CapacityExpansion is a julia implementation of an input-data-scaling capacity expansion modeling framework.

The primary purpose of the package is providing an extensible, simple-to-use generation and transmission capacity expansion model that allows addressing a diverse set of research questions in the area of energy systems planning. The secondary purposes are:

1. Providing a simple process to integrate (clustered) time-series input data, geographical input data, cost input data, and technology input data.
2. Providing a model configuration, a modular model setup and model optimization.
3. Providing an interface between the optimization result and further analysis.

Please refer to the documentation for details on how to use this software.

Model Information
Model class	Capacity Expansion Problem
Model type	Optimization, Linear optimization model input-data depending energy system
Carriers	Electricity, Hydrogen,...
Technologies	dispatchable and non-dispatchable Generation, Conversion, Storage (seasonal), Transmission
Decisions	investment and dispatch
Objective	Total system cost
Variables	Cost, Capacities, Generation, Storage, Lost-Load, Lost-Emissions

Input Data Depending	Provided Input Data
Regions	California, USA (single and multi-node) and Germany, Europe (single and multi-node)
Geographic Resolution	aggregated regions
Time resolution	hourly
Network coverage	transmission, DCOPF load flow

The package uses TimeSeriesClustering as a basis for its time-series aggregation.

Elias Kuepper @YoungFaithful and Holger Teichgraeber @holgerteichgraeber developed this package.

Installation

This package runs under julia v1.0 and higher. It depends on multiple packages, which are also listed in the Project.toml. The julia package manager automatically installs the packages:

• JuMP.jl - for the modeling environment
• CSV.jl - for handling of .csv-Files
• DataFrames.jl - for handling of tables
• StatsBase.jl - for handling of basic
• JLD2 - for saving your result data
• FileIO - for file accessing
• TimeSeriesClustering.jl - for time-series data

Install CapacityExpansion using the package mode:

]
add CapacityExpansion

or using the Pkg.add function:

using Pkg
Pkg.add("CapacityExpansion")

A solver is required to run an optimization, as explained in section Solver. Install e.g. Clp using the package mode:

]
add Clp

or using the Pkg.add function:

using Pkg
Pkg.add("Clp")

Example Workflow

using CapacityExpansion
using Clp
optimizer=Clp.Optimizer # select optimizer

## LOAD DATA ##
# laod ts-data
ts_input_data = load_timeseries_data_provided("GER_1"; T=24, years=[2016])
# load cep-data
cep_data = load_cep_data_provided("GER_1")

## OPTIMIZATION ##
# run a simple
run_opt(ts_input_data,cep_data,optimizer)

Testing

The model is being tested against a capacity expansion model presented in the paper On representation of temporal variability in electricity capacity planning models by Merrick 2016. The model additionally tests itself against previously calculated data to detect new errors.

Links

• Documentation of the stable version
• Documentation of the development version
• Contributing guidelines
• CapacityExpansion: A capacity expansion modeling framework in Julia

Citing CapacityExpansion

If you find CapacityExpansion usefuel in your work, we kindly request that you cite the following paper

@article{Kuepper2020,
  doi = {10.21105/joss.02034},
  url = {https://doi.org/10.21105/joss.02034},
  year = {2020},
  publisher = {The Open Journal},
  volume = {5},
  number = {52},
  pages = {2034},
  author = {Lucas Elias Kuepper and Holger Teichgraeber and Adam R. Brandt},
  title = {CapacityExpansion: A capacity expansion modeling framework in Julia},
  journal = {Journal of Open Source Software}
}