A fast scheme for fault detection in DC microgrid based on voltage prediction

Meghwani, Anju; Chakrabarti, Saikat; Srivastava, S. C.

doi:10.1109/npsc.2016.7858867

Cited by 26 publications

(8 citation statements)

References 17 publications

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“…Voltage prediction-based protection method has been proposed for DC ring bus topology. Fault detection and its isolation is achieved by finding the difference between the expected normal conditions and measured values in an event of a fault [95,96]. The technique is implemented by using local measurement and estimate the normal voltage value at the relay point by using a developed mathematical model which is used to interpolate/predict the next data value.…”

Section: Voltage Prediction-based Protectionmentioning

confidence: 99%

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System Configuration, Fault Detection, Location, Isolation and Restoration: A Review on LVDC Microgrid Protections

et al. 2019

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Low voltage direct current (LVDC) distribution has gained the significant interest of research due to the advancements in power conversion technologies. However, the use of converters has given rise to several technical issues regarding their protections and controls of such devices under faulty conditions. Post-fault behaviour of converter-fed LVDC system involves both active converter control and passive circuit transient of similar time scale, which makes the protection for LVDC distribution significantly different and more challenging than low voltage AC. These protection and operational issues have handicapped the practical applications of DC distribution. This paper presents state-of-the-art protection schemes developed for DC Microgrids. With a close look at practical limitations such as the dependency on modelling accuracy, requirement on communications and so forth, a comprehensive evaluation is carried out on those system approaches in terms of system configurations， fault detection, location, isolation and restoration.

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Section: Voltage Prediction-based Protectionmentioning

confidence: 99%

“…It can result in large deviation between the measured and predicted voltage values during a fault. However, the voltage difference becomes insignificant when the fault loop impedance is high [95]. Such method also heavily relies on the accuracy of the mathematical model used.…”

Section: Voltage Prediction-based Protectionmentioning

confidence: 99%

System Configuration, Fault Detection, Location, Isolation and Restoration: A Review on LVDC Microgrid Protections

et al. 2019

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“…Other is prediction of the voltage drop due to the diode commutation process in the excitation system of salient-pole synchronous generators. DC railway system emulator design for stray current, touch voltage prediction, and a fast scheme for fault detection in DC microgrids based on voltage prediction are other works [1][2][3][4]. In this study, determination of the distance between the power centers is done with artificial intelligence methods.…”

Section: Introductionmentioning

confidence: 99%

Determination of distance between DC traction power centers in a 1500-V DC subway line with artificial intelligence methods

Akçay¹,

Kocaarslan²

2019

Turk J Elec Eng & Comp Sci

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The electrification system in rail systems is designed with regard to the operating data and design parameters. While the electrification system is formed, the minimum voltage rating that the traction force requires during the operation needs to be provided. The highest value of the voltage drop occurring on the line is determined by the distance between power centers. This value needs to be kept within certain limits for the continuity of operation. In this study, the determination of the distance between DC traction power centers for a 1500-V DC-fed rail system is done by means of the adaptive neuro-fuzzy inference system (ANFIS), support vector machines (SVMs), and artificial neural networks (ANNs). The distance occurring on the line is calculated with regard to the operating parameters by means of the ANFIS, SVMs, and ANNs. The ANFIS, SVMs, and ANNs are explained and a comparison is made. The data created regarding one-way and two-way supply conditions are examined for simulation. The main contribution of this paper is the determination of the distance between railway traction power centers with artificial intelligence methods.

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“…Thus, fast fault detection and isolation during transient period is required. An investigation on unit and non-unit protection scheme for DC system has been carried out by the authors in [5,[7][8][9][10][11][12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

“…Thus, the differential protection scheme serves the best solution if reliable communication system is available. Research conducted for LVDC system suggests non-unit protection scheme for fault detection that are based on overcurrent [11][12][13] or on rate of change of current/voltage [14,15], have inherent backup facilities for adjacent networks, and have no communication delays. However, non-unit method has to deal with the impact of variable fault resistance on fault current and so issues can arise for higher levels of selectivity in network.…”

Section: Introductionmentioning

confidence: 99%