Optimal transmission switching and grid reconfiguration for transmission systems via convex relaxations

TL;DR

This paper develops convex relaxation methods to optimize transmission switching in power grids, aiming to enhance efficiency and adaptability in the face of renewable energy variability and demand fluctuations.

Contribution

It introduces novel convex relaxation formulations for optimal transmission switching, enabling more efficient and practical solutions for grid reconfiguration.

Findings

Convex relaxations improve computational efficiency.

Reconfiguration can reduce operational costs.

Method demonstrated on small test networks.

Abstract

In this paper, we formulate optimization problems to perform optimal transmission switching (OTS) in order to operate power transmission grids most efficiently. In any given electrical network, several of the transmission lines are generally equipped with switches, circuit breakers, and/or reclosers. The conventional practice is to operate the grid using a static or fixed configuration. However, it may be beneficial to dynamically reconfigure the grid through switching actions in order to respond to real-time demand and supply conditions. This has the potential to help reduce costs and improve efficiency. Furthermore, such OTS may be more crucial in future power grids with much higher penetrations of renewable energy sources, which introduce more variability and intermittency in generation. Similarly, OTS can potentially help mitigate the effects of unpredictable demand fluctuations (e.g. due to extreme weather). We explored and compared several different formulations for the OTS problems in terms of computational performance and optimality. I also applied them to small transmission test case networks as a proof of concept to see what the effects of applying OTS are.