Online detection of partial discharge inside power transformer winding through IFRA
- Authors: Mohseni, Bahar , Hashemnia, Naser , Islam, Syed
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 2017 IEEE Power and Energy Society General Meeting, PESGM 2017; Chicago, United States; 16th-20th July 2017 Vol. 2018, p. 1-5
- Full Text: false
- Reviewed:
- Description: Predictive maintenance offers substantial benefits for detecting the early signs of power transformer faults before they burgeon into catastrophic failures. Online impulse frequency response analysis is a recently-developed diagnostic method for in service transformer with a promising outlook. This paper aims to propose an online partial discharge detection method the online IFRA test. To emulate the dynamic performance characteristics of in service transformer, 3D finite element model of the transformer is calculated in Maxwell Software. In post processing, the FEM sub-circuit model is exported into an external Maxwell Spice circuit to study the terminal behaviors of the transformer. A pulse signal simulating PD is injected between sections of the LV winding. The S transform is then applied to the recorded input and output signals in healthy and faulty conditions to construct the electrical impedance as well as the time-frequency contours of the transient responses. Also, a mechanical deformation is imposed on the transformer to compare its impact on online IFRA to the impact of internal partial discharge.
Application of S transform for detection of external interferences in online transformer impulse frequency response analysis
- Authors: Mohseni, Bahar , Hashemnia, Naser , Islam, Syed
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 17th IEEE International Conference on Environment and Electrical Engineering and 2017 1st IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2017; Milan, Italy; 6th-9th June 2017 p. 1-4
- Full Text: false
- Reviewed:
- Description: Online impulse frequency response analysis is a recently-developed diagnostic method for in service transformer with a promising outlook. This paper aims to detect the impact of external interferences including pulse shaped interferences from switching operations and other phenomena in the power system on the frequency response of the transformer. For modeling the transformer for online IFRA, a simulation approach based on finite element analysis (FEA) and circuit analysis is used. In this approach, instead of using a linear model with static parameters, 3D finite element model of the transformer is calculated in Maxwell Software and then exported into an external Maxwell Spice circuit which allows for study the terminal behaviors of the transformer. A modified S transform is then applied to the recorded input and output signals in healthy and faulty conditions to construct the electrical impedance as well as the time-frequency contours of the transient responses.
Understanding online frequency response signatures for transformer winding deformation: Axial displacement simulation
- Authors: Zhao, Zhongyong , Islam, Syed , Hashemnia, Naser , Hu, Di , Yao, Chenguo
- Date: 2016
- Type: Text , Conference proceedings , Conference paper
- Relation: 2016 International Conference on Condition Monitoring and Diagnosis, CMD 2016; Xi'an, China; 25th-28th September 2016 p. 404-407
- Full Text: false
- Reviewed:
- Description: The power transformer is considered as the most critical and expensive device in substation, however, the irreversible transformer winding mechanical deformation can eventually develop into catastrophic failure if no further steps are taken in a proper way, which would cause the outage of transformer and the significant economic losses. Online frequency response analysis (FRA) has been proven to be a promising tool for condition monitoring and diagnosing of winding deformation. Online FRA relies on graphic comparison of signatures, but up to now, there is no standard and practical interpretation code for signatures classification and quantification. This paper particularly studies the characteristic of online FRA signatures under the winding axial displacement mode, in which the 3D finite element electromagnetic analysis and online transformer equivalent high frequency electrical model are established as auxiliary tools to precisely emulate winding axial displacement. Results of this simulation will provide guidance on understanding online frequency response signatures.
Condition assessment of power transformer bushing using SFRA and DGA as auxiliary tools
- Authors: Mohseni, Bahar , Hashemnia, Naser , Islam, Syed
- Date: 2016
- Type: Text , Conference proceedings , Conference paper
- Relation: 2016 IEEE International Conference on Power System Technology, POWERCON 2016; Wollongong, Australia; 28th September-1st October 2016 p. 1-4
- Full Text: false
- Reviewed:
- Description: Dielectric insulation of a transformer bushing deteriorates as a function of temperature, oxidation, and moisture. This causes accelerated aging of oil and cellulosic solid insulation, generating fault gases within bushing oil and eventual permanent failure. To prevent such failures, effective analyses and diagnoses need to be investigated. Dissolved Gas Analysis (DGA) can give the indication of internal abnormalities inside the transformer bushing. In addition, Frequency response analysis (FRA) is a widely accepted tool for mechanical deformation diagnosis within power transformers. Although a large number of studies have been conducted on the detection of transformer winding deformation by FRA technique, the impact of bushing faults on the transformer FRA signature has not been sufficiently investigated. It is the goal of this paper to propose precise simulation as well as practical analyses demonstrating the impact of bushing faults on the FRA signature. A real transformer bushing geometry is modelled through 3D finite element analysis (FEM) on which different bushing faults are emulated. To verify the derived simulation results, DGA of transformer oil as well as FRA are performed on a three-phase, 132 kV, 315 MVA power transformer. It can be observed clearly from the results, that bushing faults have an impact on the FRA signature and DGA of the power transformer.
Offline to online mechanical deformation diagnosis for power transformers
- Authors: Hashemnia, Naser , Masoum, Mohammad , Abu-Siada, Ahmed , Islam, Syed
- Date: 2014
- Type: Text , Conference proceedings , Conference paper
- Relation: 24th Australasian Universities Power Engineering Conference, AUPEC 2014; Perth, Australia; 28th September-1st October 2014 p. 1-5
- Full Text: false
- Reviewed:
- Description: Internal winding deformations of power transformers can be detected using the conventional offline frequency response analysis (FRA) which is a well-known and widely accepted tool for the detection of winding and core deformations. In addition of being offline technique, interpretation of FRA signature is based on graphical analysis that requires skilled personnel as there is no reliable standard code for FRA signature identification and quantification. This paper presents the possibility of using an alternative online technique based on construction a voltage-current (ΔV-I) locus of the operating transformer and considering it as a reference signature. In order to fully explore the performance and reliability of the new proposed approach particularly for real-life distribution transformers, the paper investigates and compares the performance of the proposed and the FRA approaches for disk space variation and axial displacement faults. The transformer distributed parameter model is used to simulate FRA signatures while a detailed three-dimensional finite element model is used to generate the ΔV-I louses for healthy and faulty operating conditions. Simulation results are compared to highlight the advantages and limitations of the two internal fault detection strategies.
Detection of power transformer disk space variation and core deformation using frequency response analysis
- Authors: Hashemnia, Naser , Abu-Siada, Ahmed , Islam, Syed
- Date: 2014
- Type: Text , Conference proceedings , Conference paper
- Relation: 2014 International Conference on Condition Monitoring and Diagnosis, CMD 2014; Jeju, Korea; 21st September 2014
- Full Text: false
- Reviewed:
- Description: Frequency response analysis (FRA) has become a widely accepted tool to detect power transformer winding deformation due to the development of FRA test equipment. Because FRA relies on graphical analysis, interpretation of its signature is a very specialized area that calls for skilled personnel, as so far, there is no reliable standard code for FRA signature classification and quantification. Many researchers investigated the impact of various mechanical winding deformations on the transformer FRA signature by changing particular electrical parameters of the transformer equivalent electrical circuit. None of them however, investigated the impact of physical fault levels on the transformer FRA signature as it is very difficult to implement faults within real transformer without damaging it. In this paper, the physical geometrical dimension of a power transformer is simulated using 3D finite element analysis to emulate the real transformer operation. Physical core deformation and disk space variation are simulated and the impact of each fault on the transformer FRA signature is investigated.
Impact of axial displacement on power transformer FRA signature
- Authors: Hashemnia, Naser , Abu-Siada, Ahmed , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 2013 IEEE Power and Energy Society General Meeting, PES 2013; Vancouver, Canada; 21st-25th July 2013 p. 1-4
- Full Text:
- Reviewed:
- Description: Frequency response analysis (FRA) is gaining global popularity in detecting power transformer winding movement due to the development of FRA test equipment. However, because FRA relies on graphical analysis, interpretation of its signatures is still a very specialized area that calls for skillful personnel to detect the sort and likely place of the fault as so far, there is no reliable standard code for FRA signature classification and quantification. This paper investigates the impact of transformer winding axial displacement on its FRA signature as a step toward the establishment of reliable codes for FRA interpretation. In this context a detailed model for a singlephase transformer is simulated using 3D finite element analysis to emulate a close to real transformer. The impact of axial displacement on the electrical distributed parameters model that are calculated based on the transformer physical dimension is examined to investigate how model’s parameters including inductance and capacitance matrices change when axial displacement takes place within a power transformer.
Application of online impulse technique to diagnose inter-turn short circuit in transformer windings
- Authors: Mohseni, Bahar , Hashemnia, Naser , Islam, Syed , Zhao, Zhongyong
- Date: 2016
- Type: Text , Conference proceedings , Conference paper
- Relation: 2016 Australasian Universities Power Engineering Conference, AUPEC 2016; Brisbane, Australia; 25th-28th September 2016 p. 1-4
- Full Text: false
- Reviewed:
- Description: Inter-turn short circuit fault is a significant problem in power transformers which if not detected at early stages, can propagate in power networks and eventually burgeon into catastrophic faults and substantial costs. Online frequency response analysis (FRA) is well on its way of becoming a reliable tool for condition monitoring and fault detection of transformer since no disconnection is required to conduct the test. Among the two existing FRA methods, sweep frequency response analysis (SFRA) and impulse frequency response analysis (IFRA), IFRA has reached the potential for online application. This contribution aims to detect interturn short circuit fault through online transfer function monitoring of the power transformer winding using the impulse technique, a method which utilizes a capacitive coupling circuit to inject a controlled high voltage nanosecond pulse into the transformer winding. To this end, 3D finite element electromagnetic analysis and transformer equivalent high frequency electrical model have been used as auxiliary tools to precisely emulate the real transformer operation and investigate the impact of inter-turn short-circuit faults on the transformer equivalent circuit parameters and thereby, transformer online FRA signature. Simulations were performed with two different levels of interturn fault severity. The results show that inter-turn short circuit can be effectively detected with the transformer in service using the impulse method.