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        "description": "=====\nEVNRG\n=====\n\n\n.. image:: https://img.shields.io/pypi/v/evnrg.svg\n        :target: https://pypi.python.org/pypi/evnrg\n\n.. image:: https://readthedocs.org/projects/evnrg/badge/?version=latest\n        :target: https://evnrg.readthedocs.io/en/latest/?badge=latest\n        :alt: Documentation Status\n\n.. image:: https://travis-ci.com/accurrently/evnrg.svg?branch=master\n    :target: https://travis-ci.com/accurrently/evnrg\n\n.. figure:: https://github.com/accurrently/evnrg/raw/master/images/w15-demand.png\n\nEVNRG is an EV electrical demand simulation package that takes in trip data and turns it into useful energy data given a set of assumptions.\n\nThis project was inspired by an earlier effort to simulate electrical demand from a theoretical electrified fleet replacement.\nThis tool is designed to track energy usage across an arbitrarily large fleet, with an arbitrary number of EVSE, and rules \nthat govern when charging occurs, and what type of queuing logic to use.\n\n\n* Documentation: https://evnrg.readthedocs.io.\n\n\nFeatures\n--------\n\nEVNRG takes in scenario definitions and interval travel data in order to generate arrays (Pandas Series) of:\n\n* Electrical demand (per EVSE bank)\n* Fuel consumption (per vehicle)\n* Battery state (per vehicle)\n* Deferred distance (per vehicle)\n* EVSE occupancy (per EVSE bank)\n\nTODO\n----\n* Write unit tests\n* Create Dask dispatcher for parallelized simulations\n* Implement geofenced rules\n* Implement smart charging behavior (throttling, round-robin) for situations where a `Bank`'s maximum power is lower the sum total of each `EVSE`'s maximum output.\n* Implement analyis (dependednt on `openei-rates`_)\n\nLicense\n-------\nThis package is Free software under the Apache Software License 2.0. See LICENSE for more information.\n\nCredits\n-------\n\nInitially written by Alex Campbell as part of a master's of science thesis project at the University of California, Davis `Energy Graduate Group`_.\nThis project falls under the auspices of the UC Davis `Institute of Transportation Studies (ITS)`_ and \nthe UC Davis `Plug-in Hybrid and Electric Vehicle Research Center`_. This project was funded by the `Office of Naval Research NEPTUNE`_ program.\n\n.. image:: https://github.com/accurrently/evnrg/raw/master/images/ITS-logo.jpg\n\n.. image:: https://github.com/accurrently/evnrg/raw/master/images/ONR-logo.png\n\n.. image:: https://github.com/accurrently/evnrg/raw/master/images/PHEV-logo.png\n\nThis package's skeleton was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.\n\n.. _Cookiecutter: https://github.com/audreyr/cookiecutter\n.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage\n.. _`Energy Graduate Group`: https://energy.ucdavis.edu/education/energy-graduate-group/\n.. _`Plug-in Hybrid and Electric Vehicle Research Center`: https://phev.ucdavis.edu\n.. _`Institute of Transportation Studies (ITS)`: https://its.ucdavis.edu\n.. _`Office of Naval Research NEPTUNE`: https://www.onr.navy.mil/en/Science-Technology/Departments/Code-33/All-Programs/333-sea-platforms-weapons/Neptune\n.. _`openei-rates`: https://github.com/accurrently/openei-rates\n\n\n=======\nHistory\n=======\n\n0.1.0 (2019-03-21)\n------------------\n\n* Re-committed base package to GitHub.\n\n\n",
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