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.
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.
Description:
Frequency response analysis (FRA) has been widely accepted as a diagnostic tool for power transformer winding deformation faults. Typically, both amplitude-frequency and phase-frequency signatures are obtained by an FRA analyzer. However, most existing FRA analyzers use only the information on amplitude-frequency signature, while phase-frequency information is neglected. It is also found that in some cases, the diagnostic results obtained by FRA amplitude-frequency signatures do not comply with some hard evidence. This paper introduces a winding deformation diagnostic method based on the analysis of binary images obtained from FRA signatures to improve FRA outcomes. The digital image processing technique is used to process the binary image and obtain a diagnostic indicator, to arrive at an outcome for interpreting winding faults with improved accuracy.
Description:
Frequency response analysis (FRA) has been widely accepted as a diagnostic tool for power transformer winding deformation faults. Typically, both amplitude-frequency and phase-frequency signatures are obtained by an FRA analyzer. However, most existing FRA analyzers use only the information on amplitude-frequency signature, while phase-frequency information is neglected. It is also found that in some cases, the diagnostic results obtained by FRA amplitude-frequency signatures do not comply with some hard evidence. This paper introduces a winding deformation diagnostic method based on the analysis of binary images obtained from FRA signatures to improve FRA outcomes. The digital image processing technique is used to process the binary image and obtain a diagnostic indicator, to arrive at an outcome for interpreting winding faults with improved accuracy.
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.
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.
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.
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.
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.
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.
Description:
Standalone hybrid remote area power systems, also known as microgrids (MGs), can provide reasonably priced electricity in geographically isolated and the edge of grid locations for their operators. To achieve the reliable operation of MGs, whilst consuming minimal fossil fuels and maximising the penetration of renewables, the voltage and frequency should be maintained within acceptable limits. This can be accomplished by solving an optimisation problem. Floating-point genetic algorithm (FP-GA) is a heuristic technique that has a proven track record of effectively identifying the optimal solutions. However, in addition to needing appropriate operators, the solver needs a fitness function to yield the most optimal control variables. In this study, a suitable fitness function is formulated, by including the operational, interruption and technical costs, which are then solved with an FP-GA, with different combinations of operators. The developed fitness function and the considered operators are tested for the non-linear optimisation problem of a 38-bus MG. Detailed discussions are provided on the impact, which different operators have upon the outcomes of the fitness function.
Description:
This study explores how the voltage control of a remote part of the utility gird can be improved using more sophisticated voltage control on wind-solar farms equipped with fast communication platforms. The idea is to make renewable plant the master voltage controller during large disturbance events in the grid. This is done by proposing an enhanced voltage droop control strategy based on instantaneous reactive power consumption by monitoring the virtual impedance of the point of connection using a new customised data class model of IEC 61850 communication protocol. The conventional centralised voltage droop control strategy and the proposed instantaneous direct voltage control method are both implemented on the White Rock Solar Wind Farm in NSW, Australia and their performances are compared using both MATLAB Simulink simulations under 5% voltage step disturbances, single-phase-to-ground and three-phase-to-ground faults as well as some tests conducted in the field.
Description:
Multi-agent-based smart grid applications have gained much attention in recent times. At the same time, information and communication technology (ICT) has become a crucial part of the smart grid infrastructure. The key intention of this work is to present a comprehensive review of the literature and technological frameworks for the application of multi-agent system (MAS) and ICT infrastructure usages in smart grid implementations. In the smart grid, agents are defined as intelligent entities with the ability to take decisions and acting flexibly and autonomously according to their built-in intelligence utilizing previous experiences. Whereas, ICT enables conventional grid turned into the smart grid through data and information exchange. This paper summarizes the multi-agent concept of smart grid highlighting their applications through a detailed and extensive literature survey on the related topics. In addition to the above, a particular focus has been put on the ICT standards, including IEC 61850 incorporating ICT with MAS. Finally, a laboratory framework concepts have been added highlighting the implementation of IEC 61850.
Description:
Multi-agent-based smart grid applications have gained much attention in recent times. At the same time, information and communication technology (ICT) has become a crucial part of the smart grid infrastructure. The key intention of this work is to present a comprehensive review of the literature and technological frameworks for the application of multi-agent system (MAS) and ICT infrastructure usages in smart grid implementations. In the smart grid, agents are defined as intelligent entities with the ability to take decisions and acting flexibly and autonomously according to their built-in intelligence utilizing previous experiences. Whereas, ICT enables conventional grid turned into the smart grid through data and information exchange. This paper summarizes the multi-agent concept of smart grid highlighting their applications through a detailed and extensive literature survey on the related topics. In addition to the above, a particular focus has been put on the ICT standards, including IEC 61850 incorporating ICT with MAS. Finally, a laboratory framework concepts have been added highlighting the implementation of IEC 61850.
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).
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).
Description:
IEEE This paper presents a new compact three-phase cascaded multilevel inverter (CMLI) topology with reduced device count and high frequency magnetic link. The proposed topology overcomes the predominant limitation of separate DC power supplies, which CMLI always require. The high frequency magnetic link also provides a galvanic isolation between the input and output sides of the inverter, which is essential for various grid-connected applications. The proposed topology utilizes an asymmetric inverter configuration that consists of cascaded H-bridge cells and a conventional three-phase two-level inverter. A toroidal core is employed for the high frequency magnetic link to ensure compact size and high-power density. Compared with counterpart CMLI topologies available in the literatures, the proposed inverter has the advantage of utilizing the least number of power electronic components without compromising the overall performance, particularly when a high number of output voltage levels is required. The feasibility of the proposed inverter is confirmed through extensive simulation and experimentally validated studies.
Description:
IEEE This paper presents a new compact three-phase cascaded multilevel inverter (CMLI) topology with reduced device count and high frequency magnetic link. The proposed topology overcomes the predominant limitation of separate DC power supplies, which CMLI always require. The high frequency magnetic link also provides a galvanic isolation between the input and output sides of the inverter, which is essential for various grid-connected applications. The proposed topology utilizes an asymmetric inverter configuration that consists of cascaded H-bridge cells and a conventional three-phase two-level inverter. A toroidal core is employed for the high frequency magnetic link to ensure compact size and high-power density. Compared with counterpart CMLI topologies available in the literatures, the proposed inverter has the advantage of utilizing the least number of power electronic components without compromising the overall performance, particularly when a high number of output voltage levels is required. The feasibility of the proposed inverter is confirmed through extensive simulation and experimentally validated studies.
Description:
One of the key challenges in multilevel inverters (MLIs) design is to reduce the number of components used in the implementation while maximising the number of output voltage levels. This paper proposes a new concept that facilitates a device count reduction technique of existing cascaded MLIs. Moreover, the proposed concept can be utilised to extend existing single phase cascaded MLI topologies to three-phase structure without tripling the number of semiconductor components and input dc-supplies as per the current practice. The new generalized concept involves two stages; namely, cascaded stage and phase generator stage. The phase generator stage is a combination of a conventional three-phase two level inverter and three bi-directional switches while the cascaded stage can employ any existing cascaded topology. A laboratory prototype model is built and extensive experimental analyses are conducted to validate the feasibility of the proposed cascaded MLI concept.
Description:
One of the key challenges in multilevel inverters (MLIs) design is to reduce the number of components used in the implementation while maximising the number of output voltage levels. This paper proposes a new concept that facilitates a device count reduction technique of existing cascaded MLIs. Moreover, the proposed concept can be utilised to extend existing single phase cascaded MLI topologies to three-phase structure without tripling the number of semiconductor components and input dc-supplies as per the current practice. The new generalized concept involves two stages; namely, cascaded stage and phase generator stage. The phase generator stage is a combination of a conventional three-phase two level inverter and three bi-directional switches while the cascaded stage can employ any existing cascaded topology. A laboratory prototype model is built and extensive experimental analyses are conducted to validate the feasibility of the proposed cascaded MLI concept.
Description:
IEEE Frequency response analysis (FRA) has recently been developed as a widely accepted tool for power transformer winding mechanical deformation diagnosis, and has proven to be effective and powerful in many cases. However, there still exist problems regarding the application of FRA. FRA is a comparative method in which the measured FRA signature should be compared with its fingerprint. Small differences of FRA signatures in certain frequency bands might be produced by external disturbance, which hinders fault diagnosis. Additionally, the existing correlation coefficient indicator recommended by power industry standards cannot reflect key information of signatures, namely the extreme points. This paper proposes an improved FRA based on binary morphology and extreme point variation. Binary morphology is first introduced to extract the certain frequency bands of signatures with significant difference. A composite indicator of extreme point variation is adopted to realize the diagnosis of fault level. A ternary diagram is constructed by the area proportions of the binary image to identify winding faults, which has a potential to realize cluster analysis of fault types.