EHVAC transmission lines maintenance techniques in Indian perspective — A review

Mawle, Prashant P.; Dhomane, G. A.; Burade, Prakash

doi:10.1109/icgtspicc.2016.7955351

Cited by 3 publications

(2 citation statements)

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“…State enumeration is efficient when component failures probabilities are very minor and complex operating conditions are neglected [3], [15]. An organized methodology for maintenance management is reliability centered maintenance (RCM) with objective to provide proper preventive maintenance (PM)…”

Section: State Enumeration Methods and Monte Carlo Simulationmentioning

confidence: 99%

“…Markov method is used to apply LLMT for given model. Figure 2 shows semi-forced outage state space diagram of a state-space model for an outage of semi-enforced system, which refers to case in which a physical problem of a systems parameter which cause system outage applying to postponement of time which can rescheduled depends on an involuntary cause [3], [15], [17]. Fs is frequency of the problem taking place (occurrences/year).…”

Section: Semi Forced Outagementioning

confidence: 99%

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Application of artificial intelligence in early fault detection of transmission line-a case study in India

Mawle

Dhomane

Burade

2022

IJECE

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<span lang="EN-US">Reliable energy is ensured by the power quality, safety and security. For reliability and economic growth of transmission utilities, it is necessary to maintain continuity of supply, which is challenging under deregulated system. It is essential for utilities to conduct regular maintenance of transmission lines before supply interrupts. To protect line from fault, it is necessary to detect fault on line, its classification and location at the earliest. Various smart techniques along with application of artificial intelligence (AI) in power system are under investigation. This paper tries to find solution by identifying practical common faults occurred on transmission lines, and also suggests the suitable maintenance methodology. It uses the artificial neural network (ANN) method and live line maintenance technique (LLMT) for pre identification of a fault and subsequent predictive maintenance. Paper compares results of combination of ANN with LLMT and cold line maintenance technique (CLMT). Comparison of statistical analysis shows combine model of ANN and LLMT results in minimize outage time, failure rate which can improve system availability and increases revenue.</span>

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Section: State Enumeration Methods and Monte Carlo Simulationmentioning

confidence: 99%

Section: Semi Forced Outagementioning

confidence: 99%