power transformers basic ppt

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    Power Transformers

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    INTRODUCTION OF POWER

    TRANSFORMER

    They have rating above 200 kva andused in generating station andsubstation used for power

    transmission line for stepping up andstepping down the voltage.

    They may be either single phase orthree phase unit.

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    CONTENTS

    INTRODUCTION OF POWER TRANSFORMER

    TYPES OF TRANSFORMER

    TRANSFORMER FAULTS

    EQIPMENTS USED FOR THE PROTECTION OF POWER

    TRANSFORMER Artificial Neural Network

    Neural network design

    ADVANTAGE

    CONCLUSION

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    TYPES OF TRANSFORMER

    Power transformer.

    Distribution transformer.

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    DETAILS OF POWER

    TRANSFORMER

    12500/10000 KVA.

    50 hz.

    132 kv (H.v. side)

    6.9 kv (L.v. side)

    54.7 amp (H.v. side)

    1045.39 amp (L.v. side)

    55 degree centigrade (max temp rise)

    14706/17100 Liter (oil)

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    TRANSFORMER FAULTS

    Transformer faults are generally classified in to

    five categories:

    Winding and terminal faults

    Core faults

    Tank and transformer accessory faults

    On-load tap changer faults Abnormal operation conditions

    Sustained or uncleared external faults

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    DAMAGE ON TRANSFORMER

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    Artificial Neural Network

    An artificial neural network(ANN) isan imitation of human neural network

    An ANN is constructed by layers ofsimulated artificial neurons.

    An artificial neuron is a simulation ofreal neuron

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    Artificial neural networks

    Inputs

    Output

    An artificial neural network is composed of many artificial

    neurons that are linked together according to a specific

    network architecture. The objective of the neural network

    is to transform the inputs into meaningful outputs.

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    Neural network design

    The neural networkconsists of two cell

    types: weight cellsand output cells.

    Weight cells act aslightfilters, and the outputcells act as reporters.

    The two cell types areused together to

    program a desiredoutput from a setinput.

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    ADVANTAGE OF NEURAL

    NETWORK

    pattern classification

    regularity detection

    image processing

    speech analysis

    optimization problems

    robot steering

    quality assurance

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    CONCLUSION

    According to the approximation ability of neural network,

    constructing the neural network model replacing the physical

    transformer model.

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