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Unformatted text preview: Power Transformers
Power INTRODUCTION OF POWER
TRANSFORMER They have rating above 200 kva and used in generating station and substation used for power transmission line for stepping up and stepping down the voltage.
They may be either single phase or three phase unit. CONTENTS
CONTENTS INTRODUCTION OF POWER TRANSFORMER
TYPES OF TRANSFORMER
EQIPMENTS USED FOR THE PROTECTION OF POWER TRANSFORMER
Artificial Neural Network
Neural network design
ADVANTAGE CONCLUSION TYPES OF TRANSFORMER
TYPES Power transformer. Distribution transformer. DETAILS OF POWER
TRANSFORMER 12500/10000 KVA.
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) TRANSFORMER FAULTS
TRANSFORMER Transformer faults are generally classified in to
Winding and terminal faults
Tank and transformer accessory faults
Onload tap changer faults
Abnormal operation conditions
Sustained or uncleared external faults DAMAGE ON TRANSFORMER
DAMAGE EQIPMENTS USED FOR THE
PROTECTION OF POWER
TRANSFORMER Lightning Arrester.
Over Current Relay.
Earth fault relay.
Oil level indicator.
Over fluxing relay. Artificial Neural Network An artificial neural network (ANN) is an imitation of human neural network
An ANN is constructed by layers of simulated artificial neurons. An artificial neuron is a simulation of real neuron Artificial neural networks
Artificial 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. Neural network design
The neural network
consists of two cell types: weight cells and output cells. Weight cells act as light
filters, and the output
cells act as reporters. The two cell types are used together to
program a desired output from a set input. ADVANTAGE OF NEURAL
∙ pattern classification ∙ regularity detection ∙ image processing ∙ speech analysis ∙ optimization problems ∙ robot steering ∙ quality assurance CONCLUSION
According to the approximation ability of neural network,
constructing the neural network model replacing the physical
transformer model. ...
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This note was uploaded on 01/05/2012 for the course ECEN 212 taught by Professor Hamilton during the Fall '11 term at BYU.
- Fall '11