# Leveraging power grid topology in machine learning assisted optimal power flow

@article{Falconer2021LeveragingPG, title={Leveraging power grid topology in machine learning assisted optimal power flow}, author={Thomas Falconer and Letif Mones}, journal={ArXiv}, year={2021}, volume={abs/2110.00306} }

—Machine learning assisted optimal power ﬂow (OPF) aims to reduce the computational complexity of these non-linear and non-convex constrained optimization problems by consigning expensive (online) optimization to ofﬂine training. The majority of work in this area typically employs fully connected neural networks (FCNN). However, recently convolutional (CNN) and graph (GNN) neural networks have also been investigated, in effort to exploit topological information within the power grid. Although…

## 4 Citations

### Learning-based AC-OPF Solvers on Realistic Network and Realistic Loads

- Computer ScienceArXiv
- 2022

An AC-OPF formulation-ready dataset called TAS-97 is constructed that contains realistic network information and realistic bus loads from Tasmania’s electricity network and it is found that the realistic loads in Tasmania are correlated between buses and they show signs of an underlying multivariate normal distribution.

### Multi-fidelity power flow solver

- Computer ScienceArXiv
- 2022

The results presented herein demonstrate MFNN’s potential and its limits with up to two orders of magnitude faster and more accurate power ﬂow solutions than DC approximation.

### Machine Learning for Electricity Market Clearing

- EngineeringArXiv
- 2022

—This paper seeks to design a machine learning twin of the optimal power ﬂow (OPF) optimization, which is used in market-clearing procedures by wholesale electricity markets. The motivation for the…

### Fast Quasi-Optimal Power Flow of Flexible DC Traction Power Systems

- Engineering
- 2022

—This paper proposes a quasi-optimal power flow (OPF) algorithm for flexible DC traction power systems (TPSs). Near-optimal solutions can be solved with high computational efficiency by the proposed…

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