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:
- Providing a simple process to integrate (clustered) time-series input data, geographical input data, cost input data, and technology input data.
- Providing a model configuration, a modular model setup and model optimization.
- 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.
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 environmentCSV.jl- for handling of.csv-FilesDataFrames.jl- for handling of tablesStatsBase.jl- for handling of basicJLD2- for saving your result dataFileIO- for file accessingTimeSeriesClustering.jl- for time-series data
Install CapacityExpansion using the package mode:
]
add CapacityExpansionor 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 Clpor using the Pkg.add function:
using Pkg
Pkg.add("Clp")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)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.
- Documentation of the stable version
- Documentation of the development version
- Contributing guidelines
- CapacityExpansion: A capacity expansion modeling framework in Julia
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}
}
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent