Wind speed modeling using a vector autoregressive process with a time-dependent intercept term

Matti Koivisto; Janne Seppänen; Ilkka Mellin; Jussi Ekström; Robert Millar; Ivan Mammarella; Mika Komppula; Matti Lehtonen

doi:10.1016/j.ijepes.2015.11.027

Wind speed modeling using a vector autoregressive process with a time-dependent intercept term

Matti Koivisto^*, Janne Seppänen, Ilkka Mellin, Jussi Ekström, Robert Millar, Ivan Mammarella, Mika Komppula, Matti Lehtonen

^*Corresponding author for this work

Research output: Contribution to journal › Article › Scientific › peer-review

28 Citations (Scopus)

Abstract

The effect of wind power on the electric power system is becoming increasingly important as more wind power is installed. This paper presents a Vector-Autoregressive-To-Anything (VARTA) process with a time-dependent intercept to model wind speeds in multiple locations. The model considers both temporal and spatial dependency structures in detail. It can be used in Monte Carlo simulations to assess the risk of very high or low wind speeds occurring in multiple locations at the same time and during consecutive hours. The long term simulation and short term forecasting results are assessed using measurements from 21 locations in Finland. A discussion on the applicability of the presented wind speed simulation method for the risk assessment of power systems is given.

Original language	English
Pages (from-to)	91-99
Number of pages	9
Journal	International Journal of Electrical Power and Energy Systems
Volume	77
DOIs	https://doi.org/10.1016/j.ijepes.2015.11.027
Publication status	Published - 1 May 2016
MoE publication type	A1 Journal article-refereed

Keywords

Forecasting
Generalized Pareto distribution
Monte Carlo simulation
Rank correlation
Vector autoregressive model
Wind speed

Access to Document

10.1016/j.ijepes.2015.11.027

Cite this

@article{4c10df7df3ae437095b85e4419013c3e,

title = "Wind speed modeling using a vector autoregressive process with a time-dependent intercept term",

abstract = "The effect of wind power on the electric power system is becoming increasingly important as more wind power is installed. This paper presents a Vector-Autoregressive-To-Anything (VARTA) process with a time-dependent intercept to model wind speeds in multiple locations. The model considers both temporal and spatial dependency structures in detail. It can be used in Monte Carlo simulations to assess the risk of very high or low wind speeds occurring in multiple locations at the same time and during consecutive hours. The long term simulation and short term forecasting results are assessed using measurements from 21 locations in Finland. A discussion on the applicability of the presented wind speed simulation method for the risk assessment of power systems is given.",

keywords = "Forecasting, Generalized Pareto distribution, Monte Carlo simulation, Rank correlation, Vector autoregressive model, Wind speed",

author = "Matti Koivisto and Janne Sepp{\"a}nen and Ilkka Mellin and Jussi Ekstr{\"o}m and Robert Millar and Ivan Mammarella and Mika Komppula and Matti Lehtonen",

year = "2016",

month = may,

day = "1",

doi = "10.1016/j.ijepes.2015.11.027",

language = "English",

volume = "77",

pages = "91--99",

journal = "International Journal of Electrical Power and Energy Systems",

issn = "0142-0615",

publisher = "Elsevier",

}

TY - JOUR

T1 - Wind speed modeling using a vector autoregressive process with a time-dependent intercept term

AU - Koivisto, Matti

AU - Seppänen, Janne

AU - Mellin, Ilkka

AU - Ekström, Jussi

AU - Millar, Robert

AU - Mammarella, Ivan

AU - Komppula, Mika

AU - Lehtonen, Matti

PY - 2016/5/1

Y1 - 2016/5/1

N2 - The effect of wind power on the electric power system is becoming increasingly important as more wind power is installed. This paper presents a Vector-Autoregressive-To-Anything (VARTA) process with a time-dependent intercept to model wind speeds in multiple locations. The model considers both temporal and spatial dependency structures in detail. It can be used in Monte Carlo simulations to assess the risk of very high or low wind speeds occurring in multiple locations at the same time and during consecutive hours. The long term simulation and short term forecasting results are assessed using measurements from 21 locations in Finland. A discussion on the applicability of the presented wind speed simulation method for the risk assessment of power systems is given.

AB - The effect of wind power on the electric power system is becoming increasingly important as more wind power is installed. This paper presents a Vector-Autoregressive-To-Anything (VARTA) process with a time-dependent intercept to model wind speeds in multiple locations. The model considers both temporal and spatial dependency structures in detail. It can be used in Monte Carlo simulations to assess the risk of very high or low wind speeds occurring in multiple locations at the same time and during consecutive hours. The long term simulation and short term forecasting results are assessed using measurements from 21 locations in Finland. A discussion on the applicability of the presented wind speed simulation method for the risk assessment of power systems is given.

KW - Forecasting

KW - Generalized Pareto distribution

KW - Monte Carlo simulation

KW - Rank correlation

KW - Vector autoregressive model

KW - Wind speed

UR - http://www.scopus.com/inward/record.url?scp=84948808861&partnerID=8YFLogxK

U2 - 10.1016/j.ijepes.2015.11.027

DO - 10.1016/j.ijepes.2015.11.027

M3 - Article

AN - SCOPUS:84948808861

SN - 0142-0615

VL - 77

SP - 91

EP - 99

JO - International Journal of Electrical Power and Energy Systems

JF - International Journal of Electrical Power and Energy Systems

ER -

Wind speed modeling using a vector autoregressive process with a time-dependent intercept term

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this