DocumentCode
3248567
Title
Modern computing environment for power system reliability assessment
Author
da Rosa, M.A. ; Miranda, V. ; Carvalho, L. ; Leite da Silva, A.M.
Author_Institution
USE - Power Syst. Unit, INESC Porto, Porto, Portugal
fYear
2010
fDate
14-17 June 2010
Firstpage
664
Lastpage
671
Abstract
A natural movement towards artificial intelligence (AI) techniques took place in the last years in power system analysis. Many research works have used AI topics like search techniques, knowledge representation, reasoning and learning systems, as well as heuristic tools to address power system problems. This paper focuses the discussion on power system reliability evaluation and this natural transition from AI topics to a more sophisticated software design, known as intelligent agent (IA) technology. Instead of applying AI techniques to improve a single stage of the Monte Carlo Simulation (MCS), the IA architecture explores new ways to support AI topics. However, this natural movement needs to be managed through the proposal of a modern framework of power system tools, where several different techniques have to be combined in order to maximize each one´s benefits and advantages.
Keywords
Monte Carlo methods; artificial intelligence; knowledge representation; power system analysis computing; power system reliability; Monte Carlo simulation; artificial intelligence techniques; computing environment; intelligent agent technology; knowledge representation; learning systems; power system analysis; power system problems; power system reliability assessment; reasoning systems; Artificial intelligence; Computer architecture; Intelligent agent; Knowledge representation; Learning systems; Power system analysis computing; Power system management; Power system reliability; Power system simulation; Software design; Distributed systems; Monte Carlo simulation; agent-based technology; reliability;
fLanguage
English
Publisher
ieee
Conference_Titel
Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4244-5720-5
Type
conf
DOI
10.1109/PMAPS.2010.5528321
Filename
5528321
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