105
+ diff_downward_shortwave_radiation_flux_gl:
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+ mean: 420584.6875
107
+ std: 715366.3125
108
+ diff_downward_ultraviolet_radiation_flux_gl:
109
+ mean: 48265.4765625
110
+ std: 81605.25
111
+ diff_direct_shortwave_radiation_flux_gl:
112
+ mean: 469169.5
113
+ std: 818950.6875
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
114
  solar_position:
 
 
 
 
 
 
115
  interval_start_minutes: -2880
116
+ interval_end_minutes: 2160
117
  time_resolution_minutes: 15
 
model_config.yaml CHANGED
@@ -11,47 +11,45 @@ nwp_encoders_dict:
11
  ecmwf:
12
  _target_: pvnet.models.late_fusion.encoders.encoders3d.DefaultPVNet
13
  _partial_: true
14
- in_channels: 14
15
  out_features: 64
 
16
  number_of_conv3d_layers: 4
17
  conv3d_channels: 32
18
- image_size_pixels: 36
19
- sat_encoder:
20
- _target_: pvnet.models.late_fusion.encoders.encoders3d.DefaultPVNet
21
- _partial_: true
22
- in_channels: 11
23
- out_features: 256
24
- number_of_conv3d_layers: 6
25
- conv3d_channels: 32
26
- image_size_pixels: 100
27
- add_image_embedding_channel: false
28
- pv_encoder:
29
- _target_: pvnet.models.late_fusion.site_encoders.encoders.SingleAttentionNetwork
30
- _partial_: true
31
- num_sites: 1
32
- out_features: 64
33
- num_heads: 4
34
- kdim: 64
35
- id_embed_dim: 64
36
  output_network:
37
  _target_: pvnet.models.late_fusion.linear_networks.networks.ResFCNet
38
  _partial_: true
39
  fc_hidden_features: 128
40
  n_res_blocks: 6
41
  res_block_layers: 2
42
- dropout_frac: 0.0
43
- embedding_dim: 16
44
  include_sun: true
45
- forecast_minutes: 2880
46
- history_minutes: 2880
 
47
  interval_minutes: 15
48
- min_sat_delay_minutes: 60
49
- sat_history_minutes: 90
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
50
  pv_history_minutes: 2880
51
- pv_interval_minutes: 15
52
  nwp_history_minutes:
53
  ecmwf: 120
54
  nwp_forecast_minutes:
55
- ecmwf: 2880
56
  nwp_interval_minutes:
57
  ecmwf: 60
 
11
  ecmwf:
12
  _target_: pvnet.models.late_fusion.encoders.encoders3d.DefaultPVNet
13
  _partial_: true
14
+ in_channels: 13
15
  out_features: 64
16
+ fc_features: 32
17
  number_of_conv3d_layers: 4
18
  conv3d_channels: 32
19
+ image_size_pixels: 10
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
20
  output_network:
21
  _target_: pvnet.models.late_fusion.linear_networks.networks.ResFCNet
22
  _partial_: true
23
  fc_hidden_features: 128
24
  n_res_blocks: 6
25
  res_block_layers: 2
26
+ dropout_frac: 0.2
 
27
  include_sun: true
28
+ target_key: site
29
+ include_gsp_yield_history: false
30
+ include_site_yield_history: true
31
  interval_minutes: 15
32
+ location_id_mapping:
33
+ 1: 1
34
+ 2: 2
35
+ 3: 3
36
+ 4: 4
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+ 5: 5
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+ 6: 6
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+ 7: 7
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+ 8: 8
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+ 9: 9
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+ 10: 10
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+ 11: 11
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+ 12: 12
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+ forecast_minutes: 2160
46
+ history_minutes: 2880
47
+ min_sat_delay_minutes: 5
48
+ sat_history_minutes: 65
49
  pv_history_minutes: 2880
 
50
  nwp_history_minutes:
51
  ecmwf: 120
52
  nwp_forecast_minutes:
53
+ ecmwf: 2220
54
  nwp_interval_minutes:
55
  ecmwf: 60
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