Title of article :
Extracting Knowledge From Substations for Decision Support
C.-L. Hor and P. A. Crossley، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2005
The growth in substation data generated by microprocessor-
based IEDs has far outstripped our capability for interpretation.
In competitive energy markets, the success and survival of
power utilities hinge upon their ability to skillfully locate, analyze
and make use of the information. Hence, it is now necessary to consider
moving beyond data acquisition to knowledge discovery. To
accomplish this task, we require a new information processing and
data analysis tool that can intelligently process a large volume of
data. The paper describes the data explosion problem and illustrates
how a new computational intelligence approach can be used
within a substation to group objects of interest into classes indiscernible
with respect to some or all of their features. This reduces
superfluous and irrelevant data, which then improves the performance
of the data analysis tools and helps speed up the knowledge
acquisition process. It also provides a condensed report summary
that can be used by the operator to react to the emergency.
Data overload , decision support , Data reduction , discernibility matrix , Knowledge acquisition , rough sets.
Journal title :
IEEE TRANSACTIONS ON POWER DELIVERY