OpenDC EEMM
OpenDC Extension for Energy Modelling & Management
- Document: https://opendc-eemm.rtfd.io
- Parent repo: https://github.com/atlarge-research/opendc
First, you need to download market data in CSV format from the following offical websites:
Note that data from ENTSO-E is in CET, whilst data from TenT is in GMT. Please make sure that all market data you selected are of the same period. The ./example/market/
directory contains two such sample datasets.
Next, to run the example, you also need the simulation results produced by the OpenDC datacenter simulator. A sample parque file can be found here.
Please follow the instructions presented here.
usage: opendc-eemm [-v] [-h] -t path [--pue float] {trace,market,decision} ...
CLI of OpenDC Extension for Energy Modelling & Managament.
optional arguments:
-v, --version Show version number of the package and exit.
-h, --help Show the help messages and exit.
-t path, --trace path
Path to simulation results (expecting a Parque file).
--pue float PUE value of the simulatied datacenter.
subcommands:
Available commands.
{trace,market,decision}
trace Visualize simulation results.
market Compare costs in different markets.
decision Optimize fine-grained decision-making.
usage: opendc-eemm trace [-h] -s ['power', 'oc'] [-f float] [-g value]
optional arguments:
-s ['power', 'oc'], --show ['power', 'oc']
Choose 'power' to show power draw; choose 'oc' to show over-commissioned.
-f float, --frequency float
Frequency of simulated machines.
-g value, --governor value
Governor to visualize.
usage: opendc-eemm market [-h] -s ['load', 'strategy'] -o float -d path -i path
optional arguments:
-s ['load', 'strategy'], --show ['load', 'strategy']
-o float, --od_price float
On-demand energy price.
-d path, --dayahead_prices path
Path to day-ahead energy prices (expecting a CSV file).
-i path, --imbalance_prices path
Path to imbalance energy prices (expecting a CSV file).
usage: opendc-eemm decision [-h] -o ['score', 'schedule'] [-f float] -d path -i path -p path -a ['first', 'last', 'mean'] [-s path]
optional arguments:
-o ['score', 'schedule'], --option ['score', 'schedule']
Choose 'score' to compute the agreement accuracy (AA) sore of the predictions; choose 'schedule' for DVFS
scheduling.
-f float, --factor float
Damping factor of the DVFS scheduler.
-d path, --dayahead_prices path
Path to day-ahead energy prices (expecting a CSV file).
-i path, --imbalance_prices path
Path to imbalance energy prices (expecting a CSV file).
-p path, --predictions path
Machine learning predictions (expecting a CSV file).
-a ['first', 'last', 'mean'], --aggregate ['first', 'last', 'mean']
Aggregation method for machine learning predictions.
-s path, --save_to path
Destination path of the DVFS schedule.