Browsing by Author "Hettiwatte, S. N"

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Analysis and interpretation of dissolved gases in transformer oil: A case study
(IEEE, 2012-09-23) Hettiwatte, S. N; Fonseka, H. A
Condition monitoring plays a vital role in any asset management plan. Dissolved gas analysis is a routine test carried out on power transformers to monitor their condition. Four power transformers selected from a repository of power transformers due to their dissolved gas levels exceeding the normal levels are analyzed using the Key Gas Method, the Roger's Ratio Method and the Duval Triangle Method to diagnose any faults. The results show that for some transformers all three diagnosis methods agree on the type of fault, whilst for others it is not so straightforward in diagnoses. In this study, the condition of each power transformer is predicted using the above methods.
Open Access
Application of Parzen Window estimation for incipient fault diagnosis in power transformers
(The Institution of Engineering and Technology, 2018-12) Islam, M. D. M; Hettiwatte, S. N; Lee, G
Accurate faults diagnosis in power transformers is important for utilities to schedule maintenance and minimises the operation cost. Dissolved gas analysis (DGA) is one of the proven and widely accepted tools for incipient fault diagnosis in power transformers. To improve the accuracy and solve the cases that cannot be classified using Rogers’ Ratios, IEC ratios and Duval triangles methods, a novel DGA technique based on Parzen window estimation have been presented in this study. The model uses the concentrations of five combustible hydrocarbon gases: methane, ethane, ethylene, acetylene and hydrogen to compute the probability of transformers fault categories. Performance of the proposed method has been evaluated against different conventional techniques and artificial intelligence-based approaches such as support vector machines, artificial neural networks, rough sets analysis and extreme learning machines for the same set of transformers. A comparison with other soft computing approaches shows that the proposed method is reliable and effective for incipient fault diagnosis in power transformers.
Embargo
Calculating a health index for power transformers using a subsystem-based GRNN approach
(IEEE, 2017-11-07) Islam, M; Lee, G; Hettiwatte, S. N; Williams, K
A power transformer is one of the most crucial items of equipment in the electricity supply chain. The reliability of this valuable asset is strongly dependent on the condition of its subsystems such as insulation, core, windings, bushings and tap changer. Integration of various measured parameters of these subsystems makes it possible to evaluate the overall health condition of an in-service transformer. This paper develops an artificially intelligent algorithm based on multiple general regression neural networks to combine the operating condition of various subsystems of a transformer to form a quantitative health index. The model is developed using a training set derived from four conditional boundaries based on IEEE standards, the literature and the knowledge of transformer experts. Performance of the proposed method is compared with expert classifications using a database of 345 power transformers. This shows that the proposed method is reliable and effective for condition assessment and is sensitive to poor condition of any single subsystem.
Open Access
CityTour Bus Locator and Bus Booking Mobile Application
(NSBM, Colombo, 2018-08-25) Chandrasiri, S; Pitipana, H; Hettiwatte, S. N
The public bus transportation system has the direct impact on economic development of the country. Scheduling, tracking and monitoring of the public bus transportation is one of the major issues for any public transportation sector. Currently, there are many vehicles tracking systems available using Global Positioning Systems (GPS) technology. At present, bus passengers are unable to gather enough information which would lead up to a stress-free bus ride. Under current conditions a passenger has to wait in the bus stand without having any prior idea about the buses. ‘CityTour’ application assists passengers and the conductor to use bus service in more stress-free, well-organized and a suggestive manner. “CityTour”, is the cross-platform application implemented with the sole purpose of addressing these problems a passenger has. The application will predict the next Bus’s arrival time, seat reservation and a rating which will give an indication regarding the quality of the service offered. Bus conductor has a say in whether a passenger gets a seat or not. ‘CityTour’ application enables the “real-time” passenger bus communication that would lead to a better collaboration and make their day-to-day work easier for both the parties.
Open Access
Condition monitoring in New Zealand power transformers
(nternational Conference on Condition Monitoring and Diagnosis (CMD2010), 2010) Hettiwatte, S. N; Fonseka, H. A
— Transpower owns and operates New Zealand’s high voltage electricity grid which includes approximately 725 in service power transformers [1]. Presently, condition monitoring of these units is routinely carried out by oil testing (moisture, acidity and dielectric breakdown) and using dissolved gas analysis (DGA), (every year), and winding resistance, insulation resistance, and bushing power factor tests (every four years). However, since the average age of a power transformer in New Zealand is nearly 40 years [1], it is considered that online condition monitoring of important transformers or transformers that have known issues is carried out to identify any incipient faults. The online condition monitoring in existing power transformers is hoped to minimize the risk of sudden failures and thereby prolong the in service life. It is equally important to decide on what to monitor in a power transformer and how to monitor, and these are also governed by the budgetary constraints. Transpower is in the process of acquiring online condition monitoring units for some of the new large power transformers it plans to purchase and will also retrofit such units to some old transformers as required. This paper presents the condition monitoring techniques currently used by Transpower on power transformers, and the online condition monitoring techniques for new and existing power transformers.
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Corrosion detection in steel reinforced aluminium conductor cables
(IEEE, 2014-09-28) Jaffrey, N. A; Hettiwatte, S. N
Aluminum Conductor Steel Reinforced (ACSR) cables, as part of transmission lines, are used in severe environments in coastal areas and industrial zones for many years. These cables are affected by galvanic corrosion in the interface between the aluminum and steel strands. This paper investigates the existing methods of corrosion detection used in ACSR cables of overhead transmission lines, and estimates the location of corrosion through simulation in a computer program. The paper also analyses two promising methods of corrosion detection, namely “electromagnetic induction” and “time domain reflectometry (TDR)”, and explains in detail their principle of operation and efficiency. The paper then thoroughly investigates the time domain reflectometry techniques by implementing it in a computer program, and the simulation results are discussed.
Embargo
An electrical PD location method applied to a continuous disc type transformer winding
(IEEE, 2003-06-01) Hettiwatte, S. N; Wang, Z. D; Crossley, P. A; Jarman, P; Edwards, G; Darwin, A
A 6.6 kV continuous disc type winding of a distribution transformer is used to investigate the propagation of partial discharges (PD) with the aim of location. The winding was modelled, as multiconductor transmission lines with each turn represented by a transmission line. This approach results in the model being valid up to a few MHz in frequency. The validity of the model was confirmed by impedance measurements on the winding. The transfer functions calculated between probable PD source locations to winding terminals showed that the troughs (or zeros) change in frequency with the location of PD source and hence can be used for the location of PD. Transfer functions obtained experimentally using a discharge calibrator as the PD source, showed very good agreement with the calculations.
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Estimating transformer parameters for partial discharge location
(IEEE, 2014) Hettiwatte, S. N; Wang, Z. D; Crossley, P. A
Partial discharge (PD) location in power transformers using electrical methods require transformer parameters to estimate the PD location. Previous research using a lumped parameter model of a transformer consisting of inductance (L), series capacitance (K) and shunt capacitance (C) has shown an algorithm for PD location. This algorithm does not require L, K and C values for the transformer in their explicit form. Rather, the products LC and LK are required. This paper presents three methods of estimating LC and LK values for a power transformer, which could then be used for PD location. The paper shows that all three methods give identical results confirming that either of these methods could be used for estimating LC and LK values. Results based on impedance measurements from two transformer windings are also presented.
Embargo
Experimental investigation into the propagation of partial discharge pulses in transformers
(IEEE, 2012-01-27) Hettiwatte, S. N; Wang, Z. D; Crossley, P. A; Darwin, A; Edwards, G
An experimental investigation into the propagation behaviour of partial discharge (PD) pulses in a continuous disc type 6.6kV transformer winding is described in this paper. PD pulses were injected into the winding using a calibrator and the resulting current signals at the line and neutral end terminals measured using wide band current transformers. The location of the troughs (or zeros) in the frequency spectra of the measured signals change in accordance with the position of the injected pulse. The crests (or poles) in the spectra convey information about the resonance frequencies of the winding and are not affected by the position of the injected pulse. The measured spectra are compared with the spectra generated by a simulation model and although differences exist the overall shape and location of the poles and zeros are similar.
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Improvement of voltage magnitude and unbalance in LV network by implementing residential demand response
(IEEE, 2017-07-16) Rahman, M. D. M; Hettiwatte, S. N; Shafiullah, G. M; Arefi, A; Pezeshki, H
Maintaining voltage levels in low voltage (LV) distribution network within the standard limits is the main constraining factor in increasing network hosting ability for high penetration of rooftop photovoltaic (PV). Distribution system operator must be able to take corrective approach to avoid critical voltage unbalance and magnitude violations where rooftop PV generation is high. This study presents an effective method for voltage management in distribution networks through implementation of optimal residential demand response (DR) and transformer tap setting using a particle swarm optimization algorithm. The method is comprehensively verified on a real Australian distribution network with considerable unbalance and distributed generations. The simulation results show that PV penetration of the network can be further increased with the proposed approach.
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Incipient fault diagnosis in power transformers by clustering and adapted KNN
(IEEE, 2016-09-25) Islam, M. D. M; Lee, G; Hettiwatte, S. N
Dissolved Gas Analysis (DGA) is one of the proven methods for incipient fault diagnosis in power transformers. In this paper, a novel DGA method is proposed based on a clustering and cumulative voting technique to resolve the conflicts that take place in the Duval Triangles, Rogers' Ratios and IEC Ratios Method. Clustering technique groups the highly similar faults into a cluster and makes a virtual boundary between dissimilar data. The k-Nearest Neighbor (KNN) algorithm is used for indexing the three nearest neighbors from an unknown transformer data point and allows them to vote for single or multiple faults categories. The cumulative votes have been used to identify a transformer fault category. Performances of the proposed method have been compared with different established methods. The experimental classifications with both published and utility provided data show that the proposed method can significantly improve the incipient fault diagnosis accuracy in power transformers.
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An intelligent approach of achieving demand response by fuzzy logic based domestic load management
(IEEE, 2014-09-28) Rahman, M. D. M; Hettiwatte, S. N; Gyamfi, S
Demand response is an important demand-side resource that allows consumers to consume less electricity when the system is under stress. Existing demand response mechanism reduces power consumption by forcefully shutting down the consumers' loads or punishing the consumers with high consumption prices during high peak hours without considering their comfort level. This paper presents a methodology to design a model for domestic load management based on fuzzy logic techniques where three optimization parameters - comfort, cost and demand response are taken into account. Furthermore a comparative analysis for the power consumption and cost saving performance is carried out to show the benefit of using renewable energy sources along with a fuzzy logic based load controller. Simulation results show that the proposed controller successfully limits the power consumption during the peak hours and concurrently maximizes the savings of energy consumption cost without violating consumers' comfort level.
Embargo
A measurements-based discharge location algorithm for plain disc winding power transformers
(IEEE, 2005-06-20) Wang, Z. D; Hettiwatte, S. N; Crossley, P. A
A measurements-based electrical method for locating partial discharges (PD) in transformers is described in the paper. This location method relies on the series resonance frequencies of the signals produced at the transformer terminals by a discharge on the winding. Based on the equivalent circuit of plain disc type winding which consists of series inductance (L), series capacitance (K) and shunt capacitance to earth (C) of the winding, an analytical location algorithm is derived which gives the relationship between the location of a discharge and its terminal response's series resonance frequencies. LKC parameters of the equivalent circuit can be estimated using the series resonance frequencies of a calibration signal measured at the bushing tap during PD calibration. The PD location algorithm was tested on 11 kV transformer winding using signals produced by a discharge simulator and real discharges, and the results confirm its validity with a location accuracy of better than 10% of the winding length. However, blind area where this location algorithm is not applicable does exist near the neutral of the winding and far away from the measuring terminal. Since this location algorithm uses the series resonance frequencies below 500 kHz, it can be implemented with conventional PD measuring circuitry and instruments to detect and locate discharges in power transformers.
Embargo
Missing measurement estimation of power transformers using a GRNN
(IEEE, 2017-11-19) Islam, M. D. M; Hettiwatte, S. N; Lee, G
Many industrial devices are monitored by measuring several attributes at a time. For electrical power transformers their condition can be monitored by measuring electrical characteristics such as frequency response and dissolved gas concentrations in insulating oil. These vectors can be processed to indicate the health of a transformer and predict its probability of failure. One weakness of this approach is that missing measurements render the vector incomplete and unusable. A solution is to estimate missing measurements using a General Regression Neural Network on the assumption that they are correlated with other measurements. If these missing values are completed, the entire vector of measurements can be used as an input to a pattern classifier. To test this approach, known values were deliberately omitted allowing an estimate to be compared with actual values. Tests show the method is able to accurately estimate missing values based on a finite set of complete observations.
Open Access
A nearest neighbour clustering approach for incipient fault diagnosis of power transformers
(Springer Berlin Heidelberg, 2017-09) Islam, M. D. M; Hettiwatte, S. N; Lee, G
Dissolved gas analysis (DGA) is one of the popular and widely accepted methods for fault diagnosis in power transformers. This paper presents a novel DGA technique to improve the diagnosis accuracy of transformers by analysing the concentrations of five key gases produced in transformers. The proposed approach uses a clustering and cumulative voting technique to resolve the conflicts and deal with the cases that cannot be classified using Duval Triangles, Rogers’ Ratios and IEC Ratios Methods. Clustering techniques group the highly similar faults into a cluster providing a virtual boundary between dissimilar data. A cluster of data points may contain single or multiple types of faulty transformers’ data with different distinguishable percentages. The k-nearest neighbour (KNN) algorithm is used for indexing the three closest clusters from an unknown transformer data point and allows them to vote for single or multiple faults categories. The cumulative votes have been used to identify a transformer’s fault category. Performance of the proposed method has been compared with different conventional methods currently used such as Duval Triangles, Rogers’ Ratios and IEC Ratios Method along with published results using computational and machine learning techniques such as rough sets analysis, neural networks (NNs), support vector machines (SVMs), extreme learning machines (ELM) and fuzzy logic. The experimental comparison with both published and utility provided data show that the proposed method can significantly improve the incipient fault diagnosis accuracy in power transformers.
Open Access
A novel visualisation technique for dissolved gas analysis datasets–A case study
(Australasian Universities Power Engineering Conference, 2013) Fonseka, H. A; Hettiwatte, S. N; Lee, G
Dissolved gas analysis is the most widely used diagnostic test in power transformers. There are established methods used in industry for interpreting DGA results. Among these are the IEEE Key Gas Method, Rogers’ Ratios and the Duval Triangle. However, collectively these methods can lead to conflicting results or unclassifiable measurements. This paper presents a visualization technique for interpreting DGA results to mitigate these effects, based on Kernel Principal Component Analysis. DGA measurements from more than 200 power transformers are used to validate the approach.
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Penetration maximisation of residential rooftop photovoltaic using demand response
(IEEE, 2016-10-06) Rahman, M. D. M; Arefi, A; Shafiullah, G. M; Hettiwatte, S. N
The increasing penetration of roof-top photovoltaic system has highlighted immediate needs for addressing power quality concerns, especially where PV generation exceeds the household demand. This study proposes an approach for optimal implementation of demand response in residential sector to eliminate voltage violations, especially during high PV generation periods. The proposed approach uses a load flow sensitivity method to optimise the demand response implementation location and size for PV penetration maximisation in distribution networks. The simulation results on IEEE 13-bus test system show that using the proposed approach every 1 kW of DR implementation increases PV penetration by 2 kW.
Embargo
Simulation of a transformer winding for partial discharge propagation studies
(IEEE, 2002-01-27) Hettiwatte, S. N; Crossley, P. A; Wang, Z. D; Darwin, A; Edwards, G
A simulation model of a continuous disc type 6.6 kV transformer winding was used to study the propagation behaviour of partial discharge (PD) pulses. The model based on multi-conductor transmission line theory uses a single turn as a circuit element with the capacitance, inductance, and losses calculated as distributed parameters. Transfer functions that describe how the location of the PD source affects the current signals measured at the terminals of the winding were calculated. The paper shows how the position of the zeros in the frequency response of the measured current signals can be used to locate the source of the discharge. Sensitivity studies on the parameters of the model were used to investigate the effect of inaccuracies in the model on the position of the zeros and hence the location of the discharge.
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Switched intelligent grid networking systems
(IEEE, 2014-05) Thorogood, A; Hettiwatte, S. N
Switched Intelligent Grid Networking Systems (SIGNS) is the result of research, analysis and development of an alternative process for controlling end-user electrical power quality, as well as transients on the incoming electricity supply grid. In the past power quality issues associated with the grid network were usually generated by the connected loads. This has changed in today's grid system with embedded intermittent renewable energy being included on the energy profile. The research demonstrated that it is possible to control end-user electrical power quality through the addition of battery storage at the user end of the grid and a switching device, forming an intelligent buffer between the electrical grid supply and the load. The function of the device is to select the most appropriate energy source to effectively absorb a proportion of any surges and transients, whilst offering a path for augmented alternative energy .