Getting Started

Installation

Quick installation

1. Check requirements:

   • Python 3.7

   • Gurobi Optimizer

2. Clone or download repository.

3. In your Python environment, run:

   1. pip install -e path_to_repository

   2. pip install -e path_to_repository/cobmo

Recommended installation

The following installation procedure contains additional steps and requirements which can improve the numerical performance when running FLEDGE.

1. Check requirements:

   • Anaconda Distribution (Python 3.x version)

   • Gurobi Optimizer or CPLEX Optimizer

2. Clone or download repository.

3. In Anaconda Prompt, run:

   1. conda create -n fledge python=3.7

   2. conda activate fledge

   3. conda install pandas

   4. pip install -e path_to_repository.

   5. pip install -e path_to_repository/cobmo

4. In fledge/config.py, change solver_name to 'gurobi' or 'cplex'.

Alternative installation

If you are running into errors when installing or running FLEDGE, this may be due to incompatibility with new versions of package dependencies, which have yet to be discovered and fixed. As a workaround, try installing FLEDGE in an tested Anaconda environment via the the provided environment.yml, which represents the latest Anaconda Python environment in which FLEDGE was tested and is expected to work.

1. Check requirements:

   • Windows 10

   • Anaconda Distribution (Python 3.x version)

   • Gurobi Optimizer

2. Clone or download repository.

3. In Anaconda Prompt, run:

   1. conda env create -f path_to_fledge_repository/environment.yml

   2. conda activate fledge

   3. pip install -e path_to_repository.

   4. pip install -e path_to_repository/cobmo

Important

Please also create an issue on Github if you run into problems with the normal installation procedure.

Examples

The examples directory contains run scripts which demonstrate possible usages of FLEDGE. You may also check the test directory for a better understanding of the API.

Papers

The following papers have been prepared in relation to FLEDGE:

• [Preprint] Troitzsch, S., Grussmann, M., Zhang, K., & Hamacher, T., Distribution Locational Marginal Pricing for Combined Thermal and Electric Grid Operation, 2020. doi: 10.36227/techrxiv.11918712

  • FLEDGE v0.3.0 was used to preare the results for this paper.

  • The related script is examples/paper_2020_dlmp_combined_thermal_electric.py.

• Troitzsch, S., Hanif, S., Zhang, K., Trpovski, A., & Hamacher, T., Flexible Distribution Grid Demonstrator (FLEDGE): Requirements and Software Architecture, in IEEE PES General Meeting, Atlanta, GA, USA, 2019. doi: 10.1109/PESGM40551.2019.8973567.

  • The paper served as an outline for the software architecture of FLEDGE.

• D. Recalde, A. Trpovski, S. Troitzsch, K. Zhang, S. Hanif, and T. Hamacher, A Review of Operation Methods and Simulation Requirements for Future Smart Distribution Grids, in IEEE PES Innovative Smart Grid Technologies Conference Asia, Singapore, 2018. doi:10.1109/ISGT-Asia.2018.8467850.

  • The review paper initiated the development of FLEDGE.

The following papers served as the methodological basis for the implementation of FLEDGE as well as for the development of test cases:

• S. Hanif, K. Zhang, C. Hackl, M. Barati, H. B. Gooi, and T. Hamacher, Decomposition and Equilibrium Achieving Distribution Locational Marginal Prices using Trust-Region Method, IEEE Transactions on Smart Grid, 2018. doi:10.1109/TSG.2018.2822766.

• K. Zhang, S. Hanif, C. M. Hackl, and T. Hamacher, A Framework for Multi-Regional Real-Time Pricing in Distribution Grids, IEEE Transactions Smart Grid, vol. 10, no. 6, pp. 6826–6838, 2019. doi:10.1109/TSG.2019.2911996.

• A. Trpovski, D. Recalde, and T. Hamacher, Synthetic Distribution Grid Generation Using Power System Planning: Case Study of Singapore, in UPEC International Universities Power Engineering Conference, 2018. doi:10.1109/UPEC.2018.8542054.

Contributing

If you are keen to contribute to this project, please see Contributing.