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Related papers: Foundation Models for the Electric Power Grid

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The energy transition, crucial for tackling the climate crisis, demands integrating numerous distributed, renewable energy sources into existing grids. Along with climate change and consumer behavioral changes, this leads to changes and…

Systems and Control · Electrical Eng. & Systems 2024-09-05 Alban Puech , Jonas Weiss , Thomas Brunschwiler , Hendrik F. Hamann

Foundation models (FMs) are general-purpose artificial intelligence (AI) models that have recently enabled multiple brand-new generative AI applications. The rapid advances in FMs serve as an important contextual backdrop for the vision of…

Networking and Internet Architecture · Computer Science 2024-05-08 Zihan Chen , Howard H. Yang , Y. C. Tay , Kai Fong Ernest Chong , Tony Q. S. Quek

As global energy systems transit to clean energy, accurate renewable generation and renewable demand forecasting is imperative for effective grid management. Foundation Models (FMs) can help improve forecasting of renewable generation and…

Systems and Control · Electrical Eng. & Systems 2025-08-01 Md Meftahul Ferdaus , Tanmoy Dam , Md Rasel Sarkar , Moslem Uddin , Sreenatha G. Anavatti

Foundation models (FMs) are changing the way medical images are analyzed by learning from large collections of unlabeled data. Instead of relying on manually annotated examples, FMs are pre-trained to learn general-purpose visual features…

Foundation models (FMs) have shown remarkable capabilities in generalized intelligence, multimodal understanding, and adaptive learning across a wide range of domains. However, their deployment in harsh or austere environments --…

Networking and Internet Architecture · Computer Science 2025-09-17 Evan Chen , Seyyedali Hosseinalipour , Christopher G. Brinton , David J. Love

Foundation models have emerged as critical components in a variety of artificial intelligence applications, and showcase significant success in natural language processing and several other domains. Meanwhile, the field of graph machine…

Machine Learning · Computer Science 2025-03-11 Jiawei Liu , Cheng Yang , Zhiyuan Lu , Junze Chen , Yibo Li , Mengmei Zhang , Ting Bai , Yuan Fang , Lichao Sun , Philip S. Yu , Chuan Shi

The increasing share of renewable energy and distributed electricity generation requires the development of deep learning approaches to address the lack of flexibility inherent in traditional power grid methods. In this context, Graph…

Machine Learning · Computer Science 2026-01-08 Mohamed Hassouna , Clara Holzhüter , Pawel Lytaev , Josephine Thomas , Bernhard Sick , Christoph Scholz

While reinforcement learning from scratch has shown impressive results in solving sequential decision-making tasks with efficient simulators, real-world applications with expensive interactions require more sample-efficient agents.…

Machine Learning · Computer Science 2025-09-22 Remo Sasso , Michelangelo Conserva , Dominik Jeurissen , Paulo Rauber

Foundation models (FMs) are recognized as a transformative breakthrough that has started to reshape the future of artificial intelligence (AI) across both academia and industry. The integration of FMs into wireless networks is expected to…

Networking and Internet Architecture · Computer Science 2026-01-07 Han Zhang , Mohammad Farzanullah , Mohammad Ghassemi , Akram Bin Sediq , Ali Afana , Melike Erol-Kantarci

Telecom networks are becoming increasingly complex, with diversified deployment scenarios, multi-standards, and multi-vendor support. The intricate nature of the telecom network ecosystem presents challenges to effectively manage, operate,…

Networking and Internet Architecture · Computer Science 2024-08-09 Tahar Zanouda , Meysam Masoudi , Fitsum Gaim Gebre , Mischa Dohler

The recent emergence of large language models (LLMs) such as GPT-3 has marked a significant paradigm shift in machine learning. Trained on massive corpora of data, these models demonstrate remarkable capabilities in language understanding,…

Systems and Control · Electrical Eng. & Systems 2025-09-23 Seyyedali Hosseinalipour , Shimiao Li , Adedoyin Inaolaji , Filippo Malandra , Luis Herrera , Nicholas Mastronarde

Management and efficient operations in critical infrastructure such as Smart Grids take huge advantage of accurate power load forecasting which, due to its nonlinear nature, remains a challenging task. Recently, deep learning has emerged in…

Machine Learning · Computer Science 2019-07-23 Alberto Gasparin , Slobodan Lukovic , Cesare Alippi

Graph Foundation Models (GFMs) are emerging as a significant research topic in the graph domain, aiming to develop graph models trained on extensive and diverse data to enhance their applicability across various tasks and domains.…

Machine Learning · Computer Science 2024-06-03 Haitao Mao , Zhikai Chen , Wenzhuo Tang , Jianan Zhao , Yao Ma , Tong Zhao , Neil Shah , Mikhail Galkin , Jiliang Tang

The transition away from carbon-based energy sources poses several challenges for the operation of electricity distribution systems. Increasing shares of distributed energy resources (e.g. renewable energy generators, electric vehicles) and…

Machine Learning · Computer Science 2021-03-15 Francesco Fusco , Bradley Eck , Robert Gormally , Mark Purcell , Seshu Tirupathi

Foundation models are deep neural networks (such as GPT-5, Gemini~3, and Opus~4) trained on large datasets that can perform diverse downstream tasks -- text and code generation, question answering, summarization, image classification, and…

Machine Learning · Computer Science 2026-05-01 Logan G Wright , Tianyu Wang , Tatsuhiro Onodera , Peter L. McMahon

Foundation models (FMs) are large-scale deep learning models trained on massive datasets, often using self-supervised learning techniques. These models serve as a versatile base for a wide range of downstream tasks, including those in…

Machine Learning · Computer Science 2025-01-17 Wasif Khan , Seowung Leem , Kyle B. See , Joshua K. Wong , Shaoting Zhang , Ruogu Fang

Federated learning (FL) offers privacy-preserving decentralized machine learning, optimizing models at edge clients without sharing private data. Simultaneously, foundation models (FMs) have gained traction in the artificial intelligence…

Machine Learning · Computer Science 2023-10-06 Sixing Yu , J. Pablo Muñoz , Ali Jannesari

Foundation Models (FMs) serve as a general class for the development of artificial intelligence systems, offering broad potential for generalization across a spectrum of downstream tasks. Despite extensive research into self-supervised…

Machine Learning · Computer Science 2024-06-17 Yuhao Xu , Xinqi Liu , Keyu Duan , Yi Fang , Yu-Neng Chuang , Daochen Zha , Qiaoyu Tan

This article reviews different kinds of models for the electric power grid that can be used to understand the modern power system, the smart grid. From the physical network to abstract energy markets, we identify in the literature different…

Foundation models (FM) have demonstrated remarkable performance across a wide range of tasks (especially in the fields of natural language processing and computer vision), primarily attributed to their ability to comprehend instructions and…

Artificial Intelligence · Computer Science 2025-02-11 Hongling Zheng , Li Shen , Anke Tang , Yong Luo , Han Hu , Bo Du , Yonggang Wen , Dacheng Tao
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