Combination of moment-matching, Cholesky and clustering methods to approximate discrete probability distribution of multiple wind farms

This study focuses on approximating a reduced discrete probability distribution (RDPD) of wind power from the original discrete probability distribution (ODPD), consisting of a large number of observed original scenarios (OSs), to relieve the burden of solving stochastic programs of wind power gener...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IET renewable power generation Ročník 10; číslo 9; s. 1450 - 1458
Hlavní autoři:	Li, Jinghua, Zhu, Dunlin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 01.10.2016
Témata:	Approximation Approximation methods approximation theory Cholesky decomposition method Cholesky methods Clustering clustering methods Computer simulation importance sampling Latin hypercube sampling Mathematical analysis Metal matrix composites moment matching moment‐matching‐clustering methods observed original scenarios original discrete probability distribution probability Research Article stochastic programs Stochasticity wind farms Wind power wind power generation wind turbines clustering methods approximation theory probability Cholesky methods Cholesky decomposition method moment-matching-clustering methods observed original scenarios importance sampling original discrete probability distribution wind farms Latin hypercube sampling stochastic programs wind power generation wind turbines moment matching
ISSN:	1752-1416, 1752-1424
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!