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Data-driven modeling is useful for reconstructing nonlinear dynamical systems when the underlying process is unknown or too expensive to compute. Having reliable uncertainty assessment of the forecast enables tools to be deployed to predict…

Methodology · Statistics 2023-11-01 Mengyang Gu , Yizi Lin , Victor Chang Lee , Diana Qiu

We present parton distribution functions which include a quantitative estimate of its uncertainties. The parton distribution functions are optimized with respect to deep inelastic proton data, expressing the uncertainties as a density…

High Energy Physics - Phenomenology · Physics 2007-05-23 Walter T. Giele , Stephane A. Keller , David A. Kosower

In this study, we present an improved formulation for the wake-added turbulence to enhance the accuracy of intra-farm and farm-to-farm wake modeling through analytical frameworks. Our goal is to address the tendency of a commonly used…

Fluid Dynamics · Physics 2024-12-11 Navid Zehtabiyan-Rezaie , Josephine Perto Justsen , Mahdi Abkar

This paper presents a method to better integrate dynamic models for renewable resources into synthetic electric grids. An automated dynamic models assignment process is proposed for wind and solar generators. A realistic composition ratio…

Systems and Control · Electrical Eng. & Systems 2021-01-08 Yijing Liu , Zeyu Mao , Hanyue Li , Komal S Shetye , Thomas J. Overbye

Given the advancements in data-driven modeling for complex engineering and scientific applications, this work utilizes a data-driven predictive control method, namely subspace predictive control, to coordinate hybrid power plant components…

Systems and Control · Electrical Eng. & Systems 2025-02-20 Manavendra Desai , Himanshu Sharma , Sayak Mukherjee , Sonja Glavaski

Many practical optimization problems involve uncertain parameters that are strictly positive. However, the most common uncertainty sets used in robust optimization are the box and the ellipsoidal sets, which may include non-positive values…

Optimization and Control · Mathematics 2026-04-29 Tatsuya Tanaka , Huimin Li , Shota Yamanaka , Ellen H. Fukuda , Nobuo Yamashita

Despite substantial improvement in the development of forecasting approaches, conditional and dynamic uncertainty estimates ought to be accommodated in decision-making in power system operation and market, in order to yield either…

Applications · Statistics 2018-08-20 Faranak Golestaneh , Pierre Pinson , Hoay Beng Gooi

To achieve virtual certification for industrial design, quantifying the uncertainties in simulation-driven processes is crucial. We discuss a physics-constrained approach to account for epistemic uncertainty of turbulence models. In order…

Machine Learning · Computer Science 2023-07-12 Marcel Matha , Christian Morsbach

Unified Power Flow Controller (UPFC) is recognized as the most powerful flexible AC transmission systems (FACTS) device for power system operation. This paper addresses how UPFC explores the transmission flexibility and facilitates the…

Optimization and Control · Mathematics 2017-10-02 Jia Li , Feng Liu , Zuyi Li , Shengwei Mei , Guangyu He

This paper proposes a novel methodology for probabilistic dynamic security assessment and enhancement of power systems that considers load and generation variability, N-2 contingencies, and uncertain cascade propagation caused by uncertain…

Systems and Control · Electrical Eng. & Systems 2025-05-05 Frédéric Sabot , Pierre-Etienne Labeau , Pierre Henneaux

Existing approaches of prescriptive analytics -- where inputs of an optimization model can be predicted by leveraging covariates in a machine learning model -- often attempt to optimize the mean value of an uncertain objective. However,…

Machine Learning · Computer Science 2025-03-05 Dimitris Bertsimas , Benjamin Boucher

Most existing generation scheduling models for power systems under demand uncertainty rely on energy-based formulations with a finite number of time periods, which may fail to ensure that power supply and demand are balanced continuously…

Optimization and Control · Mathematics 2025-04-02 Youngchae Cho , Insoon Yang , Takayuki Ishizaki

The supply of electrical energy is being increasingly sourced from renewable generation resources. The variability and uncertainty of renewable generation, compared to a dispatch-able plant, is a significant dissimilarity of concern to the…

Optimization and Control · Mathematics 2017-11-16 Farhad Samadi Gazijahani , Javad Salehi

In this article we study the problem of quantifying the uncertainty in an experiment with a technical system. We propose new density estimates which combine observed data of the technical system and simulated data from an (imperfect)…

Statistics Theory · Mathematics 2020-12-21 Sebastian Kersting , Michael Kohler

The uncertainty associated with the experimental inflow in a wind tunnel affects the prediction of the flow of interest by numerical simulations. We evaluate this impact using uncertainty quantification. A method is developed and applied to…

Fluid Dynamics · Physics 2021-04-14 Nicola Detomaso , Vincent Brion , Julien Dandois , Marie Couliou , Éric Savin

Both the level of conservativeness and the computational burden in robust optimization are critically influenced by uncertainty set design. However, contextual side information is rarely exploited in robust dispatch of power systems…

Optimization and Control · Mathematics 2026-05-11 Zhaojun Ruan , Yulin Liu , Le Fu , Libao Shi

High renewable energy penetration into power distribution systems causes a substantial risk of exceeding voltage security limits, which needs to be accurately assessed and properly managed. However, the existing methods usually rely on the…

Systems and Control · Electrical Eng. & Systems 2024-11-08 Yuanhai Gao , Xiaoyuan Xu , Zheng Yan , Mohammad Shahidehpour , Bo Yang , Xinping Guan

With the rising costs of conventional sources of energy, the world is moving towards sustainable energy sources including wind energy. Wind turbines consist of several electrical and mechanical components and experience an enormous amount…

Machine Learning · Computer Science 2020-01-13 Joyjit Chatterjee , Nina Dethlefs

Stochastic feed-in of fluctuating renewable energies is steadily increasing in modern electricity grids and this becomes an important risk factor for maintaining power grid stability. Here we study the impact of wind power feed-in on the…

Adaptation and Self-Organizing Systems · Physics 2019-11-04 Matthias F. Wolff , Katrin Schmietendorf , Pedro G. Lind , Oliver Kamps , Joachim Peinke , Philipp Maass

Higher shares of electricity generation from renewable energy sources and market liberalization is increasing uncertainty in power systems operation. At the same time, operation is becoming more flexible with improved control systems and…

Optimization and Control · Mathematics 2016-09-09 Line Roald , Sidhant Misra , Thilo Krause , Goran Andersson