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Assessment of insulation condition by sensing and subsequent analysis of oil-impregnated paper response at periodic intervals is necessary for reliable operation of transformers. Sensing frequency domain insulation response requires the application of either a sinusoidal excitation voltage (over a wide range) or a custom excitation waveform. This not only requires a specially designed variable-frequency variable-amplitude excitation voltage source but also makes measurement practically problematic. Measurement of low-frequency data is time-consuming and the data tends to get affected by field noise. In comparison, a simpler and cheaper alternative is the analysis of time-domain insulation response. This involves the measurement of low amplitude polarization and depolarization current. A pico-ammeter or Electrometer is generally used for this purpose. The available interpretation scheme of time domain response sensed using Electrometer does not consider the de-trapping charge’s polarity. The result presented in the paper shows that such an assumption inadvertently leads to inaccurate diagnosis. This, in turn, generates doubt regarding the current sensing capability of the Electrometer involved. In the present work, a better interpretation scheme of the data sensed by the Electrometer is discussed. The significance and influence of de-trapped charge polarity on polarization and depolarization currents are investigated. The analysis is tested on data collected from real-life in-service power transformers. [ABSTRACT FROM AUTHOR]

Analysis of detrapped charge [evaluated from polarization–depolarization current (PDC)] is effective in carrying out insulation diagnosis. However, computation of detrapped charge requires PDC data for at least 1600 s (PDCs each measured for 800 s). Such a technique of obtaining detrapped charge from short-duration PDC data considers few assumptions (including modeling of detrapping current by a straight line), which might not always be true for real-life equipment. Furthermore, PDC data are susceptible to noise and other environmental factors. Hence, it may be practically difficult to allow a measurement time of 1600 s during field measurement. Therefore, it is advisable to reduce the measurement time as well as the volume of data required. In this article, a method has been proposed, which is capable of estimating detrapped charge using only polarization current measured for 600 s. In addition, some unique advantages offered by the proposed method are also discussed in this article. The proposed technique is tested on data collected from several real-life in-service transformers. [ABSTRACT FROM AUTHOR]

Various types of insulation models with time‐invariant parameters are available in the literature. Depending on the aging sensitive performance parameters to be evaluated, different models need to be employed (e.g. XY model for oil and paper‐conductivity, conventional Debye model (CDM) for paper‐moisture and tanδ). While the XY model cannot be used for estimating paper‐moisture directly, analysis based on CDM parameter becomes dependent on its branch parameters, which are non‐unique. These factors lead to either incomplete or ambiguous insulation diagnosis. These problems are resolved using the proposed new insulation model containing unique time‐varying branch parameters. Another major advantage of the proposed model is that it can be used to evaluate a host of performance parameters (like paper‐conductivity, oil and paper‐moisture, dielectric loss) thus giving a complete picture of the insulation concerned. The application of the proposed model is also tested on data collected from several real‐life power transformers. [ABSTRACT FROM AUTHOR]

Polarisation current profile varies non‐linearly with a magnitude of charging voltage. This implies performance parameters obtained from polarisation–depolarisation current and those measured using specialised equipment cannot always be compared. Results reported in this study suggested that the non‐linearity in insulation response can be explained in terms of the interaction between space charge and insulation conductivity. The influence of using different charging voltages and its effect on performance parameter calculation is investigated in this study with the help of laboratory samples. It is shown in this study that with the help of a trained artificial neural network, it is possible to identify the charging voltage at which insulation response exhibits minimum non‐linearity. To test the accuracy of the proposed method performance parameters measured using commercial equipment are compared with those calculated from the polarisation current profile. [ABSTRACT FROM AUTHOR]

Induction period evaluated from time domain dielectric response of oil‐paper insulation (OPI) contains information related to heat dissipating property of oil. In the present paper, effect of aging sensitive oil properties on the value of induction period is investigated. Three types of dielectric liquids (pure mineral oil, synthetic ester, mixture of synthetic ester, and mineral oil) are considered for the present work. A neural network (NN) is used for modelling the non‐linear relationship between induction period and various oil properties. The trained network is subsequently used to study the influence of various oil properties on induction period. [ABSTRACT FROM AUTHOR]

The analysis of dielectric response function obtained from the power transformer is a well-accepted technique in insulation diagnosis. A convenient way of analysing time-domain dielectric response φ(t) is the formulation of simple resistance -capacitance-based circuits like the conventional Debye model (CDM) or the modified Debye model (MDM) that are capable of modelling φ(t). However, available techniques do not guarantee unique branch parameters of such circuits for a given φ(t). In fact, the branch parameters are known to depend on the curve-fitting procedure opted during model formulation. This makes accuracy of CDM and MDM parameter-based diagnosis techniques less reliable. Furthermore, it seems logical to analyse the time-domain dielectric response of oil-paper insulation using a model containing time-varying parameters. In this study, a methodology is proposed using which such an insulation model (containing time-varying parameters) is formulated using timedomain insulation response. Related analysis presented suggests that the proposed model is immune to problems associated with available insulation models (containing time-invariant parameters). The performance of the proposed model in indicating insulation condition is tested on data obtained from several real-life power transformers. [ABSTRACT FROM AUTHOR]