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Distributed Energy Resources Integrated Virtual Environment (DERIVE)

Digital-Twin Simulation Solution for Integrated Energy Systems


General

Integrated energy systems (IES) describe a holistic approach to finding coordinated energy and economic solutions. IES have the potential to mitigate inequities which can arise from grid, space, or economic limitations. The Distributed Energy Resources Integrated Virtual Environment (DERIVE) package introduces a simulation environment to model IES and provides a parametric analysis of battery sizes through an optimal control strategy to assess the potential of IES.

Getting Started

The following link permits users to clone the source directory containing the DERIVE package and then locally install with the pip install . command.

Examples

To illustrate the DERIVE functionality, example Jupyter notebooks can be found here.

Example 1 shows a comparison between local and integrated control of resources.

Copyright Notice

Distributed Energy Resources Integrated Virtual Environment (DERIVE) Copyright (c) 2023, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

If you have questions about your rights to use or distribute this software, please contact Berkeley Lab's Intellectual Property Office at IPO@lbl.gov.

NOTICE. This Software was developed under funding from the U.S. Department of Energy and the U.S. Government consequently retains certain rights. As such, the U.S. Government has been granted for itself and others acting on its behalf a paid-up, nonexclusive, irrevocable, worldwide license in the Software to reproduce, distribute copies to the public, prepare derivative works, and perform publicly and display publicly, and to permit other to do so.

Cite

To cite the DERIVE package, please use:

@article{gehbauer2022optimal,
  title={Optimal Sizing of Integrated Community Energy Systems Considering Equity Constraints},
  author={Gehbauer, Christoph and Wu, Yulun and Brown, James and Sohn, Michael},
  year={2022},
  journal={2022 Building Performance Analysis Conference and SimBuild},
  doi={https://doi.org/10.26868/25746308.2022.C025}
}