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The quality of electricity system modelling heavily depends on the input data used. Although a lot of data is publicly available, it is often dispersed, tedious to process and partly contains errors. We argue that a central provision of…

An effective way to oppose global warming and mitigate climate change is to electrify our energy sectors and supply their electric power from renewable wind and solar. Spatio-temporal predictions of electric load become increasingly…

Machine Learning · Computer Science 2022-11-23 Arsam Aryandoust , Anthony Patt , Stefan Pfenninger

The modern power system features high penetration of power converters due to the development of renewables, HVDC, etc. Currently, the controller design and parameter tuning of power converters heavily rely on rich engineering experience and…

Systems and Control · Electrical Eng. & Systems 2020-05-12 Linbin Huang , Huanhai Xin , Florian Dörfler

With the booming growth of advanced digital technologies, it has become possible for users as well as distributors of energy to obtain detailed and timely information about the electricity consumption of households. These technologies can…

Signal Processing · Electrical Eng. & Systems 2022-09-16 Mohamed Aymane Ahajjam , Daniel Bonilla Licea , Mounir Ghogho , Abdellatif Kobbane

Due to the penetration of renewable energy resources and load deviation, uncertainty handling is one of the main challenges for power system; therefore the need for accurate decision-making in a power system under the penetration of…

Systems and Control · Electrical Eng. & Systems 2019-11-26 Mohammad Hemmati , Behnam Mohammadi-Ivatloo , Alireza Soroudi

This paper considers the phenomenon of distinct regional frequencies recently observed in some power systems. First, a reduced-order mathematical model describing this behaviour is developed. Then, techniques to solve the model are…

Optimization and Control · Mathematics 2021-04-15 Luis Badesa , Fei Teng , Goran Strbac

Model Predictive Control (MPC) is effective at generating safe control strategies in constrained scenarios, at the cost of computational complexity. This is especially the case in robots that require high sampling rates and have limited…

The increasing penetration of renewable energy sources, characterised by low inertia and intermittent disturbances, presents substantial challenges to power system stability. As critical indicators of system stability, frequency dynamics…

Systems and Control · Electrical Eng. & Systems 2025-02-19 Xiao Li , Xinyi Wen , Benjamin Schäfer

In this paper, we propose a data-driven energy storage system (ESS)-based method to enhance the online small-signal stability monitoring of power networks with high penetration of intermittent wind power. To accurately estimate inter-area…

Systems and Control · Electrical Eng. & Systems 2021-02-23 Ilias Zenelis , Georgia Pierrou , Xiaozhe Wang

Unlike common faults, three-phase short-circuit faults in power systems pose significant challenges. These faults can lead to out-of-step (OOS) conditions and jeopardize the system's dynamic security. The rapid dynamics of these faults…

Systems and Control · Electrical Eng. & Systems 2025-04-08 Amin Masoumi , Mert Korkali

This paper presents a new control, namely additive-state-decomposition dynamic inversion stabilized control, that is used to stabilize a class of multi-input multi-output (MIMO) systems subject to nonparametric time-varying uncertainties…

Systems and Control · Computer Science 2020-03-10 Quan Quan , Guangxun Du , Kai-Yuan Cai

This paper proposes a data-driven approach for optimal power flow (OPF) based on the stacked extreme learning machine (SELM) framework. SELM has a fast training speed and does not require the time-consuming parameter tuning process compared…

Systems and Control · Electrical Eng. & Systems 2020-06-02 Xingyu Lei , Zhifang Yang , Juan Yu , Junbo Zhao , Qian Gao , Hongxin Yu

Balanced data is required for deep neural networks (DNNs) when learning to perform power system stability assessment. However, power system measurement data contains relatively few events from where power system dynamics can be learnt. To…

Signal Processing · Electrical Eng. & Systems 2024-06-14 Tetiana Bogodorova , Denis Osipov , Luigi Vanfretti

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

Sustainable and economical generation of electrical power is an essential and mandatory component of infrastructure in today's world. Optimal generation (generator subset selection) of power requires a careful evaluation of various factors…

Computational Engineering, Finance, and Science · Computer Science 2017-09-11 Biswarup Bhattacharya , Abhishek Sinha

Time-domain simulations are a critical tool for power system operators. Depending on the instability mechanism under consideration and the system characteristics, such as the time constants of controllers, either phasor or Electro-Magnetic…

Systems and Control · Electrical Eng. & Systems 2020-02-27 Georgios Misyris , Spyros Chatzivasileiadis , Tilman Weckesser

This paper presents a real time control strategy for energy storage systems integration in electric vehicles fast charging applications combined with generation from intermittent renewable energy sources. A two steps approach taking…

Online transient stability assessment (TSA) is essential for secure and stable power system operations. The growing number of Phasor Measurement Units (PMUs) brings about massive sources of data that can enhance online TSA. However,…

Systems and Control · Electrical Eng. & Systems 2021-12-16 Rui Ma , Sara Eftekharnejad , Chen Zhong , Mustafa Cenk Gursoy

In a power distribution network with energy storage systems (ESS) and advanced controls, traditional monitoring and protection schemes are not well suited for detecting anomalies such as malfunction of controllable devices. In this work, we…

Signal Processing · Electrical Eng. & Systems 2021-02-26 Nayara Aguiar , Vijay Gupta , Rodrigo D. Trevizan , Babu R. Chalamala , Raymond H. Byrne

This work primarily focuses on an operator inference methodology aimed at constructing low-dimensional dynamical models based on a priori hypotheses about their structure, often informed by established physics or expert insights. Stability…

Machine Learning · Computer Science 2024-03-04 Igor Pontes Duff , Pawan Goyal , Peter Benner
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