transient stability
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Marino Godoy Arcia ◽  
Zaid Garcia Sanchez ◽  
Hernan Hernandez Herrera ◽  
José Antonio Gonzalez Cueto Cruz ◽  
Jorge Iván Silva Ortega ◽  

The renewable energy sources (RESs) projects are solutions with environmental benefits that are changing the traditional power system operation and concept. Transient stability analysis has opened new research trends to guarantee a secure operation high penetration. Problems such as frequency fluctuations, decoupling between generator angular speed, network frequency fluctuation and kinetic energy storing absence are the main non-conventional RESs penetration in power systems. This paper analyzes short-circuit influence on frequency response, focusing on weak distribution networks and isolated, to demonstrate relevance in frequency stability. A study case considered a generation outage and a load input to analyze frequency response. The paper compares frequency response during a generation outage with a short-circuit occurrence. In addition, modular value and angle generator terminal voltage affectation by electric arc and network ratio R⁄X, failure type influence in power delivered behavior, considering fault location, arc resistance and load. The arc resistance is defined as an added resistance that appears during failure and influences voltage modulus and angle value results showing that intermittent non-conventional RES participation can lead to frequency fluctuations. Results showed that arc resistance, type of failure, location and loadability determine the influence of frequency response factors in weak power systems.

Mutegi Mbae ◽  
Nnamdi Nwulu

<p>Flexible alternating current transmission system (FACTS) devices are deployed for improving power system’s stability either singly or as a combination. This research investigates hybrid FACTS devices and studies their impact on voltage, small-signal and transient stability simultaneously under various system disturbances. The simulations were done using five FACTS devices-static var compensator (SVC), static synchronous compensator (STATCOM), static synchronous series compensators (SSSC), thyristor controlled series compensator (TCSC) and unified power flow controller (UPFC) in MATLAB’s power system analysis toolbox (PSAT). These five devices were grouped into ten pairs and tested on Kenya’s transmission network under specific contingencies: the loss of a major generating machine and/or transmission line. The UPFC-STATCOM pair performed the best in all the three aspects under study. The settling times were 3 seconds and 3.05 seconds respectively for voltage and rotor angle improvement on the loss of a major generator at normal operation. The same pair gave settling times of 2.11 seconds and 3.12 seconds for voltage and rotor angle stability improvement respectively on the loss of a major transmission line at 140% system loading. From the study, two novel techniques were developed: A performance-based ranking system and classification for FACTS devices.</p>

Yufeng Zhao ◽  
Jing Ma ◽  
Gengyu Yang ◽  
Chen Liu ◽  
Peng Cheng ◽  

2022 ◽  
Vol 20 (2) ◽  
pp. 335-343
Daiane Mara Barbosa de Siqueira ◽  
Roman Kuiava ◽  
Thelma Solange Piazza Fernandes

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 507
Petar Sarajcev ◽  
Antonijo Kunac ◽  
Goran Petrovic ◽  
Marin Despalatovic

The high penetration of renewable energy sources, coupled with decommissioning of conventional power plants, leads to the reduction of power system inertia. This has negative repercussions on the transient stability of power systems. The purpose of this paper is to review the state-of-the-art regarding the application of artificial intelligence to the power system transient stability assessment, with a focus on different machine, deep, and reinforcement learning techniques. The review covers data generation processes (from measurements and simulations), data processing pipelines (features engineering, splitting strategy, dimensionality reduction), model building and training (including ensembles and hyperparameter optimization techniques), deployment, and management (with monitoring for detecting bias and drift). The review focuses, in particular, on different deep learning models that show promising results on standard benchmark test cases. The final aim of the review is to point out the advantages and disadvantages of different approaches, present current challenges with existing models, and offer a view of the possible future research opportunities.

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