https://github.com/fneum/benchmark-teplopf

Code to reproduce benchmark of paper "Transmission Expansion Planning Using Cycle Flows"
https://github.com/fneum/benchmark-teplopf

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Code to reproduce benchmark of paper "Transmission Expansion Planning Using Cycle Flows"

• Host: GitHub
• URL: https://github.com/fneum/benchmark-teplopf
• Owner: fneum
• License: gpl-3.0
• Created: 2020-04-20T07:31:01.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2021-01-14T20:32:05.000Z (over 5 years ago)
• Last Synced: 2025-03-17T07:17:41.171Z (about 1 year ago)
• Language: Jupyter Notebook
• Size: 670 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# Benchmark of PyPSA Transmission Expansion Planning (TEP)

This repository contains the snakemake workflow to reproduce the benchmarks from the paper

**Fabian Neumann and Tom Brown. 2020. Transmission Expansion Planning Using Cycle Flows. In Proceedings of the Eleventh ACM International Conference on Future Energy Systems (e-Energy ’20).**

> The common linear optimal power flow (LOPF) formulation that underlies most

transmission expansion planning (TEP) formulations uses bus voltage angles as

auxiliary optimization variables to describe Kirchhoff's voltage law. As well

as introducing a large number of auxiliary variables, the angle-based

formulation has the disadvantage that it is not well-suited to considering the

connection of multiple disconnected networks, It is, however, possible to

circumvent these auxiliary variables and reduce the required number of

constraints by expressing Kirchhoff's voltage law directly in terms of the

power flows, based on a cycle decomposition of the network graph. In

computationally challenging benchmarks such as generation capacity expansion

with multi-period LOPF, this equivalent reformulation was shown in previous

work to reduce solving times for LOPF problems by an order of magnitude.

Allowing line capacity to be co-optimized in a discrete TEP problem makes it a

non-convex mixed-integer problem. This paper develops a novel cycle-based

reformulation for the TEP problem with LOPF and compares it to the standard

angle-based formulation. The combinatorics of the connection of multiple

disconnected networks is formalized for both formulations, a topic which has

not received attention in the literature. The cycle-based formulation is shown

to conveniently accommodate synchronization options. Since both formulations

use the big-$M$ disjunctive relaxation, useful derivations for suitable big-$M$

values are provided. The competing formulations are benchmarked on a realistic

generation and transmission expansion model of the European transmission system

at varying spatial and temporal resolutions. The cycle-based formulation solves

up to 31 times faster for particular cases, while averaging at a speed-up of

factor 4.

For a benchmark of PyPSA Linear Optimal Power Flow (LOPF) formulations, see https://github.com/FRESNA/benchmark-lopf.

## Cite As

```

@inproceedings{NeumannTEP2020,

    author = {Neumann, Fabian and Brown, Tom},

    title = {Transmission Expansion Planning Using Cycle Flows},

    year = {2020},

    booktitle = {Proceedings of the Eleventh ACM International Conference on Future Energy Systems},

    series = {e-Energy ’20}

}

```