Merge branch 'openclimatefix:main' into main

openclimatefix · Nov 12, 2024 · 0de6465 · 0de6465
2 parents 2f973d1 + 97714e5
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diff --git a/.all-contributorsrc b/.all-contributorsrc
@@ -217,6 +217,33 @@
       "contributions": [
         "code"
       ]
+    },
+    {
+      "login": "sumana-2705",
+      "name": "Sumana Sree Angajala",
+      "avatar_url": "https://avatars.githubusercontent.com/u/110307215?v=4",
+      "profile": "https://github.com/sumana-2705",
+      "contributions": [
+        "code"
+      ]
+    },
+    {
+      "login": "EmilyIsCoding",
+      "name": "Emily",
+      "avatar_url": "https://avatars.githubusercontent.com/u/98443131?v=4",
+      "profile": "https://github.com/EmilyIsCoding",
+      "contributions": [
+        "test"
+      ]
+    },
+    {
+      "login": "sergejlazuk",
+      "name": "sergejla",
+      "avatar_url": "https://avatars.githubusercontent.com/u/33606741?v=4",
+      "profile": "https://github.com/sergejlazuk",
+      "contributions": [
+        "question"
+      ]
     }
   ],
   "contributorsPerLine": 7,

diff --git a/.bumpversion.cfg b/.bumpversion.cfg
@@ -1,7 +1,7 @@
 [bumpversion]
 commit = True
 tag = True
-current_version = 1.0.75
+current_version = 1.0.81
 message = Bump version: {current_version} → {new_version} [skip ci]
 
 [bumpversion:file:pyproject.toml]

diff --git a/.env.example b/.env.example
@@ -19,6 +19,10 @@ SOLIS_CLOUD_API_PORT = '13333'
 # User needs to add their GivEnergy API details
 GIVENERGY_API_KEY = 'user_givenergy_api_key'
 
+# To connect to a Victron system use the environment variables below to set the username and password
+#VICTRON_USER=username
+#VICTRON_PASS=password
+
 # User needs to add their GivEnergy API details
 SOLARMAN_API_URL = 'https://home.solarmanpv.com/maintain-s/history/power'
 SOLARMAN_TOKEN = 'user_solarman_token'

diff --git a/.github/workflows/pytest.yaml b/.github/workflows/pytest.yaml
@@ -10,7 +10,7 @@ on:
     types: [opened, synchronize, reopened, ready_for_review]
 jobs:
   call-run-python-tests:
-    uses: openclimatefix/.github/.github/workflows/python-test.yml@main
+    uses: openclimatefix/.github/.github/workflows/python-test.yml@issue/pip-all
     with:
       # pytest-cov looks at this folder
       pytest_cov_dir: "quartz_solar_forecast"

diff --git a/README.md b/README.md
@@ -1,9 +1,16 @@
 # Quartz Solar Forecast
 
 <!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section -->
-[![All Contributors](https://img.shields.io/badge/all_contributors-23-orange.svg?style=flat-square)](#contributors-)
+[![All Contributors](https://img.shields.io/badge/all_contributors-26-orange.svg?style=flat-square)](#contributors-)
 <!-- ALL-CONTRIBUTORS-BADGE:END -->
 
+![image](https://github.com/user-attachments/assets/6563849b-b355-4842-93e4-61c15a9a9ebf)
+[![tags badge](https://img.shields.io/github/v/tag/openclimatefix/open-source-quartz-solar-forecast?include_prereleases&sort=semver&color=FFAC5F)](https://github.com/openclimatefix/open-source-quartz-solar-forecast/tags)
+[![pypi badge](https://img.shields.io/pypi/v/quartz-solar-forecast?&color=07BCDF)](https://pypi.org/project/quartz-solar-forecast/)
+[![ease of contribution: easy](https://img.shields.io/badge/ease%20of%20contribution:%20easy-32bd50)](https://github.com/openclimatefix/ocf-meta-repo?tab=readme-ov-file#overview-of-ocfs-nowcasting-repositories) 
+[![Python package tests](https://github.com/openclimatefix/open-source-quartz-solar-forecast/actions/workflows/pytest.yaml/badge.svg)](https://github.com/openclimatefix/open-source-quartz-solar-forecast/actions/workflows/pytest.yaml)
+
+
 The aim of the project is to build an open source PV forecast that is free and easy to use.
 The forecast provides the expected generation in `kw` for 0 to 48 hours for a single PV site.
 
@@ -35,16 +42,10 @@ A colab notebook providing some examples can be found [here](https://colab.resea
 
 To generate solar forecasts and save them into a CSV file, follow these steps:
 
-1. Navigate to the scripts directory
-
-```bash
-cd scripts
-```
-
-2. Run the forecast_csv.py script with desired inputs
+- Run the forecast_csv.py script with desired inputs
 
 ```bash
-python forecast_csv.py
+python scripts/forecast_csv.py
 ```
 
 Replace the --init_time_freq, --start_datetime, --end_datetime, and --site_name with your desired forecast initialization frequency (in hours), start datetime, end datetime, and the name of the forecast or site, respectively.
@@ -258,6 +259,9 @@ Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/d
     <tr>
       <td align="center" valign="top" width="14.28%"><a href="https://github.com/aayushyatiwari"><img src="https://avatars.githubusercontent.com/u/169576527?v=4?s=100" width="100px;" alt="aayush"/><br /><sub><b>aayush</b></sub></a><br /><a href="https://github.com/openclimatefix/open-source-quartz-solar-forecast/commits?author=aayushyatiwari" title="Documentation">📖</a></td>
       <td align="center" valign="top" width="14.28%"><a href="https://github.com/Brohan7524"><img src="https://avatars.githubusercontent.com/u/85754035?v=4?s=100" width="100px;" alt="Rohan Singh"/><br /><sub><b>Rohan Singh</b></sub></a><br /><a href="https://github.com/openclimatefix/open-source-quartz-solar-forecast/commits?author=Brohan7524" title="Code">💻</a></td>
+      <td align="center" valign="top" width="14.28%"><a href="https://github.com/sumana-2705"><img src="https://avatars.githubusercontent.com/u/110307215?v=4?s=100" width="100px;" alt="Sumana Sree Angajala"/><br /><sub><b>Sumana Sree Angajala</b></sub></a><br /><a href="https://github.com/openclimatefix/open-source-quartz-solar-forecast/commits?author=sumana-2705" title="Code">💻</a></td>
+      <td align="center" valign="top" width="14.28%"><a href="https://github.com/EmilyIsCoding"><img src="https://avatars.githubusercontent.com/u/98443131?v=4?s=100" width="100px;" alt="Emily"/><br /><sub><b>Emily</b></sub></a><br /><a href="https://github.com/openclimatefix/open-source-quartz-solar-forecast/commits?author=EmilyIsCoding" title="Tests">⚠️</a></td>
+      <td align="center" valign="top" width="14.28%"><a href="https://github.com/sergejlazuk"><img src="https://avatars.githubusercontent.com/u/33606741?v=4?s=100" width="100px;" alt="sergejla"/><br /><sub><b>sergejla</b></sub></a><br /><a href="#question-sergejlazuk" title="Answering Questions">💬</a></td>
     </tr>
   </tbody>
 </table>

diff --git a/examples/inverter_example.py b/examples/inverter_example.py
@@ -14,7 +14,7 @@ def main(save_outputs: bool = False):
     ts = pd.to_datetime(timestamp_str)
 
     # make input data with live enphase, solis, givenergy, or solarman data
-    site_live = PVSite(latitude=51.75, longitude=-1.25, capacity_kwp=1.25, inverter_type="enphase") # inverter_type="enphase", "solis", "givenergy", or "solarman"
+    site_live = PVSite(latitude=51.75, longitude=-1.25, capacity_kwp=1.25, inverter_type="enphase") # inverter_type="enphase", "solis", "givenergy", "solarman" or "victron"
 
     # make input data with nan data
     site_no_live = PVSite(latitude=51.75, longitude=-1.25, capacity_kwp=1.25)

diff --git a/pyproject.toml b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "quartz_solar_forecast"
-version = "1.0.75"
+version = "1.0.81"
 description = "Open Source Solar Forecasting for a Site"
 authors = [
     { name = "Peter Dudfield", email = "[email protected]" }
@@ -43,6 +43,9 @@ package-data = { "quartz_solar_forecast" = ["*"] }
 
 [project.optional-dependencies]
 dev = []
+# additional vendor-specific dependencies for connecting to inverter APIs
+inverters = ["ocf_vrmapi"] # victron
+all = ["ocf_vrmapi"]
 
 [tool.mypy]
 

diff --git a/quartz_solar_forecast/forecast.py b/quartz_solar_forecast/forecast.py
@@ -1,11 +1,13 @@
 from datetime import datetime, timedelta
+import logging
 
 import pandas as pd
 
 from quartz_solar_forecast.data import get_nwp, make_pv_data
 from quartz_solar_forecast.forecasts import forecast_v1_tilt_orientation, TryolabsSolarPowerPredictor
 from quartz_solar_forecast.pydantic_models import PVSite
 
+log = logging.getLogger(__name__)
 
 def predict_ocf(
     site: PVSite, model=None, ts: datetime | str = None, nwp_source: str = "icon"
@@ -25,13 +27,27 @@ def predict_ocf(
     if isinstance(ts, str):
         ts = datetime.fromisoformat(ts)
 
+    if site.capacity_kwp > 4:
+        log.warning("Your site capacity is greater than 4kWp, "
+                    "however the model is trained on sites with capacity <= 4kWp."
+                    "We therefore will run the model with a capacity of 4 kWp, "
+                    "and we'll scale the results afterwards.")
+        capacity_kwp_original = site.capacity_kwp
+        site.capacity_kwp = 4
+    else:
+        capacity_kwp_original = site.capacity_kwp
+
     # make pv and nwp data from nwp_source
     nwp_xr = get_nwp(site=site, ts=ts, nwp_source=nwp_source)
     pv_xr = make_pv_data(site=site, ts=ts)
 
     # load and run models
     pred_df = forecast_v1_tilt_orientation(nwp_source, nwp_xr, pv_xr, ts, model=model)
 
+    # scale the results if the capacity is different
+    if capacity_kwp_original != site.capacity_kwp:
+        pred_df["power_kw"] = pred_df["power_kw"] * capacity_kwp_original / site.capacity_kwp
+
     return pred_df
 
 

diff --git a/quartz_solar_forecast/inverters/victron.py b/quartz_solar_forecast/inverters/victron.py
@@ -0,0 +1,48 @@
+from typing import Callable
+
+import pandas as pd
+from datetime import datetime, timedelta
+from quartz_solar_forecast.inverters.inverter import AbstractInverter
+from pydantic import Field
+from pydantic_settings import BaseSettings, SettingsConfigDict
+try:
+    from ocf_vrmapi.vrm import VRM_API
+except:
+    print("Tried to import ocf_vrmapi but couldnt, Victron Inverter functions won't work")
+
+class VictronSettings(BaseSettings):
+    model_config = SettingsConfigDict(env_file='.env', extra='ignore')
+
+    username: str = Field(alias="VICTRON_USER")
+    password: str = Field(alias="VICTRON_PASS")
+
+
+class VictronInverter(AbstractInverter):
+
+    def __init__(self, get_sites: Callable, get_kwh_stats: Callable):
+        self.__get_sites = get_sites
+        self.__get_kwh_stats = get_kwh_stats
+
+    @classmethod
+    def from_settings(cls, settings: VictronSettings):
+        api = VRM_API(username=settings.username, password=settings.password)
+        get_sites = lambda: api.get_user_sites(api.user_id)
+        end = datetime.now()
+        start = end - timedelta(weeks=1)
+        get_kwh_stats = lambda site_id: api.get_kwh_stats(site_id, start=start, end=end)
+        return cls(get_sites, get_kwh_stats)
+
+    def get_data(self, ts: pd.Timestamp) -> pd.DataFrame:
+        sites = self.__get_sites()
+        # get first site (bit of a guess)
+        first_site_id = sites["records"][0]["idSite"]
+
+        stats = self.__get_kwh_stats(first_site_id)
+
+        kwh = stats["records"]["kwh"]
+
+        df = pd.DataFrame(kwh)
+
+        df[0] = pd.to_datetime(df[0], unit='ms')
+        df.columns = ["timestamp", "power_kw"]
+        return df
diff --git a/quartz_solar_forecast/pydantic_models.py b/quartz_solar_forecast/pydantic_models.py
@@ -6,6 +6,7 @@
 from quartz_solar_forecast.inverters.mock import MockInverter
 from quartz_solar_forecast.inverters.solarman import SolarmanSettings, SolarmanInverter
 from quartz_solar_forecast.inverters.solis import SolisSettings, SolisInverter
+from quartz_solar_forecast.inverters.victron import VictronSettings, VictronInverter
 
 
 class PVSite(BaseModel):
@@ -41,6 +42,8 @@ def get_inverter(self):
             return GivEnergyInverter(GivEnergySettings())
         elif self.inverter_type == 'solarman':
             return SolarmanInverter(SolarmanSettings())
+        elif self.inverter_type == 'victron':
+            return VictronInverter.from_settings(VictronSettings())
         else:
             return MockInverter()
 

diff --git a/quartz_solar_forecast/utils/forecast_csv.py b/quartz_solar_forecast/utils/forecast_csv.py
@@ -3,45 +3,56 @@
 from datetime import datetime, timedelta
 from quartz_solar_forecast.forecast import run_forecast
 from quartz_solar_forecast.pydantic_models import PVSite
-import unittest
-from unittest.mock import patch
 
 
 def generate_all_forecasts(
-        init_time_freq: int,
-        start: datetime,
-        end: datetime,
-        latitude: float,
-        longitude: float,
-        capacity_kwp: float) -> pd.DataFrame:
+    init_time_freq: int,
+    start: datetime,
+    end: datetime,
+    latitude: float,
+    longitude: float,
+    capacity_kwp: float,
+) -> pd.DataFrame:
 
     all_forecasts = pd.DataFrame()
 
     init_time = start
     while init_time <= end:
         print(f"Running forecast for initialization time: {init_time}")
-        predictions_df = forecast_for_site(latitude, longitude, capacity_kwp, init_time=init_time)
-        predictions_df['forecast_init_time'] = init_time
+        predictions_df = forecast_for_site(
+            latitude, longitude, capacity_kwp, init_time=init_time
+        )
+        predictions_df["forecast_init_time"] = init_time
         all_forecasts = pd.concat([all_forecasts, predictions_df])
         init_time += timedelta(hours=init_time_freq)
 
     return all_forecasts
 
 
-def forecast_for_site(latitude: float,
-                      longitude: float,
-                      capacity_kwp: float,
-                      model: str = "gb",
-                      init_time: datetime = None) -> pd.DataFrame:
+def forecast_for_site(
+    latitude: float,
+    longitude: float,
+    capacity_kwp: float,
+    model: str = "gb",
+    init_time: datetime = None,
+) -> pd.DataFrame:
 
     site = PVSite(latitude=latitude, longitude=longitude, capacity_kwp=capacity_kwp)
     predictions_df = run_forecast(site=site, model=model, ts=init_time)
     predictions_df.reset_index(inplace=True)
-    predictions_df.rename(columns={'index': 'datetime'}, inplace=True)
+    predictions_df.rename(columns={"index": "datetime"}, inplace=True)
     return predictions_df
 
 
-def write_out_forecasts(init_time_freq, start_datetime, end_datetime, site_name, latitude, longitude, capacity_kwp):
+def write_out_forecasts(
+    init_time_freq,
+    start_datetime,
+    end_datetime,
+    site_name,
+    latitude,
+    longitude,
+    capacity_kwp,
+):
     """
     Generates forecasts at specified intervals and saves them into a CSV file.
 
@@ -58,64 +69,15 @@ def write_out_forecasts(init_time_freq, start_datetime, end_datetime, site_name,
     start_date = start.date()
     end = datetime.strptime(end_datetime, "%Y-%m-%d %H:%M:%S")
     end_date = end.date()
-    all_forecasts = generate_all_forecasts(init_time_freq, start, end, latitude, longitude, capacity_kwp)
+    all_forecasts = generate_all_forecasts(
+        init_time_freq, start, end, latitude, longitude, capacity_kwp
+    )
 
-    output_dir = os.path.join(os.getcwd(), 'csv_forecasts')
+    output_dir = os.path.join(os.getcwd(), "csv_forecasts")
     if not os.path.exists(output_dir):
         os.makedirs(output_dir)
     output_file_name = f"forecast_{site_name}_{start_date}_{end_date}.csv"
     output_file_path = os.path.join(output_dir, output_file_name)
     all_forecasts.to_csv(output_file_path, index=False)
     print(f"Forecasts saved to {output_file_path}")
 
-if __name__ == "__main__":
-    # please change the site name, start_datetime and end_datetime, latitude, longitude and capacity_kwp as per your requirement
-    write_out_forecasts(
-        init_time_freq=6,
-        start_datetime="2024-03-10 00:00:00",
-        end_datetime="2024-03-11 00:00:00",
-        site_name="Test",
-        latitude=51.75,
-        longitude=-1.25,
-        capacity_kwp=1.25
-    )
-
-class TestGenerateForecast(unittest.TestCase):
-    def setUp(self):
-        self.site_name = "TestCase"
-        self.latitude = 51.75
-        self.longitude = -1.25
-        self.capacity_kwp = 1.25
-        self.start_datetime = "2024-03-10 00:00:00"
-        self.end_datetime = "2024-03-11 00:00:00"
-        self.init_time_freq = 6
-        self.output_dir = os.path.join(os.getcwd(), 'csv_forecasts')
-        self.output_file_name = f"forecast_{self.site_name}_{self.start_datetime[:10]}_{self.end_datetime[:10]}.csv"
-        self.output_file_path = os.path.join(self.output_dir, self.output_file_name)
-
-    @patch('forecast_csv.run_forecast')
-    def test_generate_forecast(self, mock_run_forecast):
-        mock_df = pd.DataFrame({
-            'datetime': [datetime(2024, 3, 10, 0, 0) + timedelta(hours=6 * i) for i in range(4)],
-            'power_kw': [0.1, 0.5, 0.8, 0.6],
-            'forecast_init_time': [datetime(2024, 3, 10, 0, 0)] * 4
-        })
-        mock_run_forecast.return_value = mock_df
-
-        if not os.path.exists(self.output_dir):
-            os.makedirs(self.output_dir)
-
-        write_out_forecasts(self.init_time_freq,
-                          self.start_datetime, 
-                          self.end_datetime, 
-                          self.site_name, 
-                          self.latitude, 
-                          self.longitude, 
-                          self.capacity_kwp
-                        )
-
-        self.assertTrue(os.path.exists(self.output_file_path))
-        os.remove(self.output_file_path)
-
-if __name__ == '__main__':
-    unittest.main()