reeds2pras

ReEDS2PRAS

Introduction

The purpose of ReEDS2PRAS is to translate a ReEDS system into a PRAS system ready for probabilistic resource adequacy analysis.

Installation

1. Install Julia. There are different procedures for mac/linux and windows.
   1. [mac/linux]: Julia is included in the conda environment so you should be all set.
   2. [windows]: Install Julia from https://julialang.org/downloads/.
2. From the ReEDS-2.0 directory, run julia --project=. instantiate.jl

Basic Usage

If you have a completed ReEDS run and a REPL with ReEDS2PRAS (using ReEDS2PRAS after running add ReEDS2PRAS in the julia package manager), an example of running ReEDS2PRAS is provided below

using ReEDS2PRAS

reedscase = "/projects/ntps/llavin/ReEDS-2.0/runs/ntpsrerun_Xlim_DemHi_90by2035EarlyPhaseout__core" # path to completed ReEDS run
solve_year = 2035 #need ReEDS Augur data for the input solve year
weather_year = 2012 # must be 2007-2013 or 2016-2023
timesteps = 8760
user_descriptors = "your_user_descriptors_json_location_here" # Optional - if not passed uses default values

# returns a parameterized PRAS system
pras_system = ReEDS2PRAS.reeds_to_pras(reedscase, solve_year, timesteps, weather_year, user_descriptors = user_descriptors)

This will save out a pras system to the variable pras_system from the ReEDS2PRAS run. The user can also save a PRAS system to a specific location using PRAS.savemodel(pras_system, joinpath("MYPATH"*".pras"). The saved PRAS system may then be read in by other tools like PRAS Analytics (https://github.nrel.gov/PRAS/PRAS-Analytics) for further analysis, post-processing, and plotting.

Multi-year usage

ReEDS2PRAS can be run for multiple weather years of a completed ReEDS run by passing more than 8760 hourly timestamps. For example running all 7 weather years can be accomplished as in the below example

using ReEDS2PRAS

# path to completed ReEDS run
reedscase = "/projects/ntps/llavin/ReEDS-2.0/runs/ntpsrerun_Xlim_DemHi_90by2035EarlyPhaseout__core"
solve_year = 2035 #need ReEDS Augur data for the input solve year
weather_year = 2007 # must be 2007-2013 or 2016-2023
timesteps = 61320
user_descriptors = "your_user_descriptors_json_location_here" # Optional - if not passed uses default values

# returns a parameterized PRAS system
pras_system = ReEDS2PRAS.reeds_to_pras(reedscase, solve_year, timesteps, weather_year, user_descriptors = user_descriptors)

Importantly, the timesteps count from the first hour of the first weather_year, so the user must input 2007 as the weather_year to run all 61320 hourly timesteps.

This can also be run through the command line:

julia --project=. bin/run.jl <reedscase> <solve_year> <timesteps> <weather_year> <output_filepath>

The output_filepath specifies the location to save the pras model.

Contributing Guidelines

It is always a good practice to follow the Julia Style Guide (https://docs.julialang.org/en/v1/manual/style-guide/). Please make sure you format your code to follow our guidelines using the snippet below before you open a PR:

julia  -e 'using Pkg; Pkg.add("JuliaFormatter"); using JuliaFormatter; include(".github/workflows/formatter-code.jl")'

**NOTE: You have to run the snippet above at the repo folder level.