SI-1 Methods - Full calculation
This documentation file was generated on 2020-10-13 by Kyle Proctor
Title of Dataset Agrivoltaics align with Green New Deal goals while supporting investment in the US’ rural economy SI-1 Methods
Name:Kyle W. Proctor Institution:Oregon State University College, School or Department: Biological and Ecological Engineering Address: 116 Gilmore Hall, 124 SW 26th St,Corvallis, OR, United States Email:email@example.com ORCID:0000-0002-4900-6564 Role:Data curation, Formal analysis, Software, Writing
Name:Ganti S. Murthy Institution: Indian Institute of Technology- Indore College, School or Department: Discipline of Biosciences and Biomedical Engineering Address: Khandwa Road, Simrol, Indore, Madhya Pradesh 453552, India Email: Ganti.Murthy@oregonstate.edu ORCID: 0000-0003-2774-9559 Role:Funding acquisition, Supervision, Writing- review and editing
Name:Chad W. Higgins Institution:Oregon State University College, School or Department: Biological and Ecological Engineering Address: 116 Gilmore Hall, 124 SW 26th St, Email:firstname.lastname@example.org ORCID: NA Role:Conceptualization, Funding acquisition, Supervision, Writing- review and editing
- Contact Information
Abstract for the dataset This Jupyter Notebook is intended to accompany the publication "Agrivoltaics align with Green New Deal goals while supporting investment in the US’ rural economy".This reduced-order economic analysis estimates the total construction, operation, and energy storage costs of wide scale implementation of Agrivoltaic Systems in the United States. Additionally, estimates are made for potential job creation, emissions reduction, and total required land area of these systems. The jupyter notebook contains the full calculation used for the publication, allowing users to alter key assumptions and investigate the corresponding impact.
Date of data collection: This jupyter notebook does not utilize any original data. Citations for all data used can be found in the references section of the notebook.
Funding sources that supported the collection of the data: National Science Foundation (NSF) award NSF EAR 1740082 U.S. Department of Agriculture (USDA) award OREZ-FERN-852-E
Licenses/restrictions placed on the data: This work is licensed under a Creative Commons Attribution 4.0 International License
Links to publications related to the dataset:
Proctor, K.W., Murthy, G.S., Higgins, C.W.Agrivoltaics align with Green New Deal goals while supporting investment in the US’ rural economy. Proceedings of the National Academy of Sciences of the United States Brief reports (Currently in review)
Links to other publicly accessible locations of the data: Web accesible version of notebook: https://mybinder.org/v2/gh/proctork/Reduced-Order-Agrivoltaic-Cost-Estimate/master
Recommended citation for the data: Proctor, K.W., Murthy, G.S., Higgins, C.W. (2020) Agrivoltaics align with Green New Deal goals while supporting investment in the US’ rural economy S1- Methods.Oregon State University.
Dataset Digital Object Identifier (DOI) https://doi.org/10.7267/mc87px76j
Limitations to reuse The only limitations on reuse of this content would stem from software issues, see section below on requirments to run the jupyter notebook.
VERSIONING AND PROVENANCE
- Last modification date 2020-10-02
DATA & FILE OVERVIEW
File List A. Filename:SI-1 Methods.ipynb
Short description: see abstract
B. Filename: SI-1 Methods.pdf
Short description: PDF version of jupyter notebook
.ipynb (https://fileinfo.com/extension/ipynb) .pdf
- Installation This notebook requires a python distribution. The code was developed using the anaconda distribution which can be downloaded here: https://www.anaconda.com/products/individual
The notebook was tested using the following software versions: Anaconda 4.8.4 CPython 3.7.1 IPython 7.2.0 jupyter notebook 5.7.4
The notebook requires a set of libraries but all libraries will be installed by running the code, without the user needing to do anything else.
Required libraries include: -pandas (0.23.4) -numpy (1.15.4) -ipywidgets (7.4.2) -matplotlib (3.0.2)
- Usage This code looks at a situation where utility scale Agrivoltaics are used to meet 20% of US electricity generation and estimates the following: -Total Array costs -Costs for Lithium Ion battery storage -Area required -Returns from selling energy -CO2 emission reduction -Jobs created