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We look into the fluctuations caused by disturbances in power systems. In the linearized system of the power systems, the disturbance is modeled by a Brownian motion process, and the fluctuations are described by the covariance matrix of…

Systems and Control · Electrical Eng. & Systems 2023-03-20 Xian Wu , Kaihua Xi , Aijie Cheng , Hai Xiang Lin , Jan H van Schuppen , Chenghui Zhang

A precise estimation of the Rate of Change of Frequency (RoCoF) is crucial for secure power system operation. In fact, RoCoF is strictly related to the amount of the available physical and/or virtual inertia of the system and the severity…

Systems and Control · Electrical Eng. & Systems 2025-11-06 Gutierrez-Florensa , F. Sanniti , D. Tedeschi , L. Sigrist , A. Ortega , F. Milano

System identification is of special interest in science and engineering. This article is concerned with a system identification problem arising in stochastic dynamic systems, where the aim is to estimate the parameters of a system along…

Methodology · Statistics 2022-01-27 Christos Merkatas , Simo Särkkä

The increasing amount of controllable generation and consumption in distribution grids poses a severe challenge in keeping voltage values within admissible ranges. Existing approaches have considered different optimal power flow…

Systems and Control · Electrical Eng. & Systems 2019-07-25 Miguel Picallo , Adolfo Anta , Bart De Schutter

Traditional synchronous generators with rotational inertia are being replaced by low-inertia renewable energy resources (RESs) in many power grids and operational scenarios. Due to emerging market mechanisms, inherent variability of RESs,…

Optimization and Control · Mathematics 2019-03-05 Yi Guo , Tyler H. Summers

We study the impact of stochastic perturbations to deterministic dynamical systems using the formalism of the Ruelle response theory and explore how stochastic noise can be used to explore the properties of the underlying deterministic…

Statistical Mechanics · Physics 2015-05-27 Valerio Lucarini

This letter proposes a data-driven sparse polynomial chaos expansion-based surrogate model for the stochastic economic dispatch problem considering uncertainty from wind power. The proposed method can provide accurate estimations for the…

Signal Processing · Electrical Eng. & Systems 2021-09-20 Xiaoting Wang , Rong-Peng Liu , Xiaozhe Wang , Yunhe Hou , François Bouffard

We analyse the stochastic properties of the 49 pulsars that comprise the first International Pulsar Timing Array (IPTA) data release. We use Bayesian methodology, performing model selection to determine the optimal description of the…

We propose a method for determining the most likely cause, in terms of conventional generator outages and renewable fluctuations, of power system frequency reaching a predetermined level that is deemed unacceptable to the system operator.…

Systems and Control · Electrical Eng. & Systems 2020-05-26 Brendan Patch , Bert Zwart

In this paper we develop a nonparametric maximum likelihood estimate of the mixing distribution of the parameters of a linear stochastic dynamical system. This includes, for example, pharmacokinetic population models with process and…

Methodology · Statistics 2015-09-16 Alona Kryshchenko , Alan Schumitzky , Mike van Guilder , Michael Neely

In this paper we focus on the parameter estimation of dynamic load models with stochastic terms, in particular, load models where protection settings are uncertain, such as in aggregated air conditioning units. We show how the uncertainty…

Optimization and Control · Mathematics 2020-04-30 Daniel Adrian Maldonado , Vishwas Rao , Mihai Anitescu , Vivak Patel

The power system frequency is important for the system overall stability. However, there does not exist a single measurement point of the system frequency due to the distributed nature of the system inertia and the small inconsistency of…

Systems and Control · Electrical Eng. & Systems 2021-04-23 Shutang You , Hongyu Li , Shengyuan Liu , Kaiqi Sun , Weikang Wang , Wei Qiu , Yilu Liu

Motivated by the inadequacy of conventional control methods for power networks with a large share of renewable generation, in this paper we study the (stochastic) passivity property of wind turbines based on the Doubly Fed Induction…

Systems and Control · Electrical Eng. & Systems 2021-03-05 Amirreza Silani , Michele Cucuzzella , Jacquelien M. A. Scherpen , Mohammad Javad Yazdanpanah

From an operational and planning perspective, it is important to quantify the impact of increasing penetration of photovoltaics on the distribution system. Most existing impact assessment studies are scenario-based where derived results are…

Systems and Control · Electrical Eng. & Systems 2021-04-30 Sai Munikoti , Balasubramaniam Natarajan , Kumarsinh Jhala , Kexing Lai

In this manuscript we continue the thread of [M. Chertkov, F. Pan, M. Stepanov, Predicting Failures in Power Grids: The Case of Static Overloads, IEEE Smart Grid 2011] and suggest a new algorithm discovering most probable extreme stochastic…

Systems and Control · Computer Science 2011-09-08 Michael Chertkov , Mikhail Stepanov , Feng Pan , Ross Baldick

In engineering, simulations play a vital role in predicting the behavior of a nonlinear dynamical system. In order to enhance the reliability of predictions, it is essential to incorporate the inherent uncertainties that are present in all…

Computational Engineering, Finance, and Science · Computer Science 2025-03-12 Lars de Jong , Paula Clasen , Michael Müller , Ulrich Römer

This paper proposed an approach to identify the change of inertia distribution in high renewable power systems. Using the footprints of electromechanical wave propagation at the distribution level, this approach provides a new and…

Systems and Control · Electrical Eng. & Systems 2021-03-16 Shutang You

We consider the problem of distributed secondary frequency regulation in power networks such that stability and an optimal power allocation are attained. This is a problem that has been widely studied in the literature, and two main control…

Optimization and Control · Mathematics 2020-08-12 Andreas Kasis , Nima Monshizadeh , Ioannis Lestas

We present a numerical method for learning unknown nonautonomous stochastic dynamical system, i.e., stochastic system subject to time dependent excitation or control signals. Our basic assumption is that the governing equations for the…

Machine Learning · Computer Science 2025-03-04 Yuan Chen , Dongbin Xiu

We derive an efficient stochastic algorithm for inverse problems that present an unknown linear forcing term and a set of nonlinear parameters to be recovered. It is assumed that the data is noisy and that the linear part of the problem is…

Numerical Analysis · Mathematics 2019-09-17 Darko Volkov
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