# An Accelerated-Decomposition Approach for Security-Constrained Unit Commitment with Corrective Network Reconfiguration

arXiv: https://arxiv.org/abs/1912.01764 · HTML: https://mlsanity.com/paper/1912.01764/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Dec 2019.

## Built on by (most cited first, 5 of 5)

- [Feasibility Layer Aided Machine Learning Approach for Day-Ahead Operations](https://mlsanity.com/paper/2208.06742/) (2022)
- [Spatio-Temporal Deep Learning-Assisted Reduced Security-Constrained Unit Commitment](https://mlsanity.com/paper/2306.01570/) (2023)
- [Machine Learning Assisted Approach for Security-Constrained Unit Commitment](https://mlsanity.com/paper/2111.09824/) (2021)
- [Power grid operational risk assessment using graph neural network surrogates](https://mlsanity.com/paper/2311.12309/) (2023)
- [Solve Large-scale Unit Commitment Problems by Physics-informed Graph Learning](https://mlsanity.com/paper/2311.15216/) (2023)

## Abstract (arXiv)

Security-constrained unit commitment (SCUC) model is used for power system day-ahead scheduling. However, current SCUC model uses a static network to deliver power and meet demand optimally. A dynamic network can provide a lower optimal cost and alleviate network congestion. However, due to the computational complexity and the lack of effective algorithms, network reconfiguration has not been included in the SCUC model yet. This paper presents a novel approach to handle the computational complexity in security-constrained unit commitment (SCUC) with corrective network reconfiguration (CNR) while considering the scalability through accelerated-decomposition approach with fast screening non-critical sub-problems of SCUC-CNR. The proposed approach provides substantial computational benefits and is also applicable to SCUC. Simulation results on the IEEE 24-bus system show that the proposed methods are substantially faster without the loss in solution quality while the scalability benefits are demonstrated using larger cases: the IEEE 73-bus system, IEEE 118-bus system and Polish system.