Metadata-Version: 2.1
Name: NREL-shift
Version: 0.1.0a0
Summary: Generate synthetic feeders using open street map data
Home-page: https://github.com/nrel/shift
Author: Kapil Duwadi
Author-email: kapil.duwadi@nrel.gov
Keywords: Synthetic feeder,Open steet data,OpenDSS
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3.7
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE.txt


Simple Synthetic Distribution Feeder Generation Tool (SHIFT)

<img src="docs/images/shift.svg" width="400" style="display:block;margin:auto;">


![GitHub all releases](https://img.shields.io/github/downloads/NREL/shift/total?logo=Github&logoColor=%2300ff00&style=flat-square)
![GitHub repo size](https://img.shields.io/github/repo-size/nrel/shift?style=flat-square)
![CodeFactor Grade](https://img.shields.io/codefactor/grade/github/nrel/shift?color=%23ff0000&logo=python&logoColor=%2300ff00&style=flat-square)
[![GitHub license](https://img.shields.io/github/license/NREL/shift?style=flat-square)](https://github.com/NREL/shift/blob/main/LICENSE.txt)
[![GitHub issues](https://img.shields.io/github/issues/NREL/shift?style=flat-square)](https://github.com/NREL/shift/issues)
![GitHub top language](https://img.shields.io/github/languages/top/nrel/shift?style=flat-square)
![Snyk Vulnerabilities for GitHub Repo](https://img.shields.io/snyk/vulnerabilities/github/nrel/shift?style=flat-square)

### :wave:  Welcome to SHIFT repository!

[Goto full documentation](https://nrel.github.io/shift/)

Getting free distribution feeder models for your reasearch has never been easier.
SHIFT helps you build synthetic distribution feeders models using just the OpenStreet data e.g. buildings and road network. You can configure lots of
parameters and design choices when building these models and even create multiple versions of them and choose the one that fits your needs. If you are utility no worries we 
have you covered as well. As a utility you can also integrate your data when building these models. 

Having distribution models in your hand can help you perform rich analysis in understanding impact of distributed energy resources 
such as roof top PV, energy storage (Tesla Wall, lead acid, lithium name ....), electric vehicle and more. Performing network upgrade analysis, hosting capacity 
analysis, interconnection studies all require detailed distribution models.

So what are you waiting for. We can't wait to see how you will use this tool for your as wells your organizations's benefit.

Feel free to reach out to us or send us a comment using Github issue. We don't mind if you smash that starred icon motivating our developers and contributors.
