Boštjan Polajžer (Author), Dunja Srpak (Author)

Abstract

V članku so obravnavani različni modeli verjetnostne porazdelitve napake proizvodnje vetrnih elektrarn. Poleg modelov, znanih iz literature (beta, Weibull, gamma), so obravnavani modeli z razširjeno nesimetrično posplošeno normalno porazdelitvijo. Obravnavan je tudi model s t.i. verzatilno verjetnostno porazdelitvijo, ki je občutljiv na valovitost empirične porazdelitve, vendar omogoča analitičen izračun percentilne funkcije. Dobljeni rezultati kažejo, da modeli z beta, Weibull in gamma verjetnostno porazdelitvijo ne dajejo dobrih rezultatov, bistveno bolj ustrezni so modeli z nesimetrično posplošeno normalno verjetnostno porazdelitvijo.

Keywords

model verjetnostne porazdelitve;verjetnostna analiza;porazdelitev napake;proizvodnja električne energije;vetrne elektrarne;

Data

Language: Slovenian
Year of publishing:
Typology: 1.08 - Published Scientific Conference Contribution
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
UDC: 621.311
COBISS: 20724758 Link will open in a new window
Parent publication: 26. mednarodno posvetovanje Komunalna energetika, 9. do 11. maj 2017, Maribor, Slovenija
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Other data

Secondary language: English
Secondary title: Evaluation of probability-distribution models for wind-power forecast error
Secondary abstract: This paper discusses different probability-distribution models for wind-power forecast error. Models known from the literature (beta, Weibull, gamma) are discussed along with the models with extendedskew generalized-normal distribution. Furthermore, a versatile model is discussed, which enables analytical calculation of the percentile function; however, it is sensitive to wavelets in the probability distribution. Obtained results show that beta, Weibull and gamma probability distributions do not capture the actual (empirical) one; far more adequate are models with skew generalized-normal probability distribution.
Secondary keywords: probability-distribution models;error distribution;generation;wind power;
URN: URN:SI:UM:
Type (COBISS): Not categorized
Pages: Str. [53]-59
ID: 10869798