Benchmark Dataset for the Paper "A Hybrid Optimization Method Combining Network Expansion Planning and Switching State Optimization"
A Hybrid Optimization Method Combining Network Expansion Planning and Switching State Optimization
Grid Planning Benchmark Dataset for the Paper "A Hybrid Optimization Method Combining Network Expansion Planning and Switching State Optimization"
- Clone the repository
- Install pandapower and PowerModels.jl (see 'Installation Instructions')
- Run the optimization, e.g., with
This repository contains these subfolders with the following data:
- "power_system_data" containing the power system benchmark cases included additional line and replacement measures
- "scaled_loadcases" contains the data to reproduce the mathematical programming results
Main script to run the hybrid optimization method
The script "run_greedy.py" runs the greedy heuristic combined with the PowerModels.jl optimization framework. An example call starting a combined optimization of switching measures and line measures for the 'brigande' test case is:
python run_greedy.py -grid 'brigande' -kind 'combo' -max_iterations 3 -res_dir './results'
See more options with:
python run_greedy.py -h
If you have trouble using the PowerModels.jl interface, you can just run the script without PowerModels.jl. This gives you a greedy optimization of switching and line measures. Try:
python run_greedy.py -pm ''
Additional script to run the PowerModels.jl Optimization
The repository also contains a script "run_powermodels.py" which runs the PowerModels.jl based results with the pandapower-python to PowerModels.jl-julia interface
The script has several command line options:
- model (str) - The PowerModels.jl power model e.g. "DCPPowerModel"
- solver (str) - The solver to use, e.g. "juniper", "gurobi"
- grid (str) - optional if you only want to calculate one grid, e.g. "brigande"
- kind (str) - the optimizations to run, e.g. "tnep,ots,repl". Can only be a part of these like "tnep,repl"
Example to run the model "DCPPowerModel" with "gurobi" as a solver for the grid "brigande" with the time series loadcases "ts" for the REPl "repl" problem:
python-jl run_powermodels.py --model="DCPPowerModel" --solver="gurobi" --grid="brigande" --kind="repl"
You need the following software to run the script:
- pandapower: https://github.com/e2nIEE/pandapower
- PowerModels.jl: https://github.com/lanl-ansi/PowerModels.jl/
- tqdm: https://github.com/tqdm/tqdm
The python-julia interface might require some additional installations. See the following link for details: https://pandapower.readthedocs.io/en/latest/opf/powermodels.html
- planning_benchmark_v1.zip (3.12 MB)
- planning_benchmark_v1_scripts.zip (11.56 kB)
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