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相关论文: PowerGrow: Feasible Co-Growth of Structures and Dy…

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The increasing complexity of the power grid, due to higher penetration of distributed resources and the growing availability of interconnected, distributed metering devices re- quires novel tools for providing a unified and consistent view…

机器学习 · 统计学 2017-05-25 Francesco Fusco , Seshu Tirupathi , Robert Gormally

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…

Many data-driven modules in smart grid rely on access to high-quality power flow data; however, real-world data are often limited due to privacy and operational constraints. This paper presents a physics-informed generative framework based…

机器学习 · 计算机科学 2025-04-25 Junfei Wang , Darshana Upadhyay , Marzia Zaman , Pirathayini Srikantha

Limited visibility of distribution network power flows at the low voltage level presents challenges to both distribution network operators from a planning perspective and distribution system operators from a congestion management…

系统与控制 · 电气工程与系统科学 2026-02-11 Alistair Brash , Junyi Lu , Bruce Stephen , Blair Brown , Robert Atkinson , Craig Michie , Fraser MacIntyre , Christos Tachtatzis

High-quality power flow datasets are essential for training machine learning models in power systems. However, security and privacy concerns restrict access to real-world data, making statistically accurate and physically consistent…

机器学习 · 计算机科学 2025-08-26 Milad Hoseinpour , Vladimir Dvorkin

Flexible grid topology has become a key enabler of flexibility in modern power grids, particularly for congestion management. Studying the effects of combinatorial topological changes is therefore of significant interest, though it remains…

系统与控制 · 电气工程与系统科学 2025-02-18 Antoine Marot , Noureddine Henka , Benjamin Donnot , Sami Tazi

The increasing penetration of renewable energy sources introduces significant variability and uncertainty in modern power systems, making accurate state prediction critical for reliable grid operation. Conventional forecasting methods often…

机器学习 · 计算机科学 2025-04-01 Dhruv Suri , Mohak Mangal

The necessary integration of renewable energy sources, combined with the expanding scale of power networks, presents significant challenges in controlling modern power grids. Traditional control systems, which are human and…

机器学习 · 计算机科学 2025-09-04 Carlo Fabrizio , Gianvito Losapio , Marco Mussi , Alberto Maria Metelli , Marcello Restelli

This paper presents a complex systems overview of a power grid network. In recent years, concerns about the robustness of the power grid have grown because of several cascading outages in different parts of the world. In this paper,…

适应与自组织系统 · 物理学 2010-06-24 Sakshi Pahwa , Amelia Hodges , Caterina Scoglio , Sean Wood

The conventional approach for the control of distribution networks, in the presence of active generation and/or controllable loads and storage, involves a combination of both frequency and voltage regulation at different time scales. With…

系统与控制 · 计算机科学 2015-02-05 Andrey Bernstein , Lorenzo Reyes-Chamorro , Jean-Yves Le Boudec , Mario Paolone

The power grid is going through significant changes with the introduction of renewable energy sources and incorporation of smart grid technologies. These rapid advancements necessitate new models and analyses to keep up with the various…

We introduce a framework for joint grounded scene graph - image generation, a challenging task involving high-dimensional, multi-modal structured data. To effectively model this complex joint distribution, we adopt a factorized approach:…

计算机视觉与模式识别 · 计算机科学 2025-08-05 Bicheng Xu , Qi Yan , Renjie Liao , Lele Wang , Leonid Sigal

Synthetic power grids enable secure, real-world energy system simulations and are crucial for algorithm testing, resilience assessment, and policy formulation. We propose a novel method for the generation of synthetic transmission power…

系统与控制 · 电气工程与系统科学 2023-10-31 Francesco Giacomarra , Gianmarco Bet , Alessandro Zocca

The paper is published in Chaos. Please refer to the Chaos version from now on. Anna B\"uttner, Anton Plietzsch, Mehrnaz Anvari, Frank Hellmann; A framework for synthetic power system dynamics. Chaos 1 August 2023; 33 (8): 083120.…

适应与自组织系统 · 物理学 2024-03-19 Anna Büttner , Anton Plietzsch , Mehrnaz Anvari , Frank Hellmann

Modern power systems are facing the tremendous challenge of integrating vast amounts of variable (non-dispatchable) renewable generation capacity, such as solar photovoltaic or wind power. In this context, the required power system…

系统与控制 · 电气工程与系统科学 2022-08-30 Oriol Gomis-Bellmunt , Saman Dadjo Tavakoli , Vinicius A. Lacerda , Eduardo Prieto-Araujo

The large size of multiscale, distribution and transmission, power grids hinder fast system-wide estimation and real-time control and optimization of operations. This paper studies graph reduction methods of power grids that are favorable…

系统与控制 · 计算机科学 2018-10-05 Colin Grudzien , Deepjyoti Deka , Michael Chertkov , Scott N Backhaus

Power system studies require the topological structures of real-world power networks; however, such data is confidential due to important security concerns. Thus, power grid synthesis (PGS), i.e., creating realistic power grids that imitate…

社会与信息网络 · 计算机科学 2019-04-15 Mahdi Khodayar , Jianhui Wang , Zhaoyu Wang

The transition to decarbonized energy systems has become a priority globally to mitigate carbon emissions and, therefore, climate change. However, the vulnerabilities of zero-carbon power grids under climatic and technological changes have…

Power systems are subject to fundamental changes due to the increasing infeed of decentralised renewable energy sources and storage. The decentralised nature of the new actors in the system requires new concepts for structuring the power…

适应与自组织系统 · 物理学 2020-04-22 Lia Strenge , Paul Schultz , Jürgen Kurths , Jörg Raisch , Frank Hellmann

Graph generative models are essential across diverse scientific domains by capturing complex distributions over relational data. Among them, graph diffusion models achieve superior performance but face inefficient sampling and limited…

机器学习 · 计算机科学 2025-06-17 Yiming Qin , Manuel Madeira , Dorina Thanou , Pascal Frossard
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