DocumentCode :
3295711
Title :
Cognitive engineering studies of DSS and dealing with uncertainty in load for real-time adaptive power system reconfiguration
Author :
Pendurthi, Venkata K. ; Schulz, Noel N. ; Doane, Stephanie ; Srivastava, Anurag K.
Author_Institution :
Dept. of Electr. & Comput. Eng., Mississippi State Univ., Starkville, MS
fYear :
2009
fDate :
20-22 April 2009
Firstpage :
79
Lastpage :
85
Abstract :
The quality of a decision made by human operators in a real-time reconfiguration of the power system can be improved by providing him/her with a decision support system (DSS). This paper discusses the quantitative cognitive engineering of a decision support system to improve the situational awareness of the operator working in a real-time environment. The quality of decision results in reconfiguration of a power system network is compared with and without the decision support system. Within the reconfiguration activities, lack of awareness of the uncertainty present in load data will restrict the reconfiguration algorithm to give a new optimized power system topology. Uncertainty due to faulty metering is duly analyzed and a fuzzy based approach of dealing with uncertainty is explained.
Keywords :
cognitive systems; decision support systems; fuzzy logic; power engineering computing; ships; DSS; decision support system; faulty metering; power system network; power system topology; quantitative cognitive engineering; real-time adaptive power system reconfiguration; Adaptive systems; Decision support systems; Humans; Network topology; Power engineering and energy; Power system analysis computing; Power system faults; Power systems; Real time systems; Uncertainty; Decision Support System (DSS); Interface; cognitive engineering; fuzzy logic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electric Ship Technologies Symposium, 2009. ESTS 2009. IEEE
Conference_Location :
Baltimore, MD
Print_ISBN :
978-1-4244-3438-1
Electronic_ISBN :
978-1-4244-3439-8
Type :
conf
DOI :
10.1109/ESTS.2009.4906497
Filename :
4906497
Link To Document :
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