Transmission Line Maintenance Management Using Early Fault Detection Technique

Mawle, Prashant P.; Dhomane, G. A.; Dharmadhikari, S. P.

doi:10.1109/stpec49749.2020.9297798

Cited by 3 publications

(3 citation statements)

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“…Technical operating and maintenance persons can measure parameters of energy systems, consumption for heavy electrical loads connected in that area, observe start up time, efficiency and economy measure of electrical equipment [11]. Recorded information is used to assess system reliability, calculate profit of reliability due to maintenance of each section, produce maintenance ranking order by applying benefit/cost ratio index [1], [7], [12]. Predictive maintenance (PdM) imparts condition monitoring and asset management as keys [13].…”

Section: Transmission Line Fault Analysis Methodsmentioning

confidence: 99%

“…Maintenance activities needs to be pre-scheduled in advance for all types of maintenance using ON line maintenance technique or Off-line maintenance technique. A survey said that for the year 2020, there were approximate 1,160 faults in the Indian grid, in that 65% of faults accounting on transmission lines; 20% faults related to the transformer equipment, 10% faults due to bus bar and other equipment in substation and 5% faults due to other reasons [1]. Transmission system condition study consists of age, stress condition, failure mode, safety, and working environment condition.…”

Section: Introductionmentioning

confidence: 99%

“…To addresses the issues during load forecasting and data outages various artificial models are used. Analogous theories of modeling may be used to indecisions of different information such as equipment factors and grades which impacted by different environmental parameters [1], [10].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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