This is a simple wrapper over device_kit microgrid modelling tool, that simulates market / auction based price adjustment (or equivalently distributed gradient descent), to find an optimal resource allocation and corresponding prices. Currently only supports point bid agent strategy with an optional proximal penalty. Some convenience scripts to generate plots and gifs are included.
git clone https://github.com/sgpinkus/device_kit_market_simulations && cd device_kit_market_simulations
pip install -r requirements.txt
run.py runs device_kit "scenarios" which are model of day-ahead flexibility to do anything. Example:
./run.py device_kit/sample_scenarios/ev_charge_scenario.py -i50
This will create a directory in the CWD that stores the results. The results can be inspected with report.py.
This more complex scenario is a variation of the scenario presented in Li, Chen & Low 2011:
./run.py scenario/lcl/lcl_scenario.py --stepsize="1/(steps+10)" --maxiter=100 --tol="5e-3" -d my-run
./report.py my-run --movie -v0 -e5