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

The main purpose of the package is providing an extensible, simple-to-use generation and transmission capacity extension model that allows to address 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.

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

This package is developed by Elias Kuepper @YoungFaithful and Holger Teichgraeber @holgerteichgraeber.

This package runs under julia v1.0 and higher. It depends on:

• 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

using Pkg
Pkg.add("CapacityExpansion")

A solver is required to run an optimization as explained in section Solver. Install e.g.:

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)