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Title:A fuzzy model of power supply system control
Authors:ID Usenik, Janez (Author)
Files:URL http://www.fe.uni-mb.si/images/stories/jet/e-jet/revija_jet_-_volume_5_-_issue_3_-_avgust_-_internet.pdf
 
Language:English
Work type:Not categorized
Typology:1.01 - Original Scientific Article
Organization:FE - Faculty of Energy Technology
Abstract:In this article, a mathematical model of control of a dynamic system is described; one such system could be a power supply system. Analytical approaches that have been developed to describe the influence of production and stock, i.e. additional capacities, require a hierarchical spatial pattern and demand. Demand is usually an inherently stochastic process, but in this article we simulate it as an output fuzzy variable in a fuzzy system, in which all the input variables are also fuzzy. Furthermore, an interesting use of neural sets is shown, which is presented as an efficient method for the optimisation of the fuzzy system. At the end, a numerical example is given.
Keywords:power supply system, energy capacities, demand, fuzzy logic, neural net
Year of publishing:2012
Number of pages:str. 23-37
Numbering:Vol. 5, iss. 3
PID:20.500.12556/DKUM-49548 New window
UDC:519.6:681.5
ISSN on article:1855-5748
COBISS.SI-ID:1024110428 New window
NUK URN:URN:SI:UM:DK:RHVDMXDN
Publication date in DKUM:10.07.2015
Views:2472
Downloads:40
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Categories:Misc.
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Record is a part of a journal

Title:Journal of energy technology
Publisher:Fakulteta za energetiko
ISSN:1855-5748
COBISS.SI-ID:243311360 New window

Secondary language

Language:Slovenian
Title:Mehki model upravljanja energetskega sistema
Abstract:V članku je predstavljen mehki model upravljanja dinamičnega sistema, ki je lahko tudi energetski sistem. Razviti analitični pristopi, s katerimi opišemo medsebojni vpliv proizvodnje ter zalog, v takšnih sistemih so to dodatne kapacitete, zahtevajo hierarhično porazdeljeno prostorsko dogajanje/porabo oziroma povpraševanje. Prikazana je možnost, da povpraševanje, ki je po naravi stohastični proces, simuliramo z mehkim sistemom, kjer so vhodne spremenljivke opisane z mehkimi množicami. V nadaljevanju članka pa prikažemo še možnost uporabe nevronskih mrež kot izjemno zanimiv in zlasti zelo učinkovit način optimizacije mehkega sistema. Na koncu je narejen tudi numerični izračun.
Keywords:energetski sistemi, dinamični sistemi, upravljanje, mehki model upravljanja


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