10-03-2012, 03:55 PM
DSP based Transmission line transient analyzer
Transient studies of transmission lines in electric networks are presently done in
electric networks using computer or Transient Network Analysers (TNA). The
proposed work aims in implementation of DSP based transmission line Fault
classifier and Locator.
Need for DSP based Transmission line transient analyzer
1. Fast repair to restore power system from outages,
2. Improves system availability and performance as well as reduces operating
costs.
3. Saves time and expense of crew searching in bad weather and tough terrains.
4. Helps crew in disturbance diagnostics by:
- identifying temporary faults,
- detecting weak spots
Harmonics are periodic signals that occur in power systems due to various
reasons. The frequency of harmonics is an integer multiple of the fundamental
frequency of the power system which is 50 Hz. The presence of high frequency
harmonics in voltages and currents of a power system is a key signal for
identification of faults in power systems. Therefore, DSP based monitoring of the
harmonics for admissible levels become necessary for reliable distribution of electric
energy.
The DSP technology brings unquestionable improvements in fault classification
and location in a shorter time; input signals are filtered-out more precisely; it is easy
to apply sophisticated corrections; the hardware is standardized and may
communicate with other protection and control systems. The proposed work starts
with the development of a hardware arrangement for the simulation of various types
of faults, transients similar to that occurring in power systems are generated and are
processed through a DSP processor. The processed outputs are feed for wavelets
analysis. On identification of type of fault a support vector machine (SVM) based fault
location algorithm is called.
ANN based fault Location
Since ANNs can provide excellent pattern recognition, they are proposed
by many researchers to perform different tasks in power system relaying for signal
processing and decision making. Implementation of ANN has the following steps:
1. Additional pre- and post-processing are applied to the ANN structure for training.
The training patterns exposed to the ANN cover the most important operating
conditions both faults and other disturbances.
2. The ANN is fed either with non-processed samples of the input signals, or by
features of those signals extracted using certain measuring algorithms (or by a
combination).
3. The sliding data widow consisting of the recent and a few historical samples of the
signals is then fed to the ANN.
4. The output from the ANN encodes the output decision such as type of fault,
location of fault etc.
each phase of the application development process including design, code and build,
debug, analyze, and tune. The familiar tools and interfaces allow users to get started
faster and become productive immediately. The signals processed through DSP
hardware are further analysis used wavelets for fault type identification.
The total estimated project cost is around RS 10, 75,000 (Ten Lakhs seventy five
thousand)
Transient studies of transmission lines in electric networks are presently done in
electric networks using computer or Transient Network Analysers (TNA). The
proposed work aims in implementation of DSP based transmission line Fault
classifier and Locator.
Need for DSP based Transmission line transient analyzer
1. Fast repair to restore power system from outages,
2. Improves system availability and performance as well as reduces operating
costs.
3. Saves time and expense of crew searching in bad weather and tough terrains.
4. Helps crew in disturbance diagnostics by:
- identifying temporary faults,
- detecting weak spots
Harmonics are periodic signals that occur in power systems due to various
reasons. The frequency of harmonics is an integer multiple of the fundamental
frequency of the power system which is 50 Hz. The presence of high frequency
harmonics in voltages and currents of a power system is a key signal for
identification of faults in power systems. Therefore, DSP based monitoring of the
harmonics for admissible levels become necessary for reliable distribution of electric
energy.
The DSP technology brings unquestionable improvements in fault classification
and location in a shorter time; input signals are filtered-out more precisely; it is easy
to apply sophisticated corrections; the hardware is standardized and may
communicate with other protection and control systems. The proposed work starts
with the development of a hardware arrangement for the simulation of various types
of faults, transients similar to that occurring in power systems are generated and are
processed through a DSP processor. The processed outputs are feed for wavelets
analysis. On identification of type of fault a support vector machine (SVM) based fault
location algorithm is called.
ANN based fault Location
Since ANNs can provide excellent pattern recognition, they are proposed
by many researchers to perform different tasks in power system relaying for signal
processing and decision making. Implementation of ANN has the following steps:
1. Additional pre- and post-processing are applied to the ANN structure for training.
The training patterns exposed to the ANN cover the most important operating
conditions both faults and other disturbances.
2. The ANN is fed either with non-processed samples of the input signals, or by
features of those signals extracted using certain measuring algorithms (or by a
combination).
3. The sliding data widow consisting of the recent and a few historical samples of the
signals is then fed to the ANN.
4. The output from the ANN encodes the output decision such as type of fault,
location of fault etc.
each phase of the application development process including design, code and build,
debug, analyze, and tune. The familiar tools and interfaces allow users to get started
faster and become productive immediately. The signals processed through DSP
hardware are further analysis used wavelets for fault type identification.
The total estimated project cost is around RS 10, 75,000 (Ten Lakhs seventy five
thousand)