The repo implements the dynamic marginal emissions rates calculations derived in:
Lucas Fuentes Valenzuela, Anthony Degleris, Abbas El Gamal, Marco Pavone, Ram Rajagopal.
Dynamic locational marginal emissions via implicit differentiation.
IEEE Transactions on Power Systems. 2023 Feb 22.
The package solves standard dynamic economic dispatch problems used to dispatch electricity systems. It supports a full electricity network model with linearized (DC) power flow constraints, as well as batteries and ramping constraints.
After computing the optimal dispatch, the package can compute the derivative of total emissions with respect to changes in electricity demand at a given node and time, known as the (dynamic) locational marginal emissions rate (LME). The LMEs are dynamic ⚡ because they not only calculate how changes in demand will affect emissions at the current moment, but also how they will affect emissions at other points in time.
First install Julia. Clone this repo by running
git clone https://github.com/degleris1/DynamicMarginalEmissions.jl.git
Finally, navigate to DynamicMarginalEmissions.jl, launch julia, and run
] add .
See notebooks/demo.jl for the basic functionality of the repo.
All results generated for our article are in experiments/rodm
and experiments/wecc240.
If you use our work in you research, please cite the following reference.
@article{valenzuela2023dynamic,
title={Dynamic locational marginal emissions via implicit differentiation},
author={Fuentes Valenzuela, Lucas and Degleris, Anthony and El Gamal, Abbas and Pavone, Marco and Rajagopal, Ram},
journal={IEEE Transactions on Power Systems},
year={2023},
publisher={IEEE}
}
- Remove unused exports
- Add advanced functionality