Power-Swing Detection Using Moving Window Averaging of Current Signals

Rao, J. Ganeswara; Pradhan, Ashok Kumar

doi:10.1109/tpwrd.2014.2342536

Cited by 101 publications

(60 citation statements)

References 19 publications

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“…As noise affects the performance of the sample based algorithms significantly [25], proposed method is evaluated for noisy conditions. For this, a uniform distribution noise with a zero mean and a standard deviation of 2% is introduced in a-phase current signal obtained for F 1 fault case.…”

Section: Test Results For Model Verification With Noise In the Signalmentioning

confidence: 99%

Model Verification of Fixed Series Compensation Devices Using Synchronized Data

Gajare¹,

Pradhan²,

Brahma

2016

IEEE Trans. Power Delivery

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Regulating agencies mandate that model verification of power system components must be performed to make sure the system analysis software perform accurately. Such verification is necessary for series compensation devices used in transmission systems, since they deteriorate due to aging or prolonged subjection to stressed condition, leading to changes in compensation levels or voltage-current characteristic of the metal oxide varistor (MOV) protecting them. This paper presents a method that uses synchronized time-domain data captured by intelligent electronic devices (IEDs) at both ends of a line for model verification of a fixed series compensation device installed at one location in the line. Electromagnetic transient line model is used to calculate the current and voltage across the compensation device, which in turn are used to determine the actual compensation and the actual voltage-current characteristic of MOV. These characteristics are used to detect failures in MOV and spark-gap. PSCAD/EMTDC is used to test the method.

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Section: Test Results For Model Verification With Noise In the Signalmentioning

confidence: 99%

Model Verification of Fixed Series Compensation Devices Using Synchronized Data

Gajare¹,

Pradhan²,

Brahma

2016

IEEE Trans. Power Delivery

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“…The proposed fault location method is scrutinized during the probe current incorporated with uniform distribution noise with zero mean and standard deviation of 2.5% [28] as shown in Fig. 11b.…”

Section: Performance With Noise In Measured Probe Currentmentioning

confidence: 99%

“…The envelope of probe current response is given by i p env(t) = Ke −αt = K[1-αt + (αt) 2 2! -(αt) 3 3!…”

Section: Appendixmentioning

confidence: 99%

An Accurate Noniterative Fault-Location Technique for Low-Voltage DC Microgrid

Mohanty

Balaji

Pradhan

2016

IEEE Trans. Power Delivery

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136

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The least erroneous knowledge on fault location in distribution system helps for restoration process, expedite maintenance and reduce power outage duration. A fault location method using probe power unit (PPU) in DC microgrid assumes that the natural frequency of the system is equal to damped resonant frequency of probe current. This assumption leads to prominent error in fault location calculation. To estimate location of fault in low voltage DC microgrid system, a noniterative fault location technique using PPU is proposed in this paper. Considering damping frequency and attenuation of the probe current, which is a function of fault distance and damping coefficient, fault location is obtained. The technique is tested for high resistance fault and radial and looped topologies and found to be more accurate.

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“…1. The proposed algorithm is to be initiated when power swing condition is detected in a power system [1], [29], [30], [31]. Since current signal oscillates during power swing, the frequency estimation becomes erroneous when the signal envelop is at minimum [27].…”

Section: B Phasor Estimation Using Least Squares Techniquementioning

confidence: 99%