Recent Trends in the Condition Monitoring of Transformers

Chakravorti, S.; Dey, Debangshu; Chatterjee, Biswendu

doi:10.1007/978-1-4471-5550-8

Cited by 113 publications

(88 citation statements)

References 4 publications

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“…. .`N i qˆTˆ1 00% (1) where n i = number of failures in i-th year; N i = number of transformers operating in the i-th year; and T = reference period (normally one year) The overall failure rate of substation and generator step-up units were all within 1% ( Table 2). The failure data of the full population were analyzed as a function of the primary location (component) in the transformer where the failure was initiated.…”

Section: Failure Statistic Of Power Transformersmentioning

confidence: 99%

“…Due to the increasing age of the transformer population condition assessment and thus onsite diagnostics are important issues to secure a reliable operation of the electrical power system. During the last decades, major works are being carried out for development of reliable and accurate condition assessment techniques [1]. Offline methods require disconnecting the transformer from the power network and are mainly used during scheduled inspections or when the transformer is already failure suspicious.…”

Section: Introductionmentioning

confidence: 99%

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Diagnostic Measurements for Power Transformers

et al. 2016

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Abstract:With the increasing age of the primary equipment of the electrical grids there exists also an increasing need to know its internal condition. For this purpose, off-and online diagnostic methods and systems for power transformers have been developed in recent years. Online monitoring is used continuously during operation and offers possibilities to record the relevant stresses which can affect the lifetime. The evaluation of these data offers the possibility of detecting oncoming faults early. In comparison to this, offline methods require disconnecting the transformer from the electrical grid and are used during planned inspections or when the transformer is already failure suspicious. This contribution presents the status and current trends of different diagnostic techniques of power transformers. It provides significant tutorial elements, backed up by case studies, results and some analysis. The broadness and improvements of the presented diagnostic techniques show that the power transformer is not anymore a black box that does not allow a view into its internal condition. Reliable and accurate condition assessment is possible leading to more efficient maintenance strategies.

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Section: Failure Statistic Of Power Transformersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Diagnostic Measurements for Power Transformers

et al. 2016

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“…Dielectric frequency response in the frequency domain (if it is drawn in logarithmic scale) would be approximately S-shaped [20][21][22][23]. This S-shaped curve includes a minimum point and a point of local maximum at low frequencies (typically below 1 Hz) and a local minimum point at high frequencies (usually above 10 Hz).…”

Section: Dfr Analysis By Sfrmentioning

confidence: 99%

Condition assessment of transformer insulation using dielectric frequency response analysis by artificial bee colony algorithm

Bigdeli

Aghajanloo

2016

Archives of Electrical Engineering

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Transformers are one of the most important components of the power system. It is important to maintain and assess the condition. Transformer lifetime depends on the life of its insulation and insulation life is also strongly influenced by moisture in the insulation. Due to importance of this issue, in this paper a new method is introduced for determining the moisture content of the transformer insulation system using dielectric response analysis in the frequency domain based on artificial bee colony algorithm. First, the master curve of dielectric response is modeled. Then, using proposed method the master curve and the measured dielectric response curves are compared. By analyzing the results of the comparison, the moisture content of paper insulation, electrical conductivity of the insulating oil and dielectric model dimensions are determined. Finally, the proposed method is applied to several practical samples to demonstrate its capabilities compared with the well-known conventional method.

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“…If the fault occurs on a higher level in the transmission system, entire towns or areas are affected by these outages [1]. Such situations are rare but their occurrence is increasing as the power system is ageing [2].…”

Section: Introductionmentioning

confidence: 99%

Gas measurements as a mean for identification of Partial Discharges in XLPE HV cable insulation

Janus¹,

Edin²,

Selva³

2017

NORD-IS

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Partial Discharges (PD) on high-voltage alternating current (HVAC) cables insulated with cross-linked polyethylene (XLPE) has a low occurrence, but consequences are usually severe since PD ultimately results in cable failures. Up until now the only efficient way to monitor HVAC cables for PD has been to install large coupling devices which are able to measure PDs directly from the power cables in order to verify if they are fault-free. These installations, usually of a temporary nature, are troublesome for several reasons like safety issues, measurement uncertainty, labor intensity etc.For the purpose to ultimately create a system that is able to be utilized for PD Detection by means of gas analysis, which is easily applicable in on site, on-line conditions, initial experiments were performed in order to investigate basic material properties of XLPE and to investigate the performance of tin oxide (SnO 2 ) sensors for such an application. For this purpose a specialized test cell was developed in order to be able to investigate different conditions which can be expected in a cable insulation system. It was found from the experiments that surface discharges are detectable by means of gas analysis and that these gases penetrate an XLPE sample. It was also demonstrated that the SnO 2 based sensor system displays a good selectivity to the gases emitted by PD and remain inert towards other gases emitted from XLPE samples.

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Recent Trends in the Condition Monitoring of Transformers

Cited by 113 publications

References 4 publications

Diagnostic Measurements for Power Transformers

Diagnostic Measurements for Power Transformers

Condition assessment of transformer insulation using dielectric frequency response analysis by artificial bee colony algorithm

Gas measurements as a mean for identification of Partial Discharges in XLPE HV cable insulation

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