Investigation on Flashover Development Mechanism of Polymeric Insulators by Time Frequency Analysis

Muniraj, C.; Krishnamoorthi, K. P.; Chandrasekar, S.

doi:10.5370/jeet.2013.8.6.1503

Cited by 6 publications

(4 citation statements)

References 15 publications

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“…It is important to note that in practice the pollution distribution in non-uniform over the surface and the leakage current density is non-uniform over the insulator surface and in some areas sufficient heat is developed leading to the formation of dry bands [18]. Hence, multiple light sensors should be embedded on the top surface as well as the bottom surface.…”

Section: Esdd Modelling and Discussionmentioning

confidence: 99%

Flashover monitoring system using wireless sensor network

Al-Absi

Baroudi

Al-Soufi

et al. 2014

2014 IEEE International Conference on Power and Energy (PECon)

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Flashover of insulators in transmission and distribution electric power systems causes a reduction of the system reliability and costly outages for the power company and their customers. In this paper, we present a system in which a wireless sensor network is used for continuous wirelessly monitoring contamination in high voltage insulators. The new system consists of different sensor nodes (e.g. humidity, temperature and dust) mounted on a dummy insulator that has to be placed close to high voltage substation or transmission line tower. The proposed approach is based on the Equivalent Salt Deposit Density (ESDD) severity method in order to check the pollution level on the insulator and to correlate with flashover voltage levels of the insulator string. In this approach, the photons measurement level (i.e. light intensity) is adopted as an indicator to the accumulated pollution level on the insulators. Extensive lab tests were carried out using different pollutants. ESDD measurements have been collected for all the pollution tests performed in the lab and a relationship between these values and the light intensity values has been established to correctly model the contamination level. Using, the established relationship between EESD and light intensity shall enable the power system control unit to accurately predict the flashover and accordingly schedule its crew to visit the site and clean these insulators. Index Terms--Flashover, High Voltage Insulator, Transmission Line Monitoring, Wireless sensor networks (WSN).I.

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Section: Esdd Modelling and Discussionmentioning

confidence: 99%

Flashover monitoring system using wireless sensor network

Al-Absi

Baroudi

Al-Soufi

et al. 2014

2014 IEEE International Conference on Power and Energy (PECon)

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“…At present, the common technique to predict the flashover is by means of analysis of leakage current. It indicates the surges occurring near the current peaks of dry band arcing phenomena [5][6][7][8]. For a given insulator, evolution of leakage waveform depends essentially on the changes occurring at the surface pollution layer and surface wetness of the insulator.…”

Section: Introductionmentioning

confidence: 99%

Flashover Prediction of Polymeric Insulators Using PD Signal Time-Frequency Analysis and BPA Neural Network Technique

Narayanan¹,

Karthik²,

Chandrasekar³

2014

Journal of Electrical Engineering and Technology

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-Flashover of power transmission line insulators is a major threat to the reliable operation of power system. This paper deals with the flashover prediction of polymeric insulators used in power transmission line applications using the novel condition monitoring technique developed by PD signal time-frequency map and neural network technique. Laboratory experiments on polymeric insulators were carried out as per IEC 60507 under AC voltage, at different humidity and contamination levels using NaCl as a contaminant. Partial discharge signals were acquired using advanced ultra wide band detection system. Salient features from the Time-Frequency map and PRPD pattern at different pollution levels were extracted. The flashover prediction of polymeric insulators was automated using artificial neural network (ANN) with back propagation algorithm (BPA). From the results, it can be speculated that PD signal feature extraction along with back propagation classification is a well suited technique to predict flashover of polymeric insulators.

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“…Hence pollution performance studies considering the aging effects of polymeric insulators have created lot of interest among researchers. In many earlier papers, pollution performance studies have been carried out using LC measurement [11][12][13][14][15]. In recent times, PD detection and analysis is a well recognized insulation condition monitoring method in determining the quality of insulation.…”

Section: Introductionmentioning

confidence: 99%

Investigations of Accelerated Aged Polymeric Insulators Using Partial Discharge Signal Measurement and Analysis

Mekala¹,

Chandrasekar²,

Ravindran³

2015

Journal of Electrical Engineering and Technology

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-Reduction in pollution performance of polymeric insulators, aged due to water absorption stress and thermal stress, is a major threat to the reliable operation of power transmission and distribution system. Formation of partial discharges on the surface of wet polluted insulator plays a major role in determining the life time and pollution performance of outdoor polymeric insulators. However, reports on partial discharge characteristics of water absorption stress aged and thermal aged polymeric insulators are scanty. This paper discusses the pollution performance characteristics of accelerated aged polymeric insulators using the advanced ultra wide band PD signal measurement and analysis. Laboratory experiments on accelerated aged polymeric insulators were carried out as per IEC 60507 under AC voltage, at different humidity and contamination levels using NaCl as a contaminant. PRPD pattern and Time-Frequency map analysis of PD signals were carried out. From the results, it can be speculated that PD analysis is a well suited technique to understand the pollution performance of aged polymeric insulators.

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Investigation on Flashover Development Mechanism of Polymeric Insulators by Time Frequency Analysis

Cited by 6 publications

References 15 publications

Flashover monitoring system using wireless sensor network

Flashover monitoring system using wireless sensor network

Flashover Prediction of Polymeric Insulators Using PD Signal Time-Frequency Analysis and BPA Neural Network Technique

Investigations of Accelerated Aged Polymeric Insulators Using Partial Discharge Signal Measurement and Analysis

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