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In the presented work, an efficient model for classification of fault of a transmission line is proposed. The scheme proposed is the combination of Empirical Mode Decomposition and Probabilistic Neural Network for the classification of ten types of shunt fault. Post fault current signals are used for feature extraction for further study. Empirical Mode Decomposition (EMD) method is used to disintegrate...
This paper introduces Generalized Regression Neural Network (GRNN) for long term wind speed prediction of major wind power potential states in India. The performance of proposed GRNN model is evaluated using the publicly available online dataset of National Aeronautics and Space Administration (NASA). Data samples of 26 cities are used for training the generalized regression neural network and remaining...
This paper introduces artificial neural network (ANN) for long term wind speed prediction. The online available dataset of 26 cities from NASA are used to evaluate the performance of ANN model. Data of 22 cities are used for training the neural network and remaining 4 cities data samples are used for testing purpose. Air temperature, earth temperature, relative humidity, daily solar radiation, elevation,...
The dissolved gas-in-oil analysis (DGA) is a prevailing methodology being widely used to detect incipient faults in power transformers. However various methods have been developed to interpret DGA results, they may sometimes fail to diagnose precisely. The incipient fault identification accuracy of various artificial intelligence (AI) based methodology is varied with variation of input variable. Thus,...
The main objective of present study is to compare ANN model develop with neural network fitting tool (nftool), Radial Basis Function Neural Network (RBFNN) in predicting solar radiation for power generation. The three combinations of input variables are considered for prediction. The RBFNN utilizing input parameters as latitude, longitude, height above sea level and sunshine hours has mean absolute...
The diagnosis of incipient fault is important for power transformer condition monitoring. The incipient faults are monitored by conventional and artificial intelligence based models. The key gases, percentage value of gases and ratio of Doernenburg, Roger, IEC methods are input variables to artificial intelligence (AI) models which affects the accuracy of incipient fault diagnosis so selection of...
UV-Spectrophotometer response is a nonintrusive test used to determine the transformer integrity. Information about the health of the power transformer that can be use to plan cost, maintenance, relocation and operational criteria can be accurately interpreted using UV-Spectrophotometer. As UV scan can only show the pictorial information of the age of the oil hence it is not advantageous in all aspects...
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