Tootfinder

Dynamic Line Ratings in AC Optimal Power Flow: Transient Temperature, Decomposition, and Large-scale Evaluation
Baptiste Rabecq, Thomas Lee, Andy Sun
https://arxiv.org/abs/2510.10832

Dynamic Line Ratings in AC Optimal Power Flow: Transient Temperature, Decomposition, and Large-scale Evaluation
As power grids experience increasing renewable penetration and rapid load growth from AI data centers and electrification, alleviating line congestion becomes critical to unlocking additional grid capacity. This work investigates Dynamic Line Rating (DLR), a congestion mitigation method that adjusts power line current limits in response to meteorological conditions. Unlike traditional approaches that impose predefined time-varying limits, we propose a novel optimization framework that embeds th…

FinGAN: An Interpretable RSS Generation Network for Scalable Fingerprint Localization
Jiaming Zhang, Jiajun He, Jie Zhang, Okan Yurduseven
https://arxiv.org/abs/2509.26286 https…

FinGAN: An Interpretable RSS Generation Network for Scalable Fingerprint Localization
This work introduces FinGAN, a robust received signal strength (RSS) data generator designed to expand RSS fingerprint datasets. Compared to existing generative adversarial models that either rely on known reference positions (RPs) or depend on predefined priors, FinGAN learns the latent information between RPs and RSS values by maximizing the mutual information between the generated RSS data and the RPs, enabling an end-to-end RSS generation directly from RPs. This allows us to accurately gene…