Repository containing supplementary data and code for the paper "Risk Trading in a Chance-Constrained Stochastic Electricity Market" by Robert Mieth, Matt Roveto and Yury Dvorkin. If you use this code or its for academic purposes please cite this paper.
Instructions:
The optimization model was implemented by using JuMP and auxiliary packages in the Julia programming language. Additionally, we used Mosek 8.1.0.63 in our numerical experiments. Mosek is a commercial solver which must be installed and licensed (e.g. using an academic license). The solver was chosen for its specific features for second-order conic programming. For more information on solvers, see the JuMP documentation.
The experiments require Julia 1.3. All necessary packages and their respective versions are distributed in the Project.toml file. The packages can be loaded in a new Julia environment directly via the Julia package manager IDE or running:
julia> import Pkg
julia> Pkg.activate(".")
julia> Pkg.instantiate()
Running the code:
An exemplary case study with all model formulations provided as a Jupyter Notebook risk_trading_case_study.ipynb.
To run the notebook install the IJulia package:
julia> Pkg.add("IJulia")
and then in your terminal:
jupyter notebook risk_trading_case_study.ipynb