Transmission Expansion Planning

This repo implements three different Transmission Expansion Planning (TEP) models in AMPL.

Model 1, TEP, a normal TEP model that is used as a Benchmark here.
Model 2, TEP w. SNO (“TEP-SNO-T1”), this TEP model optimizes the network topology for each season in the planning horizon. In this model, the status of new lines is NOT optimized. In other words, a new line, once it is constructed, is always considered to be in the network for all subsequent seasons.
Model 3, TEP w. Enhanced SNO (“TEP-SNO-T2”), this TEP model optimizes the network topology for each season in the planning horizon. In this model, the status of new lines is also optimized. In other words, a new line can be disconnected from the network for the subsequent seasons after its construction.

Simulations:

The test case used here is a modified IEEE RTS-96 reliability test system (24-bus). The reference is: “The IEEE Reliability Test System-1996. A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee” and link is here.
For simulation results provided here were obtained with the following computer: Intel Xeon W-2195 2.3GHz, 4.3GHz Turbo, 18C, 24.75M Cache, HT, (140W) DDR4-2666; 128GB (8x16GB) DDR4 2666MHz RDIMM ECC; M.2 512GB PCIe NVMe Class 40 Solid State Drive.
Though only tested on this single system here, these codes can work on any other systems.

The following paper provides more details about these three models:

Xingpeng Li and Qianxue Xia, “Power System Expansion Planning with Seasonal Network Optimization,” Innovative Smart Grid Technologies (ISGT), Washington D.C., USA, Feb. 2020. (DOI: 10.1109/ISGT45199.2020.9087743)

Citation:

If you use these codes for your work, please cite the following paper:

Xingpeng Li and Qianxue Xia, “Power System Expansion Planning with Seasonal Network Optimization,” Innovative Smart Grid Technologies (ISGT), Washington D.C., USA, Feb. 2020.

Contact:

Dr. Xingpeng Li

University of Houston

Email: xli83@central.uh.edu

Website: https://rpglab.github.io/

License:

This work is licensed under the terms of the Creative Commons Attribution 4.0 (CC BY 4.0) license.

Disclaimer:

The author doesn’t make any warranty for the accuracy, completeness, or usefulness of any information disclosed; and the author assumes no liability or responsibility for any errors or omissions for the information (data/code/results etc) disclosed.