Pub Date : 2008-11-01DOI: 10.1109/TENCON.2008.4766494
M. Dale, M. Joshi
In the fingerprint recognition application utilizing more information other than minutiae is much helpful. We present here a fingerprint matching scheme based on transform features and their comparison. The technique described here obviates the need for extracting minutiae points to match fingerprint images. The proposed scheme uses Discrete Cosine Transform (DCT), Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) to create feature vector for fingerprints. After finding out the core point, fingerprint image of size 64times64 is cropped around the core point. The transform is applied on the cropped image without any pre-processing. The transform coefficients are arranged in specific manner and are used to obtain the feature vector in terms of standard deviation. The fingerprint matching is based on the minimum Euclidean distance between two feature vectors. Here database is formed by capturing 8 images per person using 500 dpi optical scanner. Training images used to form feature vector are 2, 4 or 6 per person. In the matching phase either all or remaining images are checked in identification mode to find out the percentage recognition rate. Comparison for all the three transform is presented here and it is observed that DCT and DFT gives better result as compared DWT.
{"title":"Fingerprint matching using transform features","authors":"M. Dale, M. Joshi","doi":"10.1109/TENCON.2008.4766494","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766494","url":null,"abstract":"In the fingerprint recognition application utilizing more information other than minutiae is much helpful. We present here a fingerprint matching scheme based on transform features and their comparison. The technique described here obviates the need for extracting minutiae points to match fingerprint images. The proposed scheme uses Discrete Cosine Transform (DCT), Fast Fourier Transform (FFT) and Discrete Wavelet Transform (DWT) to create feature vector for fingerprints. After finding out the core point, fingerprint image of size 64times64 is cropped around the core point. The transform is applied on the cropped image without any pre-processing. The transform coefficients are arranged in specific manner and are used to obtain the feature vector in terms of standard deviation. The fingerprint matching is based on the minimum Euclidean distance between two feature vectors. Here database is formed by capturing 8 images per person using 500 dpi optical scanner. Training images used to form feature vector are 2, 4 or 6 per person. In the matching phase either all or remaining images are checked in identification mode to find out the percentage recognition rate. Comparison for all the three transform is presented here and it is observed that DCT and DFT gives better result as compared DWT.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89280810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/TENCON.2008.4766484
A. Suresh kumar, M. Subba Rao, Y. Babu
This paper deals with the conventional model reference adaptive control (MRAC) and replaces conventional control technique such as PI control with model reference adaptive control scheme with fuzzy linear adaptation. The Model Reference Adaptive Control (MRAC) speed control systems do not achieve consistent satisfactory performance over wide range of speed demand, especially at low speed and there is no defined rule to guide designers to choose the adaptation gains. The fuzzy logic model reference adaptive control maintains satisfactory response irrespective of the magnitude of the inputs. It enhances the performance of the DC drive compared to conventional MRAC. The performance of the drive system, thus obtained, is forming a set of test conditions with model reference fuzzy adaptive control. The performance of the drive is tested for load disturbances along with reference model. This work also compares the performance of Model Reference Fuzzy Adaptive scheme over conventional MRAC. This work is carried out by using MATLAB-SIMULINK.
{"title":"Model reference linear adaptive control of DC motor using fuzzy controller","authors":"A. Suresh kumar, M. Subba Rao, Y. Babu","doi":"10.1109/TENCON.2008.4766484","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766484","url":null,"abstract":"This paper deals with the conventional model reference adaptive control (MRAC) and replaces conventional control technique such as PI control with model reference adaptive control scheme with fuzzy linear adaptation. The Model Reference Adaptive Control (MRAC) speed control systems do not achieve consistent satisfactory performance over wide range of speed demand, especially at low speed and there is no defined rule to guide designers to choose the adaptation gains. The fuzzy logic model reference adaptive control maintains satisfactory response irrespective of the magnitude of the inputs. It enhances the performance of the DC drive compared to conventional MRAC. The performance of the drive system, thus obtained, is forming a set of test conditions with model reference fuzzy adaptive control. The performance of the drive is tested for load disturbances along with reference model. This work also compares the performance of Model Reference Fuzzy Adaptive scheme over conventional MRAC. This work is carried out by using MATLAB-SIMULINK.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89322352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/TENCON.2008.4766630
A. Mukhopadhyay, U. Maulik, S. Bandyopadhyay
Microarray technology facilitates the monitoring of the expression profile of a large number of genes across different experimental conditions simultaneously. This article proposes a novel approach that combines a recently proposed multiobjective fuzzy clustering scheme with support vector machine (SVM), to yield improved solutions. The multiobjective technique is first used to produce a set of non-dominated solutions. The non-dominated set is then used to find some high-confidence points using a fuzzy voting technique. The SVM classifier is trained by this high-confidence points. Finally the remaining points are classified using the trained classifier. Results demonstrating the effectiveness of the proposed technique are provided for three real life gene expression data sets. Moreover statistical significance test has been conducted to establish the significant superiority of the proposed technique.
{"title":"Improving multi-objective clustering through support vector machine: Application to gene expression data","authors":"A. Mukhopadhyay, U. Maulik, S. Bandyopadhyay","doi":"10.1109/TENCON.2008.4766630","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766630","url":null,"abstract":"Microarray technology facilitates the monitoring of the expression profile of a large number of genes across different experimental conditions simultaneously. This article proposes a novel approach that combines a recently proposed multiobjective fuzzy clustering scheme with support vector machine (SVM), to yield improved solutions. The multiobjective technique is first used to produce a set of non-dominated solutions. The non-dominated set is then used to find some high-confidence points using a fuzzy voting technique. The SVM classifier is trained by this high-confidence points. Finally the remaining points are classified using the trained classifier. Results demonstrating the effectiveness of the proposed technique are provided for three real life gene expression data sets. Moreover statistical significance test has been conducted to establish the significant superiority of the proposed technique.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89563237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/TENCON.2008.4766807
A. Mishra
Both principal component analysis (PCA) and linear discriminant analysis (LDA) have long been recognized as tools for feature extraction and data analysis. There has been reports in the open literature regarding the performance of both LDA and PCA as feature extractors in various types of classification and recognition problems. Many of the reports claim a better performance with LDA than with PCA. However, the grounds of comparison have mostly been quite narrow. In the current paper PCA and LDA based classifiers are evaluated for the problem of synthetic aperture radar based automatic target recognition problem. The results show that in terms of absolute performance, PCA outperforms LDA. Results of PCA based classifier are also found to be of higher confidence than those from LDA based classifiers, as observed from the error-bar analysis of the classifiers.With decreased amount of training dataset, the degradation in the performance of the classifiers are almost similar in nature. The current work concludes that LDA is not suitable for radar image based target recognition task. This is in line with reports from some works in the open literature which claim that the success of LDA will depend on the type of data and whether there is exhaustive data available during the training phase or not.
{"title":"Validation of PCA and LDA for SAR ATR","authors":"A. Mishra","doi":"10.1109/TENCON.2008.4766807","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766807","url":null,"abstract":"Both principal component analysis (PCA) and linear discriminant analysis (LDA) have long been recognized as tools for feature extraction and data analysis. There has been reports in the open literature regarding the performance of both LDA and PCA as feature extractors in various types of classification and recognition problems. Many of the reports claim a better performance with LDA than with PCA. However, the grounds of comparison have mostly been quite narrow. In the current paper PCA and LDA based classifiers are evaluated for the problem of synthetic aperture radar based automatic target recognition problem. The results show that in terms of absolute performance, PCA outperforms LDA. Results of PCA based classifier are also found to be of higher confidence than those from LDA based classifiers, as observed from the error-bar analysis of the classifiers.With decreased amount of training dataset, the degradation in the performance of the classifiers are almost similar in nature. The current work concludes that LDA is not suitable for radar image based target recognition task. This is in line with reports from some works in the open literature which claim that the success of LDA will depend on the type of data and whether there is exhaustive data available during the training phase or not.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89944257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/TENCON.2008.4766569
S.R. Patil, S. Pathak
In this paper we propose a novel method for designing irregular quasi-cyclic low-density parity-check (LDPC) codes from Balanced Incomplete Block Designs (BIBDpsilas). The design method hinges around finding the optimum degree profile by minimizing the threshold using density evolution. The approach for designing short block length codes is robust for practical implementation and has been found to exhibit considerable performance gain that may be attributed to a good degree profile for the codes. The design takes into consideration the code rate and code length as variable parameters. The simulation results for the designed codes are compared with regular and irregular quasi-cyclic BIBD based LDPC codes and found a relatively higher performance in terms of BER.
{"title":"Improved performance irregular quasi-cyclic LDPC code design from BIBD’s using threshold minimization","authors":"S.R. Patil, S. Pathak","doi":"10.1109/TENCON.2008.4766569","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766569","url":null,"abstract":"In this paper we propose a novel method for designing irregular quasi-cyclic low-density parity-check (LDPC) codes from Balanced Incomplete Block Designs (BIBDpsilas). The design method hinges around finding the optimum degree profile by minimizing the threshold using density evolution. The approach for designing short block length codes is robust for practical implementation and has been found to exhibit considerable performance gain that may be attributed to a good degree profile for the codes. The design takes into consideration the code rate and code length as variable parameters. The simulation results for the designed codes are compared with regular and irregular quasi-cyclic BIBD based LDPC codes and found a relatively higher performance in terms of BER.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86748004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/TENCON.2008.4766545
R. Sukanesh, R. Harikumar
The purpose of this paper is to identify the practicability of hierarchical soft (max-min) decision trees in optimization of fuzzy outputs in the classification of epilepsy risk levels from EEG (Electroencephalogram) signals. The fuzzy pre classifier is used to classify the risk levels of epilepsy based on extracted parameters like energy, variance, peaks, sharp and spike waves, duration, events and covariance from the EEG signals of the patient. Hierarchical soft decision tree (post classifier with max-min criteria) four types are applied on the classified data to identify the optimized risk level (singleton) which characterizes the patientpsilas risk level. The efficacy of the above methods is compared based on the bench mark parameters such as performance index (PI), and quality value (QV). A group of ten patients with known epilepsy findings are used for this study. High PI such as 95.88 % was obtained at QVpsilas of 22.43 in the hierarchical decision tree optimization when compared to the value of 40% and 6.25 through fuzzy classifier respectively. It is identified the hierarchical soft decision tree (Hier & h min-max) method is a good post classifier.
本文的目的是确定层次软(最大-最小)决策树在从EEG(脑电图)信号中分类癫痫风险等级的模糊输出优化中的实用性。利用模糊预分类器从患者的脑电图信号中提取能量、方差、峰值、尖峰和尖峰波、持续时间、事件和协方差等参数，对癫痫的风险等级进行分类。在分类数据上应用四种类型的分层软决策树(最大最小准则的后分类器)来识别表征患者整体风险水平的优化风险水平(单例)。基于性能指数(PI)、质量值(QV)等基准参数对上述方法的有效性进行比较。这项研究使用了10名已知癫痫症状的患者。层次决策树优化在QVpsilas为22.43时获得了95.88%的高PI，而模糊分类器的PI分别为40%和6.25。结果表明，分层软决策树(Hier & h min-max)方法是一种较好的后分类器。
{"title":"Fuzzy techniques and hierarchical aggregation functions decision trees for the classification of epilepsy risk levels from EEG signals","authors":"R. Sukanesh, R. Harikumar","doi":"10.1109/TENCON.2008.4766545","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766545","url":null,"abstract":"The purpose of this paper is to identify the practicability of hierarchical soft (max-min) decision trees in optimization of fuzzy outputs in the classification of epilepsy risk levels from EEG (Electroencephalogram) signals. The fuzzy pre classifier is used to classify the risk levels of epilepsy based on extracted parameters like energy, variance, peaks, sharp and spike waves, duration, events and covariance from the EEG signals of the patient. Hierarchical soft decision tree (post classifier with max-min criteria) four types are applied on the classified data to identify the optimized risk level (singleton) which characterizes the patientpsilas risk level. The efficacy of the above methods is compared based on the bench mark parameters such as performance index (PI), and quality value (QV). A group of ten patients with known epilepsy findings are used for this study. High PI such as 95.88 % was obtained at QVpsilas of 22.43 in the hierarchical decision tree optimization when compared to the value of 40% and 6.25 through fuzzy classifier respectively. It is identified the hierarchical soft decision tree (Hier & h min-max) method is a good post classifier.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87910081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/TENCON.2008.4766432
G.A. Srinivas, D.N. Rohith, M. Z. Ali Khan
This paper discusses techniques to reduce the demodulation complexity at the receiver of systems that use coordinate interleaving (CI) with N2-QAM constellations. CI is a method used to increase the diversity order of any modulation scheme on fading channels, but has a high demodulation complexity. The techniques described reduce the complexity required to calculate the maximum likelihood and log likelihood ratio metrics for such systems from O(N2) and O(N2logN) respectively to O(NlogN), without any loss in performance.
{"title":"A low complexity demodulator for coordinate interleaved modulation schemes","authors":"G.A. Srinivas, D.N. Rohith, M. Z. Ali Khan","doi":"10.1109/TENCON.2008.4766432","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766432","url":null,"abstract":"This paper discusses techniques to reduce the demodulation complexity at the receiver of systems that use coordinate interleaving (CI) with N2-QAM constellations. CI is a method used to increase the diversity order of any modulation scheme on fading channels, but has a high demodulation complexity. The techniques described reduce the complexity required to calculate the maximum likelihood and log likelihood ratio metrics for such systems from O(N2) and O(N2logN) respectively to O(NlogN), without any loss in performance.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89157602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/TENCON.2008.4766672
S. Arjun, N. Rao
Information hiding (also known as data hiding), is a process of embedding secret message into a cover media for the purpose of covert communication, identification, security and copyright. Information hiding is used to conceal the content of messages. This is achieved by hiding secret message into other digital media like audio, images, video etc. For hiding secret message information in images, there exists a large variety of techniques, of which most techniques cause distortions in the original image even after secret message recovery, either due to bit-replacement or quantization error or truncation. It is especially important for medical and military applications that the image obtained after data extraction should be distortion free. Reversible data-hiding is the technique which embeds data in to a digital media such that the original media can be recovered without any distortion after the hidden message has been extracted. In this paper we propose a lossless method which embeds and extracts the data in the spatial domain. This method uses only one statistic parameter which controls the embedding and extraction of data. Two methods with different block orientations have been proposed. The novel method allows for an increase of 41.57% in average embedding efficiency when compared to existing methods, while maintaining the cover image degradation (PSNR - peak signal to noise ratio) at a comparable level. We also suggest a multi-layered embedding for increasing embedding capacity further.
{"title":"An approach to reversible information hiding for images","authors":"S. Arjun, N. Rao","doi":"10.1109/TENCON.2008.4766672","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766672","url":null,"abstract":"Information hiding (also known as data hiding), is a process of embedding secret message into a cover media for the purpose of covert communication, identification, security and copyright. Information hiding is used to conceal the content of messages. This is achieved by hiding secret message into other digital media like audio, images, video etc. For hiding secret message information in images, there exists a large variety of techniques, of which most techniques cause distortions in the original image even after secret message recovery, either due to bit-replacement or quantization error or truncation. It is especially important for medical and military applications that the image obtained after data extraction should be distortion free. Reversible data-hiding is the technique which embeds data in to a digital media such that the original media can be recovered without any distortion after the hidden message has been extracted. In this paper we propose a lossless method which embeds and extracts the data in the spatial domain. This method uses only one statistic parameter which controls the embedding and extraction of data. Two methods with different block orientations have been proposed. The novel method allows for an increase of 41.57% in average embedding efficiency when compared to existing methods, while maintaining the cover image degradation (PSNR - peak signal to noise ratio) at a comparable level. We also suggest a multi-layered embedding for increasing embedding capacity further.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88979852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/TENCON.2008.4766596
R. B. Pachori, D. Hewson, H. Snoussi, J. Duchêne
Center of pressure (COP) measurements are often used to identify balance problems. A new method for analysis of COP signals using empirical mode decomposition (EMD) and Fourier-Bessel (FB) expansion is proposed in this paper. The EMD decomposes a COP signal into a finite set of band-limited signals termed intrinsic mode functions (IMFs), before FB expansion is applied on each IMF to compute mean frequency. The FB expansion based representation is suitable for use in non-stationary and very short duration signals. Seventeen subjects were tested under eyes open (EO) and eyes closed (EC) conditions, with different vibration frequencies applied for EC condition to further perturb sensory information. Mean frequency as calculated by FB expansion for the first three IMFs was able to distinguish between EO and EC conditions (p < 0.05), while only first IMF was able to detect a vibration effect.
{"title":"Analysis of center of pressure signals using Empirical Mode Decomposition and Fourier-Bessel expansion","authors":"R. B. Pachori, D. Hewson, H. Snoussi, J. Duchêne","doi":"10.1109/TENCON.2008.4766596","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766596","url":null,"abstract":"Center of pressure (COP) measurements are often used to identify balance problems. A new method for analysis of COP signals using empirical mode decomposition (EMD) and Fourier-Bessel (FB) expansion is proposed in this paper. The EMD decomposes a COP signal into a finite set of band-limited signals termed intrinsic mode functions (IMFs), before FB expansion is applied on each IMF to compute mean frequency. The FB expansion based representation is suitable for use in non-stationary and very short duration signals. Seventeen subjects were tested under eyes open (EO) and eyes closed (EC) conditions, with different vibration frequencies applied for EC condition to further perturb sensory information. Mean frequency as calculated by FB expansion for the first three IMFs was able to distinguish between EO and EC conditions (p < 0.05), while only first IMF was able to detect a vibration effect.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77182089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2008-11-01DOI: 10.1109/TENCON.2008.4766550
S. Halwi, D. G. Holmes, T. Czaszejko, M.B. Khoorasani
The importance of having accurate load models in power system stability studies has been well established in the literature as being essential for precise power system transient event investigations. The power industry presently uses composite load models in typical stability programs (e.g. LOADSYN and PSS/E). However, the parameters of the composite load models need to be tuned for each type of disturbance based on an assumed load composition, and are often inadequate for matching the modeled dynamics of the power system disturbance event to actual measured results. A stochastic time series technique in the form of an ARMAX mathematical model is presented in this paper as a novel alternative for dynamic load modeling. The model parameters are estimated using on-line measurement data for a number of disturbance events, collected from five substations in the Victorian electricity network in Australia. The performance of the model is then evaluated for other transient events, and compared against the recorded response for these events. The results achieved show that this heuristic-based model is robust and effective in predicting the dynamic response of a power system load across a range of events spanning various seasons and locations.
{"title":"Improved representation of power system load dynamics using heuristic models","authors":"S. Halwi, D. G. Holmes, T. Czaszejko, M.B. Khoorasani","doi":"10.1109/TENCON.2008.4766550","DOIUrl":"https://doi.org/10.1109/TENCON.2008.4766550","url":null,"abstract":"The importance of having accurate load models in power system stability studies has been well established in the literature as being essential for precise power system transient event investigations. The power industry presently uses composite load models in typical stability programs (e.g. LOADSYN and PSS/E). However, the parameters of the composite load models need to be tuned for each type of disturbance based on an assumed load composition, and are often inadequate for matching the modeled dynamics of the power system disturbance event to actual measured results. A stochastic time series technique in the form of an ARMAX mathematical model is presented in this paper as a novel alternative for dynamic load modeling. The model parameters are estimated using on-line measurement data for a number of disturbance events, collected from five substations in the Victorian electricity network in Australia. The performance of the model is then evaluated for other transient events, and compared against the recorded response for these events. The results achieved show that this heuristic-based model is robust and effective in predicting the dynamic response of a power system load across a range of events spanning various seasons and locations.","PeriodicalId":22230,"journal":{"name":"TENCON 2008 - 2008 IEEE Region 10 Conference","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2008-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76462983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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