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https://github.com/tum-ens/pyGRETA

python Generator of REnewable Time series and mAps
https://github.com/tum-ens/pyGRETA

csp gis high-resolution potentials pv renewable-energy renewable-timeseries wind

Last synced: 2 months ago
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python Generator of REnewable Time series and mAps

Host: GitHub
URL: https://github.com/tum-ens/pyGRETA
Owner: tum-ens
License: gpl-3.0
Created: 2019-03-08T17:08:33.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2022-04-20T09:45:25.000Z (about 2 years ago)
Last Synced: 2024-03-22T09:01:38.551Z (4 months ago)
Topics: csp, gis, high-resolution, potentials, pv, renewable-energy, renewable-timeseries, wind
Language: Python
Homepage:
Size: 224 MB
Stars: 35
Watchers: 6
Forks: 14
Open Issues: 11
Metadata Files:
- Readme: README.md
- License: LICENSE

Lists

open-sustainable-technology - pyGRETA - Python Generator of REnewable Time series and mAps: a tool that generates high-resolution potential maps and time series for user-defined regions within the globe. (Energy Systems / Energy Modeling and Optimization)

README

        






[![Documentation Status](https://readthedocs.org/projects/pygreta/badge/?version=latest)](http://pyGRETA.readthedocs.io/en/latest/?badge=latest)

[![DOI](https://zenodo.org/badge/174577484.svg)](https://zenodo.org/badge/latestdoi/174577484)

[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)

[![All Contributors](https://img.shields.io/badge/all_contributors-8-orange.svg?style=flat-square)](#contributors)

**py**thon **G**enerator of **RE**newable **T**ime series and m**A**ps: a tool that generates high-resolution potential maps and time series for user-defined regions within the globe.

## Features

* Generation of potential maps and time series for user-defined regions within the globe

* Modeled technologies: onshore wind, offshore wind, PV, CSP (user-defined technology characteristics)

* Use of MERRA-2 reanalysis data, with the option to detect and correct outliers

* High resolution potential taking into account the land use suitability/availability, topography, bathymetry, slope, distance to urban areas, etc.

* Statistical reports with summaries (available area, maximum capacity, maximum energy output, etc.) for each user-defined region

* Generation of several time series for each technology and region, based on user's preferences

* Possibility to combine the time series into one using linear regression to match given full-load hours and temporal fluctuations

## Applications

This code is useful if:

* You want to estimate the theoretical and/or technical potential of an area, which you can define through a shapefile

* You want to obtain high resolution maps

* You want to define your own technology characteristics

* You want to generate time series for an area after excluding parts of it that are not suitable for renewable power plants

* You want to generate multiple time series for the same area (best site, upper 10%, median, lower 25%, etc.)

* You want to match historical capacity factors of countries from the IRENA database

You do not need to use the code (*but you can*) if:

* You do not need to exclude unsuitable areas - use the [Global Solar Atlas](https://globalsolaratlas.info/) or [Global Wind Atlas](https://globalwindatlas.info/)

* You only need time series for specific points - use other webtools such as [Renewables.ninja](https://www.renewables.ninja/)

* You only need time series for administrative divisions (countries, NUTS-2, etc.), for which such data is readily available - see [Renewables.ninja](https://www.renewables.ninja/) or [EMHIRES](https://ec.europa.eu/jrc/en/scientific-tool/emhires)

## Outputs

Potential maps for solar PV and onshore wind in Australia, using weather data for 2015:













 

## Contributors ✨

Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)):

  

    
_kais-siala
💬 🐛 💻 📖 🤔 🚧 👀 ⚠️ 📢

    
_HoussameH
💬 💻 📖

    
_{Pierre Grimaud}
🐛

    
_thushara2020
👀

    
_lodersky
📖 💻 👀

    
_sonercandas
📖

    
_{patrick-buchenberg}
📦

  

  

    
_molarana
🎨

  

This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!

## Please cite as:

Kais Siala, & Houssame Houmy. (2020, June 1). tum-ens/pyGRETA: python Generator of REnewable Time series and mAps (Version v1.1.0). Zenodo. https://doi.org/10.5281/zenodo.3727416