EconPapers    
Economics at your fingertips  
 

Stochastic modeling to represent wind power generation and demand in electric power system based on real data

Humberto Verdejo, Almendra Awerkin, Eugenio Saavedra, Wolfgang Kliemann and Luis Vargas

Applied Energy, 2016, vol. 173, issue C, 283-295

Abstract: A methodology to model two types of random perturbation that affect the operation of electric power systems (EPS) are presented. The first uncertainty is wind power generation and is represented by a one-dimensional and by a multidimensional continuous stochastic process. The second one is power demand, and is modeled by using an hybrid structure based on harmonic regression and the Ornstein–Uhlenbeck (O–U) process. The stochastic models are applied to a real Chilean case, using real data for parametric estimation and validation models.

Keywords: Stochastic systems; Power systems; Estimation (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261916304536
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:173:y:2016:i:c:p:283-295

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2016.04.004

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:appene:v:173:y:2016:i:c:p:283-295