short circuit
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Author(s):  
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.


2022 ◽  
Vol 8 ◽  
pp. 1046-1055
Author(s):  
Fan Xiao ◽  
Yongjun Xia ◽  
Kanjun Zhang ◽  
Zhe Zhang ◽  
Xianggen Yin

2022 ◽  
Vol 8 ◽  
pp. 1383-1390
Author(s):  
Haihong Qin ◽  
Haoxiang Hu ◽  
Wenxin Huang ◽  
Yubin Mo ◽  
Wenming Chen

2022 ◽  
Vol 8 ◽  
pp. 1481-1485
Author(s):  
Qi Wang ◽  
Xiaojie Pan ◽  
Bing Zhao ◽  
Pandeng Luo ◽  
Jie Hao ◽  
...  

Author(s):  
Oscar Danilo Montoya ◽  
Carlos Alberto Ramírez-Vanegas ◽  
Luis Fernando Grisales-Noreña

<p>The problem of parametric estimation in photovoltaic (PV) modules considering manufacturer information is addressed in this research from the perspective of combinatorial optimization. With the data sheet provided by the PV manufacturer, a non-linear non-convex optimization problem is formulated that contains information regarding maximum power, open-circuit, and short-circuit points. To estimate the three parameters of the PV model (i.e., the ideality diode factor (a) and the parallel and series resistances (R<sub>p</sub> and R<sub>s</sub>)), the crow search algorithm (CSA) is employed, which is a metaheuristic optimization technique inspired by the behavior of the crows searching food deposits. The CSA allows the exploration and exploitation of the solution space through a simple evolution rule derived from the classical PSO method. Numerical simulations reveal the effectiveness and robustness of the CSA to estimate these parameters with objective function values lower than 1 × 10<sup>−28</sup> and processing times less than 2 s. All the numerical simulations were developed in MATLAB 2020a and compared with the sine-cosine and vortex search algorithms recently reported in the literature.</p>


Author(s):  
Antonio Bracale ◽  
P. Caramia ◽  
P. De Falco ◽  
A.R. Di Fazio ◽  
P. Varilone

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 577
Author(s):  
Belema P. Alalibo ◽  
Bing Ji ◽  
Wenping Cao

Multiple techniques continue to be simultaneously utilized in the condition monitoring and fault detection of electric machines, as there is still no single technique that provides an all-round solution to fault finding in these machines. Having various machine fault-detection techniques is useful in allowing the ability to combine two or more in a manner that will provide a more comprehensive application-dependent condition-monitoring solution; especially, given the increasing role these machines are expected to play in man’s transition to a more sustainable environment, where many more electric machines will be required. This paper presents a novel non-invasive optical fiber using a stray flux technique for the condition monitoring and fault detection of induction machines. A giant magnetostrictive transducer, made of terfenol-D, was bonded onto a fiber Bragg grating, to form a composite FBG-T sensor, which utilizes the machines’ stray flux to determine the internal condition of the machine. Three machine conditions were investigated: healthy, broken rotor, and short circuit inter-turn fault. A tri-axial auto-data-logging flux meter was used to obtain stray magnetic flux measurements, and the numerical results obtained with LabView were analyzed in MATLAB. The optimal positioning and sensitivity of the FBG-T sensor were found to be transverse and 19.3810 pm/μT, respectively. The experimental results showed that the FBG-T sensor accurately distinguished each of the three machine conditions using a different order of magnitude of Bragg wavelength shifts, with the most severe fault reaching wavelength shifts of hundreds of picometres (pm) compared to the healthy and broken rotor conditions, which were in the low-to-mid-hundred and high-hundred picometre (pm) range, respectively. A fast Fourier transform (FFT) analysis, performed on the measured stray flux, revealed that the spectral content of the stray flux affected the magnetostrictive behavior of the magnetic dipoles of the terfenol-D transducer, which translated into strain on the fiber gratings.


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