REAL TIME POWER SYSTEM SECURITY ASSESSMENT USING ARTIFICIAL N N

8/7/2019 REAL TIME POWER SYSTEM SECURITY ASSESSMENT USING ARTIFICIAL N N

http://slidepdf.com/reader/full/real-time-power-system-security-assessment-using-artificial-n-n 1/11

BY

Y.SRUJAN KUMAR

G.SHEKAR



INTRODUCTIONy Security refers to the ability of the system to

withstand the impact of disturbance (contingency).

y There are three basic elements of on-line security analysis and control

1) Security monitoring

2) Security Assessment

3) Emergency control



Artificial Neural Networky Artificial neural networks may either be used to gain

an understanding of Biological neural networks

y

These Biological neural networks are made up of realbiological neurons that are connected or functionally related in the peripheral nervous systems

y Basic features of Artificial neural networks are

Fault tolerance.

Training the network adopts itself, based on theinformation received from the environment

Programmed rules are not necessary



The determination of voltage contingency ranking, amethod has been suggested, which eliminates miss

ranking and masking effects and security assessmenthas been determined using Radial Basis Function(RBF) neural network



Network operation

The network has two operating modes

Training mode

Testing mode

During training the adjustable parameters of thenetwork are set so as to minimize the average error

between the actual network output and desired outputover the vectors. In the testing phase, input vectors areapplied and output vectors are produced by thenetwork.



CONTINGENCY ANALYSISy Contingency analysis is a software application run in an

energy management system to give the operators anindication what will happen to the power system in theevent of a unplanned or unscheduled equipment outage

y To achieve an accurate picture of systems several issuesused to be considered. They are :

y system model

y Contingency definition

y Contingency list

y performance

y Modeling details



.

y The identification of critical contingencies often requiresexhaustive studies of all reasonable and possible cases. When

finding critical contingencies and giving ranking to them, weshould consider the following.

Magnitude of voltage violation

Number of violations occurring

Relative importance to each voltage violation

Nearness of voltages to the security limits

Load level of the system when evaluated



Conclusions:y A new method has been reported for calculating

voltage performance index for contingency ranking.

Which eliminates miss ranking and maskingproblems? Ranking of all contingencies is sameirrespective of values of weights supplied

y The RBF neural network model provides more

accurate results for both the security and insecurity cases



THANK YOU

y Training is very fast as the RBF network has thecapability of handling large data

y Testing time is less than 0.2 micro sec.

REAL TIME POWER SYSTEM SECURITY ASSESSMENT USING ARTIFICIAL N N

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