open-meteo-solar-forecast 0.1.27

Asynchronous Python client for getting forecast solar information

Python API fetching Solarpanels forecast information.

About

With this python library you can request data from Open-Meteo and see what your solar panels may produce in the coming days.

Installation

pip install open-meteo-solar-forecast

Data

This library returns a lot of different data, based on the API:

Energy

• Total Estimated Energy Production - today/tomorrow (kWh)
• Estimated Energy Production - This Hour (kWh)
• Estimated Energy Production - Next Hour (kWh)
• Estimated Energy Production - Remaining today (kWh)

Power

• Highest Power Peak Time - Today (datetime)
• Highest Power Peak Time - Tomorrow (datetime)
• Estimated Power Production - Now (W)
• Estimated Power Production - Next Hour (W)
• Estimated Power Production - In +6 Hours (W)
• Estimated Power Production - In +12 Hours (W)
• Estimated Power Production - In +24 Hours (W)

API Info

• Timezone
• Rate limit
• Account type
• Rate remaining

Validation

• API key (bool)
• Plane (bool)

Example

import asyncio

from open_meteo_solar_forecast import OpenMeteoSolarForecast


async def main() -> None:
    """Show example on how to use the library."""
    async with OpenMeteoSolarForecast(
        latitude=52.16,
        longitude=4.47,
        declination=20,
        azimuth=10,
        dc_kwp=2.160,
		use_horizon=True,
		partial_shading=True,
        horizon_map=((0,30),(360,30),
    ) as forecast:
        estimate = await forecast.estimate()
        print(estimate)


if __name__ == "__main__":
    asyncio.run(main())

Parameter	value type	Description
base_url	str	The base URL of the API (optional)
api_key	str	Your API key (optional)
declination	int	The tilt of the solar panels (required)
azimuth	int	The direction the solar panels are facing (required)
dc_kwp	float	The size of the solar panels in kWp (required)
use_horizon	bool	Whether to use horizon shading (optional, default = False)
partial_shading	bool	Whether to use interpret horizon shading as partial** [experimental] (optional, default = False)
horizon_map	tuple of 2-tuples	Map of the horizon* (required if use_horizon = True)

*) The horizon map is a tuple of 2-tuples, where each 2-tuple consists of (azimuth,elevation). Azimuth is the compass direction in degrees (0° = north, 180° = south). The horizon map has to cover the whole range of azimuths that the sun travels through over the year (recommendation: plot the horizon from 0 to 360°). Elevation is the associated angle in degrees of any object (hill, tree, ...) casting a shadow on the modules. The elevation angle has to be in the range 0° (flat, ideal horizon) to 90° (in the sky directly over the modules). The map has to be monotonic on the azimuth axis, however this is not checked by the script! Elevation values in between are interpolated along the azimuth axis, thus non-monotonic values will give wrong results. The horizon map can also be passed from a text file, see the included example estimate_horizon.py.

**) If partial_shading is disabled and a shadow is detected on the module, only the diffuse irradiation will be used to calculate the power output. This is useful if the shading is predominantly from far-away objects, which can be treated as shading the whole module at once or not. If partial_shading is enabled and a shadow is detected on the module, the shadow is treated as partial. This is useful if the shading arises from close-by objects, which cast 'hard' contoured shadows on the module. In this case, an experimental calculation is used taking into account the 'sunniness' of the conditions. This is done via the ratio of diffuse and direct irradiation. A large share of diffuse irradiation (cloudy day) will let the module run as homogeneously shaded at diffuse power. A small share of diffuse irradiation (sunny) day will reduce the diffuse power even more, since hard partial shadows can shut down the module completely.

Contributing

Would you like to contribute to the development of this project? Then read the prepared contribution guidelines and go ahead!

Thank you for being involved! :heart_eyes:

Setting up development environment

This Python project relies on Poetry as its dependency manager, providing comprehensive management and control over project dependencies.

You need at least:

• Python 3.11+
• Poetry

Install all packages, including all development requirements:

poetry install

Poetry creates by default an virtual environment where it installs all necessary pip packages, to enter or exit the venv run the following commands:

poetry shell
exit

License

MIT License

Copyright (c) 2021-2024 Klaas Schoute
Copyright (c) 2024 Rany

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.