tell

tell: a Python package to model future total electricity loads in the United States - Published in JOSS (2022)

https://github.com/immm-sfa/tell

Science Score: 98.0%

This score indicates how likely this project is to be science-related based on various indicators:

○
CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
✓
DOI references
Found 1 DOI reference(s) in JOSS metadata
✓
Academic publication links
Links to: zenodo.org
✓
Committers with academic emails
4 of 10 committers (40.0%) from academic institutions
✓
Institutional organization owner
Organization immm-sfa has institutional domain (im3.pnnl.gov)
✓
JOSS paper metadata
Published in Journal of Open Source Software

Scientific Fields

Political Science Social Sciences - 90% confidence

Mathematics Computer Science - 84% confidence

Artificial Intelligence and Machine Learning Computer Science - 83% confidence

Last synced: 4 months ago · JSON representation

Repository

A model to predict Total ELectricity Loads (TELL)

Basic Info

Host: GitHub
Owner: IMMM-SFA
License: bsd-2-clause
Language: Python
Default Branch: main
Homepage: https://immm-sfa.github.io/tell/
Size: 202 MB

Statistics

Stars: 27
Watchers: 6
Forks: 11
Open Issues: 4
Releases: 10

Created about 5 years ago · Last pushed 6 months ago

Metadata Files

Readme Contributing License

tell

`tell` is an open-source Python package to model future hourly total electricity loads.

Purpose

tell was created to:

Project the short- and long-term evolution of hourly electricity demand in response to changes in weather and climate.
Work at a spatial resolution adequate for input to a unit commitment/economic dispatch (UC/ED) model.
Maintain consistency with the long-term growth and evolution of annual state-level electricity demand projected by an economically driven human-Earth system model.

Install `tell`

tell is available via GitHub repository by using the pip install functionality. tell requires a Python version between 3.8 and 4.0 as well as a pip install to import the package. tell has been tested on Windows and Mac platforms. (Note: For those installing on Windows, tell is supported by GeoPandas functionality. Please see suggestions for installing GeoPandas on Windows here:
https://geopandas.org/en/stable/getting_started/install.html)

bash pip install tell

Check out a quickstarter tutorial to run `tell`

Run tell using the quickstarter tutorial: Quickstarter.

Getting started

New to tell? Get familiar with what tell is all about in our Getting Started documentation.

User guide

Our User Guide provides in-depth information on the key concepts of tell and how the model works.

Contributing to `tell`

Whether you find a typo in the documentation, find a bug, or want to develop functionality that you think will make tell more robust, you are welcome to contribute. Please see our Contribution Guidelines for more details.

API reference

The API Reference contains a detailed description of the tell API. The reference describes how the methods work and which parameters can be used. It assumes that you have an understanding of the key concepts.

Contact/Help

Need help with tell or have a comment? Please open a new Issue with your question/comments.

Owner

Name: Integrated Multisector Multiscale Modeling
Login: IMMM-SFA
Kind: organization
Location: Richland, WA

Website: https://im3.pnnl.gov/
Repositories: 45
Profile: https://github.com/IMMM-SFA

Models and code from the IM3 SFA

JOSS Publication

tell: a Python package to model future total electricity loads in the United States

Published

November 11, 2022

DOI

10.21105/joss.04472

Volume 7, Issue 79, Page 4472