Recognition and Classification of Power Quality Disturbances by DWT-MRA and SVM Classifier
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 3
Abstract
Electrical power system is a large and complex network, where power quality disturbances (PQDs) must be monitored, analyzed and mitigated continuously in order to preserve and to re-establish the normal power supply without even slight interruption. Practically huge disturbance data is difficult to manage and requires the higher level of accuracy and time for the analysis and monitoring. Thus automatic and intelligent algorithm based methodologies are in practice for the detection, recognition and classification of power quality events. This approach may help to take preventive measures against abnormal operations and moreover, sudden fluctuations in supply can be handled accordingly. Disturbance types, causes, proper and appropriate extraction of features in single and multiple disturbances, classification model type and classifier performance, are still the main concerns and challenges. In this paper, an attempt has been made to present a different approach for recognition of PQDs with the synthetic model based generated disturbances, which are frequent in power system operations, and the proposed unique feature vector. Disturbances are generated in Matlab workspace environment whereas distinctive features of events are extracted through discrete wavelet transform (DWT) technique. Machine learning based Support vector machine classifier tool is implemented for the classification and recognition of disturbances. In relation to the results, the proposed methodology recognizes the PQDs with high accuracy, sensitivity and specificity. This study illustrates that the proposed approach is valid, efficient and applicable.
Authors and Affiliations
Fayyaz Jandan, Suhail Khokhar, Syed Abid Ali Shaha, Farhan Abbasi
Keywords
Related Articles
- EP ID EP499552
- DOI 10.14569/IJACSA.2019.0100348
- Views 63
- Downloads 0
Message Segmentation to Enhance the Security of LSB Image Steganography
Classic Least Significant Bit (LSB) steganography technique is the most used technique to hide secret information in the least significant bit of the pixels in the stego-image. This paper proposed a technique by sp...
A Design of Pipelined Architecture for on-the-Fly Processing of Big Data Streams
Conventional processing infrastructures have been challenged by huge demand of stream-based applications. The industry responded by introducing traditional stream processing engines along-with emerged technologies. The o...
Wavelet/PSO-Based Segmentation and Marker-Less Tracking of the Gallbladder in Monocular Calibration-free Laparoscopic Cholecystectomy
This paper presents an automatic segmentation and monocular marker-less tracking method of the gallbladder in minimally invasive laparoscopic cholecystectomy intervention that can be used for the construction of an adapt...
Applicability of the Maturity Model for IT Service Outsourcing in Higher Education Institutions
Outsourcing is a strategic option which complements IT services provided internally in organizations. This study proposes the applicability of a new holistic maturity model based on standards ISO/IEC 20000 and ISO/IEC 38...
A Multi-Stage Optimization Model With Minimum Energy Consumption-Wireless Mesh Networks
Optimization models related with routing, bandwidth utilization and power consumption are developed in the wireless mesh computing environment using the operations research techniques such as maximal flow model, transshi...