{ "info": { "author": "Jonas Hoersch (FIAS), Tom Brown (FIAS), Gorm Andresen (Aarhus University)", "author_email": "jonas.hoersch@posteo.de", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Environment :: Console", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)", "Natural Language :: English", "Operating System :: OS Independent" ], "description": "========\n Atlite\n========\n\nAtlite is a `free software\n`_, `xarray\n`_-based Python library for\nconverting weather data (such as wind speeds, solar radiation,\ntemperature and runoff) into power systems data (such as wind\npower, solar power, hydro power and heating demand time series). It is\ndesigned to work with big datasets, such as hourly global weather data\nover several years at spatial resolutions down to e.g. 0.1 x 0.1\ndegree resolution.\n\nAtlite was originally conceived as a light-weight version of the Aarhus\nUniversity RE Atlas, which produces wind and solar generation time\nseries from historical reanalysis data. It has since been extended to\nuse weather datasets simulated with projected climate change and to compute\nother time series, such as hydro power, solar thermal collectors and\nheating demand.\n\nAtlite is designed to be modular, so that it can work with any weather\ndatasets. It currently has modules for the following datasets:\n\n* `NCEP Climate Forecast System `_ hourly\n historical reanalysis weather data available on a 0.2 x 0.2 degree global grid\n* `EURO-CORDEX Climate Change Projection `_\n three-hourly up until 2100, available on a 0.11 x 0.11 degree grid for Europe\n* `ECMWF ERA5\n `_ hourly\n historical reanalysis weather data on an approximately 0.25 x 0.25 deg global\n grid\n* `CMSAF SARAH-2\n `_\n half-hourly historical surface radiation on a 0.05 x 0.05 deg grid available\n for Europe and Africa (automatically interpolated to a 0.2 deg grid and\n combined with ERA5 temperature).\n\nIt can process the following weather data fields:\n\n* Temperature\n* Downward short-wave radiation\n* Upward short-wave radiation\n* Wind \n* Runoff\n* Surface roughness\n* Height maps\n* Soil temperature\n\nThe following power-system relevant time series can be produced for\nall possible spatial distributions of assets:\n\n* Wind power generation for a given turbine type\n* Solar PV power generation for a given panel type\n* Solar thermal collector heat output\n* Hydroelectric inflow (simplified)\n* Heating demand (based on the degree-day approximation)\n\nCitation for Aarhus University RE\nAtlas: G. B. Andresen, A. A. S\u00f8ndergaard, M. Greiner, \"Validation of\ndanish wind time series from a new global renewable energy atlas for\nenergy system analysis,\" Energy 93, Part 1 (2015) 1074 \u2013 1088.\ndoi:http://dx.doi.org/10.1016/j.energy.2015.09.071.\n\nAtlite was initially developed by the `Renewable Energy Group\n`_\nat `FIAS `_ to carry out simulations\nfor the `CoNDyNet project `_, financed by the\n`German Federal Ministry for Education and Research (BMBF)\n`_ as part of the `Stromnetze\nResearch Initiative\n`_.\n\nGetting started\n===============\n\n* Install atlite from this repository with all its library dependencies\n* Download one of the weather datasets listed above (ERA5 is downloaded\n automatically on-demand after the ECMWF\n `cdsapi` client is \n properly installed)\n* Adjust the `atlite/config.py `_ directory paths to\n point to the directory where you downloaded the dataset\n* Create a cutout, i.e. a geographical rectangle and a selection of\n times, e.g. all hours in 2011 and 2012, to narrow down the scope -\n see `examples/create_cutout.py `_\n* Select a sparse matrix of the geographical points inside the cutout\n you want to aggregate for your time series, and pass it to the\n appropriate converter function - see `examples/ `_\n\nLicence\n=======\n\n\nCopyright 2016-2017 Gorm Andresen (Aarhus University), Jonas H\u00f6rsch (FIAS), Tom Brown (FIAS), Markus Schlott (FIAS), David Schlachtberger (FIAS)\n\n\nThis program (atlite) is free software: you can redistribute it and/or\nmodify it under the terms of the GNU General Public License as\npublished by the Free Software Foundation; either `version 3 of the\nLicense `_, or (at your option) any later version.\n\nThis program is distributed in the hope that it will be useful,\nbut WITHOUT ANY WARRANTY; without even the implied warranty of\nMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the\n`GNU General Public License `_ for more details.\n\n\n", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/FRESNA/atlite", "keywords": "", "license": "GPLv3", "maintainer": "", "maintainer_email": "", "name": "atlite", "package_url": "https://pypi.org/project/atlite/", "platform": "", "project_url": "https://pypi.org/project/atlite/", "project_urls": { "Homepage": "https://github.com/FRESNA/atlite" }, "release_url": "https://pypi.org/project/atlite/0.0.2/", "requires_dist": [ "numpy", "scipy", "pandas (>=0.22)", "bottleneck", "numexpr", "xarray (>=0.11.2)", "dask (>=0.18.0)", "rasterio", "shapely", "progressbar2", "geopandas" ], "requires_python": "", "summary": "Library for fetching and converting weather data to power systems data", "version": "0.0.2" }, "last_serial": 5414542, "releases": { "0.0.2": [ { "comment_text": "", "digests": { "md5": "c99a5fb8af84617a0d631b98856398f9", "sha256": "400f2320a2fc6330b63caa882c672d76917c25696668d73b3c35584a068c1023" }, "downloads": -1, "filename": "atlite-0.0.2-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "c99a5fb8af84617a0d631b98856398f9", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 71267, "upload_time": "2019-06-18T10:50:24", "url": "https://files.pythonhosted.org/packages/56/c4/8f0b19f5fe336de7cca3171a9327e91e73962c7d432ddae761c6b10634fe/atlite-0.0.2-py2.py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "1ffb9bbe9c7995d919f19cdc6c5d0a54", "sha256": "2e53da5900597aeb38e50615b3d725e1241b7215af3ce8541fa230d8082bce57" }, "downloads": -1, "filename": "atlite-0.0.2.tar.gz", "has_sig": false, "md5_digest": "1ffb9bbe9c7995d919f19cdc6c5d0a54", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 51825, "upload_time": "2019-06-18T10:50:27", "url": "https://files.pythonhosted.org/packages/a2/e5/448d8beddd6dab693d30f34558438a3459e3411f1d8f5e5c1860e8a50448/atlite-0.0.2.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "c99a5fb8af84617a0d631b98856398f9", "sha256": "400f2320a2fc6330b63caa882c672d76917c25696668d73b3c35584a068c1023" }, "downloads": -1, "filename": "atlite-0.0.2-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "c99a5fb8af84617a0d631b98856398f9", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 71267, "upload_time": "2019-06-18T10:50:24", "url": "https://files.pythonhosted.org/packages/56/c4/8f0b19f5fe336de7cca3171a9327e91e73962c7d432ddae761c6b10634fe/atlite-0.0.2-py2.py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "1ffb9bbe9c7995d919f19cdc6c5d0a54", "sha256": "2e53da5900597aeb38e50615b3d725e1241b7215af3ce8541fa230d8082bce57" }, "downloads": -1, "filename": "atlite-0.0.2.tar.gz", "has_sig": false, "md5_digest": "1ffb9bbe9c7995d919f19cdc6c5d0a54", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 51825, "upload_time": "2019-06-18T10:50:27", "url": "https://files.pythonhosted.org/packages/a2/e5/448d8beddd6dab693d30f34558438a3459e3411f1d8f5e5c1860e8a50448/atlite-0.0.2.tar.gz" } ] }