Behera, Satyajit and Send, Sudhanshu Sekhar (2015) Characterization of Various Power Quality Disturbances Based on Signal Processing and Artificial Intelligence Scheme. BTech thesis.
These days the electrical power quality has become a vital issue for the utilities and the consumers. Use of non-linear and sensitive loads add gradual deterioration of power quality. To improve power quality, automatic classification of power quality disturbances(PQDs) is much essential, which are also important for protection of transmission system network. Disturbances are mostly transient and temporary, thereby necessitate suitable method to analyze PQDs. In this paper a combined technique in the form of wavelet transform(WT) in association with fuzzy expert system is used for characterizing PQ disturbances. A no. of PQ signals are developed and decomposed using WT method for nearly exact detection of disturbances. Energy and Total Harmonic Distortion (THD) of all PQ disturbances are extracted through discrete wavelet transform (DWT) and are used in the fuzzy expert system to detect and classify different disturbances accurately. The fuzzy system used classifies the disturbances and confirms the presence of harmonics.
|Item Type:||Thesis (BTech)|
|Uncontrolled Keywords:||Power Quality, Non-Linear, Wavelet Transform, Total Harmonic Disortion, Energy, Fuzzy Logic System, Voltage Sag, Voltage Swell, Voltage Harmonics, Voltage Interruption|
|Subjects:||Engineering and Technology > Electrical Engineering > Power Systems|
Engineering and Technology > Electrical Engineering > Power Networks
|Divisions:||Engineering and Technology > Department of Electrical Engineering|
|Deposited By:||Mr. Sanat Kumar Behera|
|Deposited On:||25 May 2016 09:49|
|Last Modified:||25 May 2016 09:49|
Repository Staff Only: item control page