Improved method to obtain the online impulse frequency response signature of a power transformer by multi scale complex CWT
- Zhao, Zhongyong, Tang, Chao, Yao, Chenguo, Zhou, Qu, Xu, Lingna, Gui, Yingang, Islam, Syed
- Authors: Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Zhou, Qu , Xu, Lingna , Gui, Yingang , Islam, Syed
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 48934-48945
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- Description: Online impulse frequency response analysis (IFRA) has proven to be a promising method to detect and diagnose the transformer winding mechanical faults when the transformer is in service. However, the existing fast Fourier transform (FFT) is actually not suitable for processing the transient signals in online IFRA. The field test result also shows that the IFRA signature obtained by FFT is easily distorted by noise. An improved method to obtain the online IFRA signature based on multi-scale complex continuous wavelet transform is proposed. The electrical model simulation and online experiment indicate the superiority of the wavelet transform compared with FFT. This paper provides guidance on the actual application of the online IFRA method.
- Authors: Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Zhou, Qu , Xu, Lingna , Gui, Yingang , Islam, Syed
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Access Vol. 6, no. (2018), p. 48934-48945
- Full Text:
- Reviewed:
- Description: Online impulse frequency response analysis (IFRA) has proven to be a promising method to detect and diagnose the transformer winding mechanical faults when the transformer is in service. However, the existing fast Fourier transform (FFT) is actually not suitable for processing the transient signals in online IFRA. The field test result also shows that the IFRA signature obtained by FFT is easily distorted by noise. An improved method to obtain the online IFRA signature based on multi-scale complex continuous wavelet transform is proposed. The electrical model simulation and online experiment indicate the superiority of the wavelet transform compared with FFT. This paper provides guidance on the actual application of the online IFRA method.
Impact of distributed rooftop photovoltaic systems on short-circuit faults in the supplying low voltage networks
- Yengejeh, Hadi, Shahnia, Farhad, Islam, Syed
- Authors: Yengejeh, Hadi , Shahnia, Farhad , Islam, Syed
- Date: 2017
- Type: Text , Journal article
- Relation: Electric Power Components and Systems Vol. 45, no. 20 (2017), p. 2257-2274
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- Description: This article evaluates the effect of randomly distributed, residential single-phase rooftop photovoltaic systems in the low voltage residential networks, during short-circuit faults on the overhead lines. The important parameters such as the fault current, the current sensed at the distribution transformer secondary, and the voltage profile along the feeder during the fault are examined. A sensitivity analysis is carried out in which the rating and location of the photovoltaic systems in the feeder, as well as the fault location and type, are the considered variables. Moreover, to demonstrate the effect of multiple photovoltaic systems with different ratings and penetration levels when distributed unequally among three phases of the network, a stochastic analysis is carried out. The article summarizes the outcomes of these two analyses to provide a better understanding of the impact of single-phase rooftop photovoltaic systems on the residential feeders during short-circuit faults.
- Authors: Yengejeh, Hadi , Shahnia, Farhad , Islam, Syed
- Date: 2017
- Type: Text , Journal article
- Relation: Electric Power Components and Systems Vol. 45, no. 20 (2017), p. 2257-2274
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- Description: This article evaluates the effect of randomly distributed, residential single-phase rooftop photovoltaic systems in the low voltage residential networks, during short-circuit faults on the overhead lines. The important parameters such as the fault current, the current sensed at the distribution transformer secondary, and the voltage profile along the feeder during the fault are examined. A sensitivity analysis is carried out in which the rating and location of the photovoltaic systems in the feeder, as well as the fault location and type, are the considered variables. Moreover, to demonstrate the effect of multiple photovoltaic systems with different ratings and penetration levels when distributed unequally among three phases of the network, a stochastic analysis is carried out. The article summarizes the outcomes of these two analyses to provide a better understanding of the impact of single-phase rooftop photovoltaic systems on the residential feeders during short-circuit faults.
Investigation of microgrid instability caused by time delay
- Aghanoori, Navid, Masoum, Mohammad, Islam, Syed, Nethery, Steven
- Authors: Aghanoori, Navid , Masoum, Mohammad , Islam, Syed , Nethery, Steven
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 10th International Conference on Electrical and Electronics Engineering, ELECO 2017; Bursa, Turkey; 29th-2nd December 2017 Vol. 2018, p. 105-110
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- Description: This paper investigates the impact of time delay in the control of a grid-connected microgrid with renewable energy resources. The considered microgrid has a critical load that needs to be powered and protected in the event of grid voltage disturbance while the microgrid maintains connection to the grid. Three case studies are performed considering three different time delays to indicate the advantages of fast communication system in the performance of renewable microgrids. Detailed simulation results illustrate that the proposed communication system using IEC 61850 substation automation standard provides better voltage and current quality to the critical local load with larger phase and gain margins while keeping the microgid connected to main grid.
- Authors: Aghanoori, Navid , Masoum, Mohammad , Islam, Syed , Nethery, Steven
- Date: 2017
- Type: Text , Conference proceedings , Conference paper
- Relation: 10th International Conference on Electrical and Electronics Engineering, ELECO 2017; Bursa, Turkey; 29th-2nd December 2017 Vol. 2018, p. 105-110
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- Description: This paper investigates the impact of time delay in the control of a grid-connected microgrid with renewable energy resources. The considered microgrid has a critical load that needs to be powered and protected in the event of grid voltage disturbance while the microgrid maintains connection to the grid. Three case studies are performed considering three different time delays to indicate the advantages of fast communication system in the performance of renewable microgrids. Detailed simulation results illustrate that the proposed communication system using IEC 61850 substation automation standard provides better voltage and current quality to the critical local load with larger phase and gain margins while keeping the microgid connected to main grid.
Identification of coherent generators by support vector clustering with an embedding strategy
- Babaei, Mehdi, Muyeen, S., Islam, Syed
- Authors: Babaei, Mehdi , Muyeen, S. , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 105420-105431
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- Description: Identification of coherent generators (CGs) is necessary for the area-based monitoring and protection system of a wide area power system. Synchrophasor has enabled smarter monitoring and control measures to be devised; hence, measurement-based methodologies can be implemented in online applications to identify the CGs. This paper presents a new framework for coherency identification that is based on the dynamic coupling of generators. A distance matrix that contains the dissimilarity indices between any pair of generators is constructed from the pairwise dynamic coupling of generators after the post-disturbance data are obtained by phasor measurement units (PMUs). The dataset is embedded in Euclidean space to produce a new dataset with a metric distance between the points, and then the support vector clustering (SVC) technique is applied to the embedded dataset to identify the final clusters of generators. Unlike other clustering methods that need a priori knowledge about the number of clusters or the parameters of clustering, this information is set in an automatic search procedure that results in the optimal number of clusters. The algorithm is verified by time-domain simulations of defined scenarios in 39 bus and 118 bus test systems. Finally, the clustering result of 39 bus systems is validated by cluster validity measures, and a comparative study investigates the efficacy of the proposed algorithm to cluster the generators with an optimal number of clusters and also its computational efficiency compared with other clustering methods.
- Authors: Babaei, Mehdi , Muyeen, S. , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 105420-105431
- Full Text:
- Reviewed:
- Description: Identification of coherent generators (CGs) is necessary for the area-based monitoring and protection system of a wide area power system. Synchrophasor has enabled smarter monitoring and control measures to be devised; hence, measurement-based methodologies can be implemented in online applications to identify the CGs. This paper presents a new framework for coherency identification that is based on the dynamic coupling of generators. A distance matrix that contains the dissimilarity indices between any pair of generators is constructed from the pairwise dynamic coupling of generators after the post-disturbance data are obtained by phasor measurement units (PMUs). The dataset is embedded in Euclidean space to produce a new dataset with a metric distance between the points, and then the support vector clustering (SVC) technique is applied to the embedded dataset to identify the final clusters of generators. Unlike other clustering methods that need a priori knowledge about the number of clusters or the parameters of clustering, this information is set in an automatic search procedure that results in the optimal number of clusters. The algorithm is verified by time-domain simulations of defined scenarios in 39 bus and 118 bus test systems. Finally, the clustering result of 39 bus systems is validated by cluster validity measures, and a comparative study investigates the efficacy of the proposed algorithm to cluster the generators with an optimal number of clusters and also its computational efficiency compared with other clustering methods.
Steady-state security in distribution networks with large wind farms
- Jayaweera, Dilan, Islam, Syed
- Authors: Jayaweera, Dilan , Islam, Syed
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Modern Power Systems and Clean Energy Vol. 2, no. 2 (2014), p. 134-142
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- Description: Aging network assets, forced and unforced outages, and the way the networks are operated in a deregulated market are of significant concerns to integrate large wind farms in a distribution network. In many cases, the constrained network capacity is a potential barrier to the large-scale integration of wind power. This paper probabilistically assesses the steady-state security in a distribution network in the presence of large wind farms. The approach incorporates active distribution network operating conditions, including intermittent power outputs, random outages, demand fluctuations, and dynamic interactions and exchanges, and then assesses the steady state security using Monte Carlo simulation. A case study is performed by integrating large wind farms into a distribution network. The results suggest that intermittent outputs of large wind farms in a distribution network can impact the steady-state security considerably. However, the level of impact of wind farms does not necessarily correlate with the installed capacity of them.
- Authors: Jayaweera, Dilan , Islam, Syed
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Modern Power Systems and Clean Energy Vol. 2, no. 2 (2014), p. 134-142
- Full Text:
- Reviewed:
- Description: Aging network assets, forced and unforced outages, and the way the networks are operated in a deregulated market are of significant concerns to integrate large wind farms in a distribution network. In many cases, the constrained network capacity is a potential barrier to the large-scale integration of wind power. This paper probabilistically assesses the steady-state security in a distribution network in the presence of large wind farms. The approach incorporates active distribution network operating conditions, including intermittent power outputs, random outages, demand fluctuations, and dynamic interactions and exchanges, and then assesses the steady state security using Monte Carlo simulation. A case study is performed by integrating large wind farms into a distribution network. The results suggest that intermittent outputs of large wind farms in a distribution network can impact the steady-state security considerably. However, the level of impact of wind farms does not necessarily correlate with the installed capacity of them.
Image processing-based on-line technique to detect power transformer winding faults
- Abu-Siada, Ahmed, Islam, Syed
- Authors: Abu-Siada, Ahmed , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013; Vienna, Austria; 10th-14th November 2013 p. 1-6
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- Description: Frequency Response Analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relies on graphical analysis, it calls for an expert person to analyse the results as so far, there is no standard code for FRA interpretation worldwide. In this paper an online technique is introduced to detect the internal faults within a power transformer by constructing the voltage-current (V-I) locus diagram to provide a current state of the transformer health condition. The technique does not call for any special equipment as it uses the existing metering devices attached to any power transformer to monitor the input voltage, output voltage and the input current at the power frequency and hence online monitoring can be realised. Various types of faults have been simulated to assess its impact on the proposed locus. A Matlab code based on digital image processing is developed to calculate any deviation of the V-I locus with respect to the reference one and to identify the type of fault.
- Authors: Abu-Siada, Ahmed , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 39th Annual Conference of the IEEE Industrial Electronics Society, IECON 2013; Vienna, Austria; 10th-14th November 2013 p. 1-6
- Full Text:
- Reviewed:
- Description: Frequency Response Analysis (FRA) has been growing in popularity in recent times as a tool to detect mechanical deformation within power transformers. To conduct the test, the transformer has to be taken out of service which may cause interruption to the electricity grid. Moreover, because FRA relies on graphical analysis, it calls for an expert person to analyse the results as so far, there is no standard code for FRA interpretation worldwide. In this paper an online technique is introduced to detect the internal faults within a power transformer by constructing the voltage-current (V-I) locus diagram to provide a current state of the transformer health condition. The technique does not call for any special equipment as it uses the existing metering devices attached to any power transformer to monitor the input voltage, output voltage and the input current at the power frequency and hence online monitoring can be realised. Various types of faults have been simulated to assess its impact on the proposed locus. A Matlab code based on digital image processing is developed to calculate any deviation of the V-I locus with respect to the reference one and to identify the type of fault.
Classifying transformer winding deformation fault types and degrees using FRA based on support vector machine
- Liu, Jiangnan, Zhao, Zhongyong, Tang, Chao, Yao, Chenguo, Li, Chengxiang, Islam, Syed
- Authors: Liu, Jiangnan , Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Li, Chengxiang , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 112494-112504
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- Description: As an important part of power system, power transformer plays an irreplaceable role in the process of power transmission. Diagnosis of transformer's failure is of significance to maintain its safe and stable operation. Frequency response analysis (FRA) has been widely accepted as an effective tool for winding deformation fault diagnosis, which is one of the common failures for power transformers. However, there is no standard and reliable code for FRA interpretation as so far. In this paper, support vector machine (SVM) is combined with FRA to diagnose transformer faults. Furthermore, advanced optimization algorithms are also applied to improve the performance of models. A series of winding fault emulating experiments were carried out on an actual model transformer, the key features are extracted from measured FRA data, and the diagnostic model is trained and obtained, to arrive at an outcome for classifying the fault types and degrees of winding deformation faults with satisfactory accuracy. The diagnostic results indicate that this method has potential to be an intelligent, standardized, accurate and powerful tool.
- Authors: Liu, Jiangnan , Zhao, Zhongyong , Tang, Chao , Yao, Chenguo , Li, Chengxiang , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 112494-112504
- Full Text:
- Reviewed:
- Description: As an important part of power system, power transformer plays an irreplaceable role in the process of power transmission. Diagnosis of transformer's failure is of significance to maintain its safe and stable operation. Frequency response analysis (FRA) has been widely accepted as an effective tool for winding deformation fault diagnosis, which is one of the common failures for power transformers. However, there is no standard and reliable code for FRA interpretation as so far. In this paper, support vector machine (SVM) is combined with FRA to diagnose transformer faults. Furthermore, advanced optimization algorithms are also applied to improve the performance of models. A series of winding fault emulating experiments were carried out on an actual model transformer, the key features are extracted from measured FRA data, and the diagnostic model is trained and obtained, to arrive at an outcome for classifying the fault types and degrees of winding deformation faults with satisfactory accuracy. The diagnostic results indicate that this method has potential to be an intelligent, standardized, accurate and powerful tool.
Contributions of single–phase rooftop PVs on short circuits faults in residential feeders
- Yengejeh, Hadi, Shahnia, Farhad, Islam, Syed
- Authors: Yengejeh, Hadi , Shahnia, Farhad , 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. 1-6
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- Description: Sensitivity analysis results are presented to investigate the presence of single–phase rooftop Photovoltaic Cells (PV) in low voltage residential feeders, during short circuits in the overhead lines. The PV rating and location in the feeder and the fault location are considered as the variables of the sensitivity analysis. The single–phase faults are the main focus of this paper and the PV effect on fault current, current in distribution transformer secondary and the voltage at each bus of the feeder are investigated, during fault. Furthermore, to analyze the bus voltages and fault current in the presence of multiple PVs, each with different rating and location, a stochastic analysis is carried out to investigate the expected probability density function of these parameters, considering the uncertainties of PV rating and location as well as fault location.
- Authors: Yengejeh, Hadi , Shahnia, Farhad , 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. 1-6
- Full Text:
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- Description: Sensitivity analysis results are presented to investigate the presence of single–phase rooftop Photovoltaic Cells (PV) in low voltage residential feeders, during short circuits in the overhead lines. The PV rating and location in the feeder and the fault location are considered as the variables of the sensitivity analysis. The single–phase faults are the main focus of this paper and the PV effect on fault current, current in distribution transformer secondary and the voltage at each bus of the feeder are investigated, during fault. Furthermore, to analyze the bus voltages and fault current in the presence of multiple PVs, each with different rating and location, a stochastic analysis is carried out to investigate the expected probability density function of these parameters, considering the uncertainties of PV rating and location as well as fault location.
Dual mechanical port machine based hybrid electric vehicle using reduced switch converters
- Bizhani, Hamed, Yao, Gang, Muyeen, S., Islam, Syed, Ben-Brahim, Lazhar
- Authors: Bizhani, Hamed , Yao, Gang , Muyeen, S. , Islam, Syed , Ben-Brahim, Lazhar
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 33665-33676
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- Description: Due to the increased environmental pollution, hybrid vehicles have attracted enormous attention in today's society. The two most important factors in designing these vehicles are size and weight. For this purpose, some researchers have presented the use of the dual-mechanical-port machine (DMPM) in hybrid electric vehicles (HEVs). This paper presents two modified converter topologies with a reduced number of switching devices for use on DMPM-based HEVs, with the goal of reducing the overall size and weight of the system. Beside the design of the DMPM in the series-parallel HEV structure along with the energy management unit, the conventional back-to-back (BB) converter is replaced with nine-switch (NS) and five-leg (FL) converters. These converters have never been examined for the DMPM-based HEV, and therefore, the objective of this paper is to reveal the operational characteristics and power flow mechanism of this machine using the NS and FL converters. The simulation analysis is carried out using MATLAB/Simulink considering all HEV operational modes. In addition, two proposed and the conventional converters are compared in terms of losses, maximum achievable voltages, required dc-link voltages, the rating of the components, and torque ripple, and finally, a recommendation is made based on the obtained results.
- Authors: Bizhani, Hamed , Yao, Gang , Muyeen, S. , Islam, Syed , Ben-Brahim, Lazhar
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 33665-33676
- Full Text:
- Reviewed:
- Description: Due to the increased environmental pollution, hybrid vehicles have attracted enormous attention in today's society. The two most important factors in designing these vehicles are size and weight. For this purpose, some researchers have presented the use of the dual-mechanical-port machine (DMPM) in hybrid electric vehicles (HEVs). This paper presents two modified converter topologies with a reduced number of switching devices for use on DMPM-based HEVs, with the goal of reducing the overall size and weight of the system. Beside the design of the DMPM in the series-parallel HEV structure along with the energy management unit, the conventional back-to-back (BB) converter is replaced with nine-switch (NS) and five-leg (FL) converters. These converters have never been examined for the DMPM-based HEV, and therefore, the objective of this paper is to reveal the operational characteristics and power flow mechanism of this machine using the NS and FL converters. The simulation analysis is carried out using MATLAB/Simulink considering all HEV operational modes. In addition, two proposed and the conventional converters are compared in terms of losses, maximum achievable voltages, required dc-link voltages, the rating of the components, and torque ripple, and finally, a recommendation is made based on the obtained results.
A new technique to measure interfacial tension of transformer oil using UV-Vis spectroscopy
- Abu Bakar, Norazhar, Abu-Siada, Ahmed, Islam, Syed, El-Naggar, Mohammed
- Authors: Abu Bakar, Norazhar , Abu-Siada, Ahmed , Islam, Syed , El-Naggar, Mohammed
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 22, no. 2 (2015), p. 1275-1282
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- Description: Interfacial tension (IFT) and acid numbers of insulating oil are correlated with the number of years that a transformer has been in service and are used as a signal for transformer oil reclamation. Oil sampling for IFT measurement calls for extra precautions due to its high sensitivity to various oil parameters and environmental conditions. The current used technique to measure IFT of transformer oil is relatively expensive, requires an expert to conduct the test and it takes long time since the extraction of oil sample, sending it to external laboratory and getting the results back. This paper introduces a new technique to estimate the IFT of transformer oil using ultraviolet-to-visible (UV-Vis) spectroscopy. UV-Vis spectral response of transformer oil can be measured instantly with relatively cheap equipment, does not need an expert person to conduct the test and has the potential to be implemented online. Results show that there is a good correlation between oil spectral response and its IFT value. Artificial neural network (ANN) approach is proposed to model this correlation.
- Authors: Abu Bakar, Norazhar , Abu-Siada, Ahmed , Islam, Syed , El-Naggar, Mohammed
- Date: 2015
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 22, no. 2 (2015), p. 1275-1282
- Full Text:
- Reviewed:
- Description: Interfacial tension (IFT) and acid numbers of insulating oil are correlated with the number of years that a transformer has been in service and are used as a signal for transformer oil reclamation. Oil sampling for IFT measurement calls for extra precautions due to its high sensitivity to various oil parameters and environmental conditions. The current used technique to measure IFT of transformer oil is relatively expensive, requires an expert to conduct the test and it takes long time since the extraction of oil sample, sending it to external laboratory and getting the results back. This paper introduces a new technique to estimate the IFT of transformer oil using ultraviolet-to-visible (UV-Vis) spectroscopy. UV-Vis spectral response of transformer oil can be measured instantly with relatively cheap equipment, does not need an expert person to conduct the test and has the potential to be implemented online. Results show that there is a good correlation between oil spectral response and its IFT value. Artificial neural network (ANN) approach is proposed to model this correlation.
Estimation of induction motor parameters using hybrid algorithms for power system dynamic studies
- Susanto, Julius, Islam, Syed
- Authors: Susanto, Julius , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 2013 Australasian Universities Power Engineering Conference, AUPEC 2013; Hobart, Australia; 29th September-3rd October 2013 p. 1-6
- Full Text:
- Reviewed:
- Description: This paper proposes a hybrid Newton-Raphson and genetic algorithm for the estimation of double cage induction motor parameters from commonly available manufacturer data. The hybrid algorithm was tested on a large data set of 6,380 IEC and NEMA motors and then compared with a baseline Newton-Raphson algorithm. The simulation results show that while the proposed hybrid algorithm is more computationally intensive, it does make significant improvements to convergence and error rates.
- Authors: Susanto, Julius , Islam, Syed
- Date: 2013
- Type: Text , Conference proceedings , Conference paper
- Relation: 2013 Australasian Universities Power Engineering Conference, AUPEC 2013; Hobart, Australia; 29th September-3rd October 2013 p. 1-6
- Full Text:
- Reviewed:
- Description: This paper proposes a hybrid Newton-Raphson and genetic algorithm for the estimation of double cage induction motor parameters from commonly available manufacturer data. The hybrid algorithm was tested on a large data set of 6,380 IEC and NEMA motors and then compared with a baseline Newton-Raphson algorithm. The simulation results show that while the proposed hybrid algorithm is more computationally intensive, it does make significant improvements to convergence and error rates.
Impact of axial displacement on power transformer FRA signature
- Hashemnia, Naser, Abu-Siada, Ahmed, Islam, Syed
- 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.
- 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.
Analysis of end-to-end delay characteristics for various packets in IEC 61850 substation communications system
- Das, Narottam, Ma, Wu, Islam, Syed
- Authors: Das, Narottam , Ma, Wu , Islam, Syed
- Date: 2015
- Type: Text , Conference proceedings , Conference paper
- Relation: 25th Australasian Universities Power Engineering Conference, AUPEC 2015, Wollongong, Australia; 27th-30th September 2015 p. 1-5
- Full Text:
- Reviewed:
- Description: Substation plays an important role in power system communications for safe and reliable operation of entire power networks. Substation communication networks are connected with various substation intelligent electronic devices (IEDs), which is substation systems lifeblood and the system availability is decided by its real-Time performance. International Electro-Technical Commission (IEC) has been developed the standards based on object-oriented technologies for substation automation. IEC 61850 protocol has been applied widely in substation communication applications. It presents new challenges to realtime performance simulation and testing of protective relays. In this paper, an optimized network engineering tool (OPNET) or Riverbed modeler simulation tool/ software has been used for the modeling of IED in substation level network. Based on the simulation results, different types of data stream have been discussed, such as, periodic data stream, random data stream and burst data steam. The typical studies using these models, to construct substation automation system (SAS) network on the OPNET modeler or Riverbed modeler was made to reveal the impact of each affecting parameter or factor to the real-Time performance of substation communications system, which is also incorporated in this report.
- Description: 2015 Australasian Universities Power Engineering Conference: Challenges for Future Grids, AUPEC 2015
- Authors: Das, Narottam , Ma, Wu , Islam, Syed
- Date: 2015
- Type: Text , Conference proceedings , Conference paper
- Relation: 25th Australasian Universities Power Engineering Conference, AUPEC 2015, Wollongong, Australia; 27th-30th September 2015 p. 1-5
- Full Text:
- Reviewed:
- Description: Substation plays an important role in power system communications for safe and reliable operation of entire power networks. Substation communication networks are connected with various substation intelligent electronic devices (IEDs), which is substation systems lifeblood and the system availability is decided by its real-Time performance. International Electro-Technical Commission (IEC) has been developed the standards based on object-oriented technologies for substation automation. IEC 61850 protocol has been applied widely in substation communication applications. It presents new challenges to realtime performance simulation and testing of protective relays. In this paper, an optimized network engineering tool (OPNET) or Riverbed modeler simulation tool/ software has been used for the modeling of IED in substation level network. Based on the simulation results, different types of data stream have been discussed, such as, periodic data stream, random data stream and burst data steam. The typical studies using these models, to construct substation automation system (SAS) network on the OPNET modeler or Riverbed modeler was made to reveal the impact of each affecting parameter or factor to the real-Time performance of substation communications system, which is also incorporated in this report.
- Description: 2015 Australasian Universities Power Engineering Conference: Challenges for Future Grids, AUPEC 2015
Low-power wide-area networks : design goals, architecture, suitability to use cases and research challenges
- Buurman, Ben, Kamruzzaman, Joarder, Karmakar, Gour, Islam, Syed
- Authors: Buurman, Ben , Kamruzzaman, Joarder , Karmakar, Gour , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 17179-17220
- Full Text:
- Reviewed:
- Description: Previous survey articles on Low-Powered Wide-Area Networks (LPWANs) lack a systematic analysis of the design goals of LPWAN and the design decisions adopted by various commercially available and emerging LPWAN technologies, and no study has analysed how their design decisions impact their ability to meet design goals. Assessing a technology's ability to meet design goals is essential in determining suitable technologies for a given application. To address these gaps, we have analysed six prominent design goals and identified the design decisions used to meet each goal in the eight LPWAN technologies, ranging from technical consideration to business model, and determined which specific technique in a design decision will help meet each goal to the greatest extent. System architecture and specifications are presented for those LPWAN solutions, and their ability to meet each design goal is evaluated. We outline seventeen use cases across twelve domains that require large low power network infrastructure and prioritise each design goal's importance to those applications as Low, Moderate, or High. Using these priorities and each technology's suitability for meeting design goals, we suggest appropriate LPWAN technologies for each use case. Finally, a number of research challenges are presented for current and future technologies. © 2013 IEEE.
- Authors: Buurman, Ben , Kamruzzaman, Joarder , Karmakar, Gour , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 17179-17220
- Full Text:
- Reviewed:
- Description: Previous survey articles on Low-Powered Wide-Area Networks (LPWANs) lack a systematic analysis of the design goals of LPWAN and the design decisions adopted by various commercially available and emerging LPWAN technologies, and no study has analysed how their design decisions impact their ability to meet design goals. Assessing a technology's ability to meet design goals is essential in determining suitable technologies for a given application. To address these gaps, we have analysed six prominent design goals and identified the design decisions used to meet each goal in the eight LPWAN technologies, ranging from technical consideration to business model, and determined which specific technique in a design decision will help meet each goal to the greatest extent. System architecture and specifications are presented for those LPWAN solutions, and their ability to meet each design goal is evaluated. We outline seventeen use cases across twelve domains that require large low power network infrastructure and prioritise each design goal's importance to those applications as Low, Moderate, or High. Using these priorities and each technology's suitability for meeting design goals, we suggest appropriate LPWAN technologies for each use case. Finally, a number of research challenges are presented for current and future technologies. © 2013 IEEE.
Impact of load ramping on power transformer dissolved gas analysis
- Cui, Huize, Yang, Liuging, Li, Shengtao, Qu, Guanghao, Wang, Hao, Abu-Siada, Ahmed, Islam, Syed
- Authors: Cui, Huize , Yang, Liuging , Li, Shengtao , Qu, Guanghao , Wang, Hao , Abu-Siada, Ahmed , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 170343-170351
- Full Text:
- Reviewed:
- Description: Dissolved gas in oil analysis (DGA) is one of the most reliable condition monitoring techniques, which is currently used by the industry to detect incipient faults within the power transformers. While the technique is well matured since the development of various offline and online measurement techniques along with various interpretation methods, no much attention was given so far to the oil sampling time and its correlation with the transformer loading. A power transformer loading is subject to continuous daily and seasonal variations, which is expected to increase with the increased penetration level of renewable energy sources of intermittent characteristics, such as photovoltaic (PV) and wind energy into the current electricity grids. Generating unit transformers also undergoes similar loading variations to follow the demand, particularly in the new electricity market. As such, the insulation system within the power transformers is expected to exhibit operating temperature variations due to the continuous ramping up and down of the generation and load. If the oil is sampled for the DGA measurement during such ramping cycles, results will not be accurate, and a fault may be reported due to a gas evolution resulting from such temporarily loading variation. This paper is aimed at correlating the generation and load ramping with the DGA measurements through extensive experimental analyses. The results reveal a strong correlation between the sampling time and the generation/load ramping. The experimental results show the effect of load variations on the gas generation and demonstrate the vulnerabilities of misinterpretation of transformer faults resulting from temporary gas evolution. To achieve accurate DGA, transformer loading profile during oil sampling for the DGA measurement should be available. Based on the initial investigation in this paper, the more accurate DGA results can be achieved after a ramping down cycle of the load. This sampling time could be defined as an optimum oil sampling time for transformer DGA.
- Authors: Cui, Huize , Yang, Liuging , Li, Shengtao , Qu, Guanghao , Wang, Hao , Abu-Siada, Ahmed , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Access Vol. 7, no. (2019), p. 170343-170351
- Full Text:
- Reviewed:
- Description: Dissolved gas in oil analysis (DGA) is one of the most reliable condition monitoring techniques, which is currently used by the industry to detect incipient faults within the power transformers. While the technique is well matured since the development of various offline and online measurement techniques along with various interpretation methods, no much attention was given so far to the oil sampling time and its correlation with the transformer loading. A power transformer loading is subject to continuous daily and seasonal variations, which is expected to increase with the increased penetration level of renewable energy sources of intermittent characteristics, such as photovoltaic (PV) and wind energy into the current electricity grids. Generating unit transformers also undergoes similar loading variations to follow the demand, particularly in the new electricity market. As such, the insulation system within the power transformers is expected to exhibit operating temperature variations due to the continuous ramping up and down of the generation and load. If the oil is sampled for the DGA measurement during such ramping cycles, results will not be accurate, and a fault may be reported due to a gas evolution resulting from such temporarily loading variation. This paper is aimed at correlating the generation and load ramping with the DGA measurements through extensive experimental analyses. The results reveal a strong correlation between the sampling time and the generation/load ramping. The experimental results show the effect of load variations on the gas generation and demonstrate the vulnerabilities of misinterpretation of transformer faults resulting from temporary gas evolution. To achieve accurate DGA, transformer loading profile during oil sampling for the DGA measurement should be available. Based on the initial investigation in this paper, the more accurate DGA results can be achieved after a ramping down cycle of the load. This sampling time could be defined as an optimum oil sampling time for transformer DGA.
A new data driven long-term solar yield analysis model of photovoltaic power plants
- Ray, Biplob, Shah, Rakibuzzaman, Islam, Md Rabiul, Islam, Syed
- Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
- Full Text:
- Reviewed:
- Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.
- Authors: Ray, Biplob , Shah, Rakibuzzaman , Islam, Md Rabiul , Islam, Syed
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 136223-136233
- Full Text:
- Reviewed:
- Description: Historical data offers a wealth of knowledge to the users. However, often restrictively mammoth that the information cannot be fully extracted, synthesized, and analyzed efficiently for an application such as the forecasting of variable generator outputs. Moreover, the accuracy of the prediction method is vital. Therefore, a trade-off between accuracy and efficacy is required for the data-driven energy forecasting method. It has been identified that the hybrid approach may outperform the individual technique in minimizing the error while challenging to synthesize. A hybrid deep learning-based method is proposed for the output prediction of the solar photovoltaic systems (i.e. proposed PV system) in Australia to obtain the trade-off between accuracy and efficacy. The historical dataset from 1990-2013 in Australian locations (e.g. North Queensland) are used to train the model. The model is developed using the combination of multivariate long and short-term memory (LSTM) and convolutional neural network (CNN). The proposed hybrid deep learning (LSTM-CNN) is compared with the existing neural network ensemble (NNE), random forest, statistical analysis, and artificial neural network (ANN) based techniques to assess the performance. The proposed model could be useful for generation planning and reserve estimation in power systems with high penetration of solar photovoltaics (PVs) or other renewable energy sources (RESs). © 2013 IEEE.
Multi-level supervisory emergency control for operation of remote area microgrid clusters
- Batool, Munira, Shahnia, Farhad, Islam, Syed
- Authors: Batool, Munira , Shahnia, Farhad , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: Journal of Modern Power Systems and Clean Energy Vol. 7, no. 5 (Sep 2019), p. 1210-1228
- Full Text:
- Reviewed:
- Description: Remote and regional areas are usually supplied by isolated and self-sufficient electricity systems, which are called as microgrids (MGs). To reduce the overall cost of electricity production, MGs rely on non-dispatchable renewable sources. Emergencies such as overloading or excessive generation by renewable sources can result in a substantial voltage or frequency deviation in MGs. This paper presents a supervisory controller for such emergencies. The key idea is to remedy the emergencies by optimal internal or external support. A multi-level controller with soft, intermedial and hard actions is proposed. The soft actions include the adjustment of the droop parameters of the sources and the controlling of the charge/discharge of energy storages. The intermedial action is exchanging power with neighboring MGs, which is highly probable in large remote areas. As the last remedying resort, curtailing loads or renewable sources are assumed as hard actions. The proposed controller employs an optimization technique consisting of certain objectives such as reducing power loss in the tie-lines amongst MGs and the dependency of an MG to other MGs, as well as enhancing the contribution of renewable sources in electricity generation. Minimization of the fuel consumption and emissions of conventional generators, along with frequency and voltage deviation, is the other desired objectives. The performance of the proposal is evaluated by several numerical analyses in MATLAB (R).
- Authors: Batool, Munira , Shahnia, Farhad , Islam, Syed
- Date: 2019
- Type: Text , Journal article
- Relation: Journal of Modern Power Systems and Clean Energy Vol. 7, no. 5 (Sep 2019), p. 1210-1228
- Full Text:
- Reviewed:
- Description: Remote and regional areas are usually supplied by isolated and self-sufficient electricity systems, which are called as microgrids (MGs). To reduce the overall cost of electricity production, MGs rely on non-dispatchable renewable sources. Emergencies such as overloading or excessive generation by renewable sources can result in a substantial voltage or frequency deviation in MGs. This paper presents a supervisory controller for such emergencies. The key idea is to remedy the emergencies by optimal internal or external support. A multi-level controller with soft, intermedial and hard actions is proposed. The soft actions include the adjustment of the droop parameters of the sources and the controlling of the charge/discharge of energy storages. The intermedial action is exchanging power with neighboring MGs, which is highly probable in large remote areas. As the last remedying resort, curtailing loads or renewable sources are assumed as hard actions. The proposed controller employs an optimization technique consisting of certain objectives such as reducing power loss in the tie-lines amongst MGs and the dependency of an MG to other MGs, as well as enhancing the contribution of renewable sources in electricity generation. Minimization of the fuel consumption and emissions of conventional generators, along with frequency and voltage deviation, is the other desired objectives. The performance of the proposal is evaluated by several numerical analyses in MATLAB (R).
Market model for clustered microgrids optimisation including distribution network operations
- Batool, Munira, Islam, Syed, Shahnia, Farhad
- Authors: Batool, Munira , Islam, Syed , Shahnia, Farhad
- Date: 2019
- Type: Text , Journal article
- Relation: IET Generation, Transmission and Distribution Vol. 13, no. 22 (2019), p. 5139-5150
- Full Text:
- Reviewed:
- Description: This paper proposes a market model for the purpose of optimisation of clustered but sparse microgrids (MGs). The MGs are connected with the market by distribution networks for the sake of energy balance and to overcome emergency situations. The developed market structure enables the integration of virtual power plants (VPPs) in energy requirement of MGs. The MGs, internal service providers (ISPs), VPPs and distribution network operator (DNO) are present as distinct entities with individual objective of minimum operational cost. Each MG is assumed to be present with a commitment to service its own loads prior to export. Thus an optimisation problem is formulated with the core objective of minimum cost of operation, reduced network loss and least DNO charges. The formulated problem is solved by using heuristic optimization technique of Genetic Algorithm. Case studies are carried out on a distribution system with multiple MGs, ISP and VPPs which illustrates the effectiveness of the proposed market optimisation strategy. The key objective of the proposed market model is to coordinate the operation of MGs with the requirements of the market with the help of the DNO, without decreasing the economic efficiency for the MGs nor the distribution network. © The Institution of Engineering and Technology 2019.
- Authors: Batool, Munira , Islam, Syed , Shahnia, Farhad
- Date: 2019
- Type: Text , Journal article
- Relation: IET Generation, Transmission and Distribution Vol. 13, no. 22 (2019), p. 5139-5150
- Full Text:
- Reviewed:
- Description: This paper proposes a market model for the purpose of optimisation of clustered but sparse microgrids (MGs). The MGs are connected with the market by distribution networks for the sake of energy balance and to overcome emergency situations. The developed market structure enables the integration of virtual power plants (VPPs) in energy requirement of MGs. The MGs, internal service providers (ISPs), VPPs and distribution network operator (DNO) are present as distinct entities with individual objective of minimum operational cost. Each MG is assumed to be present with a commitment to service its own loads prior to export. Thus an optimisation problem is formulated with the core objective of minimum cost of operation, reduced network loss and least DNO charges. The formulated problem is solved by using heuristic optimization technique of Genetic Algorithm. Case studies are carried out on a distribution system with multiple MGs, ISP and VPPs which illustrates the effectiveness of the proposed market optimisation strategy. The key objective of the proposed market model is to coordinate the operation of MGs with the requirements of the market with the help of the DNO, without decreasing the economic efficiency for the MGs nor the distribution network. © The Institution of Engineering and Technology 2019.
Toward a substation automation system based on IEC 61850
- Kumar, Shantanu, Abu-Siada, Ahmed, Das, Narottam, Islam, Syed
- Authors: Kumar, Shantanu , Abu-Siada, Ahmed , Das, Narottam , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: Electronics (Switzerland) Vol. 10, no. 3 (2021), p. 1-16
- Full Text:
- Reviewed:
- Description: With the global trend to digitalize substation automation systems, International Electro technical Commission 61850, a communication protocol defined by the International Electrotechnical Commission, has been given much attention to ensure consistent communication and integration of substation high-voltage primary plant assets such as instrument transformers, circuit breakers and power transformers with various intelligent electronic devices into a hierarchical level. Along with this transition, equipment of primary plants in the switchyard, such as non-conventional instrument transformers, and a secondary system including merging units are expected to play critical roles due to their fast-transient response over a wide bandwidth. While a non-conventional instrument transformer has advantages when compared with the conventional one, extensive and detailed performance investigation and feasibility studies are still required for its full implementation at a large scale within utilities, industries, smart grids and digital substations. This paper is taking one step forward with respect to this aim by employing an optimized network engineering tool to evaluate the performance of an Ethernet-based network and to validate the overall process bus design requirement of a high-voltage non-conventional instrument transformer. Furthermore, the impact of communication delay on the substation automation system during peak traffic is investigated through a detailed simulation analysis. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
- Authors: Kumar, Shantanu , Abu-Siada, Ahmed , Das, Narottam , Islam, Syed
- Date: 2021
- Type: Text , Journal article
- Relation: Electronics (Switzerland) Vol. 10, no. 3 (2021), p. 1-16
- Full Text:
- Reviewed:
- Description: With the global trend to digitalize substation automation systems, International Electro technical Commission 61850, a communication protocol defined by the International Electrotechnical Commission, has been given much attention to ensure consistent communication and integration of substation high-voltage primary plant assets such as instrument transformers, circuit breakers and power transformers with various intelligent electronic devices into a hierarchical level. Along with this transition, equipment of primary plants in the switchyard, such as non-conventional instrument transformers, and a secondary system including merging units are expected to play critical roles due to their fast-transient response over a wide bandwidth. While a non-conventional instrument transformer has advantages when compared with the conventional one, extensive and detailed performance investigation and feasibility studies are still required for its full implementation at a large scale within utilities, industries, smart grids and digital substations. This paper is taking one step forward with respect to this aim by employing an optimized network engineering tool to evaluate the performance of an Ethernet-based network and to validate the overall process bus design requirement of a high-voltage non-conventional instrument transformer. Furthermore, the impact of communication delay on the substation automation system during peak traffic is investigated through a detailed simulation analysis. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
A new fuzzy logic approach for consistent interpretation of dissolved gas-in-oil analysis
- Abu-Siada, Ahmed, Hmood, Sdood, Islam, Syed
- Authors: Abu-Siada, Ahmed , Hmood, Sdood , Islam, Syed
- Date: 2013
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 20, no. 6 (2013), p. 2343-2349
- Full Text:
- Reviewed:
- Description: Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results however all these techniques rely on personnel experience more than analytical formulation. As a result, various interpretation techniques do not necessarily lead to the same conclusion for the same oil sample. Furthermore, significant number of DGA results fall outside the proposed codes of the current based-ratio interpretation techniques and cannot be diagnosed by these methods. Moreover, ratio methods fail to diagnose multiple fault conditions due to the mixing up of produced gases. To overcome these limitations, this paper introduces a new fuzzy logic approach to reduce dependency on expert personnel and to aid in standardizing DGA interpretation techniques. The approach relies on incorporating all existing DGA interpretation techniques into one expert model. DGA results of 2000 oil samples that were collected from different transformers of different rating and different life span are used to establish the model. Traditional DGA interpretation techniques are used to analyze the collected DGA results to evaluate the consistency and accuracy of each interpretation technique. Results of this analysis were then used to develop the proposed fuzzy logic model.
- Authors: Abu-Siada, Ahmed , Hmood, Sdood , Islam, Syed
- Date: 2013
- Type: Text , Journal article
- Relation: IEEE Transactions on Dielectrics and Electrical Insulation Vol. 20, no. 6 (2013), p. 2343-2349
- Full Text:
- Reviewed:
- Description: Dissolved gas analysis (DGA) of transformer oil is one of the most effective power transformer condition monitoring tools. There are many interpretation techniques for DGA results however all these techniques rely on personnel experience more than analytical formulation. As a result, various interpretation techniques do not necessarily lead to the same conclusion for the same oil sample. Furthermore, significant number of DGA results fall outside the proposed codes of the current based-ratio interpretation techniques and cannot be diagnosed by these methods. Moreover, ratio methods fail to diagnose multiple fault conditions due to the mixing up of produced gases. To overcome these limitations, this paper introduces a new fuzzy logic approach to reduce dependency on expert personnel and to aid in standardizing DGA interpretation techniques. The approach relies on incorporating all existing DGA interpretation techniques into one expert model. DGA results of 2000 oil samples that were collected from different transformers of different rating and different life span are used to establish the model. Traditional DGA interpretation techniques are used to analyze the collected DGA results to evaluate the consistency and accuracy of each interpretation technique. Results of this analysis were then used to develop the proposed fuzzy logic model.