Evaluation of the Effect of Power Circuit Breaker Reclosing Practices on Turbine-Generators Shafts

-Power transmission lines are one of the most important components of electric power system. Failures in the operation of power transmission lines can result in serious power system problems. Hence, fault diagnosis (transient or permanent) in power transmission lines is very important to ensure the reliable operation of the power system. A hidden Markov model (HMM), a powerful pattern recognizer, classifies events in a probabilistic manner based on fault signal waveform and characteristics. This paper presents application of HMM to classify faults in overhead power transmission lines. The algorithm uses voltage samples of one-fourth cycle from the inception of the fault. The simulation performed in EMTPWorks and MATLAB environments validates the fast response of the classifier, which provides fast and accurate protection scheme for power transmission lines.

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“…6 that the best input datum (feature) is 1 V . As a result, 1 V was chosen as the input datum for the HMM classifier in experiment 2.…”

Section: Methodsmentioning

confidence: 99%

“…Nearly 80% of faults in an EHV transmission lines are transient [1]. The most prevalent potential of transient faults is lightning and transmission line switching, among others.…”

Section: Introductionmentioning

confidence: 99%

A Novel Algorithm for Fault Type Fast Diagnosis in Overhead Transmission Lines Using Hidden Markov Models

Jannati¹,

Jazebi²,

Vahidi³

et al. 2011

Journal of Electrical Engineering and Technology

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“…On the other hand, unsuccessful reclosing during a permanent fault may aggravate the potential damage to the system equipment [3]. For some extra-high-voltage lines, especially near generating plants, the classical automatic reclosing of breakers cannot be used and therefore adaptive reclosing schemes have been introduced over the past decades [4]. Such schemes prevent unsuccessful reclosing on permanent faults, and during arcing faults reclosing is done only after full extinction of the secondary arc and complete de-ionisation of the arc path.…”

Section: Introductionmentioning

confidence: 99%

Adaptive single pole auto-reclosing using discrete wavelet transform

Jamali

Ghaffarzadeh

2010

Euro. Trans. Electr. Power

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SUMMARYThis paper proposes a new algorithm for adaptive single pole auto-reclosing (SPAR) using discrete wavelet transform (DWT). The faulted phase voltage signal is captured at a sampling rate of 2.5 kHz. The sym8 wavelet function is used to decompose the signal into level 1 and to define an index function (INDF), which is obtained from the sum of absolute values of detail coefficients of the captured signal at the level 1 resolution. Finally, a decision function (DEF) is defined by computing the second derivative of the INDF. By evaluating the sign of the DEF, transient (arcing) faults are distinguished from permanent faults and also the secondary arc extinction instant can be identified. The significant advantage of the proposed algorithm is that it does not require any threshold level and therefore its performance is independent of fault location, line parameters and operating conditions. Furthermore, it can be used in transmission lines with reactor compensation. The proposed method has been successfully tested under a variety of fault location and load angle on a 400 kV overhead line, with and without reactor compensation, using the Electro-Magnetic Transient Program. The test results validate the algorithm ability in distinguishing between arcing and permanent faults and determining the instant of secondary arc extinction.

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“…On the other hand, unsuccessful reclosing during a permanent fault may aggravate the potential damage to the system and equipment [3]. For some extra-high-voltage lines, especially near generating plants, the classical automatic reclosing of breakers cannot be used, and therefore, adaptive reclosing schemes have been introduced over the past decades [4]. Such schemes prevent unsuccessful reclosing on permanent faults, and during transient (arcing) faults, reclosing is done only after full extinction of the secondary arc and complete de-ionization of the arc path.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Single-pole Auto-reclosure for Transmission Lines Using Sound Phases Currents and Wavelet Packet Transform

Jamali

Ghaffarzadeh

2010

Electric Power Components and Systems

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This article presents a novel approach for adaptive single-pole autoreclosing of power transmission lines under transient single-phase fault conditions by using a wavelet packet transform. In the proposed method, the mode current (sum of the currents of the two healthy phases) is captured with a sampling rate of 10 kHz and de-noised using the db8 wavelet packet to obtain signals with higher signal-tonoise ratio. The db8 wavelet packet is then used to decompose the mode current signal to attain the coefficients of wavelet nodes 131, 133, 134, 136, 137, 139, and 140 and to define an index, which is the sum of the absolute values of these node coefficients. The index is used to distinguish transient (arcing) faults from permanent faults and also to identify the secondary arc extinction instant. The proposed method has been successfully tested under a variety of fault conditions on a 500-kV overhead line using electromagnetic transient program. The test results validate the algorithm ability in distinguishing between transient and permanent faults and determining the instant of secondary arc extinction. The significant advantage of the proposed algorithm is that it does not need a case-based threshold level, and therefore, its performance is independent of fault location, line parameters, and pre-fault line loading conditions. Moreover, the algorithm can be used in transmission lines with reactor compensation.

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Evaluation of the Effect of Power Circuit Breaker Reclosing Practices on Turbine-Generators Shafts

Cited by 39 publications

References 10 publications

A Novel Algorithm for Fault Type Fast Diagnosis in Overhead Transmission Lines Using Hidden Markov Models

A Novel Algorithm for Fault Type Fast Diagnosis in Overhead Transmission Lines Using Hidden Markov Models

Adaptive single pole auto-reclosing using discrete wavelet transform

Adaptive Single-pole Auto-reclosure for Transmission Lines Using Sound Phases Currents and Wavelet Packet Transform

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