Merge pull request #260 from NatLabRockies/km/docs-nlr

Update github links to github.com/NatLabRockies

Author: kennedy-mindermann

.github/workflows/build-docs-external.yml

@@ -40,7 +40,7 @@ jobs:
 
       - name: Set variables for public github repo
         run: |
-          echo "BASE_URL=https://github.com/NREL/ReEDS-2.0" >> $GITHUB_ENV
+          echo "BASE_URL=https://github.com/NatLabRockies/ReEDS-2.0" >> $GITHUB_ENV
           cd ${GITHUB_WORKSPACE}/docs/source/documentation_tools/
           sh generate_sources_md_file.sh
           cd ${GITHUB_WORKSPACE}

.pylintrc

@@ -1,4 +1,4 @@
-# This file was created based on https://github.com/NREL/reVXOrdinances/blob/main/.pylintrc,
+# This file was created based on https://github.com/NatLabRockies/reVXOrdinances/blob/main/.pylintrc,
 # and then modified for the use with ReEDS-2.0
 [MAIN]
 

README.md

@@ -3,19 +3,19 @@
 
 
 [![CI](https://github.nrel.gov/ReEDS/ReEDS-2.0/actions/workflows/python-app.yaml/badge.svg)](https://github.nrel.gov/ReEDS/ReEDS-2.0/actions/workflows/python-app.yaml)
-[![Documentation](https://img.shields.io/badge/Documentation-view%20online-0a7f5e?logo=readthedocs&logoColor=white&labelColor=555)](https://nrel.github.io/ReEDS-2.0)
+[![Documentation](https://img.shields.io/badge/Documentation-view%20online-0a7f5e?logo=readthedocs&logoColor=white&labelColor=555)](https://natlabrockies.github.io/ReEDS-2.0)
 ![Static Badge](https://img.shields.io/badge/python-3.11-blue)
-![GitHub License](https://img.shields.io/github/license/NREL/ReEDS-2.0)
+![GitHub License](https://img.shields.io/github/license/natlabrockies/ReEDS-2.0)
 [![DOI](https://zenodo.org/badge/189060033.svg)](https://doi.org/10.5281/zenodo.16943302)
 
 </br>
 </br>
 
 This GitHub repository contains the source code for NLR's ReEDS model.
 The ReEDS model source code is available at no cost from the National Laboratory of the Rockies.
-The ReEDS model can be downloaded or cloned from [https://github.com/NREL/ReEDS-2.0](https://github.com/NREL/ReEDS-2.0).
+The ReEDS model can be downloaded or cloned from [https://github.com/NatLabRockies/ReEDS-2.0](https://github.com/NatLabRockies/ReEDS-2.0).
 
-**For more information about the model, see the [open source ReEDS-2.0 Documentation](https://nrel.github.io/ReEDS-2.0).**
+**For more information about the model, see the [open source ReEDS-2.0 Documentation](https://NatLabRockies.github.io/ReEDS-2.0).**
 
 ReEDS training videos are available on the [NLR Learning YouTube channel](https://youtube.com/playlist?list=PLmIn8Hncs7bG558qNlmz2QbKhsv7QCKiC&si=NgGBaL_MxNcYiIEX).
 
@@ -27,7 +27,7 @@ ReEDS training videos are available on the [NLR Learning YouTube channel](https:
 
 [ReEDS](https://www.nrel.gov/analysis/reeds/) is a capacity planning and dispatch model for the U.S. electricity system.
 
-As NLR's flagship long-term power sector model, ReEDS has served as the primary analytic tool for [many studies](https://nrel.github.io/ReEDS-2.0/publications.html) of electricity sector research questions.
+As NLR's flagship long-term power sector model, ReEDS has served as the primary analytic tool for [many studies](https://natlabrockies.github.io/ReEDS-2.0/publications.html) of electricity sector research questions.
 Example model results are available in the [Scenario Viewer](https://scenarioviewer.nrel.gov/).
 
 
@@ -50,7 +50,7 @@ A step-by-step guide for getting started with ReEDS is available [here](https://
         2. Other commercial solvers have also been succussfully applied to ReEDS, but setup details and some solver tuning are specific to the CPLEX solver.
 3. Install Julia: <https://julialang.org/downloads/>
 4. Open a command-line interface and set up your environments:
-    1. Clone the ReEDS repository: `git clone git@github.com:NREL/ReEDS-2.0.git` or `git clone https://github.com/NREL/ReEDS-2.0.git`
+    1. Clone the ReEDS repository: `git clone git@github.com:NatLabRockies/ReEDS-2.0.git` or `git clone https://github.com/NatLabRockies/ReEDS-2.0.git`
     2. Navigate to the cloned repository
     3. Create the `reeds2` [conda environment](https://docs.conda.io/projects/conda/en/stable/user-guide/tasks/manage-environments.html): `conda env create -f environment.yml`
         1. Linux and Mac users can use the environment.yml directly. Windows users need to comment out the `- julia=1.8` line from the environment.yml file before creating the enviroment and use the version of Julia installed above.
@@ -67,4 +67,4 @@ A step-by-step guide for getting started with ReEDS is available [here](https://
 
 ## Contact Us
 
-If you have comments and/or questions, you can contact the ReEDS team at [ReEDS.Inquiries@nrel.gov](mailto:ReEDS.Inquiries@nrel.gov) or post a question on the [discussion pages](https://github.com/NREL/ReEDS-2.0/discussions).
+If you have comments and/or questions, you can contact the ReEDS team at [ReEDS.Inquiries@nrel.gov](mailto:ReEDS.Inquiries@nrel.gov) or post a question on the [discussion pages](https://github.com/NatLabRockies/ReEDS-2.0/discussions).

docs/source/model_documentation.md

@@ -9,7 +9,7 @@ We are especially grateful to Walter Short who first envisioned and developed th
 Finally, we are grateful to all those who helped sponsor ReEDS model development and analysis, particularly supporters from the U.S. Department of Energy (DOE) but also others who have funded our work over the years.
 
 ```{admonition} Suggested Citation
-National Laboratory of the Rockies. ({{ cite_date_last_updated }}). *Model documentation — ReEDS 2.0*. https://nrel.github.io/ReEDS-2.0/model_documentation.html
+National Laboratory of the Rockies. ({{ cite_date_last_updated }}). *Model documentation — ReEDS 2.0*. https://natlabrockies.github.io/ReEDS-2.0/model_documentation.html
 
 ```
 
@@ -157,7 +157,7 @@ This documentation describes the structure and key data elements of the [Regiona
 In this introduction, we provide a high-level overview of ReEDS objectives, capabilities, and applications.
 We also provide a short discussion of important caveats that apply to any ReEDS analysis.
 
-The ReEDS model code and input data can be accessed at <https://github.com/NREL/ReEDS-2.0>.
+The ReEDS model code and input data can be accessed at <https://github.com/NatLabRockies/ReEDS-2.0>.
 
 
 ### Overview
@@ -216,7 +216,7 @@ This means that ReEDS investments are not guaranteed to be aligned with cost inp
 
 - **Resolution:** Although ReEDS has high spatial, temporal, and process resolution for models of its class and scope, it cannot generally represent individual units and transmission lines, and it does not have the temporal resolution to characterize detailed operating behaviors, such as ramp rates and minimum plant runtime.
 By default, operations are modeled for a selection of representative and outlying periods (days or weeks), rather than full years, to achieve a tractable model size.
-The linkage with [PRAS](https://github.com/NREL/PRAS), which includes chronological hourly modeling for multiple years, helps ensure the ReEDS electricity system portfolios meet specified resource adequacy levels.
+The linkage with [PRAS](https://github.com/NatLabRockies/PRAS), which includes chronological hourly modeling for multiple years, helps ensure the ReEDS electricity system portfolios meet specified resource adequacy levels.
 
 - **Foresight and behavior:** ReEDS solve years are evaluated sequentially and myopically.
 The model has limited foresight and its decision making does not account for anticipated changes to markets and policies.
@@ -269,7 +269,7 @@ ReEDS is run sequentially for a series of modeled years, typically through 2050.
 The increments between solve years are user defined, but most studies use 2-year, 3-year, or 5-year increments.
 Increments can also vary between different solve years; e.g., annual increments can be used in the near term followed by multiyear increments in the latter years.
 {numref}`figure-reeds-pras` illustrates the model's sequential structure.
-For a given solve year *t*, ReEDS iterates with the [PRAS](https://github.com/NREL/PRAS) model to dynamically update stress periods and check for reliability (see more in the [Resource Adequacy](#resource-adequacy) section).
+For a given solve year *t*, ReEDS iterates with the [PRAS](https://github.com/NatLabRockies/PRAS) model to dynamically update stress periods and check for reliability (see more in the [Resource Adequacy](#resource-adequacy) section).
 Once the system design is found to be resource adequate, ReEDS advances to the next model solve year ($t + \Delta t$).
 
 ```{figure} figs/docs/reeds-pras.png
@@ -1962,7 +1962,7 @@ Existing HVDC and B2B connection capacities are taken from project websites and
 #### New transmission capacity
 
 The cost of new interzonal transmission capacity between each pair of model zones is calculated in the reV model using the base costs shown in {numref}`figure-transmission-cost-input-data`.
-For each pair of zones, a [least-cost path](https://github.com/NREL/reVX/tree/main/reVX/least_cost_xmission) between the two zone "centers" (the same "centers" described in the [Network reinforcement](#network-reinforcement) section) is determined.
+For each pair of zones, a [least-cost path](https://github.com/NatLabRockies/reVX/tree/main/reVX/least_cost_xmission) between the two zone "centers" (the same "centers" described in the [Network reinforcement](#network-reinforcement) section) is determined.
 (Example paths from Maine to each of the other ReEDS zones are shown in {numref}`figure-lcp-p134`.)
 The integrated \$/mile cost along the least-cost path determines the \$/MW cost for expanding the interface capacity between the linked zones;
 the length of the least-cost path determines the distance (used in the calculation of transmission losses within the model,
@@ -3403,7 +3403,7 @@ section of the <a href="user_guide.html">User Guide</a>.
 
 The ReEDS reduced-form dispatch aims to represent enough operational detail for realistic capacity expansion decisions,
 but the model cannot explicitly represent detailed power system operations.
-To enable more detailed study of system operations, NLR has developed a translation framework [R2X](https://github.com/NREL/R2X) to implement a ReEDS capacity
+To enable more detailed study of system operations, NLR has developed a translation framework [R2X](https://github.com/NatLabRockies/R2X) to implement a ReEDS capacity
 expansion solution for any solve year in production cost models (PCMs).
 R2X supports translations to two PCMs: Sienna and PLEXOS.
 
@@ -3424,7 +3424,7 @@ To maintain consistency, the linkage preserves the spatial resolution of ReEDS (
 The PCM translation uses ReEDS transmission interface capacity, whereas reactance and resistance are derived from ReEDS transmission assumptions to represent the aggregated transmission system.
 For generating capacity, ReEDS aggregate capacity is converted to individual units in the PCM using characteristic unit sizes for each technology.
 Where possible and reasonable, ReEDS cost and performance parameters are used.
-If a parameter is missing or inconsistently used in ReEDS because of structural differences between the models, the default translation uses average values across the [WECC](https://github.com/NREL/R2X/blob/main/src/r2x/defaults/pcm_defaults.json) for the equivalent technologies in ReEDS.[^ref63]
+If a parameter is missing or inconsistently used in ReEDS because of structural differences between the models, the default translation uses average values across the [WECC](https://github.com/NatLabRockies/R2X/blob/main/src/r2x/defaults/pcm_defaults.json) for the equivalent technologies in ReEDS.[^ref63]
 
 [^ref63]: Minimum load is an example of one such parameter.
 The aggregate representation of minimum load in ReEDS at the technology-zone level does not effectively reflect unit-level operating constraints used in PLEXOS, so PLEXOS uses native assumptions for minimum load.

docs/source/postprocessing_tools.md

@@ -92,7 +92,7 @@ This script reruns a completed ReEDS case as a dispatch simulation at higher tim
 The operational constraints in `c_supplymodel.gms` are used directly, but the investment and capacity variables are fixed to their previously optimized values; only the operational variables are re-optimized.
 365 representative 1-day periods at 1-hour resolution are used by default, but these settings can be changed using the `-s/--switch_mods` switch.
 
-This approach is distinct from the [R2X](https://github.com/NREL/R2X) tool, which formats the results of a ReEDS case as inputs to a separate production cost modeling tool such as [Sienna](https://github.com/NREL-Sienna) or [PLEXOS](https://www.energyexemplar.com/plexos).
+This approach is distinct from the [R2X](https://github.com/NatLabRockies/R2X) tool, which formats the results of a ReEDS case as inputs to a separate production cost modeling tool such as [Sienna](https://github.com/NREL-Sienna) or [PLEXOS](https://www.energyexemplar.com/plexos).
 Those tools provide more advanced and realistic features like unit commitment and rolling forecast horizons;
 by contrast, `run_pcm.py` simply reuses the existing ReEDS formulation at higher time resolution,
 and is subject to all the normal caveats and limitations of ReEDS (linear variables, pipe-and-bubble transmission flow, etc.).

docs/source/references.bib

@@ -21633,7 +21633,7 @@ @misc{nrelReEDSModelDocumentation2025
   author = {{NREL}},
   year = 2025,
   month = nov,
-  url = {https://nrel.github.io/ReEDS-2.0/model_documentation.html}
+  url = {https://natlabrockies.github.io/ReEDS-2.0/model_documentation.html}
 }
 
 @misc{nrelRegionalEnergyDeployment2020,
@@ -28591,7 +28591,7 @@ @inproceedings{weissEmpiricalApproachCalculate2013
 
 @misc{WelcomeReEDSsDocumentation,
   title = {Welcome to {{ReEDS}}'s Documentation! --- {{ReEDS}} Documentation},
-  url = {https://nrel.github.io/ReEDS-2.0/index.html},
+  url = {https://natlabrockies.github.io/ReEDS-2.0/index.html},
   urldate = {2025-05-14}
 }
 

docs/source/setup.md

@@ -1,5 +1,5 @@
 # Getting Started 
-The ReEDS model source code is available at no cost from the National Laboratory of the Rockies (NLR). The ReEDS model can be downloaded or cloned from [https://github.com/NREL/ReEDS-2.0](https://github.com/NREL/ReEDS-2.0).
+The ReEDS model source code is available at no cost from the National Laboratory of the Rockies (NLR). The ReEDS model can be downloaded or cloned from [https://github.com/NatLabRockies/ReEDS-2.0](https://github.com/NatLabRockies/ReEDS-2.0).
 
 New users may also wish to start with some ReEDS training videos which are available on the [NLR YouTube channel](https://youtu.be/aGj3Jnspk9M?si=iqCRNn5MbGZc8ZIO).
 
@@ -153,7 +153,7 @@ Screenshot of a test of GAMS from the terminal window
 ```
 
 ### Repository Setup
-The ReEDS source code is hosted on GitHub: [https://github.com/NREL/ReEDS-2.0](https://github.com/NREL/ReEDS-2.0)
+The ReEDS source code is hosted on GitHub: [https://github.com/NatLabRockies/ReEDS-2.0](https://github.com/NatLabRockies/ReEDS-2.0)
 
 1. Install Git Large File Storage, instructions can be found here: [Installing Git Large File Storage](https://docs.github.com/en/repositories/working-with-files/managing-large-files/installing-git-large-file-storage)
 
@@ -199,7 +199,7 @@ If that doesn't resolve the issue, the following may help:
 6. Enter the julia package manager by pressing `]`, then run the following commands:
     * `add Random123`   
     * `registry add https://github.com/JuliaRegistries/General.git`
-    * `registry add https://github.com/NREL/JuliaRegistires.git`
+    * `registry add https://github.com/NatLabRockies/JuliaRegistries.git`
     * `instantiate`
 
 7. Leave the package manager by pressing backspace or Ctrl+C

docs/source/user_guide.md

@@ -87,7 +87,7 @@ These files are stored in `inputs/load/{switch_name}_load_hourly.h5`.
 
 | Switch Name    | Description of Profile | Origin | Weather year included |
 | ------------- | ------------- | ------------- | ------------- |
-| historic | Detrended historic demand from 2007-2013 and 2016-2023. This is multiplied by annual growth factors from AEO to forecast load growth. | Produced by the ReEDS team from a compilation of data sources. More detail can be found in the [hourlize readme](https://github.com/NREL/ReEDS-2.0/tree/main/hourlize/plexos_to_reeds#readme). | 2007-2013 & 2016-2023 |
+| historic | Detrended historic demand from 2007-2013 and 2016-2023. This is multiplied by annual growth factors from AEO to forecast load growth. | Produced by the ReEDS team from a compilation of data sources. More detail can be found in the [hourlize readme](https://github.com/NatLabRockies/ReEDS-2.0/tree/main/hourlize). | 2007-2013 & 2016-2023 |
 | Clean2035_LTS | Net-zero emissions, economy wide, by 2050 based on the White House's Long Term Strategy as shown here: <https://www.whitehouse.gov/wp-content/uploads/2021/10/US-Long-Term-Strategy.pdf> | Developed for the 100% Clean Electricity by 2035 study: <https://www.nrel.gov/docs/fy22osti/81644.pdf> |  2007-2013 |
 | Clean2035    | Accelerated Demand Electrification (ADE) profile. This profile was custom made for the 100% Clean Electricity by 2035 study. More information about how it was formed can be found in <https://www.nrel.gov/docs/fy22osti/81644.pdf> Appendix C. | Developed for the 100% Clean Electricity by 2035 study: <https://www.nrel.gov/docs/fy22osti/81644.pdf> |  2007-2013 |
 | Clean2035clip1pct | Same as Clean2035 but clips off the top 1% of load hours. | Developed for the 100% Clean Electricity by 2035 study: <https://www.nrel.gov/docs/fy22osti/81644.pdf> |  2007-2013 |

instantiate.jl

@@ -3,7 +3,7 @@ ENV["JULIA_PKG_SERVER_REGISTRY_PREFERENCE"] = "eager"
 import Pkg
 Pkg.Registry.update()
 Pkg.Registry.add("General")
-Pkg.Registry.add(Pkg.RegistrySpec(url="https://github.com/NREL/JuliaRegistry.git"))
+Pkg.Registry.add(Pkg.RegistrySpec(url="https://github.com/NatLabRockies/JuliaRegistry.git"))
 Pkg.instantiate()
 
 Pkg.add("Random123")

postprocessing/tableau/readme.md

@@ -11,7 +11,7 @@ Before running this script for the first time, you'll need to install the Tablea
 `pip install tableauhyperapi`
 
 
-Note that if you're pulling ReEDS-to-PLEXOS results into Tableau, you'll also need to have the [h5plexos](https://github.com/NREL/h5plexos) package installed.
+Note that if you're pulling ReEDS-to-PLEXOS results into Tableau, you'll also need to have the [h5plexos](https://github.com/NatLabRockies/h5plexos) package installed.
 
 ### Example call: